Effective Machinery Measurements Using Dynamic Signal

Effective Machinery Measurements Using Dynamic Signal
Effective Machinery
Measurements using
Dynamic Signal Analyzers
Application Note 243-1
Table of Contents
Chapter 1.
1.1 Benefits of Vibration Analysis
1.2 Using This Application Note
Chapter 2.
Converting Vibration to an Electrical Signal
2.1 Vibration Basics
2.2 Transducers
2.3 Selecting the Right Transducer
2.4 Installation Guidelines
Chapter 3.
Reducing Vibration to Its Components: The Frequency Domain
3.1 The Time Domain
3.2 The Frequency Domain
3.3 Spectral Maps/Waterfalls
3.4 The Phase Spectrum
3.5 Frequency Domain Analyzers
Chapter 4.
Vibration Characteristics of Common Machinery Faults
4.1 Imbalance
4.2 Rolling-Element Bearings
4.3 Oil Whirl in Fluid-Film Bearings
4.4 Misalignment
4.5 Mechanical Looseness
4.6 Gears
4.7 Blades and Vanes
4.8 Resonance
4.9 Electric Motors
4.10 Summary Tables
Chapter 5.
Advanced Analysis and Documentation
5.1 Practical Aspects of Analysis
5.2 Using Phase for Analysis
5.3 Sum and Difference Frequencies
5.4 Speed Normalization
5.5 Baseline Data Collection
Chapter 6.
Dynamic Signal Analyzers
6.1 Types of DSAs
6.2 Measurement Speed
6.3 Frequency Resolution
6.4 Dynamic Range
6.5 Digital Averaging
6.6 HP-IB and HP Instrument Basic
6.7 User Units and Waveform Math
6.8 Synchronous Sample Control and Order Tracking
6.9 Dual/Multi-channel Enhancements
Appendix A -
Computed Synchronous Resampling and Order Tracking
Chapter 1
The analysis of machinery vibration is characterized by a number
of distinct application areas. In
evaluating machinery vibration its
paramount to ask “What is the
purpose of the measurement?”.
In general, the analysis will fall
intoone of three distinct categories:
Figure 1-1
Dynamic Signal
Analysers are
(DSAs) are the
ideal instrument
for analyzing
1) Product/machine research
and development
2) Production and quality control
(this includes rebuilding and
3) In service maintenance and
In the cases of these differing
application categories; the general principles and measurements
are often the same, but the performance characteristics, measurement flexibility functionality and
data presentation formats can
Figure 1-2
The individual
components of
vibration are
shown in DSA
displays of
amplitude versus
The implementation of machinery
vibration analysis has been
made practical by the development of analysis instruments
called Dynamic Signal Analyzers
(DSAs). Machinery vibration is a
complex combination of signals
caused by a variety of internal
sources of vibration. The power
of DSAs lies in their ability to
reduce these complex signals to
their component parts. In the example of Figure 1-2, vibration is
produced by residual imbalance
of the rotor, a bearing defect, and
meshing of the gears — each occurring at a unique frequency. By
displaying vibration amplitude as
a function of frequency (the vibration spectrum), the DSA makes it
possible to identify the individual
sources of vibration.
Dynamic Signal Analyzers can
also display the vibration amplitude as a function of time (Figure
1-3), a format that is especially
useful for investigating impulsive
vibration (e.g. from a chipped
gear). The waterfall/spectral map
format (Figure 1-4) adds a third
dimension to vibration amplitude
versus frequency displays. The
third dimension can be time, rpm
or a count triggered by an external event (e.g. load, delay from
top-dead-center, etc.). DSAs
come in many shapes, sizes and
configurations. They range from
stand- alone battery operated portables, to bench-top precision instruments, to rack-mounted
computer controlled systems.
They range from single-channel
units up through multi-channel
(~500) systems. Virtually all can
be computer automated and controlled, and a wide variety of
post-processing capabilities and
programs are available.
Figure 1-3
DSA display
of amplitude
versus time are
especially useful
for analyzing
vibration that
is characteristic
of gear and
rolling element
Figure 1-4
DSA map displays
illustrate changes
in vibration with
rpm, load, or
time. This map
is a collection
of vibration
made during a
machine runup.
This application note is a primer
on analyzing machinery vibration
with Dynamic Signal Analyzers.
Each of the important steps in the
analysis process from selecting
the right vibration transducer to
interpreting the information displayed is covered. The techniques described provide insight
into the condition of the machinery that eliminates much of the
guesswork from analysis, troubleshooting and maintenance.
1.1 Benefits of Vibration
The ability to analyze and record
vibration data has existed for a
considerable time. Its only recently with the advent of modern
DSAs that the actual detailed
analysis of vibration data has become widespread and effective.
3) Provide a consistent, repeatable measurement by which to
characterize the vibration of a
elements in the machine and
depending upon the objective,
determine whether an individual
component of the vibration is
abnormal. The total energy in any
single component is generally
small and the ability of a DSA to
individually segregate this component make it a very sensitive measure of the machine. Often a very
large change in an individual component will cause an extremely
small change in the overall
vibration level.
4) Identify characteristics that
change with time and operating
conditions, or both.
1.2 Using this Application
The principle objectives in analyzing the vibration data are:
1) Simplify and reduce the vibration data into a more compact
easily interpreted form.
2) Associate characteristics of
the vibration to specific features
of the machine vibrating.
Figure 1-2 illustrates the principles presented; the vibration data
is broken down into its individual
frequency components by the
DSA; the analysis can associate
these components to particular
This application note is organized
around four key steps in the
analysis process shown in Figure
1.2-1: (1) converting the vibration
to an electrical signal, (2) reducing it to its components, (3) correlating those components with
machine defects, and (4) documenting, archiving and analyzing
the results. Each of these steps is
vital to analysis, and viewing the
process in this manner promotes
a systematic approach that
increases the probability of
success. The contents of each
chapter, and their relation to
the steps in Figure 1.2-1 are
discussed below.
Two subjects beyond the scope of
this note are rotor dynamics and
the vibration characteristics of
specific types of machinery.
Rotor dynamics is required for
complete analysis of the rotors
used in most turbomachinery (i.e.
flexible rotors) although most of
the information in this note still
applies (we will note circumstances when it does not).
Figure 1.2-1
The process of machinery vibration analysis
consists of four steps,
each critical for success.
Understanding the vibration characteristics of specific types of machinery is important for effective
analysis. This information can be
obtained from machinery
manufacturers, independent
training centers, and from well
documented experience with
similar machines.
The analysis of machinery vibration is not an easy task, and you
will not fully understand each and
every measurement, nor will you
easily predict the effects of
changes or an impending failure.
What vibration analysis does
provide is a valuable tool to give
you additional insight into the
dynamics of a rotating machine,
the ability to predict most failures
and diagnose the cause of
excessive vibration.
Chapter Overview
Chapter 22: Converting Vibration to an Electrical Signal
Vibration is converted to an electrical signal with transducers, and effective analysis
requires a signal that accurately represents the vibration. This chapter gives you the
information needed to select and mount transducers.
Chapter 3: Reducing Vibration to its Components - The Frequency Domain
The key to successful analysis is reduction of the complex signal to simple components.
As shown in Figure 1-2, this is best done with a display of vibration amplitude vs.
frequency – a perspective known as the frequency domain. The objective of this
chapter is to provide a good working knowledge of the frequency domain.
Chapter 4: Characteristic Vibration of Common Machinery Faults
Each type of machine fault has distinctive characteristics that can be used for
identification. This chapter describes the characteristics of some of the most common
machinery faults.
Chapter 5: Advanced Analysis and Documentation
This chapter focuses on solving some of the practical problems encountered in machinery
vibration analysis, such as identifying spectral relationships, order analysis, orbits, limit
testing, automation and other advanced techniques.
Chapter 6: Dynamic Signal Analyzers
DSAs feature measurement capabilities that make them the ideal instrument for
machinery vibration analysis. This chapter explains why these capabilities are important,
describes key aspects of each and helps discriminate between the different analyzers
ranging from single-channel up through large multi-channel systems.
Chapter 2
Converting Vibration to an
Electrical Signal
Before analysis can begin, vibration must be converted to an electrical signal — a task performed
by vibration transducers. The key
considerations in obtaining a signal that accurately represents the
vibration are: (1) selecting the
right type of transducer, and (2)
locating and installing it correctly.
The four types of transducers
commonly used for machinery vibration are shown in Figure 2-1.
They are differentiated by the parameter measured (i.e. displacement, velocity, or acceleration),
and by the machine component
measured (i.e. shaft or housing).
Selection depends on the characteristics of the machine and its
expected faults. Installation requires correct placement, secure
mounting, and proper signal
In addition to the motion transducer, for many measurements
the operating speed of the shaft is
of importance. The transducer
used for this is called a tachometer; and provides a pulse type signal as opposed to the analog data
normally found in motion transducers. The tachometer normally
produces a fixed number of
“pulses” per revolution which is in
turn converted to a rotation speed
by a frequency counter. Common
types of tachometers include the
use of the displacement probe
and/or optical or magnetic sensors.
This chapter begins with a discussion of basic vibration concepts
that are fundamental to understanding transducers and their installation. This is followed by a
description of each of the three
types of motion transducers and
two common tachometer configurations. The final section of the
chapter provides transducer installation guidelines.
Figure 2.1
Four types of
commonly used
to convert machinery vibration to
an electrical
2.1 Vibration Basics
Before starting our discussion
of the details of transducers and
vibration analysis, it is important
to establish some basic concepts.
The three topics we will focus
on are:
(a) Vibration Parameters.
Using commercially available
transducers, we can measure the
displacement, velocity, or acceleration of vibration. Selecting the
right parameter is critical for effective analysis.
(b) Mechanical Impedance.
What we can measure with transducers is the response of the machine to vibration forces caused
by machinery characteristics; not
the forces themselves. The mechanical impedances of the machine shaft/rotor and housing
determine how they respond to
vibration forces and can alter significantly the characteristics of
the signal we measure. These
characteristics are often
non-linear in nature.
(c) Natural Frequencies.
When a structure is excited by an
impact, it will vibrate at one or
more of its natural frequencies or
resonance. These frequencies are
important because they are often
associated with critical speed of
the machine, where residual imbalance excites the resonance.
They can cause large changes in
the vibration response with changes in rpm and are often associated
with critical operation conditions.
Vibrations Parameters
We will start our discussion of
vibration parameters by examining the vibration produced by
simple imbalance. Referring to
the machine rotor in Figure 2.1-1,
note that the heavy spot produces
arotating force that appears
sinusoidal from any fixed reference position. At points A and C,
the force in the direction of the
reference is zero. At points B and
D it is at positive and negative
maximums, respectively.
Figure 2.1-1
A heavy spot on a
machine rotor
results in a
rotating force
vector that
appears sinusoidal
from a fixed
The amplitude of the vibration
parameters also vary with rotation
speed (rpm) — an important consideration in transducer selection.
Velocity increases in direct proportion to frequency (f), while acceleration increases with the
square of frequency. This variation with frequency, and the phase
relationships shown in Figure
2.1-3 , are illustrated in the equations below. In these equations,
which apply only to sinusoidal
vibration, A is the vibration displacement amplitude and f is the
rotor frequency of rotation (cps or
The response of the rotor to such
a force is a displacement which
moves the center of rotation away
from the geometric center (Figure
2.1-2).1 A displacement measurement performed on the rotor results in approximately the same
waveform as the force, with a
signal amplitude approximately
proportional to the magnitude of
the force. It is not exactly the
same because the dynamics of the
rotor affect the response. This is
an important point in vibration
analysis, and is discussed in more
detail in the next section.
The velocity and acceleration
parameters of the vibration are
offset in phase relative to displacement — an important consideration when using phase for
analysis. Phase relationships are
shown in Figure 2.1-3. Velocity,
for example, is offset from displacement by 90°. At point B,
when the displacement is maximum, the velocity is zero. At
point C, when displacement is
zero, velocity is maximum.
Following the same reasoning, acceleration can be shown to be offset 90° from velocity, and thus
180° from displacement.
Displacement = A sin (2p f t)
Velocity = 2p f A COS (2p f t)
Acceleration = - (2p f)2 A sin (2p f t)
The three vibration parameters
are thus closely related and, in
fact, can be derived from each
other by a Dynamic Signal Analyzer (see Section 6.6). However, the
variation in vibration amplitude
with machine speed, and transducer limitations, often mean that
only one of the parameters will
supply the information necessary
for analysis.
The impact of variations in
amplitude with rotation speed is
illustrated in Figure 2.1-4. In this
example, potentially dangerous
vibration levels are present in a
low-speed fan and a high-speed
gearbox. The two items to note
are: (1) displacement and acceleration levels differ widely, and
(2) velocity is relatively constant.
From the first, we can conclude
that frequency considerations are
important in selecting a vibration
parameter. Acceleration is not as
good a choice for very low frequency analysis, while displacement does not work well for high
frequencies. Note that these are
limitations of the vibration parameter, not the transducer.
Note: This applies to shafts that do not
bend in operation (i.e. rigid shafts).
Flexible shafts respond somewhat
differently to imbalance forces.
Frequency range limitations of
transducers are also an important
consideration in parameter selection, and are discussed in
Section 2.2.
The fact that velocity is a good indicator of damage, independent of
machine speed, implies that it is a
good parameter for general
machine monitoring. That is, a
vibration limit can be set independent of frequency. (Velocity remains constant with damage level
because it is proportional to the
energy content of vibration.) Velocity is also a good parameter for
analysis, but the upper frequency
limitation of velocity transducers
can be a problem for gear and
high-speed bladeanalysis.
Mechanical Impedance
A key point illustrated by Figure
2.1-5 is that we are measuring the
response of the machine to vibration forces, not the forces themselves. Thus the response
characteristics of the machine —
its mechanical impedance — have
a direct impact on the measured
vibration. The two key results of
this are: (1) if the response is
small, the vibration will be difficult to analyze, and (2) if response
changes drastically with frequency, changes in running speed can
produce misleading changes in
measured vibration level. These
are important considerations
in selecting and installing
Figure 2.1-2
The imbalance
force produces a
vibration whose
has approximately
the same waveform as the
force itself.
Figure 2.1-3
Velocity and
acceleration of
the vibration are
offset 90º and 180º
in phase from
Figure 2.1-4
Two cases which
illustrate the
variation of
with machine
The most common example of
low-level response involves machines with relatively light rotors
and fluid-film bearings, mounted
in heavy casings. Very little shaft
vibration is transmitted to the casing, and shaft vibration must be
measured directly (see Figure
2.1-6). Rolling element bearings
are much stiffer than most fluidfilm bearings, and transmit shaft
(and their own) vibration to the
machine case well.
An example of mechanical impedance that changes noticeably with
speed is shown in Figure 2.1-7.
This measurement shows how the
ratio of acceleration response to
input force might vary with frequency on a machine. Note that
measurements made at speeds A
and B would differ markedly in
amplitude, even if the source of
vibration remained the same.
This illustrates why simple level
measurements made on a machine
whose speed varies can be misleading.
Natural Frequencies
In the plot of Figure 2.1-7, the
response peaks occur at natural
frequencies. These are the frequencies at which a structure will
vibrate “naturally” when hit with
an impact. A good illustration of
natural frequency vibration is a
tuning fork, which is designed to
vibrate at a specific frequency
when impacted (see Figure 2.1-8).
When a vibration force occurs at a
natural frequency, the structure
will resonate (i.e. respond with a
large amplitude vibration).1
Figure 2.1-5
on a machine is
the response to
defect force, not
the force itself.
Figure 2.1-6
A relatively light
shaft turning in
fluid-film bearings
transmits little
vibration to the
machine housing.
Its vibration must
be measured
directly with a
Figure 2.1-7
A plot of vibration
response versus
frequency for a
machine housing
shows how
level can change
with rpm. A defect
force at frequency
B produces a much
larger vibration
response than the
same force level at
frequency A.
Natural frequencies relate to machinery vibration analysis in three
important areas: (1) resonances of
the structure can cause changes in
vibration level with rpm, (2) the
dynamics of rotating shafts
change significantly near natural
frequencies (or critical speeds),
and (3) resonances of transducers
limit the operating frequency
range of velocity transducers and
accelerometers. Changes in vibration response with frequency are
shown in Figure 2.1-7. Shafts
which operate above or near a
natural frequency of the shaft are
classified as flexible, and are discussed briefly in Section 3.4. Natural frequency limits on the useful
frequency range of transducers
are described in the next section
Figure 2.1-8
When excited by
an impact, a
tuning fork
vibrates at its
natural frequency.
Figure 2.1-9
The natural
frequency of a
simple mechanical
system varies with
mass and stiffness.
A relationship worth noting at this
point is the variation in natural
frequency with mass and stiffness.
The equation for the natural frequency of the simple mechanical
system in Figure 2.1-9 is given below, where k is stiffness and m is
mass. Note that natural frequency
goes up with increasing stiffness
and decreasing mass.
Natural frequency (ωn) = (k/m)1/2
If you think of piano wires or guitar strings, the tight, lightweight
ones are higher in frequency than
the loose, heavy ones. This relationship is important when determining a solution to resonance
Note: The subject of resonances and
structural vibration is dealt with in
more detail in Hewlett-Packard
Application Note AN243-3. Though
extremely important to analyzing and
understanding machine vibration; the
focus of this note is more on analyzing
operating machines than on structural
2.2 Transducers
In this section, each of the transducers shown in Figure 2.1 will be
described. We will discuss how
each one works, its important
characteristics, and the most common applications. We will also
discuss some common tachometer
type transducers used to obtain
rotation speed information on the
Displacement Transducers
Noncontacting displacement
transducers (also known as
proximity probes1), like the one in
Figure 2.2-1, are used to measure
relative shaft motion directly. A
high frequency oscillation is used
to set up eddy currents in the
shaft without actually touching it.
As the shaft moves relative to the
sensor, the eddy current energy
changes, modulating the oscillator
voltage. This signal is demodulated, providing an output voltage
proportional to displacement. This
is illustrated in Figure 2.2-2.
In practice, noncontacting displacement probes are used on virtually all turbomachinery because
their flexible bearings (fluid film)
and heavy housings result in small
external responses. Some gas
turbines, especially those used on
aircraft, use relatively stiff rollingelement bearings, and can thus
use housing-mounted transducers
(velocity and acceleration) effectively.
Key characteristics of displacement transducers
(a) Displacement transducers measure relative motion between the shaft and the
mount, which is usually the machine housing. Thus, vibration of a stiff shaft/bearing
combination that moves the entire machine is difficult to measure with displacement
transducers alone.
(b) Signal conditioning is included in the electronics. Typical outputs are 200 mV/mil or
8mV/micron (1 mil is 0.001 inches; 1 micron is 0.001 millimeters). Technically, the frequency response of displacement probes is up to 10,000 Hz (or 600,000 rpm), but as a
practical matter the displacement levels at these frequencies is so low that the actual
useful frequency range of proximity probes is about 500 Hz (30,000 rpm).
(c) Shaft surface scratches, out-of-roundness, and variation in electrical properties
due to hardness variations, all produce a signal error. Surface treatment and run-out
subtraction can be used to solve these problems [11,12].
(d) Installation is sometimes difficult, often requiring that a hole be drilled in the
machine housing.
(e) The output voltage contains a dc offset of 6 – 12 volts, requiring the use of ac
coupling for sensitive measurements. AC coupling is a feature of all DSAs, and simply
means that an input capacitor is used to block the dc. The practical disadvantage of ac
coupling is reduced instrument response below 1Hz (60 rpm).
Figure 2.2-1
include a probe
and an oscillator module.
diagram of
a typical
Note: We will limit our discussion to
eddy current probes as they are by far
the most commonly used type.
Velocity Transducers
Velocity transducers were the first
vibration transducer, and virtually
all early work in vibration severity
was done using velocity criteria.
Velocity transducer construction
is shown in Figure 2.2-4. The
vibrating coil moving through the
field of the magnet produces a relatively large output voltage that
does not require signal conditioning. The amplitude of the voltage
is directly proportional to the velocity of the vibration. As shown
in Figure 2.2-5, the spring-massdamper system is designed for a
natural frequency of 8 to 10 Hz,
which allows the magnet to stay
essentially fixed in space. This
establishes a lower frequency
limit of approximately 10 Hz
(600 rpm). The upper frequency
limit of 1000 to 2000 Hz is determined by the inertia of the springmass-damper system.
Historically, the velocity transducer was widely used in machinery
vibration measurements; but in
recent years most transducer
manufacturers have replaced this
technology with accelerometers
that have electrically integrated
outputs which provide the same
functionality as velocity probes
but with wider frequency range
and better stability. DSAs also
provide for internal integration
of acceleration signals; making
accelerometers the transducer of
choice — due to its wider frequency response, greater accuracy
and more rugged construction.
Figure 2.2-3
A typical velocity
transducer with
extension probe
Figure 2.2-4
transducer output
is a current
generated in the
coil as it moves
through the field
of the stationary
Figure 2.2-5
response of a
typical velocity
transducer. Note
that the natural
frenquency of the
magnet-springdamper system is
below the
operating range.
Accelerometers are the most
popular general purpose vibration
transducer. They are constructed
using a number of different technologies, but for general purpose
measurements and machinery vibration, the most common design
is the piezoelectric quartz accelerometer. Our discussion will be
limited to this type and its derivatives. Construction of a simple
accelerometer is shown in Figure
2.2-7. The vibrating mass applies
a force on the piezoelectric crystal
that produces a charge proportional to the force (and thus to
The frequency response of a typical accelerometer is shown in Figure 2.2-8. Note that the natural
frequency is above the operating
range of the transducer (unlike
the velocity transducer). Operation should be limited to about
20% of the natural frequency.
Accelerometer sensitivity is largely dependent on the size of the
mass, with a larger mass producing more output. High output is
especially important for increasing the usability of accelerometers
at low frequencies. However, in
our previous discussion of natural
frequency, we noted that natural
frequency decreases as mass
increases. Thus increased sensitivity tends to lead to lower operating frequency range and larger
physical size.
Key characteristics of accelerometers
(a) Accelerometers offer the broadest frequency coverage of the three transducer types.
Their weakness is at low frequency, where low levels of acceleration result in small
output voltages. Their large output at high frequencies also tends to obscure lower
frequency content when the transducer is used for measuring overall level. This can be
overcome by models with built-in integrators giving velocity output, or by added signal
(b) The low frequency response of piezoelectric accelerometers is limited to
approximately 5 Hz. This can be improved with special low frequency versions of the
accelerometer. An inherent problem still exists in measuring acceleration at low
frequency since its level tends to decrease dramatically at low frequencies.
(c) Accelerometers are very sensitive to mounting. Handheld models are available but
repeatability is very dependent upon the individual. This is increasingly true for high
frequencies. When possible, accelerometers should be securely mounted using a
threaded stud, high strength magnet, or industrial adhesive. The mounting surface
should be flat and smooth — preferably — machined. Frequently, special mounting
studs are bonded or welded in place where repeated measurements are to be made.
Figure 2.2-6
feature wide
frequency range
and ruggedness.
They should be
securely mounted
on a flat surface
for best results.
Figure 2.2-7
The output
voltage of an
is produced by the
accelerating mass
squeezing the
crystal stack.
The force — and
thusthe output
voltage —is
proportional to
Accelerometer output is a lowlevel, high-impedance signal that
requires special signal conditioning. The traditional method is to
use a separate charge amplifier,
as shown in Figure 2.2-9(a).
How-ever, accelerometers are
available with built-in signal conditioning electronics that require
only a simple current-source supply. The accelerometer can be
directly connected to most DSAs
(Figure 2.2-9(b)). Another advantage of this type of accelerometer
is that expensive low-noise cable
required of normal piezoelectric
accelerometers is not required.
This can be especially important
when long or multiple cables
are required.
Tachometers are devices used to
measure the rotation speed of a
machine shaft. They are useful in
determining accurate operating
speed and identifying speed related components of the velocity.
The transducer itself normally
provides a pulse of some fixed
amplitude at a rate related to rotation speed (typically, once per
revolution). We will discuss two
common types, the proximity
probe and the optical tachometer.
Figure 2.2-8
high frequency
response is
limited by the
natural frequency
of the spring-mass
Figure 2.2-9a
require an
external charge
amplifier for
signal conditioning.
Figure 2.2-9b
Integrated Circuit
with built-in
signal conditioning, can be
connected directly
to a compatible
The proximity probe is the same
as previously discussed, however,
it is not used to get accurate
displacement information in this
mode. It is commonly used to
detect the presence of something
such as a keyway slot (often referred to as a keyphaser) or gear
tooth. Figure 2.2-10(a) illustrates
a proximity probe detecting a
keyway to provide a once per revolution signal. This transducer
has many of the limitations previously described.
The other common tachometer
transducer is the optical tachometer. It generally consists of either
an optical or infrared light source
and a detector (Figure 2.2-10(b)).
Optionally, a lens for focusing the
beam can be provided. The beam
is trained on the rotating shaft and
detects the presence of a reflective indicator (usually, a piece of
tape or reflective paint).
The output of the tachometer is
handled in one of two ways. On
multi-channel DSAs the tachometer is fed into a channel of the
DSA where the once-per-rev pulse
train will produce a large frequency component at the rotation
speed of the machine. This is
useful in obtaining valuable phase
information about the response
channels. An alternative is to
measure the rotation speed directly with specialized hardware
interfaced directly to the DSA’s
external sample control. It is also
Figure 2.2-10a
Proximity probe
used as
tachometer to
provide signal
with repetion rate
proportional to
shaft velocity
Figure 2.2-10b
which measures
reflection of light
from a rotating
object to provide
signal proportional to rotation
common to connect the tachometer signal directly to the trigger
input of the DSA to obtain an
accurate phase reference.
Tachometers differ from motion
transducers in the fundamental
variable measured. They measure
the timing of an event, i.e. like the
passing of a reference, such as a
2.3 Selecting the Right
Selecting the right transducer for
an application is a straight forward process that is described below. Table 2.4 in the next section
is a guide for the application of
transducers to several general
types of machinery.
Step 1: Determine the Parameter
of Interest.
If you are interested in monitoring
a critical clearance or relative displacement, the only choice is a
displacement transducer. Although acceleration and velocity
can be converted to displacement,
it will be an absolute measurement, rather than the relative
measurement given by a displacement probe. If the parameter is a
quantity other than a clearance or
relative displacement, go on to
next step.
Step 2: Mechanical Impedance
If the vibration is not well transmitted to the machine case, you
must use a displacement transducer to measure the shaft runout
directly. This will be the case
with a flexible rotor-bearing system working in a heavy casing. If
the shaft is not accessible (as an
internal shaft in a gearbox), or if
the rotor-bearing system is stiff,
you should use a casing mounted
velocity or acceleration transducer. In borderline cases, it may be
Figure 2.3
A vibration nomograph shows how
the levels of
displacement and
change with
relative to the
level of velocity.
Note that the
response is very
low at 1 Hz (less
than 100 µ V with
a 10 m V / g accelerometer).
appropriate to use both absolute
and relative motion transducers.
If Steps 1 and 2 indicate a displacement transducer, it is the one
that will provide the best
results. If a housing-mounted acceleration or velocity transducer
is indicated, go on to Step 3.
Step 3: Frequency Considerations.
If the frequency of the expected
vibration is greater than 1000 Hz,
you must use an accelerometer.
(You will have a much better idea
of frequencies to expect after
reading Chapter 4). If the vibration will be in the 10 to 1000 Hz
range, either velocity or acceleration transducers can be used. Generally, an accelerometer will be
the choice in these cases. The
important thing to consider is the
individual specifications of the
accelerometer. Choose one designed for the frequency range and
vibration level anticipated. The
vibration nomograph of Figure 2.3
can be used to help determine the
required performance. In many
cases for low frequency (<20 Hz)
applications or applications where
the overall level is important for
accessing machinery health a
velocity output is required. This
will dictate using either a velocity
transducer or more commonly an
accelerometer with integrated
output proportional to velocity.
Table 2.4
Machine Description
Steam turbine/large pump or compressor
A,B,C,D. with fluid-film bearings.
Gas turbine or medium size pump
Radial horizontal at
Redundant axial at A and D.
Radial horizontal and vertical at
A and B.
Motor/fan both with fluid-film bearings
or Velocity
Motor/pump or compressor with rolling
element bearings
Velocity or
Gear box with rolling element bearings
Gearbox shafts with fluid-film bearings
2.4 Installation
After the transducer has been selected, it must be properly installed for the best results. Figure
2.4 is an example of a machine
combination that is used for the
application summary in Table 2.4.
The machine combination could
be a small motor and pump, or a
steam turbine and generator. In
general, the number of transducers used on a machine combination is determined by the purpose
of the measurement. Table 2.4
is intended to show typical applications and considerations that
can be used as a guide in selecting measurement points and
When troubleshooting a vibration
problem it is critical to get information on vibration of key components in the principle directions.
The inclusion of phase information is critical to diagnosing many
machine dynamics problems. On
the other hand, characterizing a
non-critical machine for machinery health monitoring purpose; the
Radial horizontal or vertical at
A and B.
One radial at each bearing. One
axial displacement to detect thrust
One radial at each bearing. One
axial, usually on motor, to detect
thrust wear.
Transducers mounted as close to
each bearing as possible.
Radial horizontal and vertical at each
bearing. Axial to detect thrust wear.
Figure 2.4
referenced in
Table 2.4
goal is often to find a “representative” measurement which can
characterize the general condition
of the machine with the minimum
number of measurements. When
selecting measurement points and
transducers the ultimate goal
should be kept in mind. Careful
transducer selection; bearing in
mind manufacturers specification;
proper mounting of the transducer
can be critical. One particular
caution: the transducer should
never be mounted to a sheet metal
cover, since resonances may easily be in the operating speed range
and can easily mask the real
objective of the measurement.
Chapter 3
Reducing Vibration to its
Components: The Frequency
The signal obtained from a
machinery vibration transducer is
a complex combination of responses to multiple internal and
external forces. The key to effective analysis is to reduce this
complex signal to individual components, each of which can then
be correlated with its source.
Techniques for reducing vibration
to its components are the subject
of this chapter, while the process
of correlating these components
with machinery vibration is
discussed in Chapters 4 and 5.
Two analysis perspectives are
available for determining the
components of vibration: (1) the
time domain view of vibration
amplitude versus time and (2) the
frequency domain view of vibration amplitude versus frequency.
While the time domain provides
insight into the physical nature of
the vibration, we will see that the
frequency domain is ideally suited
to identifying its components.
The advantage of Dynamic Signal
Analyzers for machinery analysis
is their ability to work in both
This chapter begins with a discussion of the relationship
between the time and frequency
domains. Waterfall/spectral maps,
which add the dimension of
machine speed or time to the
frequency domain, are presented
next. The frequency phase spectrum, an important complement to
the more familiar amplitude spectrum, is discussed in the following
section. This chapter closes with
a description of the type of instruments available for frequency
domain analysis. Information on
the time and frequency domains in
this application note is focused on
machinery vibration. For a more
general discussion of the subject
refer to Hewlett-Packard application note AN 243.
3.1 The Time Domain
One way to examine vibration
more closely is to observe how its
amplitude varies with time. The
time domain display in Figure
3.1-1 clearly shows how vibration
due to an imbalanced rotor varies
with time (we are using a displacement transducer to simplify
the phase relationship). The amplitude of the signal is proportional to the amount of imbalance,
and the speed of rotation. This
signal is easy to analyze because
we are using an idealized example
with a single source of vibration –
real world vibration signals are
much more complex.
When more than one vibration
component is present, analysis in
the time domain becomes more
difficult. This situation is illustrated in Figure 3.1-2, where two sine
wave frequencies are present. The
result of this combination is a
time domain display in which the
individual components are difficult to derive. The time domain is
a perspective that feels natural,
and provides physical insight into
the vibration. It is especially useful in analyzing impulsive signals
from bearing and gear defects,
and truncated signals from looseness. The time domain is also useful for analyzing vibration phase
relationships. However, the individual components of complex
signals are difficult to determine.
A perceptive that is much better
suited to analyzing these components is the frequency domain.
Figure 3.1-1 A
time domain
representation of vibration
due to rotor
Figure 3.1-2
Waveform (c) is
the combination
of signals (a) and
(b). The nature of
these components
is hidden in the
time domain view
of their sum.
3.2 The Frequency
Figure 3.2-1(a) is a three-dimensional graph of the signal used in
the last example. Two of the axes
are time and amplitude that we
saw in the time domain. The third
axis is frequency, which allows us
to visually separate the components of the waveform. When the
graph is viewed along the frequency axis, we see the same time
domain picture we saw in 3.1-2.
It is the summation of the two
sine waves which are no longer
easily recognizable.
However, if we view the graph
along the time axis as in Figure
3.2-1(c), the frequency components are readily apparent. In this
view of amplitude versus frequency, each frequency component appears as a vertical line. Its height
represents its amplitude and its
position represents its frequency.
This frequency domain representation of the signal is called the
spectrum of the signal.
The power of the frequency domain lies in the fact that any real
world signal can be generated by
adding up sine waves. (This was
shown by Fourier over one hundred years ago.) Thus, while the
example we used to illustrate the
frequency domain began as a summation of sine waves, we could
perform a similar reduction to
sine wave components for any
machinery vibration signal. It is
important to understand that the
frequency spectrum of a vibration
signal completely defines the
vibration – no information is lost
by converting to the frequency domain (provided phase information
is included).
analysis applied to machinery.
The internal sources of vibration
in this example are rotor imbalance, a ball bearing defect, and
reduction gear meshing. For purposes of illustration in this example, the sources of vibration
and their resulting frequency
components have been somewhat
simplified. (Details of the frequency components that each of
these defects produce are given in
Chapter 4.)
Imbalance produces a sinusoidal
vibration at a frequency of once
per revolution. If we assume a single defect in the outer race of the
ball bearing, it will produce an impulsive vibration each time a ball
passes over the defect – usually
around four times per revolution.
To simplify the example, we will
assume that this is a sine wave.
The two smaller sine waves around this frequency are caused
by interaction (modulation) of the
Figure 3.2-1
The relationship
between the time
and frequency
Figure 3.2-2
viewed in
the time and
A Machinery Example
Figure 3.2-2 should give you better
insight into frequency domain
bearing defect force with the imbalance force. These signals are
called sidebands, and occur often
in machinery vibration. They are
spaced at increments of plus and
minus the running speed from the
defect frequency. These components are often referred to as sum
and difference frequencies, and
are discussed in Section 5.3. The
gear mesh frequency appears at
running speed multiplied by the
number of teeth on the main shaft
gear, which here we assumed to
be ten. The running speed sidebands around the gear meshing
frequency usually indicate eccentricity in the gear. While this is a
greatly simplified view of machinery vibration, it demonstrates the
clarity with which vibration components can be seen in the frequency domain.
Figure 3.2-3
Small signals that
are hidden in the
time domain are
readily apparent
in the frequency
domain. By using
a logarithmic
amplitude scale,
signals which
vary in level by
a factor of over
1000 can be
Early Warning of Defects
As we pointed out in the introduction, DSAs are used to make machinery vibration measurements
in the frequency domain. This is
because the low level vibration
produced by early stages of some
defects cannot be detected by an
overall vibration meter. (In effect,
it is “buried” by the relatively
large residual imbalance component.) This is especially true of
rolling element bearings, and is
one of the reasons this particular
problem is one of the most difficult to detect.
A major advantage of the frequency domain is that low level signals
are easy to see – even in the presence of signals 1000 time larger.
This is illustrated in the time and
frequency domain displays of Figure 3.2-3, where the low-level signals that are readily apparent in
the frequency domain cannot be
seen in the time domain. A key to
this capability is logarithmic
display of amplitude.
While most people prefer the
more natural feel of a linear display, logarithmic displays are an
aid to displaying the wide dynamic range of data present in a DSA.
(Dynamic range is discussed in
section 6.4). We will present
examples using both linear and
logrithmic scales in this application note.
Spectrum Examples
Figure 3.2-6 shows the time and
frequency domain of four signals
that are common in machinery
(a) The frequency spectrum of a
pure sine wave is a single spectral
line. For a sine wave of period T
seconds, this line occurs at 1/THz.
(b) A distorted sine wave, produced by “clipping” the signal at some
prescribed amount on both the
positive and negative directions.
This is much like the truncated
signal produced by mounting or
bearing cap looseness and is made
up of a large number of odd harmonics. Harmonics are components which occur at frequency
multiples of a fundamental frequency. In machinery analysis,
we often refer to harmonics as
“orders” of the fundamental
running speed.
(c) Bearings and gears often produce impulsive signals that are
typified by harmonics in the frequency domain. These harmonics
are spaced at the repetition rate
of the impulse.
(d) Modulation can result when
some higher characteristic frequency interacts with a lower
frequency, often the residual imbalance. The frequency spectrum
of a modulated signal consists of
the signal being modulated (the
carrier), surrounded by sidebands
spaced at the modulating
Figure 3.2-6
Examples of
spectra common
in machinery
3.3 Spectral
setup used to produce it with a
Hewlett-Packard DSA with this
built-in capability (Figure 3.3-2).
The vibration characteristics of a
machine depend on its dynamics
and the nature of the forces acting
upon it. The change of these characteristics with machine speed
has two important implications
for analysis: (1) the vibration resulting from a defect may not appear in all speed ranges, and
(2) insight into the nature of the
machine may be obtained from
observing the change in vibration
with speed. Spectral maps1, such
as the one in Figure 3.3-1 are
three dimensional displays that effectively show variation in the vibration spectrum with time. These
are also called cascade plots.
Rpm spectral maps usually consist of a series of vibration spectra
measured at different speeds. A
variety of other parameters, including time, load, and temperature are also used as the third
dimension for maps and waterfalls. A common method for mapping the variations in the vibration
with rpm is to measure successive
spectra while the machine is
coasting down or running up in
speed. If the machine is instrumented with a tachometer, the
speed can be monitored and used
to trigger the measurement thus
obtaining vibration spectra at uniformly spaced rpm. Figure 3.3-1
illustrates such a map and the
In addition to showing how vibration changes with speed, spectral
maps/waterfalls quickly indicate
which components are related to
rotational speed. The components
will move across the map as the
speed changes, while fixed frequency components move straight
up the map. This feature is especially useful in recognizing
machine resonances (critical
speeds), which occur at fixed
3.4 The Phase Spectrum
The complete frequency domain
representation of a signal consists
of an amplitude spectrum and a
phase spectrum. While the amplitude spectrum indicates signal
level as a function of frequency,
the phase spectrum shows the
phase relation between spectral
components. In machinery vibration analysis, phase is required
for most balancing techniques.
It is also useful in differentiating
between faults which produce
Note: The distinction between maps and
waterfalls is often disputed. For the purposes of this note a waterfall is a “live”
continuously updating display that constantly updates itself with the latest spectrum while discarding the oldest. A map is
a display of multiple spectrums taken at
different times/conditions; often requiring
complete regeneration to add additional
similar amplitude spectra. DSAs
are unique among commonly used
frequency domain analyzers in
providing both amplitude and
phase spectra.
The concept of phase relationships is most easily seen in the
time domain. In Figure 3.4-1,
phase notation has been added to
the waveform we used in our first
time-domain example. One 360°
cycle of the rotor corresponds to
one cycle of the vibration signal.
This relationship holds regardless
of where we start on the circle,
but absolute phase numbers mean
nothing without a reference. In
Figure 3.4-1, we have defined the
reference point as A. This means
that in effect when the keyphasor
passes point A the time of the first
data point of the block is defined
as t=0. The actual phase is also
dependent upon the orientation
(and type) of the transducer. By
convention for a single-channel
measurement, a cosine wave (i.e.
positive maxima at t=0) is defined
as the zero phase reference.
Just as absolute phase can be defined relative to a reference point,
we can define the relative phase
of two signals of the same
frequency. The signals shown in
Figure 3.4-2 are separated by
1 quarter of a cycle, or 90°. We
say that the phase of the trace A
leads that of trace B because its
peak occurs first.
In the frequency domain, each
amplitude component has a corresponding phase. Figure 3.4-3 is a
DSA display of our imbalance
example, indicating a 90° phase
relationship between the frequency component and the trigger
signal (amplitude is shown as a
dashed line). The phase is -90°
because the peak of the signal
occurs after the trigger.
Figure 3.3-1
Spectral maps
show variation in
the vibration
spectrum with
time or rpm.
Figure 3.3-2
Set-up of DSA to
produce spectral
Figure 3.4-1
The phase of the
imbalance signal
corresponds to
the direction of
the displacement.
One 360º rotation
of the rotor corresponds to one
360º cycle of the
Figure 3.4-2
Two sine waves
with a phase
of 90º.
The most common application for
phase spectrum is in trim balancing. Recall from Figure 3.4-1 that
we need a reference for absolute
phase to be meaningful. In machinery analysis, this reference is
most often provided by a keyphasor – a displacement or optical
transducer which detects the passage of a keyway, set screw, or
reflecting surface. Figure 3.4-4
shows a keyphasor added to our
example machine. With the transducer 90° behind the keyphasor
(in the direction of rotation), and
the keyphasor and heavy spot
lined up, the resulting time
domain waveforms are offset in
phase by 90°. The corresponding
phase spectrum of the vibration
signal is as shown in Figure 3.4-3.
In this case, the keyphasor is used
to trigger the measurement.
Figures 3.4-3 and 3.4-4 indicate
the location of the heavy spot relative to the keyway. This information can be used in balancing to
locate a compensation weight opposite the heavy spot. This will
readily give information about the
location of the imbalance, but little information about the magnitude of the imbalance weight.
Unless the system has been calibrated previously on the same or
similar machines a two-measurement scheme which uses trial
weights is required to get accurate
data on the magnitude of the imbalance. For balancing, it’s important to note, that the previous
discussion assumed a displacement transducer; velocity transducers and accelerometers have
additional 90° and 180° phase
shifts that must be accounted for.
We have also assumed that the rotor is rigid. There are two areas of
caution. First is that a magnetic
phase detector (i.e. keyphasor)
can cause phase shifting errors.
This is due to the changing waveform shape with speed causing
the trigger point to move. The
other area is in balancing speed.
It is advisable that balancing not
be done close to resonance frequencies as the phase changes
very rapidly with speed near
resonances and this can lead to
considerable measurement error.
Other Applications of Phase
The phase spectrum is also useful
for differentiating between defects that produce similar amplitude spectra. In Section 4.4, we
will describe how axial phase
measurements can be used to
differentiate between imbalance
and misalignment. Section 5.2
explains how the relative stability
of phase can be used to gain
insight into the nature of defects.
Rigid and Flexible Rotors
We mentioned in the introduction
that flexible rotors required an understanding of the shaft dynamics
for complete analysis. As the
name implies, a flexible rotor is
one which bends during operation. This bending occurs at a natural frequency of the rotor, often
referred to as a critical speed. A
flexible rotor has several critical
speeds, each with a specific bending shape (or direction). These
shapes are called modes, and can
be predicted through structural
modeling and measured using
orbit analysis. The distinction
between rigid and flexible rotors
is important because the dynamics of a rotor change significantly
as it approaches and passes
through a critical speed. The
amplitude of the vibration
response peaks, and the phase
response shifts by 180°.
This phase shift is shown in the
plot of Figure 3.4-5 (commonly
referred to as a Bode plot). When
phase is measured at a speed well
above the critical, the high spot
measured by the displacement
transducer is at a point opposite
the imbalance – a phase shift of
180°. When operating speed is
near the critical speed, the phase
response will be shifted between
0° and 180°, depending on the
dynamics of the rotor.
Accurate interpretation of phase
spectra measured on flexible rotors requires an understanding of
rotor dynamics that is beyond the
cope of this application note.
Unless otherwise noted, all statements about the use of phase in
analysis refer only to rigid rotors
(those which operate well below
the first critical speed).
3.5 Frequency Domain
Instruments which display the
frequency spectrum are generally
referred to as spectrum analyzers,
although DSAs are also commonly
referred to as real-time or FFT
analyzers. There are three basic
types of spectrum analyzers:
(1) parallel filter, (2) swept filter,
and (3) DSA. This section will give
a short description of each, along
with advantages and disadvantages. For a more detailed discussion, refer to Hewlett-Packard
application note AN 243.
A simple block diagram of a parallel-filter analyzer is shown in
Figure 3.5-1. These analyzers have
several built-in filters that are
usually spaced at 1/3- or 1-octave
intervals. This spacing results in
resolution that is proportional to
frequency. For a 1/3-octave analyzer, resolution varies from
around 5 Hz at low frequencies to
several thousand Hertz (kHz) at
high frequency. A variation of the
parallel-filter analyzer that is
sometimes used in machinery
work has a bank of filters that can
be individually selected.
Parallel-filter analyzers offer a
good compromise between resolution and frequency span when
very large spans are required such
as in acoustics. They tend to be
expensive and do not have the
resolution required for many
machinery analysis applications.
Figure 3.4-3
DSA frequency
domain display
of a 90º phase
Referring to
Figure 3.4-2, this
is the phase of
trace B when
trace A is used to
trigger the
Figure 3.4-4
Since the heavy
spot on the rotor
passes the transducer 90º after
the keyway passes
the keyphasor,
the imbalance
signal lags the
keyphasor pulse
by 90º. The
corresponding frequency
domain phase
spectrum is
shown in
Figure 3.4-3.
Figure 3.4-5
The vibration
response of a
flexible rotor
shifts 180º in
phase as rpm
passes through a
critical speed.
Figure 3.5-1
Parallel filter
analyzers have
resolution for
Swept-filter analyzers use a
tuneable filter, much like a radio
receiver. The block diagram for
this type of analyzer is shown in
Figure 3.5-2. The frequency resolution of these instruments is on
the order of 1 to 5 Hz – better
than parallel-filter analyzers but
not good enough for many vibration analysis applications. They
are much slower than the parallelfilter analyzers as they must analyze each individual frequency one
at a time. The slowness of the
operation not only increases the
measurement time; it makes the
technique unacceptable for situations where non-steady data is
DSAs use digital techniques to
effectively synthesize a large
number of parallel-filters. The
large number of filters (typically
400 or more) provides excellent
resolution, and the fact that they
are parallel means that measurements can be made quickly.
DSAs also provide time- and
phase-spectrum displays, and
can be connected directly to computers for automated measurement. The DSA essentially uses
up FFT to create filters of constant-bandwidth resolution; unlike
the parallel filters that tend to be
proportional bandwidth. Being
digital in implementation, some
DSAs have the ability to analyze
the data in much the same way as
the parallel analyzers in addition
to its normal FFT mode; thus allowing addition flexibility. This
is referred to as digital real-time
octave analysis.
Figure 3.5-2
Swept filter
analyzers provide
better frequency
resolution than
parallel filter
analyzers, but
are too slow for
Figure 3.5-3
DSAs digitally
simulate hundreds of parallel
filters, providing
both high speed
and excellent
frequency resolution. DSAs also
provide time and
phase displays not
available on the
other frequency
domain analyzers.
Chapter 4
Vibration Characteristics of
Common Machinery Faults
In the last chapter, we saw how a
complicated time domain vibration signal can be reduced to simple spectral components using the
frequency domain. In Chapters 4
and 5, we will take the next step
in analysis – correlating these
components with specific machine characteristics or faults.
This chapter provides the basic
theory, while Chapter 5 addresses
some of the common analysis
problems and techniques.
Each machine defect produces a
unique set of vibration components that can be used for identification. This chapter describes
these vibration patterns or “signatures” for the most common
machinery defects. Where appropriate, frequency calculation formulas and details of spectrum
generation are also included. The
descriptions will give you the basic information needed to correlate vibration components with
defects; the details provide insights that will improve your ability to analyze unusual situations.
The table in Section 4.10 summarizes the vibration pattern descriptions of Chapter 4. It is important
to understand, however, that correlation is rarely as easy as matching vibration components on a
DSA display with those in a table.
Machinery dynamics, operating
conditions (e.g. load and temperature), multiple faults, and speed
variation all affect vibration, complicating the correlation process.
Methods of dealing with these
problems are the subject of
Chapter 5.
Converting a vibration spectrum
to a detailed report on machine vibration is another challenging aspect of vibration analysis. Chapter
4 and 5 are a starting point, providing a basis for building your
skills through experience.
4.1 Imbalance
Rotor imbalance exists to some
degree in all machines, and is
characterized by sinusoidal vibration at a frequency of once per
revolution. In the absence of high
resolution analysis equipment, imbalance is usually first to get the
blame for excessive once per revolution vibration – vibration that
can be caused by several different
faults. In this section, we will discuss spectral characteristics that
can be used to differentiate these
faults from imbalance, eliminating
unnecessary balancing jobs.
Phase plays a key role in detecting
and analyzing imbalance, and it is
important to remember the phase
shifts associated with flexible rotors (see Figure 3.4-5). A state of
imbalance occurs when the center
of mass of a rotating system does
not coincide with the center of rotation. It can be caused by a number of things, including incorrect
assembly, material build-up/loss,
and rotor sag. As shown in Figure
4.1-1, the imbalance can be in a
single plane (static imbalance) or
multiple planes (coupled imbalance). The combination is referred to as dynamic imbalance. In
either case, the result is a vector
that rotates with the shaft, producing the classic once per revolution vibration characteristic.
Distinguishing Characteristics
of Imbalance
The key characteristics of vibration caused by imbalance are:
(1) it is sinusoidal at a frequency
of once per revolution (1x)
(2) it is a rotating vector, and
(3) amplitude increases with
speed (i.e. F=mw2). These characteristics are very useful in differentiating imbalance from faults
that produce similar vibration.
Figure 4.1-1
whether static
or coupled,
results in a
spectral peak
at a frequency
of once per
revolution (1 x).
The driving force in imbalance is
the centrifugal forces caused by a
mass rotating about a center
point; as such, the vibration
caused by pure imbalance is a
once-per-revolution sine wave,
sometimes accompanied by lowlevel harmonics. The faults commonly mistaken for imbalance
usually produce high-level harmonics, or occur at a higher frequency. In general, if the signal
has high harmonics above once
per revolution, the fault is not a
simple imbalance. However, highlevel harmonics can occur with
large imbalance forces, or when
horizontal and vertical support
stiffnesses differ by a large
amount (see Section 4.4).
Because the imbalance force is a
rotating vector, the phase of vibration relative to a keyphasor follows transducer location, while
the amplitude changes are generally small. As shown in Figure
4.1-2, moving the transducer 90°
results in a 90° change in phase
reading with approximately the
same amplitude1. It is also common for the stiffness to vary
to some extent from vertical
to horizontal; this can under
some circumstances cause wide
variations in phase readings with
flexible rotors.
The amplitudes obtained from these two
readings can vary with support stiffness
and running speed. With flexible rotors,
small speed variations between the two
measurements will result in a phase relation very different from the one pictured.
Instrument Basic is an HP implementation
of the Basic programming language that
runs resident in many DSA analyzers.
4.2 Rolling-Element
Rolling-element (anti-friction)
bearings are the most common
cause of small machinery failure,
and overall vibration level changes are virtually undetectable in
the early stages of deterioration.
However, the unique vibration
characteristics of rolling element
bearing defects make vibration
analysis an effective tool for both
early detection and analysis of
The specific frequencies that result from bearing defects depend
on the defect, the bearing geometry, and the speed of rotation. The
required bearing dimensions are
shown in Figure 4.2-1, and are
usually available from the bearing
manufacturer. Included in this
section is an HP Instrument Basic2
program that computes the expected frequencies given bearing
parameters and rotation speed.
One caution: parameters of the
same model-number bearing can
change with manufacturer.
The major problem in detecting
the early stages of failure in rolling-element bearings is that the
resulting vibration is very low in
level and often masked by higher
level vibration. If monitoring is
performed with a simple vibration
meter (or in the time domain),
these low levels will not be detected and unpredicted failures
are inevitable (see Figure 3.2-3).
The advantage of a DSA is that
with the high resolution and dynamic range available, vibration
components as small as 1/1000th
the amplitude of higher level
vibrations can be measured and
Interestingly, some early indications of a bearing failure can later
be obliterated in the later stages
as the failure develops. For example, often in the early stages of
failure a very succinct vibration
Figure 4.1-2
The rotating nature
of the imbalance force
results in a phase
reading (relative to
a key phasor) that
follows transducer
location. This is useful in differentiating
imbalance from faults
which produce directional vibration.
component will be present. As the
failure develops, the overall energy of the fault will increase, but
often become more broad band in
nature and difficult to detect in
the presence of the other vibration
components of the machine (Fig
4.2-3). This appearance of “healing” can be misleading. The
example also illustrates a characteristic of frequency-spectrum
analysis: it’s usually easier to detect a distinct low-level narrowband tone than a wide-band signal
of high levels in the presence of
other signals or noise.
Frequencies Generated by
Rolling-Element Bearing
Formulas for calculating the frequencies resulting from bearing
defects are given in Table 4.2. The
formulas assume a single defect,
rolling contact, and a rotating inner race with fixed outer race.
The results can be expressed in
orders of rotation by leaving out
the (RPM/60) term. The I-Basic
program listing in Figure 4.2-2 will
compute the bearing frequencies
If bearing dimensions are not
available, inner- and outer-race
defect frequencies can be approximated as 60% and 40% of the number of balls multiplied by the
running speed, respectively. This
approximation is possible because
the ratio of ball diameter to pitch
diameter is relatively constant for
rolling-element bearings.
Figure 4.2-1
Using the parameters
shown, the basic
frequencies resulting
from rolling element
bearing defects can
be completed.
Table 4.2
Figure 4.2-2
The I-BASIC program
to compute bearing
characteristic frequencies. The specific unit
used in lines 230 and
240 is not critical, as
long as it is the same
for both.
While it isn’t necessary to understand the derivation of these formulas, two points of explanation
may give you a better feel for
them. (1) Since the balls contact
both the shaft-speed inner race
and the fixed speed outer race,
the rate of rotation relative to the
shaft center is the average, or 1/2
the shaft speed. This is the reason
for the factor of 1/2 in the formulas. (2) The term in parentheses is
an adjustment for the diameter of
the component in question. For
example, a ball passes over defects on the inner race more often
that those on the outer race, because the linear distance is shorter. Vibration components at the
fundamental-train frequency,
which occurs at a frequency lower
that running speed, is usually
caused by a severely worn cage.
Rolling-element bearing frequencies are transmitted well to the
machine case (because the bearings are stiff), and are best measured with accelerometers. For
bearings which provide axial support, axial measurements often
provide the best sensitivity to defect vibration (because machines
are usually more flexible in this
Factors That Modify Frequency
While the computation of characteristic
bearing frequencies is straightforward,
several factors can modify the vibration
spectrum that results from bearing
Example Spectra
The example spectrum of Figure
4.2-4 is the result of a defect in
the outer race. A printout of the
bearing data and characteristic
frequencies, computed with the
program given in Figure 4.2-2, appears below the spectrum. Note
the sidebands at running speed
which are characteristic of most
beginning spectra.
resulting spectra. The characteristics we will focus on are:
The spectrum in Figure 4.2-5 is
also the result of a defect in the
outer race. In this case, the characteristic ball-pass frequency has
disappeared, but its harmonics
remain. The component around
200 Hz is the gearmesh vibration.
In contrast to the sinusoidal vibration produced by imbalance,
vibration produced by bearing
defects is impulsive, with much
sharper edges. The effect of these
sharp edges is a large number of
higher frequency harmonics.
In Figure 4.2-6, the lower trace is
a time display of a simulated
defect and the upper trace is the
corresponding frequency spectrum. The defects are spaced at
10 ms intervals, resulting in a harmonic spacing of 100 Hz (1/10 ms)
in the frequency spectrum.
Some Details of
Spectrum Generation
To give you better insight into
how bearing spectra are generated, we’ll take a look at some simulated bearing signals and their
(1) the impulsive nature of bearing vibration (which produces
high frequency components),
(2) the effect of multiple defects,
(3) modulation of the bearing
characteristic frequencies by
running speed.
A. Bearing frequencies are usually
modulated by residual imbalance, which
will produce sidebands at running
frequency (see Figure 4.2-9). Other
vibration can also modulate (or be
modulated by) bearing frequencies, and
bearing spectra often contain components
that are sums or differences of these
frequencies (see Section 5.3).
C. Some of these frequencies will appear
in the vibration spectrum of a good
bearing. This is usually due to production
tolerances, and does not imply incipient
B. As bearing wear continues and defects
appear around the entire surface of the
race, the vibration will become much more
like random noise, and discrete spectral
peaks will be reduced, or disappear. This
will also be the case with roughness
caused by abrasive wear or lack of
lubrication. Another variation that occurs
in advanced stages is concentration of the
defect energy in higher harmonics of the
bearing characteristic frequency (see
Figure 4.2-6).
E. Contact angle can change with axial
load, causing small deviations from
calculated frequencies.
D. To modify the formulas for a stationary
shaft and rotating outer race, change the
signs in equations (1) and (2) of table 4.2.
F. Small defects in stationary races which
are out of the load zone will often only
produce noticeable vibration when loaded
by imbalance forces (ie. once per
Two important consequences of the high
frequency content are:
A. High-frequency resonances in the
bearing and machine structure may be
excited, resulting in non-order related
components not produced by other defects
(except gears). One type of vibration meter
designed for early detection of bearing
defects de-pends on these high
frequencies (20-50 kHz) to excite the
natural frequency of a special
accelerometer. (With no exciting
frequency in this range, the output of
the transducer is very low.) This type
of instrument can pro-duce misleading
results if the accelerometer is not
carefully mounted or if the defect is
such that little high frequency energy
is produced.
Figure 4.2-3
As bearing defects
progress, the vibration becomes
more like random
noise, and spectral peaks tend
to disappear.
Figure 4.2-4
HP Instrument
Basic print out of
bearing data and
frequencies with
spectra. The
result of a single
defect on outer
race is evident.
B. High-frequency content tends to
indicate the seriousness of the flaw,
since shallow defects will tend to be
more sinusoidal, producing fewer
high-frequency defects.
Figure 4.2-5
In this example
of an outer race
defect, the component at the ball
pass (outer race)
frequency has
disappeared, but
its harmonics
remain. This is
characteristic of
advanced stages
of a defect.
Figure 4.2-6
The impulsive
nature of bearing defects produces a large
number of
spaced at the
Multiple Defects and Running
Speed Sidebands
The characteristic spectrum of
multiple bearing defects is difficult to predict, depending heavily
on the nature of the defects,
Figures 4.2-7(a) and (b) show two
simulated multiple defects and
their resulting spectra. Note that
as long as the sequence repeats
itself at the appropriate characteristic frequency, the spacing of the
harmonics will be at that frequency. in this case, only the harmonic
amplitudes will change.
Every machine has some residual
imbalance which will amplitude
modulate the bearing frequencies.
In Figure 4.2-8, a bearing defect
pulse is being modulated by imbalance. The imbalance component appears at the 21 Hz running
speed, and as sidebands around
the bearing frequency harmonics.
This type of spectrum is common
with bearing defects. Note that
other defects, such as looseness
or misalignment, will also modulate the bearing frequencies.
Figure 4.2-7
Two simulated
examples of
multiple defects.
Note that the
harmonic spacing
remains at the
Figure 4.2-8
Bearing frequencies are almost
always modulated
by residual imbalance at running
4.3 Oil Whirl in
Fluid-Film Bearings
Rotors supported by fluid-film
bearings are subject to instabilities not experienced with rolling
element bearings. When the instability occurs in a flexible rotor
at a critical speed, the resulting
vibration can be catastrophic.
Several mechanisms exist for producing instabilities, including
hysteresis, trapped fluid, and shaft
vibration interacting with bearings. In this section we will
discuss only fluid-bearing instabilities, which are the most common.
A basic difference exists between
vibration due to instability, and
vibration due to other faults such
as imbalance. Consider the case
of a shaft imbalance. Vibration of
the shaft is a forced response to
the imbalance force, occurs at the
same frequency, and is proportional to the size of the force.
Instability, on the other hand, is a
self-excited vibration that draws
energy into vibratory motion that
is relatively independent of the
rotational frequency. The difference is subtle, but has a profound
effect on measures taken to
address the problem.
Oil Whirl and Whip
Deviation from normal operating
conditions (attitude angle and
eccentricity ratio) are the most
common cause of instability in
fluid-film bearing supported
rotors. As shown in Figure 4.3-1,
the rotor is supported by a thin
film of oil. The entrained fluid
circulates at about 1/2 the speed
of the rotor (the average of shaft
and housing speeds). Because of
viscous losses in the fluid, the
pressure ahead of the point of
minimum clearance is lower than
behind it. This pressure differential causes a tangential destabilizing force in the direction of the
rotation that results in a whirl – or
precession – of the rotor at slightly less than 1/2 rotational speed
(usually 0.43 - 0.48).
Whirl is inherently unstable,
since it increases centrifugal forces which in turn increase whirl
forces. Stability is normally maintained through damping in the
rotor-bearing system. The system
will become unstable when the
fluid can no longer support the
shaft, or when the whirl frequency
coincides with a shaft-natural
Changes in oil viscosity or pressure, and external preloads are
among the conditions that can
lead to a reduction in the ability
of the fluid to support the shaft.
In some cases, the speed of the
machine can be reduced to eliminate instability until a permanent
remedy can be found. Stability
sometimes involves a delicate balance of conditions, and changes
in the operating environment may
require a bearing redesign (e.g.
with tilting pad or pressure dam
designs). Whirl may also cause
instability when the shaft reaches
twice critical speed. At this speed,
the whirl (which is approximately
1/2 running speed) will be at the
critical speed, resulting in a large
vibration response that the fluid
film may no longer be able to support. The spectral map display
of Figure 4.3-2 illustrates how oil
whirl becomes unstable oil whip
when shaft speed reaches twice
critical and the oil whirl coincides
with a rotor-natural frequency.
Whirl must be suppressed if the
machine is to be run at greater
than twice the critical speed.
Figure 4.3-1
A pressure
in fluid-film
bearings produces a tangential force
that results
in whirl.
Figure 4.3-2
A spectral map
showing oil
whirl becoming
oil whip instability as shaft
speed reaches
twice critical.
4.4 Misalignment
Vibration due to misalignment is
usually characterized by a 2x
running speed component and
high axial vibration levels. When
a misaligned shaft is supported by
rolling-element bearing, these
characteristic frequencies may
also appear. Phase, both end to
end on the machine and across
the coupling, is a useful tool for
differentiating misalignment from
Misalignment takes two basic
forms: (1) preload from a bent
shaft or improperly seated bearing, (2) offset of the shaft center
lines of machines in the same
train and (3) angular misalignment. Flexible couplings increase
the ability of the train to tolerate
misalignment; however, they are
not a cure for serious alignment
problems. The axial component of
the force due to misalignment
is shown in Figure 4.4-2. Machines
are often more flexible in the axial
direction, with the result that high
levels of axial vibration usually
accompany misalignment. The
high axial levels are a key indicator of misalignment.
High second harmonic vibration
levels are also a common result
of misalignment. The ratio of 1x
to 2x component levels can be
used as an indicator of severity.
Second harmonics are caused by
stiffness asymmetry in the machine and its supports, or in the
coupling. This asymmetry causes
a sinusiodal variation in response
level – a form of rotating impedance vector. The vibration that
results from the rotating force
and impedance vectors contains
a component at twice the
rotating frequency, as shown
in Figure 4.4-1.
Vibration due to misalignment
often also contains a large number
of harmonics, much like the
characteristic spectra of looseness and excessive clearance. The
key distinguishing feature is a
high 2x component, especially in
the axial direction.
Using Phase to Detect
As shown in Figure 4.4-2, the
axial vibration at each end of the
machine (or across the coupling)
is 180º out of phase. This relationship can be used to differentiate
misalignment from imbalance,
which produces in-phase axial
vibration. This test cannot be used
in the radial direction, since
imbalance phase varies with the
type of imbalance. Relative phase
can be measured with a singlechannel DSA using a keyphaser
reference, or directly with a dualchannel DSA (see Section 6.8).
Several notes of caution relative to phase
measurements are appropriate at this
A. Machine dynamics will affect phase
read-ings, so that the axial phase
relationship may be 150° or 200° rather
than precisely 180°.
B. Transducer orientation is important.
stages of gear defects are often difficult
to analyze. Transducers mounted axially to
the outside of the machine will most often
be oriented in opposite directions. If this is
the case, a 180° phase relationship will be
measured as 0°.
C. Great care must be exercised when
meas-uring relative phase with a singlechannel DSA. Two measurements are
required, each referenced to the shaft
with a keyphasor (or similar reference).
These measurements should be made at
the same speed. In gen-eral, you should
make more than one meas-urement at
each point to insure that phase readings
are repeatable.
Figure 4.4-1
problems are
usually characterized by
a large 2 x
running speed
component, and
a high level of
axial vibration.
Figure 4.4-2
A bent or misaligned shaft
results in a
high level of
axial vibration.
4.5 Mechancial Looseness
Mechanical looseness usually
involves mounts or bearing caps,
and almost always results in a
large number of harmonics in the
vibration spectrum. Components
at integer fractions of running
speed may also occur. Looseness
tends to produce vibration that
is directional, a characteristic that
is useful in differentiating looseness from rotational defects such
as imbalance. A technique that
works well for detecting and
analyzing looseness, is to make
vibration measurements at several
points on the machine. Measured
vibration level will be highest in
the direction and vicinity of the
looseness. Also measuring vibration level on a bolt and comparing
the level measured on the housing
can pinpoint where to shim and
up. While these waveforms are
idealized, the mechanism for
producing harmonics should be
clear. The general term for
deviation from expected behavior,
as when the sinusoidal vibration
is interrupted by a mechanical
limit, is non-linearity.
Belt drives present one situation
where looseness does not result in
a large number of harmonics. In
this case, the impacts and sharp
truncations are damped by the
belt and the resulting vibration is
largely once per revolution. The
directionality that usually accompanies looseness results in vibration levels that vary significantly
with transducer direction. In other
words, while imbalance response
is usually about the same in horizontal and vertical directions,
looseness in a mount that produces a large vertical component may
produce a much smaller horizontal component.
Figure 4.5
Looseness usually
results in a truncated waveform
that produces a
spectrum with a
large number of
both odd and even
The harmonics that characterize
looseness are a result of impulses
and distortion (limiting) in the
machine response. Also, measuring vibration level on a bolt and
comparing the level measured
on the housing can pinpoint where
to shim and troque. Consider the
bearing shell in Figure 4.5. When
it is tight, the response to imbalance at the transducer is sinusoidally varying. When the mounting
bolt is loose, there will be truncations when the looseness is taken
4.6 Gears
Gear problems are characterized
by vibration spectra that are
typically easy to recognize, but
difficult to interpret. The difficulty
is due to two factors: (1) it is
often difficult to mount the
transducer close to the problem,
and (2), the number of vibration
sources in a muilti-gear drive
result in a complex assortment
of gear mesh, modulation, and
running frequencies. Because of
the complex array of components
that must be identified, the high
resolution provided by a DSA is a
virtual necessity. It is helpful to
detect problems early through
regular monitoring, since the
advanced stages of gear defects
are often difficult to analyze.
Baseline vibration spectra are
helpful in analysis because highlevel components are common
even in new gear boxes. Baseline
spectra taken when the gearbox
is in good condition make it easier
to identify new components,
or components that change
significantly in level.
Hints On Gear Analysis
A. Select And Mount Transducers
Carefully. If gearmesh or natural
frequencies above 2000 Hz are expected,
use an accelerometer. Mounting should be
in the radial direction for spur gears, axial
for gears that take a thrust load, and as
close to the bearings as possible.
B. Determine Natural Frequencies. Since
recognition of natural frequencies is so
important for analysis, take every opportunity to determine what they are. This
can be done by impacting the shaft of the
as-sembled gearbox, and measuring the
vibration response of the housing. This
measurement should be done with a twochannel DSA for best results (Section 6.8),
but a single-channel measurement will
give you an idea of the frequencies to
C. Identify Frequencies. Take the time to
diagram the gearbox, and identify gearmesh and shaft speed frequencies. Even if
you don’t know the natural frequencies,
shaft speed sidebands will often indicate
the bad gear.
Characteristic Gear
A. Gear Mesh: This is the frequency most commonly associated
with gears, and is equal to the
number of teeth multiplied by the
rotational frequency. Figure 4.6-2
is a simulated vibration spectrum
of a gearbox with a 15-tooth
gear running at 3000 rpm (50 Hz).
The gear-mesh frequency is 15 x
15 = 750 Hz. This component will
appear in the vibration spectrum
whether the gear is bad or not.
Low-level-running-speed sidebands around the gearmesh
frequency are also common.
These are usually caused by
small amounts of eccentricity or
The amplitude of the gearmesh
component can change significantly with operating conditions,
implying that gearmesh level is
not a reliable indication of condition. On the other hand, high-level
sidebands or large amounts of
energy under the gearmesh or
gear-natural-frequency components (Figure 4.6-2), are a good
indication that a problem exits.
B. Natural Frequencies: The impulse that results from large gear
defects usually excites the natural
frequencies of one or more gears
in a set. Often this is the key indication of a fault, since the amplitude of the gearmesh frequency
does not always change. In the
simulated vibration spectrum
of Figure 4.6-2, the gearmesh
frequency is 1272 Hz. The broadband response around 600 Hz is
centered on a gear-natural frequency, with sidebands at the
running speed of the bad gear.
The high-resolution-zoomed spectrum of 4.6-2(b) shows this detail.
C. Sidebands: Frequencies generated in a gearbox can be modulated by backlash, eccentricity,
loading, bottoming, and pulses
produced by defects. The sidebands produced are often valuable
in determining which gear is bad.
In the spectrum of Figure 4.6-2(b),
for example, the sidebands
around the natural frequency
indicate that the bad gear has a
running speed of 12.5 Hz. In the
case of eccentricity, the gearmesh
frequency will usually have
sidebands at running speed.
Figure 4.6-1
The characteristic spectrum
of a gearset in
good condition
contains components due to
running speed
of both shafts,
and gear-meshing frequency.
4.7 Blades and Vanes
Problems with blades and vanes
are usually characterized by high
fundamental vibration or a large
number of harmonics near the
blade or vane passing frequency.
Some components of passing
frequency (number of blades
or vanes x speed) are always
present, and levels can vary markedly with load. This is especially
true for high speed machinery,
and makes the recording of operating parameters critical. It is very
helpful in the analysis stage to
have baseline spectra for several
operating levels.
If a blade or vane is missing, the
result will typically be imbalance,
resulting in high 1x vibration. For
more subtle problems such as
cracked blades, changes in the
vibration are both difficult to
detect and difficult to quantify.
Detection is a problem, especially
in high- speed machinery, because
blade vibration can’t be measured
directly. Strain gauges can be
used, but the signal must be either
tele-metered or transferred
through slip rings. Indirect detection produces a spectrum that
is the result of complex interactions that may be difficult to
explain. This, combined with
the large variation of levels
with load, make spectra difficult
to interpret quantitatively.
Figure 4.6-2
Gear natural frequencies, excited
by impulses from
large defects, are
often the only
indication of
problems. The
zoom spectrum
in (b) shows the
natural frequency,
with sidebands
that correspond
to running speed
of the bad gear.
Figure 4.7
A space in the
vibration signal caused by
a missing blade
results in a
large number
of harmonics.
A missing
blade usually
also causes
enough imbalance to
increase the
1 x level.
One characteristic that often
appears in missing- or crackedblade spectra is a large number of
harmonics around the blade passing frequency. Figure 4.7 shows
how a space in the vibration signal greatly increases the number
of harmonics without changing
the fundamental frequency.
4.8 Resonance
Problems with resonance occur
when natural frequencies of the
shaft, machine housing, or attached structures are excited by
running speed (or harmonics of
running speed). These problems
are usually easy to identify
because levels drop appreciably
when running speed is raised
or lowered. Spectral maps are
especially useful for detecting
resonance vibration because the
strong dependence on rotational
speed is readily apparent (see
Figure 4.8). Phase is also a useful
tool for differentiating resonances
from rotationally related components. Say, for example, that you
encounter a high level of vibration
at 16-times running speed. If the
vibration is rotationally related
(e.g. a blade passing frequency),
the phase relative to a keyphasor
signal or residual imbalance will
be constant. If the vibration is a
resonance, the phase will not be
constant. This is a useful technique when it is not practical to
vary the speed of the machine.
Piping is one of the most common
sources of resonance problems.
When running speed coincides
with a natural frequency of the
pipe, the resulting vibration will
be excessive, and strain on both
the pipe and the machine can lead
to early failure. The most logical
approach is to change the natural
frequency of the pipe. It can be
raised by making the pipe shorter
or stiffer (e.g. by adding a support), or lowered by making the
pipe longer (see Figure 2.1-9). The
same rules apply to any attached
structure. Structural analysis of
the structure by measuing operating mode shapes is useful in
determining optimal positioning
of supports and braces.
Shaft resonance problems in highspeed machinery are sometimes
caused by changes in the stiffness
provided by fluid-film bearings,
load changes, or by the effects
of machines added to the train.
Bearing wear, for example, can
reduce the stiffness of the shaft/
bearing system, and lower the resonant frequency to running speed
multiples. Coupling changes can
raise or lower torsional natural
frequencies to running speed. The
dynamics of these situations can
be quite complex, and are beyond
the scope of this note. HewlettPackard application note AN 243-3
deals with the topic of measuring
the resonance and structural properties of machines in some detail.
The key is to understand that
maintenance and installation related factors can alter assumptions made in the rotor design.
Figure 4.8
Spectral Maps are
especially useful
for analyzing vibration due to
4.9 Electric Motors
4.10 Summary Tables
Excessive vibration in electric
motors can be caused by either
mechanical, or electromagnetic
defects. The latter can often
be isolated by removing power:
vibration caused by electrical or
magnetic defects will disappear.
The high frequency resolution
of DSAs is key for analyzing
electrical problems in induction
motors, since running speed and
power-line related components
are often very closely spaced (see
Section 6.3 on resolution).
Tables 4.10-1 (below) and 4.10-2
(next page) summarize the vibration characteristics information
in this chapter. This information
should be used as a guide only,
since the vibration resulting from
specific defects can be modified
by machinery dynamics.
Vibration caused by electrical
problems in induction motors can
be analyzed to determine the
nature of the defect. In general, a
stationary defect such as a shorted stator produces a 2 x powerline
frequency component. A rotating
defect, such as a broken rotor bar,
produces 1 x running speed with
2 x slip frequency sidebands. (Slip
frequency = line synchronous
frequency – running frequency).
Table 4.10-1
Phase Characteristics of
Common Vibration Sources
Rolling element
bearing defect
Gear mesh
Oil whirl
Unstable unless synchronous motor
Stable unless caused by uneven loading or cavitation.
Phase follows transducer location (4.1)
Unstable; may be highly directional
Stable; relation between axial phase at shaft
ends should be approximately 180°
Unstable; large phase change with change in
speed in rpm.
The vibration spectrum of induction motors always contains
significant components at powerline frequency times the number
of poles. A great deal of research
has been done on the subject of
relating the spectrum of the electric supply current to specific
problems. A number of commercially available software products
which can readily identify electric-motor faults from frequency
spectra of the current taken with
a DSA and a current probe.
Table 4.10-2
Vibration Frequencies
Related To Machinery
1 x rpm
Possible Cause
Misalignment or Bent Shaft
2 x rpm
N x rpm
Misalignment or Bent Shaft
Oil whirl
Bearing cage
Rolling element bearings
N x powerline Electrical
Steady phase that follows transducer. Can
be caused by load variation, material
buildup, or pump cavitation.
High axial levels, ~180° axial phase
relation at the shaft ends. Usually
characterized by high 2x level.
Caused by casing or foundation distortion,
or from attached structures (e.g. piping).
Directional – changes with transducer
location. Usually high harmonic content and
random phase.
Drops off sharply with changes in speed.
From attached structures or changes in
attitude angle or eccentricity ratio.
Broken rotor bar in induction motor. 2x slip
frequencies sidebands often produced.
High levels of axial vibration.
Impulsive or truncated time waveform;
large number of harmonics.
Shaft contacting machine housing.
Typically 0.43 - 0.48 rpm; unstable phase
See formula in Table 4-2.2
See formulas in Table 4-2.2 Usually
modulated by running speed.
Gearmesh (teeth x rpm); usually modulated
by running speed of bad gear.
Belt x running speed and x 2 running.
Number of blades/vanes x rpm; usually
present in normal machine. Harmonics
usually indicate that a problem exists.
Shorted stator; broken or eccentric rotor.
Several sources, including shaft, casing,
foundation and attached structrues.
Frequency is proportional to stiffness and
inversly proportional to mass.
Chapter 5
Advanced Analysis
and Documentation
5.1 Practical Aspects of
In the literature and discussions
on the subject of machinery vibration analysis, several factors are
regularly mentioned as keys to
success. In this section, we will
discuss five of these factors:
(1) documentation, (2) machinery
knowledge, (3) severity criteria,
(4) instrumentation, and (5)
analysis personnel. Its important
to note that a clear objective as
to the purpose and scope of the
measurements must be established. As noted in Chapter 1,
there are a number of reasons for
undertaking a vibration analysis
program (for example, new machine development, quality improvement, maximize service life,
maintenance program, and field
balancing). It is important at the
onset of the program to have a
clear understanding of the purpose of the measurement; why
and how each measurement is to
be used; and a sound basis for
making the measurement.
Chapter Overview
5. Advanced Analysis and Documentation
Chapters 1 through 4 provide the basic information needed for the analysis of machinery
vibration. Chapter 5 contains practical information that will help in determining specific
defects, and in assessing their severity.
5.1 Pracitical Aspects of Analysis
A discussion of 5 practical aspects for successful analysis.
5.2 Using Phase for Analysis
We have discussed the importance of phase in analyzing imbalance and misalignment.
This section is an extension of that discussion, and an introduction to the related
concept of time averaging.
5.3 Sum and Difference Frequencies
Multiple defects often produce vibration components that are sums and differences of
characteristic frequencies.
5.4 Speed Normalization
A common problem when making direct spectral comparisons is shift in frequency of
vibration components caused by changes in running speed. This section discusses
solutions to this problem.
5.5 Baseline Data Collection
Records of vibration spectra taken when a machine is in good condition or of a similar
machine can provide significant insight into the interpretation of machinery vibration
data. This section presents guidelines for collecting baseline data.
Figure 5.1-1
Complete documentation
consists of baseline
vibration spectra,
maintenance history,
and engineering data.
Thorough documentation often
provides the information required
to successfully analyze a vibration problem. Complete documentation includes baseline
vibration spectra, machine maintenance history, and engineering
The baseline vibration measurements made on a machine provide
a reference for detecting changes
or differences which indicate
problems — and for identifying
significant components when
problems do occur. Without this
information, you can easily waste
time determining the source of
a vibration component that is
perfectly normal and expected.
History records include machine
failures, and vibration spectra before and after significant modifications or repairs. These records
are often in the form of computer
digital data and organized in an
information data base. You
should, for example, be able to
immediately identify the changes
in the vibration spectrum of a machine that has had a major modification. This will immediately
give some insight into the relationship between major machinery components and the vibration
Engineering data includes bearing
and gear parameters used to calculate characteristic frequencies,
and machine dynamic models
used to predict vibration response
characteristics (or as an alternative, the results of a structural
test conducted on the machine).
Also useful are manufacturer’s
data on vibration limits and characteristics. This data will not
always be easy to obtain — the
key is to collect the available data
before hand so it is available for
correlation with measured vibration data.
Computers have become an
indispensable tool in organizing
records and data. A number of
software suppliers offer products
that organize vibration data,
analyze trends (Fig 5.1-1), and
provide detailed correlation of
spectra with known characteristic
frequencies. In some cases such
as ball bearings, they even provide a data base of characteristic
frequencies by product number.
Machinery Knowledge
The design and operating characteristics of a machine determine
both the type of defects that are
possible, and the vibration response to those defects. Vibration analysis is difficult without a
working knowledge of these characteristics. Another important
consideration is the effect of
changes in operating condition
on measured vibration. By understanding how vibration changes
with such variables as load and
temperature, you will be better
able to determine whether an increased level of vibration is due
to a defect, or to a change in
operating conditions.
The best sources of information
on these characteristics are the
manufacturer of the machine, and
historical records on the same or
similar machines. In applications
such as machinery maintenance,
courses from manufacturers can
provide insight into both the possible defects, and the mechanisms
of vibration response for specific
machines. Several baseline spectra taken under different operating conditions are useful for
documenting the effects of changing operating parameters.
Severity Criteria
Once a vibration spectra is measured and its individual components identified and correlated,
the problem of interpreting the
severity of the vibration level
(amplitude) often arises. Machines will inevitably vibrate and
will also undoubtedly produce
spectral components at characteristic frequencies given the resolution and sensitivity of modern
DSAs. The issue then becomes —
what is an acceptable level? It is
difficult to generalize here but a
number of sources are useful.
Figure 5.1-1
An example of a
"trend analysis"
simplified from
vibration spectrum
data over a period
of weeks/months
by post-test
analysis software.
Figure 5.1-2
Tables of vibration severity,
like this one
published by the
ISO, * are most
useful as guidelines rather than
absolute limits.
Vibration Severity
In./sec. mm/sec
Support Classification
Hard Supports
Soft Supports
* This material is reproduced with
permission from International Organization for Standardization Standard 39451977, Mechanical Vibration of Large
Rotating Machines with Speed Range
from 10 to 200 rev/s - Measurement and
Evalutation of Vibration Severity in Situ,
copyrighted by the American National
Standards Institute, 1430 Broadway, New
York, NY 10018.
References for severity include
published vibration standards and
historic vibration measurements.
The table in Figure 5.1-2 is an
example of a published vibration
standard. This particular standard is from the International
Standards Organization (ISO).
To make the standard more
applicable to a wide range of
machines, a distinction is made in
the severity criteria between soft
and hard supports. The essential
problem with such published
standards is that they are too
general to allow us to make high
accuracy judgements with the
power and accuracy available
with modern DSAs. They were
originally devised as a tool for interpreting severity on the basis of
overall level measurements. Modern analyzers can identify components of the vibration which
contribute negligibly to the overall spectral energy, but may be
indicative of very important local
A number of techniques have
been developed for refining the
method of defining the severity
critera for frequency bands in the
vibration spectrum. Figure 5.1-3
is an example of one technique
that breaks the spectrum into 6frequency bands and specifies the
allowable severity level for each
band based on the predominant
vibration mechanism present in
each particular band.
Historic vibration measurements
are an excellent reference for
severity measurements, because
they are specific to the machine
or type of machine in question. In
the case of machine development
or modification the historical data
on a machine or class of machines
can provide a valuable “yard stick”
by which to began the evaluation.
While absolute vibration limits
for a machine may not be known,
there is a high probability that
large changes in vibration level
indicate something significant
with respect to the operating condition of the machine. The process of monitoring vibration level
for changes is referred to as,
trend analysis. Since the vibration level in a machine is variable,
it isn’t always obvious how much
change is tolerable. The best approach is to analyze the statistics
of variability for each machine,
and base change limits on that.
An increase in vibration that exceeds two standard deviations is
usually a sign of a problem. In
the absence of this type of analysis, you can use a factor of 2 increase as an approximate change
limit threshold.
When significant changes are detected, vibration level and other
key operating parameters should
be monitored regularly. The rate
of change of these parameters is
a good indication of the severity
of the problem. The existence of
a consistent pattern of change is
indicative of a developing problem and/or changing operating
A wide variety of features and
capabilities are available in instrumentation ranging from transducers to DSAs to applications
software. Chapter 6 addresses
many of the issues in the selection of DSAs but it's important to
put the instrumentation requirements in the context of the individual task being addressed. In
many applications particular performance issues or features can
be critical to the measurement,
while others are convenience features or totally superfulous.
For example, in predictive
maintenence or troubleshooting
applications portablility and battery operation could outweigh
considerations of dynamic range,
Figure 5.1-3
A specification
of machine severity
criteria by specifying individual
frequency band
* This material is reproduced with permission from reference [8]: Berry, James E.,
Proven Method for Specifying Spectral
Band Alarm Levels and Frequencies
Using Today's Predictive Maintenance
Software Systems, Technical Associates
of Charlotte, Inc., 1990).
real-time bandwidth or programmability. In the case of production quality testing of automobile
engines; automation and measurement time will be more important
than portability. It would be nice
to have an instrument, that is portable, fast, programmable, etc..
But these attributes are not easily
attainable, often not necessary
and undoubtedly expensive.
Though expense is frequently the
driving factor; it is important to
put cost in its proper prospective,
and access the return on investment. A computer and applicable
software that automatically retrieves vibration data and analyzes trends can quickly pay for
itself. Instrumentation with a
general purpose feature set, high
performance, a convenient-user
interface, often finds itself being
used in many applications not initially envisioned. Programmability is another cost factor that will
direcly impact use ability. Instruments with built in HP Instrument
Basic can greatly reduce measurement automation tasks and
can circumvent the need for an
external computer to control
and automate processes. Easy
programmability will allow
less skilled personnel to collect
data and do preliminary level
severity checks.
The quality and effectiveness of
a vibration analysis program is
most often limited by the availability of capable and skilled
personel. Successful programs
are characterized by people who
are properly trained and given a
chance to develop analysis expertise. In some applications it is
neither practical nor desirable
to train individual operators as
vibration analysts. An example
Table 5.2-1
Phase Characteristics of Common
Vibration Sources
Rolling element
bearing effect
Unstable unless synchronous motor
Gear mesh
Stable, unless caused by uneven loading
or cavitation. Phase follows transducer
location (4.1)
Unstable , may be highly directional
Stable, relation between axial phase at
shaft ends should be approximately 180°
Oil Whirl
Unstable, large phase change with
change in speed in rpm.
would be a production assembly
person. In this case the need for
training can be aleviated to some
extent by built-in automation
capability which can make repetitive measurements and access
the results.
Also consider and experienced
consultant to help setup and establish your maintenance program. The consultant can help
overcome the extensive expertise
required early on in the establishment of a machine vibration monitoring program. With time, more
and more of the task can be taken
over by local personnel.
5.2 Using Phase for
The usefulness of the phase spectrum as a means for differentiating between defects with similar
amplitude spectra has already
been discussed. We will present
a more general discussion of the
subject in this section. Time averaging, a powerful processing
technique related to phase, will
also be described.
In general, the phase of vibration
caused by a defect will either be
stable or unstable relative to a
fixed reference (i.e. keyphasor).
The nature of this relationship is
shown in Table 5.2-1. Figure 5.2-1
is a sequence of vibration spectra
that shows phase for imbalance
(1x), and running speed harmonics, and unstable phase for powerline related components. Also,
the relative phase relationship
between vibration at different
points on a machine can be used
to differentiate between faults —
as in the case of misalignment
and imbalance (see Section 4.4).
Instrumentation required for
phase measurements is shown in
Figure 5.2-2 and 5.2-3. The keyphasor senses shaft rotation and
serves as the phase reference.
The phase of vibration that is synchronous (i.e. an integer multiple)
with rotation is constant, while
that of nonsynchronous vibration
varies. Relative phase measurements can be made sequentially,
as long as the same reference (i.e.
keyphasor) is used (see Section
6.8 on a dual-channel DSA).
Running speed should remain
constant between measurements
to minimize the phase effects of
mechanical impedance. Relative
phase measurements on flexible
rotors must include considerations of shaft dynamics.
signal to provide a more stable
The keyphasor, which is often a
proximity sensor that detects a
keyway or setscrew, provides a
relatively good signal for triggering. Because the gap of the proximity probe can vary with speed,
there can be some error in the
phase measurement as the trigger
point shifts with the gap causing
the actual position on the shaft of
the trigger point to vary to some
degree. A better trigger is often
obtainable with an optical sensor
and reflective tape or paint.
Sometimes an electrical signal
such as the spark ignition on a
gasoline engine is used, though
here again, there is a propensity
for this to shift under differing
operating conditions (vacuum
Figure 5.2-1
A sequence of
vibration spectra
with phase shows
constant phase for
imbalance (1 x and
harmonics), and
unstable phase
for power-line
(60 Hz harmonics).
The actual vibration signal is
usually not suitable for triggering
even though there exists some
instrumentation designed for
this purpose. This method relys
on the fact that the imbalance
(1x) is often the largest component; however, noise in the spectrum adds uncertainty to level,
and thus trigger timing. If an independent tachometer reference
is not practical, then it may be
possible to use a band-pass or
low pass filter to reduce the level
of noise and higher frequency
components in the vibration
When measuring relative phase
between two ends of a machine, it
is important to mount the transducer with the same orientation.
When measuring axial vibration,
for example, if both transducers
face the machine, they are
mounted 180° out of phase.
Thus vibration due to misalignment, which you would expect to
be 180° out of phase, will be measured as in phase. It is likewise
Figure 5.2-2
setup for phase
and time averaging.
Figure 5.2-3
Alternate instrumentation setup for
relative phase
mesurements using
2 channel DSA.
important to remember that phase
response of a system is related to
the variable measured; that is,
displacement and acceleration
measurements are 180° out of
phase and if the phase between
these is being compared, it is necessary to take into account any
phase difference between different types of motion variables.
Time averaging is explained in
Section 6.4, and is a powerful
technique for eliminating nonsynchronous components from a
vibration spectrum. It is most
useful for reducing the level of
background noise, especially vibration from other machines. It
must be used with care, however,
since it will reduce the level of all
vibration components that are
nonsynchronous, including bearing and gear frequencies. In the
plot of Figure 5.2-4, a time-averaged spectrum (dashed line) is
overlaid on a non-averaged spectrum. The synchronous components have not changed in level,
while the nonsynchronous background noise components are
greatly reduced.
5.3 Sum and Difference
Vibration spectra often contain
components that are the result
of interaction between multiple
vibration mechanisms. These
components appear as sum and
difference frequencies of the
mechanisms involved, and can be
useful as indications of specific
problems, especially in gears and
bearings. When the major frequency components are closely
spaced, the difference frequency
is often audible. These “beat” frequencies are common in rotating
machinery and are the result of a
process called “modulation”.
In Figure 5.3-1, the difference between running speed at 144 Hz
and the 2nd harmonic of the line
frequency at 120 Hz is 24 Hz.
This component appears at 24 Hz
and as sidebands around the harmonics of the rotational speed.
The exact mechanisms which
generate sum and difference frequencies can be quite complex
and a detailed mathematical analysis is beyond the scope of this
note. However, you can get a feel
Figure 5.2-4
Time averaging
is effective in
reducing the level
of background
Figure 5.3-1
A vibration spectrum
with sum and
difference frequencies.
The 24 Hz difference
between rotational
frequency and the
120 Hz powerline
component appears
both as a discrete
signal, and as
side-bands around
rotational speed
Figure 5.3-2
The number of
sum and difference
components depends
on the number of
harmonics in the
signals involved.
Phase and frequency modulation are
also present and produce many of the
same sum and difference frequencies
but their phase relationships differ. A
detailed discussion of this is beyond
the scope of this note.
for the interactions involved by
thinking of them as a form of amplitude modulation1. In the trigonometric identity given below,
The most common faults indicated by sum and difference frequencies are associated with rolling
element bearings and gears.
cos(f1) * cos(f2) =
1/2[cos(f1+f2) + cos(f1-f2)]
A. Rolling element bearings.
Defects in rolling element bearings are almost always modulated
by residual imbalance. As the
wear progresses, and characteristic frequencies are replaced by
noise, these running frequency
sidebands may be the only indication of trouble (see Section 4.2).
it is apparent that the interaction
of one frequency with another
results in sum and difference
frequencies. If one of the signals
contains a large number of harmonics, then multiple sum and
difference frequencies will
appear. This is illustrated in
Figure 5.3-2. Phase can be an aid
in identifying sum and difference
frequencies, since it will be unstable unless the phase of both
sources is stable.
Figure 5.3-3
The Z axis in a map
or waterfall display
can be precisely
controlled by the
DSA trigger arming
B. Gears. As pointed out in Section 4.6, gear defects often appear
as gear natural frequencies with
sidebands at the running speed of
the defective gear. These running
speed sidebands may also appear
around the gearmesh frequency.
Spectral Map and
Waterfall Displays
Waterfalls and spectral maps are
a useful technique for detecting
changes with time and identifying
speed related components in a
variable-speed machine. Technically, a waterfall differs from a
map only in the way in which the
map is updated. Waterfalls generally are a continuously updating
display with the newest spectrum
appearing at the top of the display
and the oldest scrolling off at the
bottom (hence the name waterfall, from the appearance of the
data migrating down the trace
like a waterfall).
Spectral maps on the other hand
are generally a fixed set of data
starting at a defined time or condition (rpm) and ending as some
predetermined time or number
of spectra later. These are sometimes referred to as cascade plots
and appear the same once the
measurement has been paused.
Many people use the terms interchangeably causing some confusion as to what is meant.
Figure 5.3-3 shows the topology
of this type of three dimensional
display. The third dimension
(z-axis) is the number traces, rpm
increments, or time increments
in the display. This is controlled
by the analyzer's trigger- arming
capability which determines
when a spectrum will be acquired
and displayed. This allows for the
very precise determination of
when data will be taken and
5.4 Speed Normalization
A common problem in machinery
vibration analysis is running
speed variation — both long-term
and short-term. Short-term variations in speed make real-time
analysis difficult. Long-term variations make point-by-point comparisons between current and
baseline spectra virtually impossible. Synchronous sample control
(also known as order tracking)
can be used to compensate for
both problems while the measurement is in progress.
Traditionally, these systems
where limited to direct control of
the analog-to-digital sampler by
an external source synchronized
to the machine running speed.
Recently however, advances in
digital technology have allowed
for the sampling synchronization
to be performed digitally, thus
avoiding some of the problems
of the older analog technology.
Either scheme seeks to lock the
sample rate to the speed of the
machine so that speed related
components appear at a stationary frequency. This is very useful
in machinery analysis, as was discussed in Chapter 4, since most
machinery defects are related to
some shaft- rotation frequency.
The details of controlling the
sample rate and of digital order
tracking are discussed in Section
6.7 and Appendix A. A good way
to illustrate the effects of synchronous (or external) sample
control is with spectral maps
made in external and normal sample modes, as shown in Figure
5.4-1. These maps were made
during a run-up. Note in the
normal sample-mode map of (a),
rotational speed-related components move to the right as speed
increases, while fixed frequency
components (e.g. structural resonances and powerline related)
move straight up. In the external
sample-control map of (b), rotational speed-related components
move straight up the map, while
fixed frequency components
move to the left (they are relatively lower in frequency as speed
The main advantage of synchronous sample control is that realtime displays of the order related
spectral components remain fixed
Figure 5.4-1
Two spectral maps
of a machine run-up
illustrate the effect
of external sample
rate control.
Figure 5.4-2
A "slice marker"
function is used
to extract the order
related information
from the synchronously sampled
map display (lower)
and and constructs
an order track
(upper) for the
3rd order.
within the horizontal position
speed. During individual measurements (or especially with
averaging) speed variations do
not cause a “smearing” of the
frequency over a range. Another
advantage is the extraction of order tracks is greatly simplified
and the accuracy improved. An
order track is the plot of an individual order as the rotation speed
changes. Since the frequency of
these components has been normalized to a fixed value, a simple
marker function can be used to
extract the order track from the
map display (see figure 5.4-2).
Frequency can also be normalized
to rotational speed after a measurement. In the display of Figure 5.4-3, note that the frequency
axis and the readout are in terms
of orders of rotation (multiples
of running speed), rather than in
frequency. This technique simply
amounts to re-scaling the frequency axis when the running
speed is known or can be deduced, it is not normally useful
with map/waterfall displays. This
normalization does not work in
real time, and resolution is not a
constant percentage of running
speed (as with synchronous sample control). However, it is useful
when no tachometer/keyphasor
signal is readily available.
Short-term speed variation causes
a broadening of spectral lines in
the vibration spectrum, as shown
in Figure 5.4-4. As speed changes
during the sampling interval for
one measurement, the DSA is effectively analyzing several different spectra. This results in the
broadened spectral components
of Figure 5.4-4(b).
Figure 5.4-3
DSA display
in which the
(frequency) axis
is calibrated in
multiples (orders)
of running speed.
Figure 5.4-4
Short-term speed
variation results
in a broadening
of spectral
components (b).
a) Constant running speed
b) Changing running speed
5.5 Baseline Data
Baseline vibration spectra are reference data that represent normal
machine condition, and are essential to effective analysis. In the
event of trouble, they quickly indicate the frequency components
that have changed. Baseline data
is also the basis for trend monitoring; it is a much more specific
indicator of normal vibration than
generalized vibration severity
charts. To be most useful, the
guidelines below should be followed in collecting baseline data.
The key objective of the process
is to understand the characteristics of the machine.
A. Normalize for Speed.
Normalizing the vibration spectrum for speed is required for direct spectrum comparison.
Section 5.4 discussed the alternative methods for accomplishing this. Whichever method
is chosen, some provision should be made when taking baseline data.
A spectral map/waterfall of a run-up or coast-down is also useful in dealing with
changes in speed. A spectral map can quickly show how vibration level changes with
speed, and the resonances and other fixed frequencies that are present in the vibration
B. Be Complete
You can’t take baseline data after the machine has a problem, so it is important to take
all the data you can when it is operating normally. Follow the guidelines in Chapter 2 for
transducer selection and placement. For machines with rolling-element bearings or
gears, consider taking high- and low-frequency spectra. The low-frequency spectrum
(0-500 Hz) provides good resolution for most analysis, while the high frequency spectrum
(0-5 kHz) will provide a baseline for the high frequencies that can indicate problems with
bearings and gears.
In addition to vibration data, operating parameters such as oil pressure. temperature,
load, bearing and gear parameters should be collected. Also, any information available
from the machine manufacturer regarding vibration characteristics and failure mechanisms should be included.
Thermal gradient in a machine can cause temporary misalignment; so making several
temperature readings along the machine may be useful in diagnosing vibration problems.
C. Check Statistical Accuracy
This just means that one measurement may not be representative of normal operation.
For example, an adjacent machine may be vibrating excessively when baseline signatures
are taken, or an older machine may already have excessive vibration levels.
The best approach is to take several spectra over time and perform a statistical analysis
to yield mean and standard deviation. This results in a representative average level, and
also provides a quantitative basis (e.g. 1 or 2 standard deviations) for determining
whether a change in level is significant. The accuracy of these statistics can be
improved by updating them with data from regular vibration monitoring data.
D. Document the Effect of Load Vibration
This is not strictly required, but can be invaluable when determining whether a change is
due to a fault, or just a change in load.
E. Update Regularly
Baseline data should be updated after major repairs or changes in operating conditions.
Figure 5.5-1
Baseline data
should include
fully documented
vibration spectra
and engineering
data, such as
bearing and gear
parameters, which
can be invaluable
for analysis.
Chapter 6
Dynamic Signal Analyzers
Chapter Overview
6.1 Types of DSAs
Dynamic Signal Analyzers are available in a number of different form factors and capabilities.
Generally, the “classes” of DSAs can be broken into handheld/portable, benchtop instrument
and computer controlled systems.
6.2 Measurement Speed
Machinery vibration is a dynamic phenomenon that can change quickly — so quickly that
slower swept spectrum and some DSAs can completely miss key events. DSAs can capture a
typical vibration signal and transform it to the frequency domain within seconds. Another
method involves capturing data in a digital form and post- test processing it; thus allowing for
much higher acquisition rates than is possible with on-line processing. Post-test processing
also allows data to be processed and presented in different forms.
6.3 Frequency Resolution
Closely spaced machinery vibration signals often must be resolved for accurate analysis.
Often industry standards and technical requirements dictate the use of 1/3-octave analysis,
especially in the areas of noise control, acoustics and transients.
6.4 Dynamic Range
Vibration components are often very small relative to vibration from residual imbalance or
other machines. The wide dynamic range of DSAs allow them to resolve signals less than
1/1000 the level of the background vibration or residual imbalance.
Chapter 6 describes the important
measurement capabilities of
DSAs as they relate to machinery
vibration analysis. For a more
detailed discussion of DSAs
and how they work, refer to
Hewlett-Packard applications
note AN 243.
Figure 6.1-1
DSAs representative of the handheld, benchtop
and systems
6.5 Digital Averaging
Machinery vibration signals often contain large amounts of background vibration that can
reduce accuracy and obscure small signals. The digital averaging feature of DSAs can be
used to reduce both of these effects.
6.6 HP-IB and HP I-BASIC1
The Hewlett-Packard Interface Bus is a standardized interface that makes it easy to connect a
DSA to a computer, printer or digital plotter. It is important in automating repeated tests and
transferring data to computer data bases and/or analysis programs. The processing power of
modern DSAs has advanced to the point where HP has implemented a version of the BASIC
programming language resident in the instrument. This allows for extreme flexibility in
adapting the instrument to dedicated tasks.
6.7 User Units and Unit Conversion
DSA displays can be calibrated in vibration units such as inches/seconds and rpm. Units of
vibration amplitude can also be converted to other parameters (e.g. acceleration to velocity)
using the processing capabilities of DSAs.
6.8 Synchronous Sample Rate Control
By controlling the data-sampling rate with a tachometer pulse, the frequency axis can be
normalized to rotational speed. Traditionally, this was done with external analog circuitry
directly controlling the sampling rate of the analyzer. Increased digital processing power has
allowed this task to be handled digitally, bringing with it increased capability and accuracy.
6.9 Two-Channel Enhancement
While single-channel DSAs address most of the needs of machinery analysis, dual- and
multi-channel DSAs provide important enhancements such as real-time phase comparisons
and transfer function measurements.
HP-IB: Not just IEEE-488, but the hardware, documentation and support that delivers the shortest path to a
measurement system.
6.1 Types of DSAs
There is a wide variety of DSAs
on the market; and generally, they
can be broken down into three
1) Handhelds
2) Benchtop Instruments
3) Computer Controlled Systems
Though there are variations on
this theme this covers by far the
majority of systems on the market. Obviously, there is a long list
of features and trade-offs to consider; including speed, portability,
number of channels, display resolution and price. Figure 6.1-1 is a
photograph of three HewlettPackard products representative
of these categories.
The product offerings change rapidly as technology advances, it is
hard to make generalizations, but
the following are some key considerations for each DSA type.
Handhelds are light-weight, portable and battery operated. They
generally have a LCD display that
limits their resolution and display
update rate. The power consumption considerations lead to design
compromises, that make this
class of DSA the lowest performing as a group in terms of speed,
dynamic range and accuracy.
They tend to be lower in cost but
have a relatively robust set of capabilities. In machinery analysis
applications these are well suited
for maintenance and troubleshooting where portability is very
The advantage of this type instrumentation in predictive maintenance is the operator receives
immediate vibration spectral
results and preliminary vibration
severity analysis.
is desirable. In machinery analysis they are used in many
of the same general areas as
benchtops and in continuous machinery monitoring applications.
6.2 Measurement Speed
Benchtop instruments range from
relatively low-cost, low-performance instruments to high-performance instruments. Generally,
the benchtop instruments give exceptional performance in a small
easily operated package. The
tight coupling of the hardware
and software within the instrument, leads to very high display
updates, extremely powerful
analysis capability and generally
very high accuracy and dynamic
range. In machinery analysis
these are generally used in troubleshooting, research and development, and in certification
testing where portability is less
an issue and a small number of
channels is necessary.
DSA systems consist of an instrumentation mainframe connected
to a computer. The system is actually a DSA instrument that uses
the computer as the user interface and data storage device.
Most often, systems are multichannel in nature having from 2
to 500 channels of data acquired
simultaneously. Systems are also
capable of being customized by
users or software developers to
perform dedicated or high-performance tasks. They are generally
used when multi-channels are required and the computer interface
Speed is important in machinery
analysis because vibration characteristics can change quickly.
This is illustrated in the spectral
map of Figure 6.2-1, where measurements of a machine run-up
spaced at 0.5 s intervals show significant variation. Speed is also
important for reducing the time
required to characterize a machine. The time required to make
a measurement with a DSA is
determined by two factors: (1)
measurement resolution, and (2)
transform computation time.
High resolution measurements require a long data sampling time
(frequency resolution spaced at
1 Hz intervals requires a 1 s measurement time). This is a physical fact, independent of the
design of the DSA. Computation
time, however, varies widely
among DSAs, and can make a noticeable difference in measurement time. Computation time is
usually expressed in terms of
real-time bandwidth — the frequency span at which data sampling and computation times are
equal (higher real-time bandwidth
implies faster computation). This
is theoretically the maximum
bandwidth that data can be collected without gaps while simultaneously computing spectra.
Real-time bandwidth example
Suppose you were making measurements with a 2000 Hz frequency span. The data sampling
time for this span on DSAs with 400-lines resolution (see Section 6.2) is 0.200 s. If the
computation time were also 0.200 s, then sampling would never have to stop to let the
computation catch up. (This computation time would correspond to a real-time bandwidth of
2000 Hz). If the computation time were 1 s (a real-time bandwidth of 400 Hz), the analyzer
would miss large amounts of data while waiting for the computation.
Actual real-time bandwidth and
specified bandwidth can vary considerably. Its important to note
that a number of factors influence
the actual real-time bandwidth.
Often the processor is required to
perform a number of additional
calculations to display the data;
this can have a considerable effect on the real-time bandwidth.
Although an increase in the data
block size will increase data sampling time the calculation time increases at a faster rate for larger
blocks; thereby, reducing the realtime bandwidth for larger block
sizes and increasing it for smaller.
Obviously, the number of simultaneous channels will also effect
the rate. For these reasons, the
real-time bandwidth is normally
specified for a block size of 1024
time sample points and with the
display update turned off (i.e. fast
averaging). Therefore, if realtime performance (i.e. gap free)
is necessary, caution should be
exercised in interpreting the
One way of circumventing the
problem is to buffer up the rawtime- domain digital data in either
the analyzer memory (RAM) or on
a high-speed data-storage device
(normally a hard disk drive).
These capabilities are referred to
as time capture and throughput,
respectively. Figure 6.2-3 illustrates the concept of time capture. In this manner the analyzer
can acquire gap free data, store it
in memory, and analyze it later
without relying on the processing
speed of the analyzer being able
to keep up with the data acquisition rate. An additional benefit, is
the ability to go back and reanalyze the data in a number of different ways after the fact, without
reacquiring the data.
Figure 6.2-1
vibration spectra
can change very
quickly, as this
spectral map of
a run-up test
Slower swept
analyzers can
miss these
Figure 6.2-2
Total DSA
time is the sum of
data sampling time
and computation
time. While
sampling time is
fixed for a given
computation times
vary widely among
available DSAs.
Figure 6.2-3
Block diagram of
data flow in a DSA
using time capture.
The data is first
acquired and
stored in RAM;
then analyzed
to product
spectra, etc.
This mode is similar to tape
recording data and then postprocessing it. The advantage of
throughput or time capture is the
integration of the process into the
DSA eliminating the extra calibration and setup steps of a separate
recorder. Post-processing is
greatly simplified, saving time
and allowing previewing of the
analyzed data immediately.
One of the shortcomings of this is
that the real-time spectral display
update is not available, since the
data isn’t analyzed until after the
test. DSA systems generally have
the capability to monitor input
data and acquire the throughput/
time capture simultaneously. Also,
since, all of the data is held in
memory it requires a considerable
portion of the analyzer memory
resources; especially, if long
records are required. Many times,
what is required is not real-time
data acquisition — the real issue
is display update rate. It is possible to keep track of fast changing
spectrums and not have real-time
performance; the gaps do not
materially effect steady or
pseudo-steady state conditions.
Generally, real-time performance
is required when transients are
present and non-real-time analysis would risk missing an important event.
6.3 Frequency Resolution
High resolution is required for
analysis when vibration signals
are closely spaced, or when the
frequency of a component must
be read with high precision. A
common example of closely
spaced signals are the 1 x and
powerline components of induction motor vibration, which can
be separated by a few Hz. The
sidebands around rolling- element
bearing and gear frequencies are
often closely spaced. High precision is required when the characteristic vibration frequencies of
two possible sources are close together, as in the case of a bearing
frequency and a running speed
Frequency resolution in a DSA is
determined primarily by the number of filters (or lines of resolution), and the ability to zoom.
The filters of a DSA are shown in
Figure 6.3-1. Signals must lie in
different filters to be resolved, so
resolution depends on the spacing
of the filters. If the number of filters is fixed, filter spacing is determined by the number of filters
and the analysis span. More filters imply better resolution for a
given span.
Figure 6.3-1
resolution in a
DSA is determined
primarily by the
number of filters,
and the ability to
zoom. In a zoom
measurement, the
component of
interest is made
the center frequency
of the analysis,
allowing the use of
an arbitrarily
narrow frequency
Figure 6.3-2
An example gear
vibration spectrum that illustrates the need for
zoom. The sidebands around
gearmesh often
indicate the bad
gear, but are too
closely spaced to
to resolve in (a).
The zoom
measurement in (b)
centers a narrower frequency
span on the gearmesh, increasing
If the span required for the desired resolution is too narrow to
include all the frequencies of interest, then the analysis must
start at a frequency above zero.
This process is referred to as
zooming (because it involves
zooming in on an arbitrary center
frequency), and is a feature of
most DSAs. Ideally, the zoom
feature should allow frequency
spans down to 1 Hz to be
centered on any frequency in the
analysis range. Typically, implementation of zoom should have
no effect on the real-time bandwidth of the analyzer, since the
process is normally handled by
dedicated hardware that operates
independently of the other computational hardware.
The gear spectrum in Figure 6.3-2
illustrates why the ability to zoom
is so important. In the low-resolution spectrum of (a), the sidebands around the gearmesh
frequency indicate a problem, but
the exact spacing (which will indicate which gear has the defect)
is difficult to determine. Since
the gearmesh is at a relatively
high frequency, a span narrow
enough to resolve the sidebands
cannot cover the entire frequency
range starting at 0 Hz. Thus we
must zoom on the gearmesh frequency to complete the analysis.
(See Section 4.6 for more information on gear analysis.)
Window Functions
Frequency resolution is also affected by the shape of the filters
— determined in a DSA by the
window function selected. The
window function shapes the input
data to compensate for discontinuities in the sampling process
(see application note AN 243).
Figure 6.3-3 shows the same vibration spectrum measured with
the three windows commonly
available on DSAs.
A. The Flat Top window is optimized for level accuracy, with a
response variation with frequency
of 0.1%. This is the window to
use unless maximum frequency
resolution is required, or you are
capturing a transient.
B. The Hanning window provides
improved frequency resolution
(note the Bandwidth notation at
the bottom of the display), but
sacrifices amplitude accuracy.
Variation with frequency is up
to 15%.
C. The Uniform window provides
no weighting, and should be used
only for totally observed transients, or specialized signals.
The wide skirts, known as leakage, severely restrict frequency
Figure 6.3-3
A comparison of
3 common window
types: a) flat top,
b) Hanning and
c) uniform.
Figure 6.3-4
1/3 octave data
from FFT requires
multilple FFT bands
of analyses. The
lower fre-quencies
of the 1/3 octave
have resolution
requirements of
∆ f 5Hz while the
high frequencies
require ∆ f 5kHz.
resolution. (Leakage is what
weighting in the other two window functions minimizes.) Amplitude variation is up to 36%.
Octave Band Analysis
During most of this note we have
concentrated on FFT analysis because it is most useful in machinery vibration. This is because,
many of the vibration components
are very narrow in bandwidth and
repeat themselves in a uniformly
spaced relationship with respect
to frequency (i.e. harmonics and
sidebands). Sometimes it is desirable to have the frequency
resolution spaced in a logarithmic
or octave fashion, with the frequency resolution depicted proportionally rather than uniformly
as in FFT analysis. This type of
analysis is useful when high resolution is not required, and for reasons beyond the scope of this
note, is useful in detecting and
analyzing transient behavior.
This type analysis is referred to
as octave-band analysis.
One method of obtaining this type
of analysis is to resynthesize the
octave analysis data from high
resolution FFT data. Figure 6.3-4
illustrates the concept of synthesis of 1/3-octave data from
multiple passes of FFT data
(1/3-octave refers to a doubling of
the frequency for every third data
point). Figure 6.3-5 is a comparison of comparable 1/3- and 1/12octave analysis and narrow-band
FFT analysis of the same data.
Since the analysis requires multiple “passes” and differing data
acquisition times, the process
of synthesis is NOT real-time.
Therefore, it is only useful for
steady state analysis.
Real-time octave analysis is a process of obtaining octave data by
programming the analyzer to perform digital filtering on the data
rather than FFTs. The digital filtering process is inherently proportional and logarithmic in
nature and readily yields the octave spectra. Though this is beyond the scope of this note, this
capability is often required for
noise and acoustics problems
associated with machines. It is
specified in a number of international standards and the capability is available in a number of
6.4 Dynamic Range
Dynamic range is another aspect
of resolution. It is a measure of
the ability to analyze small signals in the presence of large ones,
as shown in Figure 6.4-1. DSAs
feature wide dynamic range, with
most able to display signals that
differ in amplitude by factors of
1000 or more. Logarithmic display
scales are used to take advantage
of this measurement capability.
Wide dynamic range is important
for analyzing low-level vibration
signals in the presence of large
residual imbalance components.
Figure 6.3-5
A comparision of
measurements of
the same spectrum made with
(FFT), 1/3 octave
and 1/12 octave.
Figure 6.4-1
Dynamic range
is defined as the
ratio between
the largest and
smallest signals
that can be
analyzed at the
same time.
Dynamic range is also important
when the component to be analyzed is small compared to the total power level. That is, a large
number of relatively low-level signals result in a high total power
level that limits input sensitivity
in the same way a single large
signal would. This is often the
case, for example, when analyzing low frequency vibration with
an accelerometer.
Dynamic range in an analyzer is a
cumulative specification of a
DSAs ability to distinguish small
signals in the presence of larger
signals. It is effected by a number of components in the data acquisition portion of the analyzer:
Analog-to-digital converter resolution (number of bits, linearity
etc.), input amplifier noise floor,
anti-aliasing filter performance,
spurious signals within the analyzer, digital signal processor performance, etc.. Generally, the
specification is for the worst case
situations (i.e. max requency span
and lowest input range) and typical performance in the frequency
range for most machinery measurements and reasonable input
ranges is significantly higher
(20 dB is common). It is important to understand the difference
between specified dynamic range
(i.e. guaranteed ) and typical
(i.e. expected under common
6.5 Digital Averaging
Machinery vibration spectra often
contain large levels of background noise, vibration from
adjacent machines, or components that vary in amplitude.
Three types of digital averaging
are available to reduce the problems that these conditions imply
for analysis.
A. RMS. The result of a RMS average of successive spectra is an
improved estimate of the mean
level of vibration components.
RMS averaging should be used
when component levels vary significantly.
B. TIME. While RMS averaging
reduces the variance of signal levels, it does nothing to reduce unwanted background noise. This
background noise may mask
low-level components, or add
unrelated components to the
spectrum. Time (or synchronous)
averaging effectively reduces
components that are not related
to a once per revolution trigger,
which is usually a key-phasor.
Time averaging can be used when
background noise or vibration
from adjacent machines interferes with analysis. Time averaging requires very good speed
regulation to be effective. Time
averaging in the computed order
tracking mode will eliminate the
speed regulation requirement.
C. PEAK. It is often desirable to
hold peak vibration levels during
a run-up or coast-down, or over a
period of time. The result of peak
averaging is a display of the maximum level at each frequency
Figure 6.5-1
When RMS
averaging is
which vary in
converge to
their mean value,
providing a
better statistical
estimate of
a) random noise
average over
10 records.
b) un-averaged
random noise.
RMS Averaging
Because noise can cause spectral
components to vary widely in amplitude, a single measurement is
not statistically accurate. While
watching the components vary in
amplitude, you could visually average them and determine the
mean level. This is essentially
what RMS averaging does, and
the more averages you take the
better the accuracy will be. RMS
averaging can be thought of as
amplitude averaging, since phase
is ignored. (RMS, or root mean
square, is the square root of the
mean of the squared spectra.) The
effect of RMS averaging
is shown in Figure 6.5-1.
RMS averaging improves the
statistical accuracy of a noisy
spectrum, and does not require
a trigger, but it does not actually
reduce the noise level.
Time Averaging
Time averaging is a technique
that can be used to reduce the
level of noise, and thus uncover
low-level signals that may have
been obscured by the noise.
Sometimes referred to as linear
averaging, this type of averaging
requires a synchronizing trigger
— usually a keyphasor.
Time averaging can be implemented in either the time or frequency domains, but the time
domain is traditional (thus the
name). In this form, the blocks
of time data that are transformed
by the analyzer to the frequency
domain are averaged before the
transformation. Signals that are
fixed in the time record (i.e. synchronous with the trigger) will
remain, while nonsynchronous
signals eventually average to
zero. This is shown in Figures
6.5-2(a) and (b), where time averaging a noisy square wave has
reduced the noise level, while
keeping the square wave intact.
An example with machinery spectrum can be found in Section 5.2.
Peak Hold
Peak hold is a function usually
grouped with averaging in DSAs.
By displaying the maximum level
at each frequency over a number
of samples, this feature provides
a history of peak levels. Two applications are shown in Figure
6.5-3. In (a), peak hold has been
used during a machine coast
down, providing a simple track of
the maximum level (which is usually 1 x rpm)*. The display in (b)
is a peak hold over a relatively
long period that shows the range
of speed variation of a nominally
constant speed motor. This could
be used, for example, as an indication of load variation. Peak
hold is also useful for recording
momentary vibration peaks (e.g.
from start-ups or load changes).
Figure 6.5-2
The time averaged
displays in (b) show
a reduction in the
level of components
that are nonsynchronous with the
Figure 6.5-3
Peak hold used
(a) to track peak
level during a coastdown, and (b) to
indicate variation
in speed over time.
* In applications where a tachometer signal is
available, an order track measurement is
preferable to this method (see sec. 6.8).
6.6 HP-IB and
HP Instrument BASIC
The Hewlett-Packard Interface
Bus (HP-IB) is a standardized
interface that can be used to
connect a number of instruments,
plotters, printers and computers
together. Most DSAs come standard with a HP-IB interface and
a set of commands that allows
virtually unlimited possibilities
for automatic data storage, presentation, and analysis. Most
commonly the interface is used
to provide for hardcopy output of
DSA results using a digital printer
or plotter that can be connected
and controlled directly.
Computer Data Storage
and Analysis
A common problem encountered
in machinery vibration monitoring
is the need to organize, store, plot
and archive large amounts of
data. Often extensive post-test
data processing is required depending on the specific application. It is often convenient to put
the data in a data base type applications program so that trends
can be analyzed and specific data
easily retrieved.
Though most DSAs have extensive data storage capabilities, it
is often desirable to transfer the
data to a computer, most commonly, using HP-IB. It is also desirable to place data collected on
different DSAs on a common platform for comparison and analysis.
Hewlett-Packard has standardized
on a common data storage structure for its DSA analyzers allowing for easy transfer of data
between instrument types and application programs using a set of
utility programs and a Standard
Data Format (SDF). Figure 6.6-1
* MS-DOS and MS Windows are U.S. registered
trademarks of Microsoft Corporation.
Figure 6.6-1
Use of a Standard
Data format (SDF)
allows data to be
easily interfaced
and simplifies the
conversion of
non-SDF DSAs
data to a standard
Figure 6.6-2
HP-IB system for
scanning a number
of transducers. Such
a system can be
configured to take
appropriate action
(e.g. sound an alarm
or remove power)
when current
vibration level
exceeds predefined limits.
illustrates the concept of the standardized format and the use of
the utilities. The utilities consist
of a set of MS-DOS® programs for
viewing, converting, and transferring data.
Instrument Systems
and I-Basic
Hewlett-Packard has implemented a proprietary version of the
BASIC programming language
that allows for many of the capabilities of the computer/DSA system without needing an external
computer. HP Instrument Basic
(I-Basic) is a version of the HP
Basic language which is designed
to run inside many HP instruments. I-Basic is also available to
run in DOS and MS Windows®.
I-Basic is optimized for instrument control applications, letting
the user customize measurements. It is most commonly used
for automatic and repetitive tests.
Not only can I-Basic address the
host DSA, it can communicate
over the HP-IB to other instruments or peripherals that are attached. Figure 6.6-2 illustrates
the advantage of this in a particular application.
Whether through the use of I-Basic or some other programming
language the HP-IB capability on
test equipment allows for tying
together a number of instruments
over the HP-IB and controlling
them in concert with each other
to make automated and complex
measurements using an Instrument System concept. The HP
DSA Systems are a specific example of this approach, but the same
concept can be applied to traditional DSAs.
6.7 User Units
and Waveform Math
Vibration displays are easier to
interpret if they are presented in
units that are relevant to machinery. DSAs provide the capability
for user calibration of amplitude
units, and a selection of units for
the frequency axis. DSAs can also
convert spectra from one vibration parameter to another through
integration and differentiation.
User units calibration is accomplished by entering a calibration
factor (such as, 10 mV/g) or using
the marker function to specify a
known value (such as, marker
value equals 94 dB SPL). The
DSA performs the conversion and
displays the vibration spectrum in
the desired units, usually referred
to as “EU” (Engineering Units).
DSAs also provide for custom
labeling of user defined units
(e.g. g's, in/s, mils, etc.).
The frequency units used for machinery vibration analysis include
Hertz, rpm, and orders. Orders
refer to “orders of rotation”, and
are harmonics of the rotation
speed. Orders are handy for analysis because many vibration problems are order-related. By using
external-sample control, orders
can be fixed on the display while
speed changes (see Section 6.8).
Often it is desirable to convert
from one vibration motion variable to another. Referring to the
formulas for displacement, velocity, and acceleration in Section
2.1, it should be apparent that
they are related by frequency and
a phase shift. For example acceleration can be converted to velocity through division by jω = j(2πf).
This operation is commonly referred to as artificial integration
(the “j” term is an operator that
Figure 6.7-1
A comparison
between an integrated acceleration
spectrum and an
actual velocity
spectrum (dashed
Table 6.7
Acceleration ⇑ velocity
Single integration
Acceleration ⇑ displacement
Double integration
Velocity ⇑ displacement
Single integration
Velocity ⇑ acceleration
Displacement ⇑ velocity
Displacement ⇑ acceleration
Double differentiation
implies a 90° phase shift), and is
a feature of most DSAs. Figure
6.7-1 shows an integrated acceleration spectrum overlaid on an
actual velocity spectrum measured at the same point.
Table 6.7 summarizes vibration
parameter conversion. Two
things to note about these conversions: (1) integrating absolute
velocity will not result in relative
displacement (i.e. integrated measurements from a case-mounted
velocity transducer will not give
the same result as a displacement
transducer that measures the
shaft directly),and (2) differentiation is usually not recommended,
since noise in the spectrum to be
differentiated tends to give misleading results.
A feature of many DSAs which actually implement this capability is
waveform math. It fundamentally
allows you to define mathematical relationships between data
traces within the DSA and calculate supplemental data from the
results of measurements; much
the same way as a calculator can
be used to calculate the results of
static measurements. Some DSAs
implement this conversion explicitly. Order analysis conversion is
more complex but possible.
Historically, these conversions
were made with analog hardware
circuitry built into the DSA or signal conditioning. This is being
largely replaced by the math calculation which gives good results
and does not require the costly
additional circuitry. Though
these operations are time proven
and straightforward to implement; whenever performing this
type operation it is recommended
that the operation and units be
checked carefully and tested to
insure that there has not been
some unexpected error
6.8 Synchronous
Sample Control and
Order Tracking
One of the complications encountered in analyzing rotating machinery is variation in speed. For
machines that will operate over a
wide range of speeds, it is desirable to measure vibration over
the entire range. With a fixed-frequency axis, spectral components
are constantly moving with the
changes in speed. For machines
that run at a nominally constant
speed, even small changes can
make point-for-point comparisons
The problem of wide-speed variation is sometimes addressed by
post-test manipulation of the
data. The frequency display can
be normalized (i.e. calibrated to
fixed location, orders of rotation)
through software manipulation.
But often what is required is the
order track (i.e. the locus of
points characterized by the amplitude as a function of rotation
speed for a particular order, see
figure 6.8-1). There are a number
of problems with this approach:
(1) it does not provide real-time
display update of the data; (2) the
number of orders measured
changes with measurement speed
and the resolution appears different at different running speeds;
and (3) the scheme assumes that
the software can calculate or somehow determined the running speed.
To circumvent these problems,
external sample control was introduced. By controlling the datasampling-rate with a signal tied to
rotating speed, the display will
have a fixed calibration in orders
of rotation. (See Section 5.4).
This is a result of the analyzer, in
effect, sampling at a constant delta angle of rotation.
Figure 6.8-1
The order track
is the locus of
points of a particular
order as a function
of machine speed.
Illustrated is the
plot of this data
super-imposed on
a waterfall plot.
Figure 6.8-2
setup for controlling sample
rate externally.
Figure 6.8-2 shows the instrumentation required for controlling the
sample rate externally. Typically,
a once per revolution pulse multiplied by a ratio synthesizer is
used for sample control. The ratio synthesizer is required because DSAs typically sample at a
rate of 2.56 times the frequency
span. Since it is usually desirable
to look at several orders, the once
per revolution tachometer pulse
must be multiplied by 2.56 times
the number of orders to be analyzed. (If you needed to analyze a
machine out to a frequency of 100
orders with a once per revolution
tachometer signal the ratio synthesizer would be required to
produce 2.56 * 100 = 256 sample
pulses per revolution. If the
block size was 1024 points, there
would be exactly 4 revolutions in
one data record). An important
requirement for the ratio synthesizer is anti-aliasing protection.
Aliasing occurs when the datasample rate is too slow, allowing
high-frequency signals to be misrepresented as low-frequency signals. Aliasing is avoided if a filter
is used to limit input signals to
frequencies less than 1/2 the sample rate (See Hewlett-Packard
Application Note AN 243 for more
information on aliasing.) Since
the sampling rate is varying its
necessary to have a variable (or
tracking) filter.
Two problems arise out of this
scheme because of the additional
hardware used. First, the ratio
synthesizer is a phase lock loop
and it has some inherent time lag
and phase error problems. In order tracking very small errors in
frequency can cause significant
amplitude and phase errors. Second, the tracking filter can be one
of a number of types, the most
popular is switched capacitance
due to its low cost and ease of
implementation. Though it is low
cost, it typically has a limited
dynamic range because of the
switching "spurs" (noise spikes
that appear as signals) making it
unsuitable. (See appendix A).
To avoid these problems HP
schemes, they use the digital
signal processing power available
inside the DSA to perform the ratio synthesizer functions and to
digitally resample the data to
produce conceptually the same
effect as the external sample
control without the addition of
analog hardware. Additionally,
the flexibility and power of digital
processing allowed for the elimination of many problems inherent
in the older technology. Figure
6.8-3 shows a block diagram of
this digital implementation of
synchronous- sample control.
Appendix A of this note contains
a more detailed discussion of the
implementation of this scheme.
When the data is synchronously
sampled, producing the order
track data is very easy, because
it's simply the locus of points at
a fixed frequency (in the order
domain) as a function of
rotation speed.
Machine Runup Measurements
An important measurement made
using the order tacking capability
of DSA's is the machine runup/
down. In many machines the
only time they operate at certain
important speeds (ie. critical
Figure 6.8-3
for synchronous
sample control for
DSA with digital
Figure 6.8-4(a)
Bode plot of a
machine runup for
a simple flexible
rotor system
showing the
critical speed.
The plot represents
magnitude as linear
magnitude and the
"X" axis is linear to
conform to normal
convention, though
the DSA's can also
scale the data in
a Logrithmic format.
Figure 6.8-4(b)
Polar plot of runup
depicting the
magnitude and
phase plotted in a
polar fashion.
Note the rotation
intended to compensate for positioning
of the phase
reference and the
speeds, at structural resonances,
etc.) is during a runup or rundown. This measurement is an
important indication of machinery
health and is commonly used to
qualify new and overhauled high
speed machinery. The measurement uses the residual imbalance
in the machine to excite it at
different frequencies as it runs up
to operating speed and measures
the response (magnitude and
phase) as a function of speed.
This utilizes the basic order tracking capability of the analyzer coupled with special display features
required of this measurement.
Two common display formats are
used with this measurement; one
is the Bode diagram* and the other is the polar display. The bode
plot depicts the magnitude and
the phase response of the system
to the runup as a function of
speed (RPM). A benefit of the
DSA in this measurement is its
ability to simultaneously track
multiple orders and display them
in addition to the fundamental rotation speed (1st order); as well
as the overall level and the RPM
profile Figure 6.8-5.
6.9 Dual/Multi-Channel
Most of our discussion has center
around spectrum measurements
which can be made with a singlechannel DSA, and in some cases a
reference trigger to obtain phase
information. This is not to imply
that a single-channel DSA is the
best solution to vibration analysis
problems, it merely points out
that many measurements CAN be
made with a single-channel analyzer. In fact, advances in technology have significantly reduced
the price differential between 1-,
2-, and multi-channel DSAs; making their usage common in machinery vibration analysis.
A multi-channel DSA is much
more than multiple separate analysis channels, because it can
measure the amplitude and phase
relationships between two signals
or sets of signals. Another relationship that is commonly measured is called the frequency
response function. It is especially
useful for performing real-time
phase comparisons, and identifying the source of vibration or
* Bode diagram conventions for rotating
machine applications differ from
electrical and servo conventions;
here the convention common to
machinery vibrations are used.
Figure 6.8-5
Runup depiction of
the 2nd and 3rd
orders as well as
the overall level
and the RPM profile.
Figure 6.9-1
Misalignment is
indicated by a 180°
phase relation
between A and B.
For transducer
oriented as shown
(180° relation),
the relative phase
will be 0°.
noise in a machine. The frequency-response function can also be
used to determine natural frequencies of shafts, gears, and machine housings that can be critical
for analysis. Multi-channel DSAs
can display shaft orbits. These
displays give insight into the path
of the shaft as it rotates, and are
especially useful in high-speed
machinery. For a more general
discussion of dual-channel DSA
capabilities, refer to HewlettPackard application note AN 243.
Real-Time Comparisons
Comparative phase measurements are a powerful tool for
analysis, especially for differentiating between similar forms of vibration (see Section 4.4 and 5.2).
This measurement is made both
easier and more accurate with a
dual-channel DSA. Referring to
the motor-pump combination in
Figure 6.9-1, suppose that you are
not sure whether the high-vibration level is due to imbalance or
misalignment. As pointed out in
Section 4.4, the relative phase of
axial vibration at A and B will be
180° if misalignment is the problem (assuming a rigid-rotor).
With a single-channel analyzer,
you would use a keyphasor as a
reference, and measure the two
ends one at a time. With a dualchannel analyzer, all you have to
do is connect an end to each
channel and measure the transfer
function phase (this connection is
diagrammed in Figure 6.9-1.)
Thus, relative phase measurements can be made with a singlechannel DSA, but are much easier
(and less error-prone) with a
dual- or multi-channel DSA.
Another important place where a
dual- or multi-channel DSA is useful is in two- or multi-plane balancing. The vibration level at
multiple planes can be monitored
simultaneously, while at the same
time utilizing the external trigger
to provide for phase information
for all channels. This can effect
large reductions in the number of
measurement runs required to
balance a machine.
Cause and Effect Relationships: The Coherence Function
A common problem in machinery
vibration analysis is that vibration
from one machine in a train is
coupled to the other machines.
The coherence function can help
with these problems by indicating
the cause and effect relationship
between vibration at two
The coherence display covers a
range of 0 to 1, and indicates the
percentage of power in channel 2
that is coherent (i.e. linearly related) with channel 1. Let’s suppose
that vibration levels at points A
and D on the motor pump combination of Figure 6.9-1 are similar,
and rather high. You would like
to know whether they are independent or related. A low value
of coherence between vibration
components from A and D indicates that they are not related. A
high coherence value for a component implies that there may be
a causal relationship. (The high
coherence component could, for
Figure 6.9-2
Coherence measured
between a pump
and motor clearly
indicates which
components are
Figure 6.9-3
The transfer
function of a
gearbox can be
measured with
an instrumented
hammer and a
two-channel DSA.
example, be from a third source
of vibration.) Coherence measured between end points on a
motor and pump is shown in
Figure 6.9-2. Note that coherence
is high for all the major vibration
components except 240 Hz indicating that this vibration is not
from the motor. The technique
will not work 100% of the time,
and you will have to get a feel for
what constitutes a high level of
coherence, but it may save in disconnecting machines to isolate
the source of vibration.
Natural Frequency
The natural frequencies of a machine housing or foundation can
be easily determined through
what is sometimes referred to as
a “bump” test. A single impulsive
signal produces a broad spectrum
of energy. If the housing is impacted with sufficient force (typically with a block of wood), all
the natural frequencies will be excited. The response can be measured with a single-channel DSA,
but an imperfect impact may
result in a misleading spectrum.
A better way to make this measurement is with a multi-channel
analyzer and an instrumented
hammer. This is shown diagrammatically in Figure 6.9-3, where
the natural frequencies of a gearbox are being determined. As we
saw in Section 4.6, gear defects
often show up at the natural frequencies, so this information is
valuable. It can also help identify
critical rotor frequencies in
high speed machinery. HewlettPackard application note
AN 243-3 contains more detailed
information on measuring the response of mechanical structures.
Figure 6.9-4
setup for orbit
using orthogonal
proximity probe
and a 2 channel
Figure 6.9-5
The orbit capability of some twochannel DSAs
provides insight
into rotor motion
in machines with
fluid-film bearings.
HP dual-channel DSAs have the
ability to display orbit diagrams,
Figure 6.9-4 shows how an orbit
diagram is generated utilizing two
proximity probes mounted at 90°
to each other. Figure 6.9-5 shows
diagramatically a typical orbit diagram. They are useful for gaining insight into rotor motion in
turbo-machinery. The subject of
orbit interpretation is covered
well in Reference 30. If a multichannel system (≥4 channels) is
used it is possible and often desirable to make multiple simultaneous orbit measurements at
different shaft locations.
Figure 6.9-6
Orbit diagram
using synchronous sampling
will accurately
represent the
angular position
(note the marker
read out).
The orbit diagram is fundamentally a time domain measurement
and it should be emphasized that
a DSA will typically low pass filter the data before collection. In
some cases unfiltered time data is
desired, and many DSAs allow for
bypassing the filters just for this
On the orbit diagram as you move
about the orbit pattern the independent variable is time. If the
measurement is triggered by a
shaft reference (i.e. keyphasor)
then the actual position can be
marked on the diagram and if the
rpm is known the location of any
point can be calculated. An alternative method is to use synchronous sample control in orbit
measurement (see Section 6.8)
with an external reference for
trigger (this can be the same signal as the tachometer signal).
Now the independent variable is
not time but shaft position and
can be read directly from the
DSA's display as shown in Figure
Figure 6.9-7
method for
measuring filtered
orbits using
tracking filters
and an oscilloscope.
Filtered Orbits
Normal orbit diagrams represent
the contribution of all frequencies
within the bandwidth of analysis.
These include contributions from
surface defects and anomolies,
higher (or lower) order components, powerline harmonics, machine noise and the like. Filtered
orbits is a technique for focusing
the orbit analysis on a select frequency range (or ranges) of interest. This was traditionally done
by placing a tracking narrow
bandpass filter in the analysis
stream (Fig 6.9-7). This allows
the analysis to focus on contributions to the orbit associated with
that particular frequency or order. The traditional technique
requires special purpose analog
hardware and has many of the
limitations associated with the
use of similar techniques discussed elsewhere in this note.
In an FFT analyzer the filtered
orbit information is contained
within the linear spectrum or order ratio spectrum measurements
(Note: phase information is required, ie. power spectrum measurements are not sufficient).
The individual frequency components of the spectrum represent
precisely the same sine wave that
would be extracted by narrow
band filtering. The advantages
are the presence of all frequencies simultaneously, the precision
and accuracy of the digital
impementation and in the convenient user interface.
Figure 6.9-8 is an example of a
traditional orbit diagram and a filtered orbit (of the fundemental
rotation frequency) for the same
Figure 6.9-8(a)
Complex orbit
diagram of a
rotating shaft at
low speed with
significant noise
and distortion
present. All
components are
Figure 6.9-8(b)
Filtered orbit
of frequency
to first order.
Only the single
component is
displayed for
same measurement
as Figure 6.9-8(a).
This data was
extracted from
linear spectra
frequency domain
data measured at
a single rotation
Figure 6.9-9
Filtered orbit of
the first order
component taken
at the peak
response of the
order track for the
first order (note
position of the
marker in the
upper trace). This
data was extracted
from measurement
of a run-up using
order tracking
signal. The higher order information has been effectively “filtered
out”. Both measurements were
actually made simultaneously
using the frequency domain measurement mode. The measurement could also be made in the
order domain using either
order tracks or order ratio spectra. Figure 6.9-9 is a filtered orbit
taken from a run up measurement
using order tracking; in this measurement an entire range of filtered orbits as a function of RPM
become part of the measurement
set allowing any orbit shape to be
review for any time/rpm in the
run-up. A capability of the digital
implementation is the ability to
add together related components
to obtain a composite filtered orbit containing only those frequency (or order) components desire.
(Figure 6.9-10).
Figure 6.9-10(a)
Filtered orbit
consisting of the
contributions of
4 individual orders
to the orbit shape.
The marker
positions of the
upper trace specify
the components to
include in the
Figure 6.9-10(b)
The filtered orbit
diagram for same
data containing
only the contribution of the first
Appendix A
Computed Synchronous
Resampling and Order Tracking
Digital Resampling
Digital signal processing (DSP)
hardware and software have continually improved, allowing the
substitution of digital processing
in many areas which have traditionally used analog processes.
This appendix discusses the implementation of DSP techniques
in the processing of time sampled
data to produce rotating machinery order domain information.
In DSAs the traditional method
for order analysis involved varying the actual sample rate (∆t) of
the data to correspond to some
multiple of machine rotation
speed, so that sampling is locked
to a constant angle of shaft rotation. This generally led to a requirement for a significant
amount of ancillary equipment,
making the measurement less
practical and less commonly used
(Figure A-1). The use of ratio
synthesizers (phase locked loops)
led to a number of problems, particularly in machines with fast
run-up rates or where high order
numbers were being analyzed.
A significant improvement is
possible by applying the power
of the DSP and microprocessors
in high-performance dynamic signal analyzers (DSAs) to replace
external sampling and low-pass
tracking filter hardware with a
digital implementation. One immediate advantage is the use of
existing general-purpose DSA
hardware, since the entire process is carried out in software
Figure A-1
external sampling
method of order
domain analysis.
Figure A-2
Block diagram of
digital resampling
method of order
domain analysis.
(Figure A-2). Many of the shortcomings of older techniques can
be overcome by using digital
There are three basic contributions through digital implementation:
1) Calculation of the resample
times avoids many of the pitfalls
of ratio synthesizers and approaches the “theoretically” perfect resampling times that would
be present from a physical device,
such as a shaft encoder.
2) Eliminates the need and the
limitations of tracking, low-pass
anti-aliasing filters by replacing
their functionality with equivalent
digital filters.
3) Allows the digital data to be
captured in mass memory and
post-test analyzed using techniques without extraneous and
unwieldy recording, and AD/DA
conversions required of the analog approach.
External Sampling
The ideal technique for measuring
an order spectrum has long been
considered the use of an encoder
physically attached to a shaft to
generate sampling pulses at uniform angular intervals around
some reference shaft. This directly determines the sampling
times as a function of shaft position. Then, if various transducers
are sampled at these times, the
resulting frequency spectrum will
show components that depend
upon multiples of the shaft-rotation rate as stationary lines, independent of shaft rpm. This sort of
spectral display is plotted versus
order (multiples of the shaft rotation rate), instead of frequency.
Thus, if the shaft rotation rate is
changed, any frequency components that are locked to this rotation rate will appear stationary
in the order spectrum, while the
spectra of any fixed frequency
components will appear to move
(Figure A-3).
Unfortunately, the appropriate
shaft encoders are not always
practical to install and do not, in
themselves, address the problem
of aliasing, so other approaches
must often be considered. The
classical method of bypassing the
requirement for a shaft encoder is
using a phase-locked loop (PLL)
to generate a sampling frequency
that is a suitable multiple of some
shaft rotation rate by synchronizing the loop to a small number
of pulses per revolution. For example, an optically reflective
stripe might be attached to the
shaft, giving one synchronizing
pulse per revolution. Then the
phase-locked loop might be set
to generate exactly 256 sampling
Figure A-3
Sample plots of
analysis done in
the frequency
(a) and the order
(b) domains.
Figure A-4
Deviation of an
“ideal” PLL’s
estimate of shaft
angular position
from actual shaft
with constantly
increasing RPM.
Figure A-5
Digital data
processing of
tachometer and
data for order
domain processing prior to FFT.
pulses per shaft revolution, no
matter what the shaft rotation
rate might be (Figure A-1). This
would yield an analysis typically
up to 100 orders on an FFT analyzer utilizing external sampling.
This technique works reasonably
well as long as the shaft speed
does not change too quickly, and
the phase noise generated by the
phase-locked loop is negligible.
However, when the shaft is accelerating rapidly, the phase-locked
loop lags behind, since the loop
cannot begin to adjust to a new
rpm until after some change in
speed has occurred (Figure A-4).
In this situation, the samples are
not spaced uniformly relative to
the shaft angle, and the estimate
of rpm can be in error. The response time of the phased-locked
loop can be reduced by increasing
the bandwidth of the loop, but
this also increases the noise level.
At some point, the resulting phase
noise will begin to “smear” the
higher order spectral lines. Small
errors in the sampling rate with
respect to rotation rate become
much more critical at higher orders, where the error is effectively magnified by the order number.
Digital Resampling Times
Due to improvements in microprocessor performance (faster
computations at lower cost), and
to lower cost memory chips, it is
feasible to design a tracking
scheme that is independent of
shaft acceleration and that has
negligible internal phase noise.
The idea is to collect measured
data at some fixed rate, and to
store this data in a large buffer
Figure A-6
Processing of
signals to obtain
estimates of
resample times
of uniform shaft
Figure A-7
Use of resampling
on a fast sinesweep at a
frequency of five
orders sampled at
uniform time (a)
and uniform angle
memory. Simultaneously, the arrival times of each synchronizing
tachometer pulse are measured
and stored (Figure A-5). Then, the
microprocessor can be used to
determine the shaft angle and velocity at intermediate points between the tachometer pulses,
based upon a model of constant
shaft acceleration. The sampling
times corresponding to the desired shaft angular increments
can be calculated, and the stored
measurement data can be interpolated in some optimum manner to
obtain new samples at the desired
time points (Figure A-6).
Figure A-7a shows a sinusoid
chirp having a linear frequency
versus time characteristic,
sampled at uniform time intervals. Figure A-7b shows this same
signal after resampling at uniform
shaft angle increments. The frequency spectrum of the swept
sine in Figure A-7a is “smeared”
over a band of frequencies, while
that for Figure A-7b occurs at
only the 5th harmonic of the shaft
rotation rate in the order domain
(5th order), assuming that the
plot is scaled to show exactly
one revolution of the shaft
(Figure A-7c).
Since the data is buffered in memory, it is possible to “look ahead,”
and to use data points that occur
before the desired tachometer
pulse times occur. This allows
the design of a tracking algorithm
that has no inherent time delay,
and thus never gets behind, as
long as the shaft is constantly
accelerating (or running at a constant velocity). In addition, the
shaft velocity can be correctly
calculated at each instant in time.
There is no significant internal
phase noise introduced by this
procedure, although it is important to measure the arrival time
of each tachometer pulse very
accurately to reduce the effects
of time jitter.
Figure A-8
Example of errors
inherent in a
simple two point
linear interpolation scheme.
Figure A-9
Illustration of the
implementation of
a multi-point FIR
Though in actual measurements
the requirement that the shaft acceleration be constant is not met,
the model can be updated at each
tachometer pulse so errors introduced generally are quite small. It
is possible to use a more complex
model of the shaft acceleration,
but this would introduce an additional performance penalty due to
the increased computation time,
and the increases in accuracy
have not warranted this step.
Generally, the traditional phase
lock loop/ratio synthesizer implementation can be thought of as
modeling the shaft position as
constant velocity between tachometer pulses. Figure A-4
illustrates the problems with this
The computed order tracking approach requires considerably less
in the way of special hardware,
compared to the classical technique. For example, in addition
to the need for a tracking ratio
synthesizer, the classical order
tracking method requires tracking
anti-aliasing filters on each data
channel and often a frequency
counter to determine shaft velocity. With the new approach, a
fixed analog anti-aliasing filter is
used, and the remaining filtering
operations are done digitally (this
is the same hardware used in
the normal FFT analysis mode).
There is no need for an analog
tracking ratio synthesizer, since
the shaft position is continually
calculated from the tachometer
pulse arrival times.
Resampling Amplitude
With traditional ratio synthesizer/
shaft encoder techniques, once
the resampling signals have been
created, the remainder of the order analysis can use standard
FFT technology with variable A/D
converter sampling rates to accomplish the remainder of the
processing. This assumes that
adequate alias protection is provided by some variable low pass
filtering technique.
In the case of digital order tracking, the situation is not as
straightforward since the data has
already been anti-alias filtered
and digitized at some fixed rate.
The digital resampling process actually accomplishes two functions; first it provides the variable
sample rates. Second, it provides
the variable frequency low pass
filtering (in conjunction with the
fixed filtering of the DSA’s digital
and analog anti-alias filters)
required for adequate alias protection. External sampling implementations must handle the
anti-alias filtering as a separate
step; normally adding a separate
analog tracking filter to the input.
As described in the previous section, the desired sampling times
were calculated based on the
tachometer pulses and a linear
acceleration model. In general,
these times will lay between two
fixed rate samples and an estimate must be made of the amplitude at the desired time based on
existing data. The fixed sample
data is buffered in computer
memory so, again, we can look
both ahead and back in time at
the data to estimate the new
resampled value. The simplest
scheme would be to use linear
interpolation between the two
neighboring points. Though this
would work to some extent, it’s
apparent from Figure A-8 that significant errors can be introduced.
This approach would lead to amplitude errors and a severe limitation on the system’s dynamic
range. In the case of simple linear
interpolation, an amplitude error
of 10% and an effective dynamic
range of only 26 dB would be realizable. To reduce this error and
increase the dynamic range, it’s
necessary to use more data in
evaluating our resampled amplitude. The current implementation
utilizes ten neighboring data
points (five before and five after
the resample time) to calculate
the resample data point, formulated as a finite impulse response
(FIR) filter (Figure A-9).
Theoretically, this formulation
would lead to amplitude accuracy
of .08% and a dynamic range of
approximately 104 dB. To improve speed, the actual filter is
implemented as a look-up table
in memory, which leads to some
round-off errors yielding the desired 80 dB dynamic range.
Example Measurements
To demonstrate the digital
implementation under realistic
conditions, run-up tests were performed on an automobile utilizing
moderate run-up rates. The data
was actually digitally recorded
and analyzed using traditional external sampling/ratio synthesis
techniques as well as the digital
resampling technique. The following plots illustrate the differences
between the two techniques.
In Figure A-12A the ramp rates
were not particularly fast nor the
order analysis very high, which
are the conditions where the computed method would normally be
expected to perform better. In
spite of the low ramp rate, the
automobile engine RPM was not
particularly steady and would
“jitter” about its average value.
The traditional method’s phase
lock loop tended to average these
variations and consequently resulted in some loss of resolution.
Figure A-10 is the computed order
tracking measurement and the
half and odd number orders are
quite clear as are the dominant
even order, which would be expected from a four-cylinder, fourcycle engine. Also visible is the
60 Hz noise component, which is
lost in Figure A-11.
Figure A-10
Order ratio map
of an automobile
run-up with a
four-cycle engine
utilizing computed resampling.
Figure A-11
Order ratio map
utilizing external
sampling and
a PLL ratio
Figure A-12
Order track
made using
digital resampling
(a) Time vs RPM
(b) Amplitude of
two order vs RPM
and (c) Phase of
two order vs RPM.
Figure A-11 is a similar measurement using external sampling
and a tracking ratio synthesizer
with a tracking low-pass filter.
The conditions have been set to
give equivalent resolution and
low-amplitude orders are much
less distinct and the 60 Hz is not
The differences can be attributed
to phase lock loop delay. Reference [36] further illustrates this
by examining the ability of a ratio
synthesizer to track a square
wave swept at known rates.
Figure A-12a and b illustrate the
order tracking capability of the
digital technique which includes
phase information. The FIR filter
used in the digital implementation
has essentially no phase shift or
time delay allowing accurate
phase measurements.
Acceleration. The time rate of
change of velocity. Typical units
are ft/s/s, meters/s/s, and G’s
(1G = 32.17 ft/s/s = 9.81 m/s/s).
Acceleration measurements are
usually made with accelerometers.
Accelerometer. Transducer
whose output is directly proportional to acceleration. Most commonly use piezoelectric crystals
to produce output.
Aliasing. A phenomenon which
can occur whenever a signal is
not sampled at greater than twice
the maximum frequency component. Causes high frequency signals to appear at low frequencies.
Aliasing is avoided by filtering
out signals greater than 1/2 the
sample rate.
Alignment. A condition whereby
the axes of machine components
are either coincident, parallel or
perpendicular, according to design requirements.
Amplification Factor (Synchronous). A measure of the
susceptibility of a rotor to vibration amplitude when rotational
speed is equal to the rotor natural
frequency (implies a flexible rotor). For imbalance type excitation, synchronous amplification
factor is calculated by dividing
the amplitude value at the resonant peak by the amplitude value
at a speed well above resonance
(as determined from a plot of synchronous response vs. rpm).
Amplitude. The magnitude of
dynamic motion or vibration. Amplitude is expressed in terms of
peak-to- peak, zero-to-peak, or
rms. For pure sine waves only,
these are related as follows: rms
= 0.707 times zero-to-peak; peakto-peak = 2 times zero-to-peak.
DSAs generally display rms for
spectral components, and peak
for time domain components.
Anti-Aliasing Filter. A lowpass filter designed to filter out
frequenices higher than 40% the
sample rate in order to prevent
Anti-Friction Bearing. See Rolling Element Bearing.
Asymetrical Support. Rotor
support system that does not provide uniform restraint in all radial
directions. This is typical for
most heavy industrial machinery
where stiffness in one plane may
be substantially different than
stiffness in the perpendicular
plane. Occurs in bearings by design, or from preloads such as
gravity or misalignment
Auto Spectrum (Power Spectrum). DSA spectrum display
whose magnitude represents the
power at each frequency, and
which has no phase. Rms averaging produces an auto spectrum.
Averaging. In a DSA, digitally
averaging several measurements
to improve accuracy or to reduce
the level of asynchronous components. Refer to definitions of rms,
time, and peak-hold averaging.
Axial. In the same direction as
the shaft centerline.
Axial Position. The average position, or change in position, of a
rotor in the axial direction with
respect to some fixed reference
position. Ideally the reference is a
known position within the thrust
bearing axial clearance or float
zone, and the measurement is
made with a displacement transducer observing the thrust collar.
Balancing Resonance
Speed(s). A rotative speed that
corresponds to a natural resonance frequency.
Asynchronous. Vibration components that are not related to rotating speed (also referred to as
Balanced Condition. For rotating machinery, a condition where
the shaft geometric centerline coincides with the mass centerline.
Attitude Angle (Steady-State).
The angle between the direction
of steady-state preload through
the bearing centerline, and a line
drawn between the shaft centerline and the bearing centerline.
(Applies to fluid-film bearings.)
Balancing. A procedure for adjusting the radial mass distribution of a rotor so that the mass
centerline approaches the rotor
geometric centerline.
Band-Pass Filter. A filter with a
single transmission band extending from lower to upper cutoff
frequencies. The width of the
band is determined by the separation of frequencies at which
amplitude is attenuated by
3 dB (0.707).
Bandwidth. The spacing between frequencies at which a
band-pass filter attenuates the
signal by 3 dB. In a DSA, measurement bandwidth is equal to
[(frequency span)/(number of filters) x (window factor)]. Window
factors are: 1 for uniform, 1.5 for
Hanning, and 3.63 for flat top.
Baseline Spectrum. A vibration
spectrum taken when a machine
is in good operating condition;
used as a reference for monitoring and analysis.
Blade Passing Frequency. A
potential vibration frequency on
any bladed machine (turbine,
axial compressor, fan, etc.).
It is represented by the number
of blades times shaft-rotating
Block Size. The number of samples used in a DSA to compute
the Fast Fourier Transform.
Also the number of samples in
a DSA time display. Most DSAs
use a block size of from 250 to
8192. Smaller block size reduces
Bode Plot. Rectangular coordinate plot of 1x component amplitude and phase (relative to a
keyphasor) vs. running speed.
BPFO, BPFI. Common abbreviations for ball pass frequency of
defects on outer and inner bearing races, respectively.
Bow. A shaft condition such that
the geometric centerline of the
shaft is not straight. Also called
shaft sag.
Brinneling (False). Impressions made by bearing rolling
elements on the bearing race;
typically caused by external
vibration when the shaft is
Calibration. A test during which
known values of the measured
variable are applied to the transducer or readout instrument, and
output readings varied or adjusted.
Campbell Diagram. A mathematically constructed diagram
used to check for coincidence of
vibration sources (i.e. 1 x imbalance, 2 x misalignment) with rotor natural resonances. The form
of the diagram is a rectangular
plot of resonant frequency
(y-axis) vs excitation frequency
(x-axis). Also known as an interference diagram.
Cascade Plot. See Spectral Map.
Cavitation. A condition which
can occur in liquid-handling machinery (e.g. centrifugal pumps)
where a system pressure decrease in the suction line and
pump inlet lowers fluid pressure
and vaporization occurs. The result is mixed flow which may
produce vibration.
Center Frequency. For a
bandpass filter, the center of the
transmission band.
Charge Amplifier. Amplifier
used to convert accelerometer
output impedance from high to
low, making calibration much
less dependent on cable capacitance.
Coherence. The ratio of coherent output power between channels in a dual-channel DSA. An
effective means of determining
the similarity of vibration at two
locations, giving insight into the
possibility of cause and effect relationships.
Constant Bandwidth Filter. A
band-pass filter whose bandwidth
is independent of center frequency. The filters simulated
digitally in a DSA are constant
Constant Percentage Bandwidth. A band-pass filter whose
bandwidth is a constant percentage of center frequency. 1/3
octave filters, including those
synthesized in DSAs, are constant
percentage bandwidth.
Critical Machinery. Machines
which are critical to a major part
of the plant process. These machines are usually unspared.
Critical Speeds. In general, any
rotating speed which is associated with high vibration amplitude. Often, the rotor speeds
which correspond to natural
frequencies of the shaft or the
Critical Speed Map. A rectangular plot of system natural frequency (y-axis) versus bearing or
support stiffness (x-axis).
Cross Axis Sensitivity. A measure of off-axis response of velocity and acceleration transducers.
Cycle. One complete sequence of
values of a periodic quantity.
Damping. The quality of a mechanical system that restrains the
amplitude of motion with each
successive cycle. Damping of
shaft motion is provided by oil in
bearings, seals, etc. The damping
process converts mechanical energy to other forms, usually heat.
Damping, Critical. The smallest
amount of damping required to return the system to its equilibrium
position without oscillation.
Decibels (dB). A logarithmic
representation of amplitude ratio,
defined as 20 times the base ten
logarithm of the ratio of the measured amplitude to a reference.
dB readings, for example, are referenced to 1 volt rms. dB or Log
amplitude scales are required to
display the full dynamic range of
a DSA.
Degrees Of Freedom. A phrase
used in mechanical vibration to
describe the complexity of the
system. The number of degrees
of freedom is the number of independent variables describing the
state of a vibrating system.
Digital Filter. A filter which
acts on data after it has been
sampled and digitized. Often used
in DSAs to provide anti-aliasing
protection after internal re-sampling.
Differentiation. Representation
in terms of time rate of change.
For example, differentiating velocity yields acceleration. In a
DSA, differentiation is performed
by multiplication by jw, where
w is frequency multiplied by 2p.
(Differentiation can also be used
to convert displacement to velocity.)
Discrete Fourier Transform. A
procedure for calculating discrete
frequency components (filters or
lines) from sampled time data.
Since the frequency domain result
is complex (i.e., real and imaginary components), the number of
points is equal to half the number
of samples.
Dynamic Signal Analyzer
(DSA). Vibration analyzer that
uses digital signal processing and
the Fast Fourier Transform to display vibration frequency components. DSAs also display the time
domain and phase spectrum, and
can usually be interfaced to a
Displacement. The change in
distance or position of an object
relative to a reference.
Eccentricity, Mechanical. The
variation of the outer diameter of
a shaft surface when referenced
to the true geometric centerline
of the shaft. Out-of-roundness.
Displacement Transducer. A
transducer whose output is proportional to the distance between
it and the measured object (usually the shaft).
DSA. See Dynamic Signal Analyzer.
Dual Probe. A transducer set
consisting of displacement and
velocity transducers. Combines
measurement of shaft motion
relative to the displacement transducer with velocity of the displacement transducer to produce
absolute motion of the shaft.
Dual Voting. Concept where
two independent inputs are required before action (usually machine shutdown) is taken. Most
often used with axial position
measurements, where failure of a
single transducer might lead to an
unnecessary shutdown.
Dynamic Motion. Vibratory motion of a rotor system caused by
mechanisms that are active only
when the rotor is turning at
speeds above slow roll speed.
Eccentricity Ratio. The vector
difference between the bearing
centerline and the average steadystate journal centerline.
Eddy Current. Electrical current which is generated (and dissipated) in a conductive material
in the presence of an electromagnetic field.
Electrical Runout. An error signal that occurs in eddy current
displacement measurements
when shaft surface conductivity
Engineering Units. In a DSA,
refers to units that are calibrated
by the user (e.g., in/s, g’s).
External Sampling. In a DSA,
refers to control of data sampling
by a multiplied tachometer signal.
Provides a stationary display of
vibration with changing speed.
Fast Fourier Transform (FFT).
A computer (or microprocessor)
procedure for calculating discrete
frequency components from sampled time data. A special case of
the discrete Fourier transform
where the number of samples is
constrained to a power of 2.
Filter. Electronic circuitry designed to pass or reject a specific
frequency band.
Filtered Orbit. An orbit diagram in which the vertical and
horizontal displacement signals
have been filtered. This is normally a bandpass filter centered
at a running speed, however, digital systems are capable of multiple bandpass regions.
Finite Element Modeling. A
computer aided design technique
for predicting the dynamic behavior of a mechanical system prior
to construction. Modeling can be
used, for example, to predict the
natural frequencies of a flexible
Flat Top Filter. DSA window
function which provides the best
amplitude accuracy for measuring
discrete frequency components.
Fluid-Film Bearing. A bearing
which supports the shaft on a thin
film of oil. The fluid-film layer
may be generated by journal rotation (hydrodynamic bearing), or
by externally applied pressure
(hydrostatic bearing).
Forced Vibration. The oscillation of a system under the action
of a forcing function. Typically
forced vibration occurs at the frequency of the exciting force.
Free Vibration. Vibration of a
mechanical system following an
initial force — typically at one or
more natural frequencies.
Frequency. The repetition rate
of a periodic event, usually expressed in cycles per second
(Hz), revolutions per minute
(rpm), or multiples of a rotational
speed (orders). Orders are
commonly referred to as 1x for
rotational speed, 2x for twice
rotational speed, etc.
Frequency Response. The
amplitude and phase response
characteristics of a system.
G. The value of acceleration produced by the force of gravity.
Gear Mesh Frequency. A potential vibration frequency on any
machine that contains gears;
equal to the number of teeth multiplied by the rotational frequency
of the gear.
Hanning Window. DSA window
function that provides better frequency resolution than the flat
top window, but with reduced
amplitude accuracy.
Harmonic. Frequency component at a frequency that is an integer multiple of the fundamental
Heavy Spot. The angular location of the imbalance vector at a
specific lateral location on a
shaft. The heavy spot typically
does not change with rotational
Hertz (Hz). The unit of frequency represented by cycles per
High Spot. The angular location
on the shaft directly under the vibration transducer at the point of
closest proximity. The high spot
can move with changes in shaft
dynamics (e.g., from changes in
High-Pass Filter. A filter with a
transmission band starting at a
lower cutoff frequency and extending to (theoretically) infinite
Hysteresis. Non-uniqueness in
the relationship between two
variables as a parameter increases or decreases. Also called
deadband, or that portion of a
system’s response where a
change in input does not produce
a change in output.
Imbalance. Unequal radial
weight distribution on a rotor system; a shaft condition such that
the mass and shaft geometric
centerlines do not coincide.
Impact Test. Response test
where the broad frequency range
produced by an impact is used as
the stimulus. Sometimes referred
to as a bump test.
Impedance, Mechanical. The
mechanical properties of a machine system (mass, stiffness,
damping) that determine the response to periodic forcing functions.
Influence Coefficients. Mathematical coefficients that describe
the influence of system loading
on system deflection.
Integration. A process producing a result that, when differentiated, yields the original quantity.
Integration of acceleration, for
example, yields velocity. Integration is performed in a DSA by dividing by jw, where w is
frequency multiplied by 2p. (Integration is also used to convert velocity to displacement).
Journal. Specific portions of the
shaft surface from which rotor applied loads are transmitted to
bearing supports.
Keyphasor. A signal used in rotating machinery measurements,
generated by a transducer observing a once-per-revolution event.
The keyphasor signal is used in
phase measurements for analysis
and balancing.
Lateral Location. The definition
of various points along the shaft
axis of rotation.
Lateral Vibration. See Radial
Leakage. In DSAs, a result of finite time record length that results in smearing of frequency
components. Its effects are
greatly reduced by the use of
weighted window functions such
as flat top and Hanning.
Linearity. The response characteristics of a linear system remain
constant with input level. That is,
if the response to input a is A, and
the response to input b is B, then
the response of a linear system to
input (a + b) will be (A + B). An
example of a non-linear system is
one whose response is limited by
mechanical stop, such as occurs
when a bearing mount is loose.
Lines. Common term used to
describe the filters of a DSA (e.g.,
400 line analyzer).
Linear Averaging. See Time
Low-Pass Filter. A filter whose
transmission band extends from
dc to an upper cutoff frequency.
Mechanical Runout. An error in
measuring the position of the
shaft centerline with a displacement probe that is caused by
out-of-roundness and surface
Micrometer (MICRON). One
millionth (.000001) of a meter.
(1 micron = 1 x E-6 meters @
0.04 mils.)
MIL. One thousandth (0.001) of
an inch. (1 mil = 25.4 microns.)
Modal Analysis. The process of
breaking complex vibration into
its component modes of vibration,
very much like frequency domain
analysis breaks vibration down to
component frequencies.
Mode Shape. The resultant deflected shape of a rotor at a specific rotational speed to an
applied forcing function. A threedimensional presentation of rotor
lateral deflection along the shaft
Modulation, Amplitude (AM).
The process where the amplitude
of a signal is varied as a function
of the instantaneous value of another signal. The first signal is
called the carrier, and the second
signal is called the modulating
signal. Amplitude modulation produces a component at the carrier
frequency, with adjacent components (sidebands) at the frequency of the modulating signal.
Modulation, Frequency (FM).
The process where the frequency
of the carrier is determined by the
amplitude of the modulating signal. Frequency modulation produces a component at the carrier
frequency, with adjacent components (sidebands) at the frequency of the modulating signal.
Natural Frequency. The frequency of free vibration of a system. The frequency at which an
undamped system with a single
degree of freedom will oscillate
upon momentary displacement
from its rest position.
Nodal Point. A point of minimum shaft deflection in a specific
mode shape. May readily change
location along the shaft axis due
to changes in residual imbalance
or other forcing function, or
change in restraint such as
increased bearing clearance.
Noise. Any component of a
transducer output signal that does
not represent the variable intended to be measured.
Nyquist Criterion. Requirement
that a sampled system sample at
a frequency greater than twice
thehighest frequency to be
Nyquist Plot. A plot of real versus imaginary spectral components that is often used in servo
analysis. Should not be confused
with a polar plot of amplitude and
phase of 1x vibration.
Octave. The interval between
two frequencies with a ratio of
2 to 1.
Oil Whirl/Whip. An unstable
free vibration whereby a fluidfilm bearing has insufficient unit
loading. Under this condition, the
shaft centerline dynamic motion
is usually circular in the direction
of rotation. Oil whirl occurs at the
oil flow velocity within the bearing, usually 40 to 49% of shaft
speed. Oil whip occurs when the
whirl frequency coincide with
(and becomes locked to) a shaft
resonant frequency. (Oil whirl
and whip can occur in any case
where fluid is between two
cylindrical surfaces.)
Orbit. The path of the shaft
centerline motion during rotation.
The orbit is observed with an oscilloscope connected to x and yaxis displacement transducers.
Some dual-channel DSAs also
have the ability to display orbits.
Oscillator-Demodulator. A signal conditioning device that sends
a radio frequency signal to an
eddy-current displacement probe,
demodulates the probe output,
and provides output signals proportional to both the average and
dynamic gap distances. (Also referred to as Proximitor, a Bently
Nevada trade name.)
Peak Hold. In a DSA, a type
of averaging that holds the peak
signal level for each frequency
Period. The time required for
a complete oscillation or for a
single cycle of events. The reciprocal of frequency.
Phase. A measurement of the
timing relationship between two
signals, or between a specific vibration event and a keyphasor
Piezoelectric. Any material
which provides a conversion between mechanical and electrical
energy. For a piezoelectric crystal, if mechanical stresses are
applied on two opposite faces,
electrical charges appear on some
other pair of faces.
Polar Plot. Polar coordinate representation of the locus of the 1x
vector at a specific lateral shaft
location with the shaft rotational
speed as a parameter.
Power Spectrum. See Auto
Preload, Bearing. The dimensionless quantity that is typically
expressed as a number from zero
to one where a preload of zero indicates no bearing load upon the
shaft, and one indicates the maximum preload (i.e., line contact
between shaft and bearing).
Preload, External. Any of several mechanisms that can externally load a bearing. This includes
“soft” preloads such as process
fluids or gravitational forces as
well as “hard” preloads from gear
contact forces, misalignment,
rubs, etc.
Proximitor. See Oscillator/
Radial. Direction perpendicular
to the shaft centerline.
Radial Position. The average
location, relative to the radial
bearing centerline, of the shaft
dynamic motion.
Radial Vibration. Shaft dynamic
motion or casing vibration which
is in a direction perpendicular to
the shaft centerline.
Real-Time Analyzer. See
Dynamic Signal Analyzer.
Real-Time Rate. For a DSA, the
broadest frequency span at which
data is sampled continuously.
Real-time rate is mostly dependent on FFT processing speed.
Rectangular Window. See Uniform Window.
Relative Motion. Vibration measured relative to a chosen reference. Displacement transducers
generally measure shaft motion
relative to the transducer mounting.
Repeatability. The ability of a
transducer or readout instrument
to reproduce readings when the
same input is applied repeatedly.
Resolution. The smallest change
in stimulus that will produce a detectable change in the instrument
Resonance. The condition of
vibration amplitude and phase
change response caused by a
corresponding system sensitivity
to a particular forcing frequency.
A resonance is typically identified
by a substantial amplitude increase, and related phase shift.
Rolling Element Bearing. Bearing whose low friction qualities
derive from rolling elements
(balls or rollers), with little
Root Mean Square (rms).
Square root of the arithmetical average of a set of squared instantaneous values. DSAs perform rms
averaging digitally on successive
vibration spectra.
Rotor, Flexible. A rotor which
operates close enough to, or beyond its first bending critical
speed for dynamic effects to influence rotor deformations. Rotors
which cannot be classified as
rigid rotors are considered to
be flexible rotors.
Rotor, Rigid. A rotor which operates substantially below its first
bending critical speed. A rigid rotor can be brought into, and will
remain in, a state of satisfactory
balance at all operating speeds
when balanced on any two arbitrarily selected correction planes.
RPM Spectral Map. A spectral
map of vibration spectra versus
Runout Compensation. Electronic correction of a transducer
output signal for the error resulting from slow roll runout.
Seismic. Refers to an inertially
referenced measurement or a
measurement relative to free
Seismic Transducer. A transducer that is mounted on the case
or housing of a machine and measures casing vibration relative to
free space. Accelerometers and
velocity transducers are seismic.
Signal Conditioner. A device
placed between a signal source
and a readout instrument to
change the signal. Examples: attenuators, preamplifiers, charge
Signature. Term usually applied
to the vibration frequency spectrum which is distinctive and special to a machine or component,
system or subsystem at a specific
point in time, under specific machine operating conditions, etc.
Used for historical comparison of
mechanical condition over the operating life of the machine.
Slow Roll Speed. Low rotative
speed at which dynamic motion
effects from forces such as imbalance are negligible.
Spectral Map. A three-dimensional plot of the vibration amplitude spectrum versus another
variable, usually time or rpm.
Torsional Vibration. Amplitude
modulation of torque measured in
degrees peak-to-peak referenced
to the axis of shaft rotation.
Spectrum Analyzer. An instrument which displays the frequency spectrum of an input
Tracking Filter. A low-pass or
band-pass filter which automatically tracks the input signal. A
tracking filter is usually required
for aliasing protection when data
sampling is controlled externally.
Stiffness. The spring-like quality
of mechanical and hydraulic elements to elasticity deform under
Strain. The physical deformation, deflection, or change in
length resulting from stress
(force per unit area).
Subharmonic. Sinusoidal quantity of a frequency that is an integral submultiple of a fundamental
Component(s) of a vibration signal which has a frequency less
than shaft rotative frequency.
Synchronous Sampling. In a
DSA, it refers to the control of
the effective sampling rate of
data; which includes the processes of external sampling and
computed resampling used in
order tracking.
Time Averaging. In a DSA, averaging of time records that results
in reduction of asynchronous
Time Record. In a DSA, the sampled time data converted to the
frequency domain by the FFT.
Most DSAs use a time record of
1024 samples.
Transducer. A device for translating the magnitude of one quantity into another quantity.
Transient Vibration. Temporarily sustained vibration of a mechanical system. It may consist of
forced or free vibration or both.
Typically this is associated with
changes in machine operating
condition such as speed, load,
Transverse Sensitivity. See
Cross-Axis Sensitivity.
Trigger. Any event which can be
used as a timing reference. In a
DSA, a trigger can be used to initiate a measurement.
Unbalance. See Imbalance.
Uniform Window. In a DSA, a
window function with uniform
weighting across the time record.
This window does not protect
against leakage, and should be
used only with transient signals
contained completely within the
time record.
Vector. A quantity which has
both magnitude and direction
Waterfall Plot. See Spectral
Application Notes:
243 The Fundamentals of Signal
Analysis. The time, frequency,
and modal domains are explained
without rigorous mathematics.
Provides a block-diagram level
understanding of DSAs.
243-3 The Fundamentals of
Modal Testing. The basics of
structural analysis presented
at a block diagram level of
Machinery Monitoring:
1) Dodd, V.R. and East, J.R., The
Third Generation of Vibration
Surveillance, Minicourse notes,
Machinery Monitoring and Analysis Meeting, Vibration Institute,
Clarendon Hills, IL 1983.
2) Dodd, V.R., Machinery
Monitoring Update, Sixth
Turbomachinery Symposium
Proceedings, Texas A&M
University, 1977.
3) Mitchell, John S., Machinery
Analysis and Monitoring, Second Edition, Penn Well Books,
Tulsa, OK, 1993.
4) Myrick, S.T., Survey Results
on Condition Monitoring of
Turbomachinery in the Petrochemical Industry; I. Protection
and Diagnostic Monitoring of
‘Critical’ Machinery, Vibration
Institute, 1982.
5) Tiedt, Brain, Economic
Justification for Machinery
Monitoring, Bently Nevada
Publication L0377-00.
6) Wett, Ted, Compressor Monitoring Protects Olefins Plant’s
Reliability. Bently Nevada Publication L0339-00.
7) Steward, R.M., The Specification and Development of a Standard for Gearbox Monitoring,
Vibrations in Rotating Machinery,
Mechanical Engineering Publications Limited, Inc. London, 1980.
8) Berry, James E., Proven
Method for Specifing Spectral
Band Alarm Levels and Frequencies Using Todays Predictive
Maintenance Software Systems,
Technical Associates of Charlotte, Inc., 1990.
9) Bently, Donald, Shaft Vibration Measurement and Analysis
Techniques, Noise and Vibration
Control International, April, 1983.
10) Dranetz, Abraham I. and
Orlacchio, Anthony W., Piezoel
electric and Piezoresistive Pickups, in Shock and Vibration Handbook, C.M. Harris and C.E. Crede,
eds., McGraw-Hill, 1976.
11) Glitch: Definition of and
Methods for Correction, including Shaft Burnishing to Remove
Electrical Runout, Bently Nevada
Application Note L0195-00,
August 1978.
12) How to Minimize Electrical
Runout During Rotor Manufacturing, Bently Nevada Application Note L0197-00, July 1969.
13) Judd John, Noise in Vibration Monitoring, Measurements
and Control, June 1983.
14) REBAM (TM) - A Technical
Review, Bently Nevada Publication, 5/83.
15) Stuart, John W., Retrofitting
Gas Turbines and Centrifugal
Compressors with Proximity
Vibration Probes, Bently Nevada
Publication L0357-00, June 1981.
16) Wilson, Jon, Noise Suppression and Prevention in Piezoelectric Transducer Systems,
Sound and Vibration, April 1979.
Vibration Analysis:
17) Ehrich, F.F., Sum and Difference Frequencies in Vibration of
High Speed Rotating Machinery,
Journal of Engineering for Industry, February 1972.
18) Eshleman, Ronald L., The
Role of Sum and Difference Frequencies in Rotating Machinery
Fault Analysis, Vibrations in
Rotating Machinery, Mechanical
Engineering Publications Limited,
Inc., London, 1980.
19) Jackson, Charles, The Practical Vibration Primer, Gulf Publishing Company, Houston, Texas,
20) Steward, R.M., Vibration
Analysis As an Aid to the Detection and Diagnosis of Faults in
Rotating Machinery, I Mech E,
C192/76, 1976.
21) Maxwell, J. Howard,
Introduction Motor Magnetic
Vibration, Proceedings of the
Vibration Institute Machinery Vibration Monitoring and Analysis
Meeting, Houston, Texas, April
1983, Vibration Institute,
Clarendon Hills, IL.
Fluid Film Bearings and
Rotor Dynamics:
24) Rieger, N.F. and Crofoot, J.F.,
Vibrations of Rotating Machinery, Vibration Institute, 1977.
25) Bently, Donald E., Oil Whirl
Resonance, Bently Nevada
Publication L0324-01, July, 1981.
26) Ehrich, E.F., Indentification
and Avoidance of Instabilities
and Self-Excited Vibrations in
Rotating Machinery, ASME
Paper 72-DE-21.
27) Gunter, E.J., Rotor Bearing
Stability, Vibration Institute,
28) Loewy, R.G. and Piarulli, V.J.,
Dynamics of Rotating Shafts,
The Shock and Vibration
Information Center, 1969.
29) McHugh, J.D., Principles
of Turbomachinery Bearings,
Proceedings of the 8th
Turbomachinery Symposium,
Texas A&M University.
30) Orbits, Bently Nevada
Applications Notes.
Vibration Control:
31) Beranek, L.L., Noise and
Vibration Control, McGraw-Hill
Book Co., New York, NY, 1971.
32) Fundamentals of Balancing,
Schenck Trebel Corporation, Deer
Park, NY, 1983.
33) Dodd, V.R., Total Alignment,
Penn Well Books, Tulsa, OK,
34) Gunter, E.J., Ed., Field
Balancing of Rotating Equipment, Vibration Institute, 1983.
35) Hagler, R., Schwerdin, H., and
Eshleman, R., Effects of Shaft
Misalignment on Machinery
Vibration, Design News,
January, 1979.
Digital Order Tracking:
36) Potter, Ron and Gibler, Mike,
Computer Order Tracking
Obsoletes Older Methods, "SAE
Noise and Vibration Conference,
May 16-18, 1989, pp 63-67.
37)Potter, Ron, A New Order
Tracking Method for Rotating
Machinery, Sound & Vibration
Sept 1990, pp30-34.
22) Taylor, James I., An Update
of Determination of Antifriction
Bearing Condition by Spectral
Analysis, Vibration Institute,
23) Taylor, James I., Identification of Gear Defects by Vibration
Analysis, Vibration Institute,
Accelerometers 13, 14, 15
Aliasing 56, 59, 61
Anti-Friction Bearings 28
Averaging 51, 53, 57
rms 57
time 5, 46, 52, 53, 60, 62, 66
peak hold 57
Balancing 24, 27
Ball Spin Frequency 29
Baseline Data 41, 50
Bearing (rolling element)
Characteristic Frequencies 29
BASIC program to calculate 29
factors modifying 30
example spectra 30
Blade Passing Frequency 37
Bode Plot 62
Bump Test 65
Cascade Plots (Spectral Maps,
Waterfalls) 22, 47
Coastdown Tests 50, 55, 57, 58
Coherence Function 64
Computer Data Storage
and Analysis 59
Contact Angle 30
Critical Speed 24, 32, 33, 62
Differentiation 60
Digital Plotters 51, 59
Displacement Transducers 12
Documentation 6, 41, 51
Dual-Channel DSA 34, 45, 63, 65
Dynamic Range 22, 28, 43, 51, 52,
Eddy Current Probe 12
Electrical Defects 39
Engineering Units Calibration 60
External Sample Control
(Synchronous Sample) 48, 60,
Filtered Orbits 66, 67
Flat Top Window (DSA) 55
Flexible Rotor 17, 23, 32
Fluid-Film Bearings 10, 32, 33, 38
Frequency Domain 19, 20, 25
Frequency Resolution 26, 54, 55
Fundamental Train Frequency 30
Gears 22, 36, 47
gearmesh frequency 34, 47, 55
natural frequency 31, 36, 47, 63
Hanning Window (DSA) 55
Heavy Spot (balancing) 8, 24
High Spot 24
Hewlett-Packard Interface Bus
(HP-IB) 51, 59
IEEE-488 Interface (HP-IB) 51
Imbalance 27, 28, 33, 34, 35, 41, 44,
51, 56, 63
Impulsive Signal Spectrum 19, 22,
Inner Race Defect 29
Integration 13, 60
Keyphasor 15, 23, 24, 44, 63
Leakage (DSA) 55
Looseness 22, 32, 35
Measurement Speed (DSA) 52
Mechanical Impedance 8, 10, 17
Misalignment 32, 34, 44, 45, 63
Missing Blade Spectrum 38
Multiple Rolling Element Bearing
Defects 32
Natural Frequencies 36, 38
effect of mass and stiffness 11
measurement of 65
1/3 Octave Analyzers 25, 56
Oil Whirl 32, 33
Oil Whip 33
Orbits 62
Order Tracking 48, 61, 62
Outer Race Defect Frequency 20,
29, 30
Parallel Filter Analyzer 25
Peak Average 57
Phase 22, 23, 38
detecting misalignment 34
measurement with
dual-channel DSA 63
use in analysis 44
Pitch Diameter 29
Predictive Maintenance 43
Proximity Probe (Displacement
Transducer) 12
Ratio Synthesizer 61, 66
Real-Time Bandwidth 53
Real-Time Comparisons 63
Resonance 38
Rigid Rotor 24
Rotor Dynamics 5, 24
Rotor, Cracked
(Induction Motor) 39
RMS Averaging 57
Runup Measurements 62
Runup Tests 50, 52, 57
Severity Criteria 41, 42, 43
Sidebands 21, 22, 30, 32, 36, 37, 38
Speed Variation 27, 48, 49, 57, 58, 61
Spectral Maps 19, 22, 47, 50
Spectrum 3, 20, 22, 24
Statistical Accuracy 50, 55, 57
Sum and Difference Frequencies
19, 41, 46
Swept Filter Analyzers 26
Synchronous (Time) Averaging 57
Synchronous Sample Control 48,
61, 62
Time Domain 19
Transducer Installation Guidelines
Transfer Function Measurement 51
Trend Analysis 43
Truncation 35
Uniform Window (DSA) 55
Units Calibration 60
Units Conversion 51
Vane Passing Frequency 37
Velocity Transducers 9, 11, 13
Vibration Parameters 8, 9, 60
phase relationships 8
variation in level with rpm 11
Waterfall 22, 47
Window Function (DSA) 55
Zoom Analysis (DSA) 7, 54
For more information about HewlettPackard test & measurement products,
applications, services, and for a current
sales office listing, visitour web site,
http://www.hp.com/go/tmdir. You can
also contact one of the following
centers and ask for a test and
measurement sales representative.
United States:
Hewlett-Packard Company
Test and Measurement Call Center
P.O. Box 4026
Englewood, CO 80155-4026
1 800 452 4844
Hewlett-Packard Canada Ltd.
5150 Spectrum Way
Mississauga, Ontario
L4W 5G1
(905) 206 4725
European Marketing Centre
P.O. Box 999
1180 AZ Amstelveen
The Netherlands
(31 20) 547 9900
Hewlett-Packard Japan Ltd.
Measurement Assistance Center
9-1, Takakura-Cho, Hachioji-Shi,
Tokyo 192, Japan
Tel: (81) 426 56 7832
Fax: (81) 426 56 7840
Latin America:
Latin American Region Headquarters
5200 Blue Lagoon Drive
9th Floor
Miami, Florida 33126
Tel: (305) 267-4245
(305) 267-4220
Fax: (305) 267-4288
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31-41 Joseph Street
Blackburn, Victoria 3130
Tel: 1 800 629 485 (Australia)
0800 738 378 (New Zealand)
Fax: (61 3) 9210 5489
Asia Pacific:
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1 Matheson Street, Causeway Bay,
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Tel: (852) 2599 7777
Fax: (852) 2506 9285
Data subject to change.
Copyright © 1994, 1997
Hewlett-Packard Co.
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