A Review of Microwave Thermography

A Review of Microwave Thermography
sensors
Review
A Review of Microwave Thermography
Nondestructive Testing and Evaluation
Hong Zhang 1, *, Ruizhen Yang 2 , Yunze He 3, *, Ali Foudazi 4 , Liang Cheng 5 and Guiyun Tian 5
1
2
3
4
5
*
School of Electronic and Information Engineering, Fuqing Branch of Fujian Normal University,
Fuzhou 350300, China
Department of Civil and Architecture Engineering, Changsha University, Changsha 410022, China;
[email protected]
College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
Electrical and Computer Engineering Department, Missouri University of Science and Technology, Rolla,
MO 65409, USA; [email protected]
School of Electrical and Electronic Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK;
[email protected] (L.C.); [email protected] (G.T.)
Correspondence: [email protected] (H.Z.); [email protected] (Y.H.);
Tel.: +86-157-1591-8377 (H.Z.); +86-134-6769-8133 (Y.H.)
Received: 21 March 2017; Accepted: 10 May 2017; Published: 15 May 2017
Abstract: Microwave thermography (MWT) has many advantages including strong penetrability,
selective heating, volumetric heating, significant energy savings, uniform heating, and good thermal
efficiency. MWT has received growing interest due to its potential to overcome some of the limitations
of microwave nondestructive testing (NDT) and thermal NDT. Moreover, during the last few decades
MWT has attracted growing interest in materials assessment. In this paper, a comprehensive review
of MWT techniques for materials evaluation is conducted based on a detailed literature survey.
First, the basic principles of MWT are described. Different types of MWT, including microwave
pulsed thermography, microwave step thermography, microwave pulsed phase thermography, and
microwave lock-in thermography are defined and introduced. Then, MWT case studies are discussed.
Next, comparisons with other thermography and NDT methods are conducted. Finally, the trends in
MWT research are outlined, including new theoretical studies, simulations and modelling, signal
processing algorithms, internal properties characterization, automatic separation and inspection
systems. This work provides a summary of MWT, which can be utilized for material failures
prevention and quality control.
Keywords: infrared thermography; NDT; microwave thermography; volumetric heating; material
1. Introduction
Infrared (IR) thermography plays an important role in structural health monitoring (SHM) [1]
and non-destructive testing (NDT) [2]. IR thermography has great potential and advantages, including
fast inspection time, high sensitivity and spatial resolution owing to commercial IR cameras’ ability
to detect inner defects as a result of heat conduction. It can be split into two categories: passive and
active. For the passive approach, the IR camera is used to measure the temperature of materials under
test without any external excitation source. The passive thermography configuration is illustrated
in Figure 1a. In many industrial processes, passive thermography has been used in production and
predictive maintenance [3]. While passive thermography allows qualitative analyses to be performed,
active thermography is both qualitative and quantitative [4].
Contrary to the passive approach, an external thermal excitation is required for active
thermography. The known characteristics of this external excitation enable depth quantification
Sensors 2017, 17, 1123; doi:10.3390/s17051123
www.mdpi.com/journal/sensors
Sensors 2017, 17, x FOR PEER REVIEW
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composites’ debonding detection [5]. As shown in Figure 1b, the configuration of the active infrared
approach
is similar
to thatdetection
of the passive
except 1b,
for the
theconfiguration
utilization of of
anthe
excitation
source
in
composites’
debonding
[5]. Asapproach,
shown in Figure
active infrared
to generate
distinctive
thermal
contrast.approach,
As illustrated
infor
Figure
1b, the IR camera
is situated
on the
approach
is asimilar
to that
of the passive
except
the utilization
of an excitation
source
to
same
side
of
the
excitation
source
in
reflection
configuration.
For
transmission
configuration,
the
IR
generate a distinctive thermal contrast. As illustrated in Figure 1b, the IR camera is situated on the
camera
is situated
on the opposite
side
of the excitation
source.
The
IR camera is
synchronizedthe
with
same
side
of the excitation
source in
reflection
configuration.
For
transmission
configuration,
IR
the excitation
source
by opposite
a controlside
unit.ofAthe
computer
is source.
required
toIR
process
display the obtained
camera
is situated
on the
excitation
The
cameraand
is synchronized
with the
thermal images.
contrast
and quantify
defects,
is obtained
often performed
excitation
source To
by aimprove
control unit.
A computer
is required
to active
processthermography
and display the
thermal
with advanced
signalcontrast
processing
the reflection
mode isis often
suitable
for detecting
images.
To improve
andmethods.
quantify Normally,
defects, active
thermography
performed
with
defects
situated
near
the
surface,
while
deeper
defects
can
be
detected
in
the
transmission
mode.
advanced signal processing methods. Normally, the reflection mode is suitable for detecting defects
However,
thethe
transmission
approach
becan
used
some cases
the target
is inaccessible
situated
near
surface, while
deepercannot
defects
be in
detected
in thewhere
transmission
mode.
However,
[6–8].
the
transmission approach cannot be used in some cases where the target is inaccessible [6–8].
Figure
Figure 1.
1. MWT setup for (a) the passive approach and (b) the active approach.
Depending on the external thermal excitation, different active thermography methods have been
Depending on the external thermal excitation, different active thermography methods have been
developed, such as pulsed thermography (PT) [9], step thermography (ST) [10] and modulated
developed, such as pulsed thermography (PT) [9], step thermography (ST) [10] and modulated
thermography (MT) or so-called lock-in thermography (LT) [11]. Finally, there is pulsed phase
thermography (MT) or so-called lock-in thermography (LT) [11]. Finally, there is pulsed phase
thermography (PPT) [12], developed by Maldague and Marinetti in 1996, which combines the
thermography (PPT) [12], developed by Maldague and Marinetti in 1996, which combines the
advantages of PT and MT [13,14].
advantages of PT and MT [13,14].
Various physical heating sources have been adopted as thermal stimulation sources, such as
Various physical heating sources have been adopted as thermal stimulation sources, such as thermal
thermal lamps, lasers, ultrasound devices, and electromagnetic waves. Accordingly, laser
lamps, lasers, ultrasound devices, and electromagnetic waves. Accordingly, laser thermography [15],
thermography [15], ultrasonic thermography and eddy current thermography [16,17] were
ultrasonic thermography and eddy current thermography [16,17] were developed. Taking eddy current
developed. Taking eddy current thermography as an example, it combines the advantages of IR
thermography as an example, it combines the advantages of IR thermography and eddy current testing,
thermography and eddy current testing, such as being fast and non-contact [18–21]. Eddy current
such as being fast and non-contact [18–21]. Eddy current thermography can heat many materials
thermography can heat many materials such as metals and carbon fiber reinforced polymer (CFRP)
such as metals and carbon fiber reinforced polymer (CFRP) with eddy current heating. However,
with eddy current heating. However, it only works for conductive materials [22–24], therefore, the
it only works for conductive materials [22–24], therefore, the excitation source needs to be chosen
excitation source needs to be chosen according to the specific problem. In the last decade, researchers
according to the specific problem. In the last decade, researchers have shown an increased interest
have shown an increased interest in microwave heating techniques. Microwave heating has been
in microwave heating techniques. Microwave heating has been exhibited advantages of rapid heat
exhibited advantages of rapid heat transfer (due to volumetric heating), efficiency, heating
transfer (due to volumetric heating), efficiency, heating uniformity, compact equipment, and being
uniformity, compact equipment, and being easy to control, etc. Meanwhile, microwave heating has
easy to control, etc. Meanwhile, microwave heating has emerged as a powerful platform due to
emerged as a powerful platform due to dielectric loss and eddy current heating with different
dielectric loss and eddy current heating with different materials under test. So far, built microwave
materials under test. So far, built microwave thermography devices have shown some unique
Sensors 2017, 17, 1123
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thermography devices have shown some unique advantages such as: (1) microwaves will produce
reflection, scattering, transmission at a discontinuous interface. With microwave signal reflection and
scattering in the defect area, less microwave energy can be used for heating, and the temperature raise
in a defect area is slower than in a non-defect area during microwave heating. IR cameras will capture
this abnormal thermal image which will strengthen the effectiveness of defect detection; (2) the heating
pattern of microwave heating is relatively uniform, volumetric and selective, and can be achieved in
a short time; (3) microwave heating is easy to control, and it is easy to implement different heating
function modulations. However, it is necessary to restrict microwave leakage as they are dangerous to
human health, therefore, the leakage of the microwaves needs to be kept below a certain recommended
level. Generally, in industry microwave heating is operated from 890 MHz to 2.45 GHz to minimize
any possible interference with communication services [25].
Thermography has been associated with microwaves in numerous applications. MWT has been
employed by some scientists to detect wet rotten wood [26], mines and surrogate signatures [27,28].
MWT has also been used to inspect and characterize various kinds of materials and phenomena,
such as debonding and delamination in composite materials [29]. So far, although there are several
review works [30–44], they have been limited to a specific field such as composite or renewable energy,
so a review of MWT in the material detection field which includes the principles, advantages and
disadvantages, developments and research trends is still needed. In this paper, a comprehensive review
of MWT techniques for material evaluation has been provided, based on a detailed literature survey.
The overall structure of this paper includes the following: the principle of MWT is presented in
Section 2. Then, typical types of MWT applications are summarized in Section 3. Section 4 reviews the
development of MWT with case studies. Then, a comparison and discussion are provided in Section 5.
Trends are shown in Section 6. Finally, the conclusions are outlined in Section 7.
2. Principle of Microwave Thermography
The principles of MWT mainly include microwave heating and 3D heat conduction. These are
analyzed theoretically in the following subsections.
2.1. Microwave Based Heating
The heating style of microwave thermography can be divided into volume heating and surface
heating [45], therefore the heating process can be divided into volumetric heating (i.e., dielectric loss
heating) and surface heating (i.e., eddy current heating).
2.1.1. Dielectric Loss Heating
For dielectric materials, such as glass fiber composite materials, microwave heating is volumetric
heating (i.e., dielectric loss heating). Considering glass fiber composites for instance, material dielectric
loss in the microwave radiation field will generate heat. The dissipated power P per unit volume can
be expressed as follows [46]:
P = 2π f ε 0 ε00 E2
(1)
where f is the frequency of an electric field, E is the RMS value of the electric field, ε0 is the permittivity
of air, and ε” is the relative loss factor. Without considering the heat diffusion, the temperature change
per unit at heating time t with a continuous microwave source is [46]:
T (t) =
Pt
ωε 0 ε00 E2
=
t
ρCp
ρCp
(2)
where ρ is the density of the material and Cp is heat capacity. Obviously, with constant microwave
parameters and constant properties of the material under test, the temperature increases linearly with
time (during a short period of time).
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The basic
Sensorsprinciples
2017, 17, 1123 of MWT volumetric heating are shown in Figure 2a: firstly,
4 of a
33 microwave
excitation module is used to generate a microwave radiation field; secondly, microwaves penetrate
The basic
MWT volumetric
heatingwill
are shown
firstly, a microwave
the material under
test,principles
and theofmedium
molecules
moveinatFigure
the 2a:
frequency
of the electric field
excitation
module
is
used
to
generate
a
microwave
radiation
field;
secondly,
microwaves
penetrate around the
which generates heat and eventually is converted into Joule heat, which then will transfer
the material under test, and the medium molecules will move at the frequency of the electric field
material based
on the diffusion equation; finally, an IR camera is utilized to obtain the temperature
which generates heat and eventually is converted into Joule heat, which then will transfer around the
variation inmaterial
the material
test. equation;
Due to the
differences
inisdensity
heat
capacity between the
based onunder
the diffusion
finally,
an IR camera
utilized toand
obtain
the temperature
variation
in the
material
underinformation
test. Due to theabout
differences
in density
heat capacity
between
materials under
test
and
defects,
surface
andand
internal
defects
canthebe obtained.
materials under test and defects, information about surface and internal defects can be obtained. Thus,
Thus, the processes of MWT for dielectric materials evaluation are based on microwave radiation,
the processes of MWT for dielectric materials evaluation are based on microwave radiation, dielectric
dielectric loss
Joule
heat transfer,
and IR radiation.
lossto
to generate
generate Joule
heat,heat,
heat transfer,
and IR radiation.
Figure 2. Basic schematic of MWT: dielectric material (a) and conductive material (b).
Figure 2. Basic
schematic of MWT: dielectric material (a) and conductive material (b).
2.1.2. Eddy Current Heating
2.1.2. Eddy Current Heating
For conductive materials, like metals and carbon fiber composites, microwave heating is eddy
current heating.
Since the like
material
underand
test iscarbon
electrically
conductive,
microwaves
cannot penetrate
For conductive
materials,
metals
fiber
composites,
microwave
heating is eddy
the conductor material. Thus, the principle of microwave heating is that the energy is radiated to the
current heating.
Since the material under test is electrically conductive, microwaves cannot penetrate
conductive material surface by microwaves, an alternating electric field is generated, then, induced
the conductor
material.
the from
principle
of microwave
heating
is that
energy
is radiated to the
surface
currentsThus,
are excited
the alternating
electric field,
resulting
in an the
alternating
magnetic
Next, surface
a vortex electric
field is generated
this alternating
magnetic
field,
vortex electric
conductive field.
material
by microwaves,
an by
alternating
electric
field
is the
generated,
then, induced
field promotes the movement of electrons which will generate Joule heat. Finally, the conduct material
surface currents are excited from the alternating electric field, resulting in an alternating magnetic
is heated by Joule heat as shown in Figure 2b. Power P and heat Q generated by eddy current heating
field. Next, can
a vortex
electric
field is generated by this alternating magnetic field, the vortex electric
be expressed
as [47]:
r
field promotes the movement of electrons which
will
µ f generate Joule heat. Finally, the conduct
2
P ∼ Iinductor
(3)
σ
material is heated by Joule heat as shown in Figure 2b. Power
P
and
heat
Q
generated
by
eddy current
r
µf
2
heating can be expressed as [47]:
Q = Pt ∼ Iinductor
t
(4)
σ
where, Iinductor is the current flowing through the inductor,
σ is
f the conductivity (S/m), µ is the magnetic
2
Pf is Ithe
permeability of the material under test and
frequency
of the induced current. It is observed that
inductor

with a stable induced current and induced current frequency, the generated heat is directly proportional
to the microwave excitation time and it is inversely proportional to the square root of the conductivity.
However, due to the presence of heat transfer and dissipation problems during actual applications,
f
2
MWT must be corrected in order to minimize
Q  Pt theImeasurement
terror.
inductor

(3)
(4)
where, Iinductor is the current flowing through the inductor, σ is the conductivity (S/m), μ is the magnetic
permeability of the material under test and f is the frequency of the induced current. It is observed
that with a stable induced current and induced current frequency, the generated heat is directly
proportional to the microwave excitation time and it is inversely proportional to the square root of
the conductivity. However, due to the presence of heat transfer and dissipation problems during
Sensors 2017, 17, 1123
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Due to the skin effect, induced current depth (within the skin depth) in the conductive material is
an extremely important factor. The skin depth can be obtained by the following equation [48]:
δ= p
1
πµσ f
(5)
where f is the microwave’s frequency, σ is the conductivity (S/m), and µ is the magnetic permeability
(H/m) of the material under test. A typical conductivity of CFRP is probably 1000 S/m, and the
permeability is around 1. With 2.4 GHz microwave excitation, the skin depth is about 0.002 mm.
Therefore, MWT belongs to the surface heating category as only the surface of the CFRP is heated.
2.2. 3D Heat Transfer and Temperature Field
Heat Q generated by dielectric loss or the Joule heat will be conducted from inside to the
surrounding material. The heat conduction equation is a time-dependent heat diffusion equation [49]:
∂T
k
=
∂t
ρC p
|
∂2 T
∂2 T
∂2 T
1
+
+
+
Q( x, y, z, t)
2
2
2
ρC p
∂x
∂y
∂z
{z
} |
{z
}
Thermal diffusion
(6)
Microwave heating
where, T = T ( x, y, z, t) is the temperature distribution of the surface, k is the material thermal
conductivity (W/m × K), C p is specific heat capacity (J/kg × K), ρ is the density (kg/m3 ),
and Q( x, y, z, t) is the heat generation function with microwave heating (the dielectric loss heating or
eddy current heating). A surface temperature distribution will eventually reflect disturbances of the
electromagnetic and thermal fields. Therefore, MWT has the potential to characterize and track the
property variations of the material, such as magnetic permeability, electrical conductivity, permittivity,
thermal conductivity, thermal diffusivity, etc. In addition, the depth of defects can be quantified.
The heat generated by Joule heat will propagate a certain distance within the material in the form of
heat waves. The penetration depth δth of these heat waves is [50]:
√
δth ≈ 2 αt
(7)
α = (k/ρCp)
(8)
where, α is the thermal diffusivity, and t is the observation time. α can be expressed as a function of
the density of the material ρ, heat capacity Cp and thermal conductivity k, as shown in Equation (8).
It shows that the penetration depth of heat δth is proportional to the square root of t and α [11]. In the
case of a modulated thermal wave, the length of thermal diffusion decides the penetration depth,
which can be found from the following equation [11]:
s
µt =
2k
=
ωρCp
r
α
πf
(9)
where, ρ is density, k is thermal conductivity, α is thermal diffusivity, Cp is heat capacity, and f is the
frequency of the thermal wave. The penetration depth is proportional to the reciprocal of the square
root of f and α. In other words, the detection depth varies according to the modulation frequency.
In summary, the detection ability of microwave thermography is closely related to the electrical,
dielectric and thermal properties of the material under test.
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3. Types of Microwave Thermography
3.1. Classification of Excitation Configuration
According to the excitation configurations of microwave heating, MWT can be divided into
microwave pulsed thermography (MPT),microwave pulsed phase thermography (MPPT), microwave
lock-in thermography (MLT) [51], or microwave step thermography (MST), also known as microwave
time-resolved thermography [52]. With MPT, the material under test is heated by a small period
of microwave excitation as shown in Figure 3a. The variation of temperature is observed in the
heating phase and the cooling phase. For MST, the sample is step heated by a long pulse as shown in
Figure 3b, and the variation of temperature is observed in the heating phase. As shown in Figure 3c,
the material under test is heated by a periodic amplitude modulated microwave with MLT and the
periodic temperature change is captured. A square pulsed modulated excitation is used to derive phase
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information from multiple thermal waves with one inspection. The influence of non-uniform heating is
been reduced
and deeper
displayed
a displayed
higher contrast.
A pulse
excitation
uniform heating
is beendefects
reducedcan
andbe
deeper
defectswith
can be
with a higher
contrast.
A pulsesignal
is usedexcitation
by MPPT.
Phase
analysis
is carried
outanalysis
in the frequency
domain
Predictably,
microwave
signal
is used
by MPPT.
Phase
is carried out
in the[13].
frequency
domain
[13].
Predictably,
microwave
frequency
modulated
thermography
will
employ
a
frequency
modulated
frequency modulated thermography will employ a frequency modulated microwave excitation in order
microwave
excitation in order
to the
derive
phase
information.
From the above
the that:
conclusion
to derive
phase information.
From
above
analysis,
the conclusion
can analysis,
be reached
MPT and
can
be
reached
that:
MPT
and
MST
analyze
the
temperature
of
thermal
imaging
in
the
time
domain,
MST analyze the temperature of thermal imaging in the time domain, which is affected
by surface
which is affected by surface emissivity variations and non-uniform heating; MLT obtains information
emissivity variations and non-uniform heating; MLT obtains information in the frequency domain such
in the frequency domain such as phase, which can suppress the influence of the surface emissivity
as phase, which can suppress the influence of the surface emissivity variations and non-uniform heating.
variations and non-uniform heating. However, the MLT inspection system requires a long
However,
the MLT time
inspection
requires
a long measurement time and it is relatively complex.
measurement
and it issystem
relatively
complex.
Figure 3. Excitation functions of MWT: (a) MPT; (b) MST; (c) MLT.
Figure 3. Excitation functions of MWT: (a) MPT; (b) MST; (c) MLT.
Comparisons among MPT, MST, MLT, and MPPT are listed in Table 1. Due to the use of an IR
Comparisons
among
MPT,
MST,
MLT, and
are listed
in Table
1. Due
to thevisibility.
use of an IR
camera, all of them
exhibit
high
sensitivity,
highMPPT
resolution,
full-field
detection
and good
camera,
all of them
exhibit high
sensitivity,
high
resolution,
full-field
and good visibility.
In addition,
quantification
information
can be
achieved
based on
the heatdetection
conduction:
In addition,
quantification
information
can
be
achieved
based
on
the
heat
conduction:
1. MPT can be fast and easily deployed. Surface temperature gradients will be introduced not only
1.
2.
3.
4.
defects,
but easily
also local
variations
in surface
emissivitygradients
and non-uniform
heating. A long
MPT from
can be
fast and
deployed.
Surface
temperature
will be introduced
not only
inspection
time
is
required
for
a
thick
material.
In
addition,
the
material
could
be
from defects, but also local variations in surface emissivity and non-uniformdamaged
heating.due
A long
to the high heating energy.
inspection time is required for a thick material. In addition, the material could be damaged due
2. MST is a time-resolved method and it can be used to quantify defect depth. However, the
to the high heating energy.
radiation from the heat source in the continuous heating process could deteriorate the
MST temperature
is a time-resolved
method and
it can
used to quantify
depth.emissivity
However,variation
the radiation
measurements.
Also,
the be
non-uniform
heatingdefect
and surface
from have
the adverse
heat source
continuous
effectsin
on the
defect
evaluation. heating process could deteriorate the temperature
3. MLT generally
required
less excitation energy
MPT.
MLTemissivity
exhibits a higher
sensitivity
measurements.
Also,
the non-uniform
heatingthan
and
surface
variation
havethan
adverse
MPT.
The
phase
data
can
be
extracted
which
is
independent
of
surface
emissivity
and
heating
effects on defect evaluation.
variations. Tests are repeated with various frequencies and it becomes a time-consuming process
MLT generally
required less excitation energy than MPT. MLT exhibits a higher sensitivity than MPT.
to detect defects with various depths. However, MLT offer a compromise with a better depth
The phase data can be extracted which is independent of surface emissivity and heating variations.
resolution.
Tests
are repeated with various frequencies and it becomes a time-consuming process to detect
4. MPPT combines the advantages of MPT and MLT. MPPT is less sensitive to non-uniform heating
defects
with
various
depths.
However,
MLTphase
offerinformation
a compromise
with
a betterMoreover,
depth resolution.
and
surface
emissivity
than
MLT as only
can be
obtained.
MPPT
MPPTemployed
combines
the advantages
of MPT
and
MLT. than
MPPT
is less
sensitive
to non-uniform
a short
excitation pulse
which
is faster
MLT
and wide
frequency
spectra can heating
be
obtained.
However, with
frequency,
transferredcan
energy
is decreasedMoreover,
with MPPT.
and surface
emissivity
thanincreasing
MLT as only
phasethe
information
be obtained.
MPPT
With
post
processing
algorithm,
MPPT
exhibits
better
detect
ability
and
resolution
than
MPT
for
employed a short excitation pulse which is faster than MLT and wide frequency spectra can be
deeper
defects. with increasing frequency, the transferred energy is decreased with MPPT.
obtained.
However,
With post processing algorithm, MPPT exhibits better detect ability and resolution than MPT for
Table 1. Comparisons among MPT, MST, MLT and MPPT.
deeper defects.
Techniques
Strength
Microwave pulsed
thermography [13]
Full-field, high resolution, high sensitivity, good
visibility, quantification, fast, easy deployment
Microwave step
thermography [52]
Full-field, high resolution, high sensitivity, good
visibility, quantification, fast, easy deployment,
Limitation
Small depth, long time for thick material,
emissivity and non-uniform heating
dependence, high power
The radiation from heat source in the
continuous heating process could have a
negative influence on temperature
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Table 1. Comparisons among MPT, MST, MLT and MPPT.
Techniques
Strength
Limitation
Microwave pulsed thermography [13]
Full-field, high resolution, high sensitivity, good visibility,
quantification, fast, easy deployment
Small depth, long time for thick material, emissivity
and non-uniform heating dependence, high power
Microwave step thermography [52]
Full-field, high resolution, high sensitivity, good visibility,
quantification, fast, easy deployment, time-resolved
The radiation from heat source in the continuous
heating process could have a negative influence on
temperature measurements of MUT, emissivity,
and non-uniform heating dependence
Microwave lock-in thermography [51]
Full-field, high resolution, higher sensitivity, good visibility,
quantification, low power, emissivity independence,
elimination of non-uniform heating
Compromise between depth and depth
resolution, time-consuming,
Microwave pulsed phase thermography
Full-field, high resolution, high sensitivity, good visibility,
quantification, fast, emissivity independence, elimination of
non-uniform heating, greater depth and resolution, better detectability
Post signal processing,
energy attenuation with frequency
Sensors 2017, 17, x FOR PEER REVIEW
Microwave
pulsed
Sensors 2017,
17, 1123
phase thermography
Full-field, high resolution, high sensitivity, good
visibility, quantification, fast, emissivity
independence, elimination of non-uniform
heating, greater depth and resolution, better
detectability
7 of 33
Post signal processing, energy attenuation 8 of 33
with frequency
3.2. Classification by Heating Style
3.2. Classification by Heating Style
MWT can be classified into surface heating thermography, volume heating thermography, and
MWT
can be
classified into surface
thermography,
volume
heating
thermography,
abnormal
heating
thermography
[14,45].heating
In Figure
4a, for eddy
current
heating,
MWT can and
be also
abnormal
heating
thermography
[14,45].
In
Figure
4a,
for
eddy
current
heating,
MWT
can
be
also
called surface heating thermography (SHT). Due to the great permeability, the skin depth is very
called
surface
heating
thermography
(SHT).
Dueoftothe
theSHT
greatfamily.
permeability,
the skin depth
is the
veryheat
small
[53–55].
Thus,
it can
be classified
as part
With reflection
mode,
small [53–55]. Thus, it can be classified as part of the SHT family. With reflection mode, the heat
conduction from surface to inside is used to quantify the depth of defect.
conduction from surface to inside is used to quantify the depth of defect.
MWT exhibits volumetric heating for dielectric material inspection. MWT can be called volume
MWT exhibits volumetric heating for dielectric material inspection. MWT can be called volume
heating thermography (VHT), as illustrated in Figure 4b [45,55]. For the transmission and reflection
heating thermography (VHT), as illustrated in Figure 4b [45,55]. For the transmission and reflection
modes
with
VHT,
thethe
characterizations
similar[54].
[54].Only
Only
interesting
areas
heated
modes
with
VHT,
characterizationsof
ofdefects
defects are
are similar
interesting
areas
are are
heated
without
heating
thethe
host
material
Abnormalheat
heatwill
willcaused
caused
defects.
Furthermore,
without
heating
host
materialininsome
somecases.
cases. Abnormal
byby
defects.
Furthermore,
this this
abnormal
heat
is
used
to
quantify
depth
information
of
the
related
defect.
In
Figure
4c, these
abnormal heat is used to quantify depth information of the related defect. In Figure 4c, these
methods
are called
abnormal
heating
thermography
(AHT).
For detecting
water water
in concrete
structures,
methods
are called
abnormal
heating
thermography
(AHT).
For detecting
in concrete
structures,
MWT can be
as a kind of AHT.
MWT
can be considered
asconsidered
a kind of AHT.
Figure4.4.Styles
Stylesof
ofheating:
heating: (a)
AHT.
Figure
(a)SHT;
SHT;(b)
(b)VHT;
VHT;(c)(c)
AHT.
4. Developments
and
Case
Studies
4. Developments
and
Case
Studies
4.1. 4.1.
A History
of MWT
Development
A History
of MWT
Development
Developed
countries
have
taken
useof
ofMWT
MWTtotocarry
carry
related
researches
Developed
countries
have
takenthe
thelead
lead on
on the use
outout
related
researches
and and
achieved
some
interesting
results
[56–58].Levesque
Levesque and Ambrosio
study
on MWT
in in
achieved
some
interesting
results
[56–58].
Ambrosiodid
dida apreliminary
preliminary
study
on MWT
the 1990s.
Levesque
et al.
employedXXand
andKu
Ku bands
bands (range
toto
1818
GHz)
horns
andand
parabolic
the 1990s.
Levesque
et al.
employed
(rangefrom
from88GHz
GHz
GHz)
horns
parabolic
antennas
to excite
sampleunder
undertest
test[59].
[59]. The
The excitation
is provided
by aby100
W W
antennas
to excite
thethe
sample
excitationofofthe
theantenna
antenna
is provided
a 100
amplifier.
Thermal
images
are
produced
by
an
AGEMA
(model
782
LWB)
IR
camera
with
8
μm–12
μm
amplifier. Thermal images are produced by an AGEMA (model 782 LWB) IR camera with 8 µm–12 µm
range. An area of 300 × 300 mm22 is been measured due to the limited excitation area. Several 10 mm
range.
An area of 300 × 300 mm is been measured due to the limited excitation area. Several 10 mm
thick glass-epoxy composites have been tested to identify the inserted carbon particles area. The
thick glass-epoxy composites have been tested to identify the inserted carbon particles area. The proposed
proposed method were used to characterize artificial defects’ size and location under different depths
method were used to characterize artificial defects’ size and location under different depths in composite
in composite materials. Ambrosio et al. used a cavity with a minimum 600 W to detect artificial
materials.
et al. used
a cavity
with
minimum
600×W
to×detect
artificial
in non-metallic
3 whichdefects
defectsAmbrosio
in non-metallic
composites
[60].
Thea cavity
was 300
200
280 mm
is excited
by a 2.45
3 which is excited by a 2.45 GHz magnetron and
composites
[60].
The
cavity
was
300
×
200
×
280
mm
GHz magnetron and an Alter VPG1540 power supply unit (maximum power 1200 W). They used a
an Alter
VPG1540
powermeter
supplytounit
(maximum
power and
1200reflected
W). Theymicrowave
used a Cober
PM45 Two
power
meter to
Cober
PM45 power
monitor
the incident
powers.
cavity
monitor
the incident
andcavity
reflected
microwave
Two
cavity applicators
open cavity
applicator
applicators
(an open
applicator
and a powers.
large cavity
applicator)
have been(an
proposed
to avoid
the
edge effects
and tohave
improve
field uniformity
the sample.
Toeffects
estimate
thetodefect
and aperture
a large cavity
applicator)
beenthe
proposed
to avoid over
the aperture
edge
and
improve
permittivity
andover
depth
surface temperature
perturbation,
theoretical
modeling
the field
uniformity
theinfluence
sample. on
To estimate
the defect permittivity
and
depth influence
onand
surface
numerical
simulations
were
carried
out.
temperature perturbation, theoretical modeling and numerical simulations were carried out.
In 1999,
Takahide
OsakaUniversity
University applied
surface
breaking
cracks
in in
In 1999,
Takahide
et et
al.al.atatOsaka
appliedMWT
MWTtotodetect
detect
surface
breaking
cracks
reinforced
concrete
structures
and
they
pointed
out
that
the
tip
of
crack
will
produce
more
heat
reinforced concrete structures and they pointed out that the tip of crack will produce more heat during
during the test [61]. Heat was introduced by a time-gated microwave source into the homogeneously
the test [61]. Heat was introduced by a time-gated microwave source into the homogeneously reinforced
reinforced concrete structure. With the microwave penetration features, the subsurface of the
concrete structure. With the microwave penetration features, the subsurface of the reinforced concrete
reinforced concrete structure could be inspected. Moreover, wet cracks could be selectively heated.
structure
could
be inspected.
wet cracks
could bewith
selectively
heated. Therefore,
Therefore,
subsurface
cracksMoreover,
will be immediately
identified
MWT. Analyses
of time andsubsurface
spatial
cracks will be immediately identified with MWT. Analyses of time and spatial dependence features of
measured thermal images are possible to quantify cracks’ depth and thermal diffusivity information [61].
In the 21st century, groups in the USA, UK, France, Poland, Italy, Korea, etc. have developed MWT
for metal, dielectric material, cement/concrete, GFRP, CFRP, honeycomb and cement-based composites
detection problems. These works have been simply summarized in Table 2 and are introduced in detail in
the following Sections 4.2–4.9.
Sensors 2017, 17, 1123
9 of 33
Table 2. Summary of researches with MWT.
Hardware Development
Software Development
Experimental Study
Operation
Frequency
Antenna/Sensor
Power
IR Camera
Simulation Study
Sampling Software
Signal Processing
Material under Test
Defects
8 GHz to
18 GHz [59]
Horns and parabolic
antennas [59]
100 W [59]
AGEMA 782
LWB [59]
Not available
CEDIP PTR-9010
system [59]
Normalized the infrared images
pixel by pixel [59]
Glass-epoxy
composites [59]
Delaminations
HP 8757 C network
analyzer [60]
Open cavity applicator and large
cavity applicator have been
designed [60]
Kevlar or fiberglass slabs
and sandwich
samples [60]
Defects
Mortar block [61]
Cracks
Reinforced steel bars [62],
Rebar in air [63];
Embedded in cement
[63,65], CFRP [64]
Corrosion, delaminations,
debonding and crack
Magnetron [60]
600 W–1700 W [60]
AGEMA AGA
880 [60]
Influence of defect
permittivity and depth
has been estimated [60].
Microwave oven [61]
1400 W [61]
Nikon LAIRD-3 [61]
Not available
Not available
Thermal image
was taken at 20 s [61]
2 GHz to 3 GHz [62],
2.45 GHz [63,64]
TEM horn
antenna [62,64]
50 W [62,64],
10 W [63]
DRS Tamarisk 320
[62,64], FLIR SC
500 [63]
CST Microwave Studio
and MPHYSICS
Studio [62].
Not available
The surface thermal profile was
taken after 10 s of heating [62].
The surface thermal profile was
taken after 5 s
and 15 s of heating [63].
2.45 GHz [65]
Magnetron generated
horn antenna [65]
600 W [65]
Not available
Not available
ALTAIR software
A contrast algorithm is used to
analyze the thermogram series
with 5 min of heating [65].
5 GHz to 10 GHz [66]
Horn antenna [66]
Mikron 6T61 and
SantaBarbara IR
camera [66]
Not available
Macintosh
microcompute [66]
A 2.7 s microwave
pulse was used [66]
Multilayered
plexiglass-water-teflon
specimen [66]
Debonding
Santa Barbara
Focalplane [67]
Not available
LabVIEW
The surface thermal profile was
taken after 8 s
and 10 s of heating [67]
Carbon fibers in different
epoxy structures [67]
Embedded fibers
Rohde & Schwarz
SMF 100 A signal
generator [57]
The surface thermal profile was
taken after 10 min of heating [57]
2.45 GHz [60,61]
2.3 W [66,67]
9 GHz [67]
A single flare horn
antenna [67]
18 GHz [57]
Flann 18 094-SF40
waveguide [57]
WR430 waveguide [57]
1 W [57]
FLIR SC7500 [57]
COMSOL Multiphysics
and CST Microwave
Studio [57]
1000 W [57]
Flir A325 [57,68]
2.45 GHz [56,68]
1 GHz [69]
The surface thermal profile was
obtained after 10 s to 15 s of
heating [57]
Not available
Magnetron [68]
500 W [68]
Pyramidal horn
antenna [56]
360 W [56]
Not available
Not available
Coaxial-type
probes [69]
0.1 W [69]
FLIR T620 [69]
CST Microwave
Studio [69]
Steel bar corrosion
Defects
GFRP [57]
Debonding and
delamination
A sequence of 180 thermograms
was obtained and processed by
using normalized, standardized
contrast and cosine transform [68]
Composite materials with
adhesive bounded
joints [68]
Defects
ALTAIR
program [56]
The surface thermal profile was
taken after 150 s of heating [56]
CFRP [56]
Defects
Spectrometer [69]
Normalized to the maximum
value of field intensity [69]
Carbon-fiber composite
materials [69]
Conductivity
measurement
Not available
Sensors 2017, 17, 1123
x FOR PEER REVIEW
10
9 of 33
4.2. Metals and Corrosion
etal.
al.from
from
Missouri
University
of Science
and Technology
proposed
the
of
Foudazi et
thethe
Missouri
University
of Science
and Technology
proposed
the use
ofuse
MWT
MWT
the detection
and characterization
of corroded
reinforced
In Figure
5a,
for
thefor
detection
and characterization
of corroded
reinforced
steel steel
bars bars
[62]. [62].
In Figure
5a, the
2 horn antenna to
2 horn
the measurement
setup
for steel
bars
is illustrated.
They employed
a 14
24 cm
measurement
setup
for steel
bars is
illustrated.
They employed
a 14 × 24
cm×
antenna
to irradiate
irradiate
with
a 50 W microwave
signal
fordistance
10 s. The
distance
the
steel
and
steel
barssteel
with bars
a 50 W
microwave
signal for 10
s. The
between
thebetween
steel bars
and
thebars
antenna
the antenna
was 1the
cm.experiment,
During thefour
experiment,
piecesmaterial
of corroded
mounted
on
was
1 cm. During
pieces offour
corroded
were material
mountedwere
on steel
bars and
steel bars
and
spaced
1 cmTamarisk
apart. A320
DRS
Tamarisk
320 was
thermal
camera
was utilized
to obtain
spaced
1 cm
apart.
A DRS
thermal
camera
utilized
to obtain
the thermal
profilethe
of
thermal
of the
steel
bars with aIn0.05
K sensitivity.
In Figure
5b,profiles
the surface
thermal
the
steel profile
bars with
a 0.05
K sensitivity.
Figure
5b, the surface
thermal
for steel
bars profiles
after 10
bars after
s as detected
GHz,are
and
3 GHz energy
are bars
provided.
steel
sfor
assteel
detected
with 10
2 GHz,
2.5 GHz,with
and 23GHz,
GHz 2.5
energy
provided.
The steel
were aThe
smooth
bars were
a smooth
rebar
without
ribs.rebar
The radius
thiswhich
rebar contained
was 4.8 cma which
containedarea.
a 1 cm
rebar
without
ribs. The
radius
of this
was 4.8ofcm
1 cm corrosion
In
corrosion
In Figure
theare
visible
hot spots areas
are theoncorroded
areas
on Because
these steel
Because
Figure
5b,area.
the visible
hot5b,
spots
the corroded
these steel
bars.
of bars.
the relatively
of the
relatively
low thermal
conductivity
corroded
steel,
heat quickly
dissipatessteel.
in uncorroded
low
thermal
conductivity
of corroded
steel,ofheat
quickly
dissipates
in uncorroded
Moreover,
steel. Moreover,
these
temperature
differences
betweenareas
the corroded
areas
different
these
temperature
differences
between
the corroded
indicated
thatindicated
differentthat
amounts
of
amounts ofabsorb
corrosion
absorbamounts
different amounts
of microwave
a preliminary
simulation
corrosion
different
of microwave
energy. energy.
With aWith
preliminary
simulation
and
and experimental
study
ofMWT,
the MWT,
it demonstrated
a higher
excitation
microwave
frequency
experimental
study
of the
it demonstrated
that that
a higher
excitation
microwave
frequency
will
will
to a higher
temperature
for corrosion
detection
in bars.
steel Moreover,
bars. Moreover,
increased
corrosion
lead lead
to a higher
temperature
for corrosion
detection
in steel
increased
corrosion
leads
leads
to absorption
of microwave
energy
increasing
results
a greater
difference
in the
measured
to
absorption
of microwave
energy
increasing
results
in a in
greater
difference
in the
measured
IR
IR images.
images.
Figure 5. (a)
(a) MWT
MWT measurement
measurement setup
setup for
for corroded
corroded rebar detection;
detection; (b)
(b) temperature
temperature profile for
corroded steel bar [62]. Reprinted/reproduced
Reprinted/reproducedwith
with permission
permission from
from IEEE.
IEEE. ..
Pieper et al. demonstrated an active MWT for inspection of large corrosion areas on reinforcing
Pieper et al. demonstrated an active MWT for inspection of large corrosion areas on reinforcing
steel bars for cement-based structures [63]. They used CST Microwave studio and MultiPhysics studio
steel bars for cement-based structures [63]. They used CST Microwave studio and MultiPhysics
to construct a coupled microwave and thermal simulation model. The effects of steel bars have been
studio to construct a coupled microwave and thermal simulation model. The effects of steel
investigated in the air and in concrete. To detect the change in temperature with a thermal camera, the
bars have been investigated in the air and in concrete. To detect the change in temperature with
incident microwave power should be increased because some of the microwave energy is absorbed by
a thermal camera, the incident microwave power should be increased because some of the microwave
the concrete. The effect of different polarization has been studied with CST. With 10 W incident power,
energy is absorbed by the concrete. The effect of different polarization has been studied with
the parallel polarization generates the most uniform heating in that of orthogonal polarization and
CST. With 10 W incident power, the parallel polarization generates the most uniform heating in
circular polarization, but the temperature increase was the lowest (only 0.014 °C). The highest
that of orthogonal polarization and circular polarization, but the temperature increase was the
temperature increase
was generated by orthogonal polarization (around 0.025 °C), therefore,
lowest (only 0.014 ◦ C). The highest temperature increase was generated by orthogonal polarization
orthogonal polarization
is the best choice for thin corrosion detection.
(around 0.025 ◦ C), therefore, orthogonal polarization is the best choice for thin corrosion detection.
During the experimental study, two steel (AISI 1008) bars (each of length 150 mm and radius 4.8
During the experimental study, two steel (AISI 1008) bars (each of length 150 mm and radius 4.8 mm)
mm) were measured, which have been embedded in parallel in a concrete block (170 × 150 × 50 mm33).
were measured, which have been embedded in parallel in a concrete block (170 × 150 × 50 mm ).
The sample was heated for 5 s by a microwave oven operating at 2.45 GHz. A FLIR Thermacam SC
The sample was heated for 5 s by a microwave oven operating at 2.45 GHz. A FLIR Thermacam
500 was used to provide thermal images with a sensitivity of 0.1 °C. In Figure
6a, the two steel bars
SC 500 was used to provide thermal images with a sensitivity of 0.1 ◦ C. In Figure 6a, the two
have been heated by microwave energy for 15 s. One (top) with localized significant corrosion (on
steel bars have been heated by microwave energy for 15 s. One (top) with localized significant
the order of 1 mm–4 mm) on a portion of its length, the one below with light corrosion (on the order
corrosion (on the order of 1 mm–4 mm) on a portion of its length, the one below with light corrosion
0.2 mm or less) along half of its length. As illustrated in Figure 6b and 6c, the corroded areas in the
(on the order 0.2 mm or less) along half of its length. As illustrated in Figure 6b,c, the corroded areas
two steel bars have been identified in the thermal images as indicated by the black circle. Moreover,
in the two steel bars have been identified in the thermal images as indicated by the black circle.
in Figure 6c, the uncorroded area in the steel bar is also visible, appearing as a relatively lower
Moreover, in Figure 6c, the uncorroded area in the steel bar is also visible, appearing as a relatively
temperature line (in the left of the black circle). In Figure 6e, the corroded steel bar is still detectable
when embedded in a concrete block as highlighted by the black circle. These results show that steel
Sensors 2017, 17, x; doi: FOR PEER REVIEW
www.mdpi.com/journal/sensors
Sensors 2017, 17, 1123
11 of 33
lower temperature line (in the left of the black circle). In Figure 6e, the corroded steel bar is still
Sensors 2017, 17, x FOR PEER REVIEW
10 of 33
detectable when embedded in a concrete block as highlighted by the black circle. These results show
that
steel corrosion
in concrete
will
to a higher
loss tangent
and
the thermal
properties
are changed.
corrosion
in concrete
will lead
to alead
higher
loss tangent
and the
thermal
properties
are changed.
With
With
microwave
heating,
the
physical
property
changes
due
to
corrosion
become
measurable
microwave heating, the physical property changes due to corrosion become measurable in
in the
the
thermograms.
onon
thethe
orientation
and thickness
of corrosion,
the polarization
of the incident
thermograms.Depending
Depending
orientation
and thickness
of corrosion,
the polarization
of the
microwave
signal can signal
be optimized
simulation.
effect ofThe
corrosion
thicknesslayer
on
incident microwave
can be through
optimized
through The
simulation.
effect layer
of corrosion
microwave
heating
has
been
investigated.
thickness on microwave heating has been investigated.
Figure
Figure6.6.(a)
(a)Photograph
Photographof
oflocalized
localizedcorrosion
corrosion(top)
(top)and
andlight
lightcorrosion
corrosion(bottom);
(bottom);(b)
(b)thermal
thermalimages
images
ofofaasteel
steelbar
barwith
withlight
lightcorrosion
corrosionand
and(c)
(c)localized
localizedcorrosion;
corrosion;(d)
(d)photograph
photographofofclean
clean(left)
(left)and
and
corroded
(right)
steel
bars;
(e)
thermal
images
of
clean
(left)
and
corroded
(right)
steel
bars
embedded
corroded (right) steel bars; (e) thermal images of clean (left) and corroded (right) steel bars embedded
ininthe
theconcrete
concreteblock
blockafter
aftermicrowave
microwaveheating
heating[63].
[63].Reprinted/Reproduced
Reprinted/Reproducedwith
withpermission
permissionfrom
fromAIP
AIP
Publishing
PublishingLLC.
LLC.
Keoetetal.al.
presented
a pyramidal
antenna
based toMWT
detect corroded
steel in a
Keo
presented
a pyramidal
horn horn
antenna
based MWT
detecttocorroded
steel in a reinforced
reinforced
concrete
wall [65].
the experimental
study, a commercial
operating
concrete
wall
[65]. During
the During
experimental
study, a commercial
magnetron magnetron
operating at
2.45 GHzat
2.45
GHz
was
used
to
irradiate
a
maximum
800
W
of
microwave
energy.
The
steel
reinforcements
was used to irradiate a maximum 800 W of microwave energy. The steel reinforcements (each one
(eacha one
with aofdiameter
of 12 mm,
a regular
of 10acm)
withconcrete
a 38 mmcovering
concrete
with
diameter
12 mm, located
at alocated
regularatspacing
of spacing
10 cm) with
38 mm
3
covering
were embedded
in ablock
concrete
block
(1000
mmspecimen
). The specimen
was by
heated
by
were
embedded
in a concrete
(1000
× 1000
× ×651000
mm×3 ).65The
was heated
600 W
600
W
microwave
energy
for
5
min.
The
reflection
mode
was
used
as
the
thermal
camera
was
placed
microwave energy for 5 min. The reflection mode was used as the thermal camera was placed on
on same
the same
as the
excitation
source.
A data
analysis
method
basedonona acontrast
contrastalgorithm
algorithmwas
was
the
sideside
as the
excitation
source.
A data
analysis
method
based
used
to
analyze
the
thermogram
series
to
reduce
the
effect
of
non-uniform
excitation.
As
shown
used to analyze the thermogram series to reduce the effect of non-uniform excitation. As shown inin
Figure7a,
7a,the
theinfrared
infraredcamera
camerawas
wascomposed
composedofofa a320
320××256
256matrix
matrixdetector
detectorofofindium
indiumantimonide
antimonide
Figure
◦
(InSb)with
with aa sensitivity
sensitivity range
antenna
was
placed
in ain45°
direction
to heat
(InSb)
range of
of 3–5
3–5μm.
µm.The
Theexcitation
excitation
antenna
was
placed
a 45
direction
to
the
largest
surface
area
of
the
specimen.
In
addition,
the
infrared
camera
was
placed
at
2.32
m
away
heat the largest surface area of the specimen. In addition, the infrared camera was placed at 2.32 m
◦ direction
from from
the specimen
in ain30°
direction
which
can
detect
area of
of the
the
away
the specimen
a 30
which
can
detectthe
thelargest
largestpossible
possible surface
surface area
specimen.Thermograms
Thermogramswere
wererecorded
recorded
1 image
s by
using
ALTAIR
software
(developed
specimen.
atat
1 image
perper
s by
using
thethe
ALTAIR
software
(developed
by
by
FLIR
for
obtaining
measurement
data).
Figure
7b
shows
the
obtained
thermograms
at
the
250
FLIR for obtaining measurement data). Figure 7b shows the obtained thermograms at the 250 s instant.s
instant.
The abnormal
temperature
areas correspond
to the corrosion
areasteel
in the
steel reinforcements.
The
abnormal
temperature
areas correspond
to the corrosion
area in the
reinforcements.
In the
In
the
preliminary
experimental
study
of
the
MWT,
it
was
demonstrated
that
the
detection
depth
of
preliminary experimental study of the MWT, it was demonstrated that the detection depth of MWT
MWT
was
about
3.8
cm
in
a
thick
concrete
block.
was about 3.8 cm in a thick concrete block.
Sensors 2017, 17, 1123
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Sensors 2017, 17, x FOR PEER REVIEW
12 of 33
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Figure
7. Photograph
of microwave
thermographymeasurement
measurement setup
setup (a)
(a) and
Figure
7. Photograph
of microwave
thermography
and temperature
temperatureprofile
profile for
for
corroded
steel
bar
(b)
[65].
Reprinted/reproduced
with
permission
from
Elsevier.
corroded steel bar (b) [65]. Reprinted/reproduced with permission from Elsevier.
7. Photograph
4.3. Figure
Dielectric
Materials of microwave thermography measurement setup (a) and temperature profile
4.3. Dielectric
Materials
for corroded
steel bar (b) [65]. Reprinted/reproduced with permission from Elsevier.
Osiander et al. employed a time-resolved MWT system for surface and sub-surface inspection
Osiander
et al. employed
a time-resolved
MWTatsystem
for
surface
and
sub-surface
inspection
on Plexiglass-water-Teflon
specimens
with absorbers
different
depths
(0.15,
0.30
and 0.45 mm)
[66].
4.3. Dielectric Materials
on Plexiglass-water-Teflon
specimens
with absorbers
different
depths
(0.15,was
0.30
andto0.45
mm) [66].
Figure 8a shows a diagram
of the experimental
setup.atAn
HP 6890B
oscillator
used
generate
al.with
employed
time-resolved
for6890B
surface
and 1277
sub-surface
inspection
microwave
a of
frequency
range fromMWT
5 GHzsystem
to 10HP
GHz.
A Hughes
X-band
traveling
Figure
8aOsiander
showspulses
aetdiagram
thea experimental
setup.
An
oscillator
was
used
to generate
on
Plexiglass-water-Teflon
specimens
with
absorbers
at
different
depths
(0.15,
0.30
and
0.45
mm)
[66].
wave
tube
amplifier
with
2.3
W
maximum
power
was
utilized
as
a
power
amplifier.
An
excitation
microwave pulses with a frequency range from 5 GHz to 10 GHz. A Hughes 1277 X-band traveling
Figure
8a
shows
a
diagram
of
the
experimental
setup.
An
HP
6890B
oscillator
was
used
to
generate
horn
antenna
was
placed
in
a
45°
direction
with
respect
to
the
sample
surface.
Two
infrared
cameras
wave tube amplifier with 2.3 W maximum power was utilized as a power amplifier. An excitation
pulses
with the
a frequency
range from 5ofGHz
to 10 GHz.
A Hughes
X-band
traveling
were
usedwas
to monitor
temperature
the sample
test.
One1277
was
a Mikron
6T61
hornmicrowave
antenna
placed
in
a surface
45◦ direction
with respect
to the under
sample
surface.
Two
infrared
cameras
infrared
withwith
an HgCdTe
detector. The
second
was aas
SantaBarbara
infraredAn
camera
with
wave
tubescanner
amplifier
2.3 W maximum
power
wasone
utilized
a power amplifier.
excitation
were used to monitor the surface temperature of the sample under test. One was a Mikron 6T61
a 128antenna
× 128 pixels
InSb focal
array. The
resolution
of the first
camera
wascameras
0.1 K.
horn
was placed
in a plane
45° direction
withtemperature
respect to the
sample surface.
Two
infrared
infrared
scanner
with
an HgCdTe
detector. resolution
The second
one 0.003
was aK.SantaBarbara
infrared
camera
For
the
second
IR
camera,
the
temperature
is
about
The
specimen
under
test
is
were used to monitor the surface temperature of the sample under test. One was a Mikron 6T61
withinfrared
a 128 ×scanner
128
pixels
InSb
focal
plane
array.
The
temperature
resolution
of
the
first
camera
illustrated
in Figure
8b.
It
is
structured
with
a
Teflon
layer
of
varied
thickness
and
a
water
layer
with
with an HgCdTe detector. The second one was a SantaBarbara infrared camera withwas
0.1 K.
For
the
second
IRbacked
camera,
the
temperature
resolution
isthe
about
K. camera
The specimen
under
constant
Plexiglass
layers.
Considering
power,
thefirst
microwave
horn0.1
was
aa128
× 128 thickness
pixels InSb
focal with
plane
array.
The
temperature
resolution
of0.003
the
was
K.
test For
isworking
illustrated
in
Figure
8b.
It
is
structured
with
a
Teflon
layer
of
varied
thickness
and
a
in the IR
near
field. The
dataresolution
was normalized
to 0.003
the peak
amplitude
to eliminate
thewater
the second
camera,
the measured
temperature
is about
K. The
specimen
under test
is
effects
non-uniform
distribution.
Figure
8c shows
IR images
ofthe
the
test
sample
before,
layerillustrated
with aofconstant
backed
with
layers.
Considering
the
microwave
in Figurethickness
8b. microwave
It is structured
withPlexiglass
a Teflon
layer
of varied
thickness
andpower,
a water
layer
with
and
afterinathe
2.7 near
s microwave
pulse.
Three Considering
water
corresponding
to the
Teflon
layer
hornaduring
was
working
field.
The
measured
data layers
was normalized
tomicrowave
the
peak
amplitude
constant
thickness
backed
with
Plexiglass
layers.
the
power, the
horn
was to
thicknesses
appear
in the
IRmeasured
images
indata
a temporal
order. With
the potential
of surface
working
the
near
The
wasdistribution.
normalized
toFigure
theMWT,
peak
eliminate
the test
eliminate
theineffects
offield.
non-uniform
microwave
8camplitude
shows
IRto
images
of the
temperature
versus time
has been
shown forFigure
subsurface
defects
quantitative
characterization.
effects
of
non-uniform
microwave
distribution.
8c
shows
IR
images
of
the
test
sample
before,
sample before, during and after a 2.7 s microwave pulse. Three water layers corresponding to the
Compared
with
beam
heating, dry
epoxy
coated
steel
samples
exhibit a very
small
response
during
after laser
a 2.7appear
s microwave
Three
layers
corresponding
to the
Teflon
layer of
Teflon
layerand
thicknesses
in the pulse.
IR images
inwater
a temporal
order. With MWT,
the
potential
with
microwave
heating.
When
a
debonding
region
contains
water,
the
whole
structure
of
the
thicknesses
appear
in thetime
IR has
images
inshown
a temporal
order. With
MWT,
the potential
of surface
surface
temperature
versus
been
for subsurface
defects
quantitative
characterization.
debonding
region
can
be
illustrated.
The
wavelength
independent
resolution
has
been
demonstrated
temperature versus time has been shown for subsurface defects quantitative characterization.
Compared
with
laser
beam heating,
dry
epoxy
coated steel
samples
exhibit
a very small
response
to be 30
μm.
Anlaser
analytical
hasdry
been
provided
extract
the time
dependence
of the
surface with
Compared
with
beam model
heating,
epoxy
coatedtosteel
samples
exhibit
a very small
response
microwave
heating.
When
a
debonding
region
contains
water,
the
whole
structure
of
the
debonding
temperature
where
quantitative
such as theregion
depth of
the defect
can be
with
microwave
heating.
Whendata
a debonding
contains
water,
theextracted.
whole structure of the
region
can be illustrated. The wavelength independent resolution has been demonstrated to be 30 µm.
debonding region can be illustrated. The wavelength independent resolution has been demonstrated
An analytical
model
has beenmodel
provided
to extract
thetotime
dependence
of the surface
temperature
to be 30 μm.
An analytical
has been
provided
extract
the time dependence
of the
surface
where
quantitative
data
such
as
the
depth
of
the
defect
can
be
extracted.
temperature where quantitative data such as the depth of the defect can be extracted.
Figure 8. Schematic diagram of the experimental setup (a), the specimen under test (b) and IR images
(c) [66]. Reprinted/reproduced with permission from SPIE.
Figure
8. Schematic
diagram
theexperimental
experimental setup
setup (a),
under
testtest
(b)(b)
andand
IR images
Figure
8. Schematic
diagram
ofofthe
(a),the
thespecimen
specimen
under
IR images
(c) [66]. Reprinted/reproduced with permission from SPIE.
(c) [66]. Reprinted/reproduced with permission from SPIE.
Sensors 2017, 17, 1123
Sensors 2017, 17, x FOR PEER REVIEW
13 of 33
12 of 33
4.4.
4.4. Cement
Cement and
and Concrete
Concrete
Takahide
Takahideet
etal.
al. proposed
proposed the
the use
use of
of MWT
MWT for
for detecting
detecting surface-breaking
surface-breaking cracks in concrete [61].
Surface-breaking
cracks
can
be
penetrated
with
water.
The
crack
Surface-breaking cracks can be penetrated with water. The crack opening
opening distance
distance was
was 0.2
0.2 mm
mm and
and
0.4
0.4 mm.
mm. The size of the
the cracks
cracks was
was 10
10 mm
mm in
in depth
depth and
and 40
40mm
mmininwidth.
width. Since
Since the
the microwave
microwave
absorptivity
absorptivity of
of the
the concrete
concrete is
is much
much smaller
smaller than
than that
that of
of water,
water, cracks
cracks containing
containing water
water can
can be
be
selectively
heated.
By
applying
microwaves
to
the
concrete
structure,
the
thermal
conduction
of
selectively
By applying microwaves to the concrete structure, the thermal conduction of these
these
heated
cracks
generate
localized
high-temperature
regions.
experimental
MWT
setup
heated
cracks
will will
generate
localized
high-temperature
regions.
TheThe
experimental
MWT
setup
is
is
illustratedininFigure
Figure9a.
9a.AAcommercially
commerciallyavailable
available2.45
2.45 GHz
GHz magnetron
magnetron was
was used to
illustrated
to irradiate
irradiate
microwaves
mortar block
blockwith
withaamaximum
maximum1400
1400WW
output
power.
specimen
under
microwaves into the mortar
output
power.
TheThe
specimen
under
test
test
placed
in the
microwave
oven.
NikonLAIRD-3
LAIRD-3with
withPtSi
PtSiarray
arraywas
was used
used to measure
waswas
placed
in the
microwave
oven.
AA
Nikon
measure the
the
temperature
distribution
of
the
mortar
block.
In
Figure
9b,
four
artificial
cracks
have
been
introduced
temperature distribution of the mortar block. In Figure 9b, four artificial cracks have been introduced
to
hardening
mortar
blockblock
specimen.
By injecting
water into
crackinto
C and
applying
microwaves
toa arapid
rapid
hardening
mortar
specimen.
By injecting
water
crack
C and
applying
for
5 s, crack Cfor
with
selectively
heated.
Compared
withCompared
the non-crack
area,
temperature
microwaves
5 s,water
crackwas
C with
water was
selectively
heated.
with
thethe
non-crack
area,
◦ C to 8 ◦ C after microwave heating. As shown in Figure 9c, the position of
of
the
crack
rose
about
6
the temperature of the crack rose about 6 °C to 8 °C after microwave heating. As shown in Figure 9c,
the
C can
be crack
easilyCdetected
from detected
the thermal
taken immediately
after the microwave
the crack
position
of the
can be easily
fromimage
the thermal
image taken immediately
after the
excitation.
authors found
the temperature
of the crackregion
degraded
aftercrack
20 s
microwaveMeanwhile,
excitation.the
Meanwhile,
the that
authors
found that region
the temperature
of the
due
to
the
thermal
diffusion
from
the
crack
into
the
surrounding
area.
The
relation
between
the
crack
degraded after 20 s due to the thermal diffusion from the crack into the surrounding area. The relation
size
and temperature
rise
should
be determined
for quantitative
investigations.
between
the crack size
and
temperature
rise should
be determined
for quantitative investigations.
Figure9.
9. Schematic
Schematic diagram
diagram of
of MWT
MWT (a),
(a), mortar
mortar block
block specimen
specimen with
with artificial
artificialcracks
cracks(b)
(b)and
andthermal
thermal
Figure
imagestaken
takenafter
aftermicrowave
microwaveheating
heating(c)
(c)[61].
[61].Reprinted/reproduced
Reprinted/reproduced with
with permission
permission from
from SPIE.
SPIE.
images
4.5. Glass
Glass Fiber
Fiber Composite
Composite Structures
Structures
4.5.
Bowenet
etal.
al. introduced
introduced microwave-source
microwave-source time-resolved
time-resolvedinfrared
infraredradiometry
radiometryfor
fordetecting
detectingand
and
Bowen
characterizing
microwave
absorption
in
dielectric
materials
[67].
An
HP
6890B
oscillator
was
used
to
characterizing microwave absorption in dielectric materials [67]. An HP 6890B oscillator was used
excite
a 9a GHz
microwave
signal.
AA
Hughes
1277
X-band
traveling
wave
tube
amplifier
was
used
to
to
excite
9 GHz
microwave
signal.
Hughes
1277
X-band
traveling
wave
tube
amplifier
was
used
amplify
this
signal
to
a
maximum
2.3
W
power.
A
single
flare
horn
antenna
with
about
50°
beam
◦
to amplify this signal to a maximum 2.3 W power. A single flare horn antenna with about 50 beam
width was
was placed
placed15
15cm
cmfrom
fromthe
thesample
sampleunder
undertest.
test.AASanta
SantaBarbara
Barbaracamera
camerawith
with128
128×× 128
128 InSb
InSb
width
focal plane
plane array
array was
was used
used to
to detect
detect the
the IR
IR radiation.
radiation. The
The temperature
temperature resolution
resolution is
is about
about 0.003
0.003 K.
K.
focal
With
embedded
fibers
at
different
locations,
a
fiberglass-epoxy
specimen
was
measured.
The
depth
With embedded fibers at different locations, a fiberglass-epoxy specimen was measured. The depth of
of the
fibers
was
0.25
mm
and
0.75
mm.
Due
theloss
losstangent
tangentand
andJoule
Jouleheating,
heating,there
thereisisaavery
veryhigh
high
the
fibers
was
0.25
mm
and
0.75
mm.
Due
toto
the
contrast
for
defects
in
embedded
epoxy
materials.
The
size
and
orientation
of
these
embedded
fibers
contrast for defects in embedded epoxy materials. The size and orientation of these embedded fibers in
in the
measured
thermal
images
studied.
The interaction
is strongly
dependent
on the
the
measured
thermal
images
havehave
been been
studied.
The interaction
is strongly
dependent
on the length
length
of the
fiberto(930mm
to and
30 mm)
and orientations.
The temperature
showsdistribution
a modal distribution
of
the fiber
(9 mm
mm)
orientations.
The temperature
shows a modal
along the
along
the
fiber
for
fibers
longer
than
12
mm.
fiber for fibers longer than 12 mm.
Cheng et al. [57] developed a microwave pulsed thermography system for glass fiber composite
measurement. Figure 10a illustrates the setup of the experimental system: (1) an adaptor connected
with the waveguide; (2) GFRP wind turbine blade; (3) microwave generator linked with cable; (4) IR
Sensors 2017, 17, 1123
14 of 33
Cheng et al. [57] developed a microwave pulsed thermography system for glass fiber composite
measurement. Figure 10a illustrates the setup of the experimental system: (1) an adaptor connected
with
the waveguide; (2) GFRP wind turbine blade; (3) microwave generator linked with
cable;
Sensors 2017, 17, x FOR PEER REVIEW
13 of 33
(4) IR camera. GFRP wind turbine blade with 4 holes (4.5 mm in radius) at the root was heated
bycamera.
an open-ended
waveguide
connected
Flann
Theheated
adaptor
linked
GFRP wind
turbine blade
with 4 with
holes a(4.5
mm18
in 094-SF40
radius) at adaptor.
the root was
by was
an openwaveguide
a Flann
18 094-SF40
adaptor.
The adaptoroutput
was linked
to of
a signal
to ended
a signal
generatorconnected
(Rohde &with
Schwarz
SMF
100 A) with
the maximum
power
30 dBm
generator
(Rohde
Schwarz SMF
A) with
thethe
maximum
power aof45
30degree
dBm (1illumination
W) at 18
(1 W)
at 18 GHz.
The&waveguide
was100
placed
above
sample output
with roughly
GHz. The
was
above
sample
withthe
roughly
a 45 degree
illumination
direction.
direction.
A waveguide
FLIR SC7500
IRplaced
camera
was the
used
to obtain
temperature
distribution.
Artificial
holes
A
FLIR
SC7500
IR
camera
was
used
to
obtain
the
temperature
distribution.
Artificial
holes
with 4.5
with 4.5 mm radius were investigated. During the experiment, the signal generator provided
1W
mm radius
were investigated.
the experiment,
signal
generator
1 W microwave
microwave
power,
although onlyDuring
115.2 mW
microwave the
power
was
emitted provided
from the waveguide
due to
although
onlyto115.2
mW microwave
was emitted
waveguide
due to loss
the cable
thepower,
cable loss.
In order
maximize
the actualpower
illumination
powerfrom
andthe
minimize
the power
during
loss.
In
order
to
maximize
the
actual
illumination
power
and
minimize
the
power
loss
during
the
the transmission, 22.7 mm was selected as the standoff distance (distance between the microwave
transmission, 22.7 mm was selected as the standoff distance (distance between the microwave
antenna aperture and sample under test) due to the impedance matching (this distance should be
antenna aperture and sample under test) due to the impedance matching (this distance should be
around λ/4 to maximum power transfer, where λ is the wavelength of microwave). In their primary
around λ/4 to maximum power transfer, where λ is the wavelength of microwave). In their primary
experimental results, a discontinuous temperature was captured in the defect region (mainly at the
experimental results, a discontinuous temperature was captured in the defect region (mainly at the
edges). A high power heating system is required for a better contrast of heat patterns between defect
edges). A high power heating system is required for a better contrast of heat patterns between defect
and non-defect regions.
and non-defect regions.
Figure 10. MWT setup in Newcastle University (a) and West Pomeranian University of Technology
Figure 10. MWT setup in Newcastle University (a) and West Pomeranian University of Technology
(b) [57]. Reprinted/reproduced with permission from IEEE.
(b) [57]. Reprinted/reproduced with permission from IEEE.
A magnetron-based microwave pulsed thermography system has been developed by West
A magnetron-based
pulsed
thermography
systemdebonding
has been and
developed
by West
Pomeranian
University microwave
of Technology
for glass
fiber composite
delamination
Pomeranian
University
of Technology
for(BLADES200W
glass fiber composite
debonding
and
detection [57].
A GFRP wind
turbine blade
from Navitron)
with a 4.5
mmdelamination
hole at the
middle [57].
was the
study wind
object.
Figureblade
10b illustrates
system setup
for high power
pulsed
detection
A GFRP
turbine
(BLADES200W
from Navitron)
with microwave
a 4.5 mm hole
at the
thermography.
With aobject.
maximum
1 kW
the microwave
excitation
waspower
a 2.45 microwave
GHz magnetron.
middle
was the study
Figure
10bpower,
illustrates
system setup
for high
pulsed
An open-ended
aperture
was matched
a WR-430
waveguide.
1000
thermography.
With
a maximum
1 kW impedance
power, thewith
microwave
excitation
wasDipolar
a 2.45 Magdrive
GHz magnetron.
was
used
to
control
the
output
power.
A
Flir
A325
device
was
used
to
obtain
thermograms.
A
0.238
An open-ended aperture was matched impedance with a WR-430 waveguide. Dipolar Magdrive 1000
°Cused
maximum
temperature
raise
can beAobtained
2 s heating.
In to
their
primary
experimentAresults,
was
to control
the output
power.
Flir A325from
device
was used
obtain
thermograms.
0.238 ◦ C
the location and the size information of the defect have been detected from the continuities in the
line-scan results.
Ryszard et al. also employed MWT for inspecting adhesive joints in composite materials [68].
Due to the dielectric property differences between defects (lack of adhesive or delamination) and the
Sensors 2017, 17, 1123
15 of 33
maximum temperature raise can be obtained from 2 s heating. In their primary experiment results,
the location and the size information of the defect have been detected from the continuities in the
line-scan results.
Ryszard et al. also employed MWT for inspecting adhesive joints in composite materials [68].
Sensors 2017, 17, x FOR PEER REVIEW
14 of 33
Due to the dielectric property differences between defects (lack of adhesive or delamination) and the
background,
energy
in the
defect
region
and and
the background
in thein
material
under
background,the
theinduced
inducedthermal
thermal
energy
in the
defect
region
the background
the material
test
is
different.
The
experimental
setup
is
illustrated
in
Figure
11a:
(1)
an
IR
camera
in
a
protective
under test is different. The experimental setup is illustrated in Figure 11a: (1) an IR camera in a
box
to prevent
damage
caused
by the
highby
power
microwaves;
(2) a 500 W (2)
magnetron
at
protective
box to
prevent
damage
caused
the high
power microwaves;
a 500 W working
magnetron
2.45
GHz;
(3)
microwave
absorbers;
(4)
an
open-ended
rectangular
waveguide;
(5)
the
sample
under
working at 2.45 GHz; (3) microwave absorbers; (4) an open-ended rectangular waveguide; (5) the
test;
(6) under
a cooling
for thesystem
magnetron.
MWT observation
time was settime
to 180
to obtain
sample
test;system
(6) a cooling
for theThe
magnetron.
The MWT observation
wass set
to 180
180
thermograms
in
one
sequence.
The
measured
results
were
obtained
by
using
dedicated
image
s to obtain 180 thermograms in one sequence. The measured results were obtained by using dedicated
processing
algorithms.
As shown
Figure 11b–e,
the original
thermogram
(b), cosine transform
(c),
image processing
algorithms.
Asinshown
in Figure
11b–e, the
original thermogram
(b), cosine
standardized
contrast
(d)
and
contrast
enhancement
(e)
were
used
to
obtain
images
of
the
defect.
In
the
transform (c), standardized contrast (d) and contrast enhancement (e) were used to obtain images of
primary
experiment
results,experiment
approximate
location
and the sizelocation
information
about
be
the defect.
In the primary
results,
approximate
and the
sizedelamination
information can
about
obtained
in
the
thermograms
after
processing.
delamination can be obtained in the thermograms after processing.
Figure 11.11.
Experimental
setup for
MWTfor
(a) and
measurement
(b–e) [68]. Reprinted/reproduced
Experimental
setup
MWT
(a) andresults
measurement
results (b–e) [68].
with
permission from authors.
Reprinted/reproduced
with permission from authors.
We also
also investigated
investigated MWT
MWT for
for defect
defect detection
detection in
in aa glass
glass fiber
fiber wind
wind turbine
turbine blade,
blade, as
as shown
shown in
in
We
Figure 12.
12. A
A horn
horn antenna
antenna (ETS
(ETS Lindgren
Lindgren 3115,
3115, frequency
frequency range:
range: 750
750 MHz–18
MHz–18 GHz.)
GHz.) was
was used
used for
for
Figure
microwave
excitation.
The
antenna
was
connected
to
Rohde
&
Schwarz
SMF
100
A
signal
generator
microwave excitation. The antenna was connected to Rohde & Schwarz SMF 100 A signal generator
with aa maximum
maximum output
output power
power of
of 11 W.
W. The
The waveguide
waveguide was
was placed
placed above
above the
the sample
sample with
with roughly
roughly
with
90 degree
degree illumination
illumination direction.
direction. A
used to
to obtain
obtain the
the temperature
temperature
90
A FLIR
FLIR SC7500
SC7500 IR
IR camera
camera was
was used
distribution
of
sample
under
test.
During
the
experiment,
the
signal
generator
provided
1 W at
0.915
distribution of sample under test. During the experiment, the signal generator provided
1W
at
GHz and
order
detect
during the
experiment,
the microwave
heating duration
0.915
GHz2.45
andGHz.
2.45 In
GHz.
Intoorder
todefects
detect defects
during
the experiment,
the microwave
heating
was selected
1 min as
(as1 shown
Figurein13a,c)
2 min
shown
in Figure
13b,d).13b,d).
In our In
initial
duration
was as
selected
min (asinshown
Figureand
13a,c)
and(as
2 min
(as shown
in Figure
our
experiment
results,
a
discontinuous
temperature
was
captured
in
the
defect
region.
Furthermore,
the
initial experiment results, a discontinuous temperature was captured in the defect region. Furthermore,
heating
effect
of 2.4
is not
good
as 0.915
GHz GHz
due to
thetopenetration
abilityability
difference.
With
the
heating
effect
ofGHz
2.4 GHz
is as
not
as good
as 0.915
due
the penetration
difference.
the
captured
IR
images,
defects
around
1
mm
radius
with
0.2
mm
in
depth
could
be
obtained
in
With the captured IR images, defects around 1 mm radius with 0.2 mm in depth could be obtainedthe
in
GFRP
sample.
With
a longer
heating
duration,
thethe
number
of defects
became
hard
to identify
due
to
the
GFRP
sample.
With
a longer
heating
duration,
number
of defects
became
hard
to identify
due
thethe
heat
diffusion,
therefore,
thethe
heating
time
must
bebe
optimized
forfor
different
situations.
to
heat
diffusion,
therefore,
heating
time
must
optimized
different
situations.
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Figure 12. Experimental setup for defect detection with MWT.
Figure
Figure 12.
12. Experimental
Experimental setup
setup for
for defect
defect detection
detection with
with MWT.
MWT.
Figure 13. IR results with MWT for defect detection in glass fiber wind blade after 1 min microwave
Figure 13.
13. IR
IR results
results with
with MWT
MWT for
for defect
defect detection
detection in
in glass
glass fiber
fiber wind
wind blade
blade after
after 11 min
min microwave
microwave
Figure
excitation with 0.915 GHz (a), after 2 min microwave excitation with 0.915 GHz (b), after 1 min
excitation with
with 0.915
0.915 GHz
GHz (a),
(a), after
after 22 min
min microwave
microwave excitation
excitation with
with 0.915
0.915 GHz
GHz (b),
(b), after
after 11 min
min
excitation
microwave excitation with 2.45 GHz (c) and after 2 min microwave excitation with 2.45 GHz (d).
microwave excitation
excitation with 2.45 GHz (c) and after 2 min microwave excitation with 2.45 GHz (d).
microwave
4.6. Carbon Fiber Composite Materials
4.6.
4.6. Carbon
Carbon Fiber
Fiber Composite
Composite Materials
Materials
In France, Keo et al. developed a microwave pulsed thermography for CFRP detection [56]. They
In
developed
a microwave
pulsed
thermography
for CFRP
detection
[56]. They
In France,
France,Keo
Keoetetal.al.
developed
a microwave
pulsed
thermography
for CFRP
detection
[56].
used a commercial 2.45 GHz magnetron to generate microwave signals. With a detector with a 320 ×
used
commercial
2.45 GHz
to generate
microwave
signals.signals.
With a detector
with a 320
×
Theyaused
a commercial
2.45magnetron
GHz magnetron
to generate
microwave
With a detector
with
256 InSb matrix, the sensitivity of the IR camera is in a range of 3 μm–5 μm. To capture the whole
256
InSb
matrix,
sensitivity
of the IRofcamera
in a range
3 μm–5
Toµm.
capture
the whole
a 320
× 256
InSbthe
matrix,
the sensitivity
the IR is
camera
is in aofrange
of 3μm.
µm–5
To capture
the
inspection area, the sample was placed 1.5 m away from IR camera at 55°. The CFRP
sample was 40
◦ . Thesample
inspection
area, the
sample
was placed
1.5 m away
camera
at 55°. The
was 40
whole inspection
area,
the sample
was placed
1.5 mfrom
awayIRfrom
IR camera
at 55CFRP
CFRP sample
2 defect was created at the middle of the CFRP sample by the absence of
× 40 × 4.5 cm33. A 10 × 10
cm
2
3
2
×was
40 ×404.5
. A4.5
10cm
× 10. cm
was defect
createdwas
at the
middle
of the
CFRPofsample
by the
absence
of
× cm
40 ×
A 10defect
× 10 cm
created
at the
middle
the CFRP
sample
by the
adhesive. The antenna was placed in the 45° direction
as shown in Figure 14a. In Figure 14b, the
adhesive.
antenna
placed
inplaced
the 45°
as shown
in Figure
14a. In14a.
Figure
14b, 14b,
the
absence ofThe
adhesive.
Thewas
antenna
was
in2direction
the 45◦ direction
as shown
in Figure
In Figure
microwave beam was guided by a 59 × 56 cm2 pyramidal
horn antenna onto the sample under test.
microwave
beam
was was
guided
by aby
59a×59
56×
cm56 pyramidal
horn horn
antenna
onto onto
the sample
underunder
test.
the microwave
beam
guided
cm2 pyramidal
antenna
the sample
With the ALTAIR program provided by FLIR, a computer was used to record thermograms at 1 Hz.
With
the ALTAIR
program
provided
by FLIR,
a computer
was used
record
thermograms
at 1 Hz.
test. With
the ALTAIR
program
provided
by FLIR,
a computer
was to
used
to record
thermograms
at
A 360 W microwave was used to heat the specimen for 150 s. The same testing procedure was carried
A
360
W
microwave
was
used
to
heat
the
specimen
for
150
s.
The
same
testing
procedure
was
carried
1 Hz. A 360 W microwave was used to heat the specimen for 150 s. The same testing procedure was
out on samples with/without defect. As shown in Figure 15, the thermograms at the 100 s were
out
on samples
with/without
defect. As
shown
Figure
the 15,
thermograms
at the at
100the
s were
carried
out on samples
with/without
defect.
As in
shown
in 15,
Figure
the thermograms
100 s
obtained. In Figure 15a, a non-defect specimen has been shown in the thermogram at the 100 s instant.
obtained.
In Figure
15a, a non-defect
specimen
has beenhas
shown
the thermogram
at the 100at
s instant.
were obtained.
In Figure
15a, a non-defect
specimen
beeninshown
in the thermogram
the 100
In Figure 15b, a specimen with a defect has been shown in the thermogram. In Figure 15c, the
In
Figure In
15b,
a specimen
with a defect
been
in the in
thermogram.
In Figure
15c, 15c,
the
s instant.
Figure
15b, a specimen
with ahas
defect
hasshown
been shown
the thermogram.
In Figure
thermogram of the sample with a defect (Figure 15a) has been subtracted with the thermogram of the
thermogram
of the
withwith
a defect
(Figure
15a)15a)
has been
subtracted
withwith
the thermogram
of the
the thermogram
of sample
the sample
a defect
(Figure
has been
subtracted
the thermogram
of
sample without defect (Figure 15b) at the same instant. In Figure 15d, the thermogram in Figure 15c
sample
without
defect
(Figure
15b)
at the
same
instant.
InIn
Figure
the sample
without
defect
(Figure
15b)
at the
same
instant.
Figure15d,
15d,the
thethermogram
thermogramin
inFigure
Figure 15c
15c
is subtracted from its initial thermogram in order to highlight the defect. In the primary experiment
is
is subtracted
subtracted from
from its initial thermogram in order to highlight the defect. In
In the
the primary
primary experiment
experiment
results, the CFRP defect area can be clearly found. It is hotter than the non-defect area due to the
results, the CFRP defect area can be clearly found. It is hotter than the non-defect area due to the
Sensors 2017, 17, 1123
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16 of 33
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results,ofthe
CFRP defect
area
canarea
be clearly
found.
It is directly
hotter than
thethe
non-defect
area due
to the10absence
absence
adhesive.
The
defect
cancan
bebe
estimated
from
thermograms
(about
× 10
absence of
adhesive.
The
defect
area
estimated
directly
from
the
thermograms
(about
10
× 10
of
adhesive.
The
defect
area
can
be
estimated
directly
from
the
thermograms
(about
10
×
10 cm2 ) [56].
2) [56].
cmcm
2) [56].
(a)(a)
(b)(b)
Figure
14.14.
MWT
setup
(a)(a)
and
Horn
(b)(b)
in in
University
Institute
of of
Technology
of of
Bethune
[56].
Figure
MWT
setup
(a)
and
Horn
(b)
University
Institute
of
Technology
Bethune
[56].
Figure
14.
MWT
setup
and
Horn
University
Institute
Reprinted/reproduced
with
permission
from
Scientific
Research
Publishing
Inc.
Reprinted/reproduced
with permission
permission from
from Scientific
Scientific Research
Reprinted/reproduced with
Research Publishing
Publishing Inc.
Inc.
Figure
15.15.
MWT
results
forfor
thethe
absence
of adhesive
in CFRP:
thethe
thermogram
of the
sample
without
Figure
MWT
results
absence
of adhesive
adhesive
in CFRP:
CFRP:
thermogram
of the
the
sample
without
Figure
15. MWT
results
for the
absence
of
in
the thermogram
of
sample
without
defect
(a),
the
thermogram
of
the
sample
with
the
defect
(b),
the
subtraction
between
the
thermograms
defect
(a),
the
thermogram
of
the
sample
with
the
defect
(b),
the
subtraction
between
the
thermograms
defect (a), the thermogram of the sample with the defect (b), the subtraction between the thermograms
of the
sample
with and
without thethe
defect (c),(c),
thermogram subtracted
from
its its
initial
thermogram
(d)(d)
of the
the
sample
subtracted
from
initial
thermogram
of
sample with
with and
andwithout
without thedefect
defect (c),thermogram
thermogram
subtracted
from
its
initial
thermogram
[56].
Reprinted/reproduced
with
permission
from
Scientific
Research
Publishing
Inc.Inc.
[56].
Reprinted/reproduced
with
permission
from
Scientific
Research
Publishing
(d)
[56].
Reprinted/reproduced
with
permission
from
Scientific
Research
Publishing
Inc.
In In
2014,
Foudazi
et et
al.al.
investigated
MWT
forfor
thethe
inspection
of of
rehabilitated
cement-based
2014,
Foudazi
investigated
MWT
inspection
rehabilitated
cement-based
In 2014,
Foudazi
et al. investigated
MWTinfor
the inspection
of rehabilitated
cement-based
structures
[64].
The
experimental
setup
is
shown
Figure
16a,b,
2.4
GHz
microwaves
have
been
structures [64]. The experimental setup is shown in Figure 16a,b, 2.4 GHz microwaves
have
been
structures
[64].
The
experimental
setup
is
shown
in
Figure
16a,b,
2.4
GHz
microwaves
have
been
transmitted
with
50
W
power.
A
sweep
oscillator
(HP8690B)
and
a
power
amplifier
(OphirRF
transmitted with 50 W power. A sweep oscillator (HP8690B) and a power amplifier (OphirRF
transmitted
withto50generate
W power.
A sweep
oscillator
(HP8690B)
and sample
a powerunder
amplifier
(OphirRF
5303084)
5303084)
areare
used
high
power
microwave
signals.
The
test
was
illuminated
5303084)
used to generate
high
power
microwave
signals.
The sample
under
test
was
illuminated
used to
generateWith
highapower
microwave
signals.
The
sample
underoftest
illuminated
by awas
horn
byare
a horn
antenna.
sensitivity
of of
0.05
K, K,
thethe
thermal
profile
thewas
sample’s
surface
by
a horn
antenna. With
a sensitivity
0.05
thermal
profile of
the
sample’s
surface
was
3
antenna.
With
a
sensitivity
of
0.05
K,
the
thermal
profile
of
the
sample’s
surface
was
captured
by
captured
by
an
IR
camera
(DRS
Tamarisk
320).
In
Figure
16c,
the
sample
is
a
20
×
20
×
4
cm
mortar
3
captured by an IR camera (DRS Tamarisk 320). In Figure 16c, the sample is a 20 × 20
× 4 cm mortar
3 mortar
2
2
an
IR
camera
(DRS
Tamarisk
320).
In
Figure
16c,
the
sample
is
a
20
×
20
×
4
cm
sample
sample
covered
with
a 13
× 13
cmcmCFRP.
There
is ais 2a ×2 2×cm
2 mm
depth
delamination
in in
thethe
2 CFRP.
2 and
sample
covered
with
a 13
×2 13
There
2 cmand
2 mm
depth
delamination
covered
with
a 13 ×
13 cm
CFRP.
There is
a2×
2 cm2 and 2 mm
depth
delamination
in standoff
the center
center
of
the
sample
[58].
With
5
s
heating
time,
measurements
were
performed
at
a
6
cm
center of the sample [58]. With 5 s heating time, measurements were performed at a 6 cm standoff
of the sample
[58]. With
5 s heating time,
measurements
were
at a 6 cm
standoff
distance.
distance.
Meanwhile,
measurements
were
also
performed
at at
aperformed
45
cmcm
standoff
distance
with
15 15
s s
distance.
Meanwhile,
measurements
were
also
performed
a 45
standoff
distance
with
Meanwhile,
measurements
were
also
performed
at aand
45 cm
standoff
distance
with16d,
15 sthe
heating
time.
heating
time.
Thermal
profiles
were
captured
before
after
heating.
In
Figure
thermal
heating time. Thermal profiles were captured before and after heating. In Figure 16d, the thermal
Thermal
profiles
were
captured before
and
after
heating.
In Figure
16d,
the 5thermal
image
before
image
before
heating
is is
provided.
Figure
16e16e
shows
thethe
thermal
image
after
In In
their
image
before
heating
provided.
Figure
shows
thermal
image
after s5 heating.
s heating.
their
heating
is
provided.
Figure
16e
shows
the
thermal
image
after
5
s
heating.
In
their
primary
experiment
primary
experiment
results,
thethe
delamination
in in
CFRP
cancan
bebe
easily
identified.
Both
thethe
level
of of
primary
experiment
results,
delamination
CFRP
easily
identified.
Both
level
results,
the
delamination
in CFRP
can be easily
identified.
Both
the level ofInpower
andthey
heating
time
power
and
heating
time
should
be
optimized
to
detect
small
size
disbands.
addition,
found
power and heating time should be optimized to detect small size disbands. In addition, they found
should
be optimized
toisdetect
smallaffected
size disbands.
Ineffects
addition,
they
found
that the
measured
result is
that
thethe
measured
result
evidently
byby
edge
with
45 45
cm
standoff
distance,
as as
shown
that
measured
result
is evidently
affected
edge
effects
with
cm
standoff
distance,
shown
evidently
affected
by
edge
effects
with
45
cm
standoff
distance,
as
shown
in
Figure
16f.
in in
Figure
16f.
Figure
16f.
Sensors 2017, 17, 1123
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Sensors 2017, 17, x FOR PEER REVIEW
17 of 33
Figure 16.
16. MWT
cm
(b)(b)
standoff,
photograph
of
Figure
MWT measurement
measurementsystem
systemsetup
setupused
usedfor
for4545cm
cm(a)
(a)and
and6 6
cm
standoff,
photograph
mortar
sample
with
delamination
(c).
Measurements
on
mortar
sample
before
heating
(d),
6
cm
of mortar sample with delamination (c). Measurements on mortar sample before heating (d), 6 cm
standoff after
after 55 ss heat
heat (e)
(e) and
and 45
45cm
cmstandoff
standoffafter
after15
15s sheat
heat(f)(f)[58].
[58].Reprinted/reproduced
Reprinted/reproduced with
with
standoff
permission
from
IEEE.
permission from IEEE.
Recently, Foudazi has shown that the MWT method can be used for detection of delaminations,
Recently, Foudazi has shown that the MWT method can be used for detection of delaminations,
debonding and cracks in rehabilitated cement-based materials [70]. The experimental setup is shown
debonding and cracks in rehabilitated cement-based materials [70]. The experimental setup is shown
in Figure 17a. Three CFRP-strengthened cement-based specimens have been measured (a unbonded
in Figure 17a. Three CFRP-strengthened cement-based specimens have been measured (a unbonded
defect was made by placing a 5 mm thin sheet of foam with dimensions of 6 cm × 8 cm in a sample
defect was made by3 placing a 5 mm thin sheet of foam with dimensions of 6 cm × 8 cm in a sample
with 52 × 38 × 9 cm , several delaminations (with thicknesses ranging from 1 mm to 3 mm and areas
with 52 × 38 × 9 cm23 , several delaminations
(with thicknesses ranging from 1 mm to 3 mm and areas
ranging from 10 cm to 100 cm2) have been formed in a sample with dimensions of 52 × 38 × 7.8 cm3,
ranging from 10 cm2 to 100 cm2 ) have been formed in3 a sample with dimensions of 52 × 38 × 7.8 cm3 ,
the crack sample had dimensions of 52 × 38 × 9 cm ), as shown in Figure 17b. Thermal profiles for
the crack sample had dimensions of 52 × 38 × 9 cm3 ), as shown in Figure 17b. Thermal profiles
these specimens are illustrated in Figure 17c. The approximate location and the size information
for these specimens are illustrated in Figure 17c. The approximate location and the size information
about defects in these specimens have been obtained. Meanwhile, the temperature of the defect will
about defects in these specimens have been obtained. Meanwhile, the temperature of the defect
be affected by the orientation of the carbon fibers (due to the electric field difference). In their initial
will be affected by the orientation of the carbon fibers (due to the electric field difference). In their
experimental results, for the case of unidirectional carbon fiber, if the electric field is along the fiber
initial experimental results, for the case of unidirectional carbon fiber, if the electric field is along the
direction, the temperature change for the defected area will be smaller compared to the case of
fiber direction, the temperature change for the defected area will be smaller compared to the case of
perpendicular polarization. This is due to the different electromagnetic response of the carbon fiber
perpendicular polarization. This is due to the different electromagnetic response of the carbon fiber
at different polarizations. In other words, if the wave is parallel to the fiber orientation, it will react
at different polarizations. In other words, if the wave is parallel to the fiber orientation, it will react
as an electric conductor, while for the perpendicular case it is similar to high loss dielectric materials.
as an electric conductor, while for the perpendicular case it is similar to high loss dielectric materials.
Additionally, the thermal contrast (TC) between healthy and defective areas is much greater.
Additionally, the thermal contrast (TC) between healthy and defective areas is much greater. Moreover,
Moreover, increasing defect dimensions also led to a greater TC.
increasing defect dimensions also led to a greater TC.
Furthermore, the authors used MWT to monitor debonding in CFRP by using different excitation
antennas [64]. A horn antenna linked with a double-ridged waveguide operating at frequency ranged
from 0.75 GHz to 18 GHz was employed. The aperture size of this antenna is 14 × 24 cm2 . In Figure 18a,
the CFRP sample is 30 × 30 × 0.2 cm3 backed with 40 × 40 × 5 cm3 Al sheet which containing six
debonds with dimensions of 6 × 6 cm2 , 5 × 5 cm2 , 4 × 4 cm2 , 3 × 3 cm2 , 2 × 2 cm2 , and 1 × 1 cm2 ,
respectively. Figure 18b shows top and side views of the CFRP backed by a layer of Al sheet. During
experiment, the sample under test was illuminated at 2.4 GHz microwave signal of different power
(50, 100, 150 and 200 W). In addition, the effect of the heating time (from 10 s to 30 s) has been
investigated by using CST Microwave Studio and MultiPhysics Studio. As shown in Figure 18c,d,
normalized thermal images of CFRP with different excitation power levels at 10 s and 30 s have been
demonstrated. In the preliminary experimental results, they found that a higher excitation microwave
power is needed for a smaller debond detection. In addition, the debonding becomes clearly visible
Sensors 2017, 17, 1123
19 of 33
with increasing excitation power due to the temperature difference increase. Therefore, increasing
the incident power improves the detection of small disbonds. Meanwhile, an increase of the heating
time leads to an increased temperature throughout the sample under test, thereby the possibility of
detecting the disbonds is reduced, therefore, the heating time must be optimized according to the
actual
situation.
Figure
17.x FOR
MWT
measurement
setup (a), samples under test (b) and thermal profiles for samples
Sensors
2017,
17,
PEER
REVIEW
18 of 33
under test (c) [70]. Reprinted/reproduced with permission from IEEE.
Furthermore, the authors used MWT to monitor debonding in CFRP by using different
excitation antennas [64]. A horn antenna linked with a double-ridged waveguide operating at
frequency ranged from 0.75 GHz to 18 GHz was employed. The aperture size of this antenna is 14 ×
24 cm2. In Figure 18a, the CFRP sample is 30 × 30 × 0.2 cm3 backed with 40 × 40 × 5 cm3 Al sheet which
containing six debonds with dimensions of 6 × 6 cm2, 5 × 5 cm2, 4 × 4 cm2, 3 × 3 cm2, 2 × 2 cm2, and 1 ×
1 cm2, respectively. Figure 18b shows top and side views of the CFRP backed by a layer of Al sheet.
During experiment, the sample under test was illuminated at 2.4 GHz microwave signal of different
power (50, 100, 150 and 200 W). In addition, the effect of the heating time (from 10 s to 30 s) has been
investigated by using CST Microwave Studio and MultiPhysics Studio. As shown in Figure 18c and
18d, normalized thermal images of CFRP with different excitation power levels at 10 s and 30 s have
been demonstrated. In the preliminary experimental results, they found that a higher excitation
microwave power is needed for a smaller debond detection. In addition, the debonding becomes
clearly visible with increasing excitation power due to the temperature difference increase. Therefore,
increasing the incident power improves the detection of small disbonds. Meanwhile, an increase of
the heating time leads to an increased temperature throughout the sample under test, thereby the
Figure 17.
17. MWTmeasurement
measurementsetup
setup
(a), samples
under
(b) thermal
and thermal
profiles
for samples
Figure
(a),
under
test test
(b) and
profiles
samples
under
possibility
of MWT
detecting the disbonds
is samples
reduced,
therefore,
the heating
timefor
must
be optimized
under
[70]. Reprinted/reproduced
with permission
from IEEE.
test
(c) test
[70].(c)
Reprinted/reproduced
with permission
from IEEE.
according to the actual situation.
Furthermore, the authors used MWT to monitor debonding in CFRP by using different
excitation antennas [64]. A horn antenna linked with a double-ridged waveguide operating at
frequency ranged from 0.75 GHz to 18 GHz was employed. The aperture size of this antenna is 14 ×
24 cm2. In Figure 18a, the CFRP sample is 30 × 30 × 0.2 cm3 backed with 40 × 40 × 5 cm3 Al sheet which
containing six debonds with dimensions of 6 × 6 cm2, 5 × 5 cm2, 4 × 4 cm2, 3 × 3 cm2, 2 × 2 cm2, and 1 ×
1 cm2, respectively. Figure 18b shows top and side views of the CFRP backed by a layer of Al sheet.
During experiment, the sample under test was illuminated at 2.4 GHz microwave signal of different
power (50, 100, 150 and 200 W). In addition, the effect of the heating time (from 10 s to 30 s) has been
investigated by using CST Microwave Studio and MultiPhysics Studio. As shown in Figure 18c and
18d, normalized thermal images of CFRP with different excitation power levels at 10 s and 30 s have
been demonstrated. In the preliminary experimental results, they found that a higher excitation
microwave power is needed for a smaller debond detection. In addition, the debonding becomes
clearly visible with increasing excitation power due to the temperature difference increase. Therefore,
increasing the incident power improves the detection of small disbonds. Meanwhile, an increase of
the heating time leads to an increased temperature throughout the sample under test, thereby the
possibility of detecting the disbonds is reduced, therefore, the heating time must be optimized
according to the actual situation.
Figure 18. MWT experimental setup (a), sample (b), measurement results for 10 s heating (c) and 30 s
heating (d) [64]. Reprinted/reproduced with permission from IEEE.
A microwave time-resolved infrared radiometry system was proposed by scientists in The John
Hopkins University [71]. The experimental setup is shown in Figure 19a. 9 GHz microwave signals
were produced by an HP 6890B Oscillator. A Hughes 1277 X-band traveling wave tube amplifier
was used to amplify these signals and then to feed them into a rectangular waveguide linked with
a single flare horn antenna. The beam width of this horn antenna is about 50◦ and the sample was
placed about 15 cm away. 2.3 W input power was transmitted to the antenna and a 20 mW/cm2 power
A microwave time-resolved infrared radiometry system was proposed by scientists in The John
Hopkins University [71]. The experimental setup is shown in Figure 19a. 9 GHz microwave signals
were produced by an HP 6890B Oscillator. A Hughes 1277 X-band traveling wave tube amplifier was
used to amplify these signals and then to feed them into a rectangular waveguide linked with a20
single
Sensors 2017, 17, 1123
of 33
flare horn antenna. The beam width of this horn antenna is about 50° and the sample was placed
about 15 cm away. 2.3 W input power was transmitted to the antenna and a 20 mW/cm2 power
density
density was
was created
created for
for the experimental
experimental study.
study. Both
Both the
the polarization
polarization of
of the
the microwave
microwave and
and the
the angle
angle
of
incidence
were
controlled.
By
operating
in
the
3
µm–5
µm
band,
a
128
×
128
InSb
focal
plane
array
of incidence were controlled. By operating in the 3 μm–5 μm band, a 128 ×
infrared
infrared camera
camera was
was used
used to
to monitor
monitor the
the surface
surface temperature
temperature of
of the
the sample
sample under
under test.
test. Before, during
during
and after
after the
the application
application of the microwave
microwave step heating pulse, a series of frames were recorded for
time-dependent
initial
experimental
results,
the authors
measured
carboncarbon
fibers
time-dependentmeasurements.
measurements.InInthethe
initial
experimental
results,
the authors
measured
with
different
depthsdepths
(0.25 mm
and
0.75
mm)
fiberglass-epoxy.
The temperature
at the center
fiberstwo
with
two different
(0.25
mm
and
0.75inmm)
in fiberglass-epoxy.
The temperature
at the
of
the
fiber
is
shown
in
Figure
19b.
Moreover,
they
found
that
the
experimental
data
can
be
fitted
center of the fiber is shown in Figure 19b. Moreover, they found that the experimental data can be
with
solidaline.
determination
of surface
layer thickness
and thermal
diffusivity
can be almost
fittedawith
solidThe
line.
The determination
of surface
layer thickness
and thermal
diffusivity
can be
independent
from thefrom
surface
properties
of the layer.
almost independent
the surface
properties
of the layer.
Figure
Figure 19.
19. Schematic diagram of the experimental setup in The John Hopkins
Hopkins University
University (a) and
and
Surface
as aafunction
functionofofsquare
squareroot
roottime
time
a single
point
fibers
in 0.25
Surface temperature as
forfor
a single
point
on on
fibers
in 0.25
mmmm
and and
0.75
0.75
depth
(b) [71].
Reprinted/reproduced
permission
mm mm
depth
(b) [71].
Reprinted/reproduced
with with
permission
fromfrom
SPIE.SPIE.
Lee et
et al.
al. proposed
microwave probe
probe pumping
pumping technique
technique to
to characterize
characterize the
the anisotropic
anisotropic
Lee
proposed aa microwave
electrical
conductivity
in
carbon-fiber
composite
materials
[69].
They
used
CST
Microwave
Studio to
to
electrical conductivity in carbon-fiber composite materials [69]. They used CST Microwave Studio
investigate the
the electromagnetic
electromagnetic field
field distribution
distribution with
with different
different anisotropic
anisotropic conductivity.
conductivity. Two
Two 10
10 mm
mm
investigate
coaxial
probes
were
used
to
pump
and
scan
the
microwave
field.
The
pumping
probe
was
fixed
on
coaxial probes were used to pump and scan the microwave field. The pumping probe was fixed
the
backside
of
the
sample
under
test.
The
near-field
distribution
was
scanned
by
the
scanning
probe.
on the backside of the sample under test. The near-field distribution was scanned by the scanning
A spectrometer
was used
measure
the microwave
power.
A network
analyzer
was was
usedused
as the
probe.
A spectrometer
wasto
used
to measure
the microwave
power.
A network
analyzer
as
microwave
source
with
a
continuous
mode.
A
FLIR
T620
was
used
for
measurement.
A
1
GHz
the microwave source with a continuous mode. A FLIR T620 was used for measurement. A 1 GHz
microwave source
source with
with 20
20 dbm
dbmpower
powerwas
wasused
usedduring
duringthe
themeasurements.
measurements.AA5050××50
50×× 0.1
0.1 mm
mm33
microwave
carbon-fiber/PEEK composite
carbon-fiber/PEEK
composite sheet
sheet with
with aa defect
defect (characteristic
(characteristic length
length is
is 55 mm)
mm) has
has been
been measured.
measured.
In
the
initial
experimental
results,
they
obtained
an
intense
area
around
the
scanning
probe.
In the initial experimental results, they obtained an intense area around the scanning probe. Moreover,
Moreover,
found
that the conductivity
of the carbon-fiber/PEEK
has an
elliptical distribution.
they
found they
that the
conductivity
of the carbon-fiber/PEEK
has an elliptical
distribution.
4.7. Honeycomb Structures
Structures
4.7.
Microwavepulsed
pulsed
thermography
for water
measurement
in honeycomb
materials
was
Microwave
thermography
for water
measurement
in honeycomb
materials was
developed
◦ beam
developed
in Poland
They introduced
2 GHz antennas
a 30°
beamThe
width.
The
by
scientistsbyinscientists
Poland [72].
They [72].
introduced
2 GHz antennas
with a 30with
width.
surface
2
2
surface
of a honeycomb
was illuminated
a 30 mW/cm
power
density.
antenna
of
a honeycomb
samplesample
was illuminated
with awith
30 mW/cm
power
density.
TheThe
antenna
andand
IR
IR camera
were
arranged
a reflection
configuration.The
Theproposed
proposedMWT
MWTdetection
detectionsystem
systemis
is shown
shown
camera
were
arranged
in in
a reflection
configuration.
in Figure
Figure 20a.
20a. The antenna was located at 1 m away from the sample
sample under test and the IR
IR camera
camera
2
was placed at 0.7 m. The sample was a 290 × 215 mm sandwich panel with two 0.7 mm thickness
Fibredux face skins. Different quantities of water (5.0, 2.5, 1.2 and <1 mL) are introduced in the sample
to form four defects. Microwaves were used to irradiate the sample for 5 s, and then the IR camera
was used to capture thermal images for 20 s at a rate of 1 Hz. In their experiment results, as shown
in Figure 20b, the location of water can be well visible even in small quantities with the reflection
and transmission arrangement, but it is difficult to qualify precisely the water content due to the
phenomenon of longitudinal heat diffusion.
Fibredux face skins. Different quantities of water (5.0, 2.5, 1.2 and <1 mL) are introduced in the sample
to form four defects. Microwaves were used to irradiate the sample for 5 s, and then the IR camera
was used to capture thermal images for 20 s at a rate of 1 Hz. In their experiment results, as shown in
Figure 20b, the location of water can be well visible even in small quantities with the reflection and
transmission
arrangement, but it is difficult to qualify precisely the water content due to
Sensors
2017, 17, 1123
21 ofthe
33
phenomenon of longitudinal heat diffusion.
Figure 20.
20. MWT
MWT setup
setup at
at the
the Military
Military Institute
Institute of
of Armament
Armament Technology
Technology (a)
(a) and
and results
results for
for water
water in
in
Figure
the
honeycomb
material
(b)
[72].
the honeycomb material (b) [72].
4.8. Cement
Cement Based
Based Composite
Composite
4.8.
Foudazi et
active
MWT
to evaluate
steel fiber
in cement-based
mortars
Foudazi
etal.
al.proposed
proposed
active
MWT
to evaluate
steeldistribution
fiber distribution
in cement-based
3 fiber-reinforced cement-based mortar (FRCM) samples were measured. The
[73].
200
×
200
×
200
mm
3
mortars [73]. 200 × 200 × 200 mm fiber-reinforced cement-based mortar (FRCM) samples were
steel fibers have
diameters
0.55 diameters
mm and lengths
30 and
mm. lengths
The effects
clumping,
dielectric
measured.
The steel
fibersofhave
of 0.55 of
mm
of 30ofmm.
The effects
of
properties and
fiber depth
have and
beenfiber
evaluated
full-wave
coupled
electromagnetic-thermal
clumping,
dielectric
properties
depthwith
havea been
evaluated
with
a full-wave coupled
TM. As illustrated in Figure 21a,
simulation which was conducted
by which
using CST
Studio
electromagnetic-thermal
simulation
was MultiPhysics
conducted by
using CST
MultiPhysics StudioTM .
microwave
signals
were
generated
by
a
signal
generator
at
the
desired
2.4
GHz
operational
frequency.
As illustrated in Figure 21a, microwave signals were generated by a signal generator
at the
desired
A 50
W power
amplifier
was used
the excitation
power
level. Athe
horn
antenna power
was used
to
2.4
GHz
operational
frequency.
A 50to
Wamplify
power amplifier
was used
to amplify
excitation
level.
radiate
a
relatively
uniform
microwave
excitation
toward
the
sample’s
surface.
A
DRS
Tamarisk
320
A horn antenna was used to radiate a relatively uniform microwave excitation toward the sample’s
thermal camera
was utilized
capturecamera
the surface
of the
surface.
A DRS Tamarisk
320tothermal
was thermal
utilized profile
to capture
thesample.
surface thermal profile of
During
measurements,
microwave
energy
was
applied
for
30
s
and
an additional 90 s of thermal
the
sample.
Sensors 2017, 17, x FOR PEER REVIEW
21 of 33
profile measurement followed to capture the cooling period. As shown in Figure 21b, surface
temperature differences after 30 s microwave heating were provided for 1%, 2% and 3% of steel fiber
contents. In their primary experiment results, they found that a larger temperature difference was
contributed by the induced surface current on areas containing steel fibers. Therefore, with increasing
volume content of steel fibers, the temperature will increase. Due to variation in heating associated
with induced surface current and dielectric heating, fiber depth and dielectric properties of mortar
have a significant influence on the temperature difference at the surface of samples. They found that
MWT is capable of determining the presence of the fiber clumping in the cement-based composite
structures: 1% and 2% steel fibers are shown to have higher surface temperature difference compared
to the sample made with 3% fiber content.
Figure 21.
21. MWT measurement setup (a) and specimen
specimen surface temperature variation with different
steel fiber contents (b)
with permission
permission from
from Springer.
Springer.
(b) [73].
[73]. Reprinted/reproduced
Reprinted/reproduced with
4.9. Advanced
Signal and Image
Processingenergy
Methods
During measurements,
microwave
was applied for 30 s and an additional 90 s of thermal
profile
measurement
followed
to capture
the cooling
period.
As shown
in Figuredi21b,
Microwave
lock-in
thermography
has been
developed
by scientists
at Politecnico
Barisurface
[74]. A
temperature
differences
after
30
s
microwave
heating
were
provided
for
1%,
2%
and
3%
of steel
function generator was used to control the power by switching the oven off/on. The frequency
of
fiber
contents.
experiment
found that
larger temperature
was
excitation
was In
0.1their
Hz. primary
As shown
in Figure results,
22a, thethey
IR camera
wasapositioned
at 15 cm difference
from the oven
contributed
the induced
surfacethe
current
areas containing
steel fibers.
Therefore,
with
increasing
to allow it tobyfocus
on and frame
wholeon
specimen.
The dimensions
of the
specimen
were
76 mm
volume
content
fibers,
temperature
will
increase.
Dueheat
to variation
heatingand
associated
in length,
76 mmofinsteel
width
and 8the
mm
in thickness.
Due
to the low
diffusionin
velocity
thermal
with
induced asurface
andtemperature
dielectric heating,
fiber
depth
dielectric
properties
mortar
conductivity,
strong current
drift in the
evolution
over
timeand
is noted.
Moreover,
this of
setup
can
have
a
significant
influence
on
the
temperature
difference
at
the
surface
of
samples.
They
found
that
avoid damage due to possible microwave leakage. To obtain the amplitude and the phase
information, Fast Fourier Transform-based algorithms were used to process the thermal image data
which acquires thermal images frame by frame over time. Figure 22b shows the phase image and
Figure 22c shows amplitude image. In the experimental results, the problem of the specimen’s edges
was observed. Due to the interaction between the specimen geometry and the electromagnetic field,
a high temperature was exhibited near the edge of the specimen. Nevertheless, the authors could
Sensors 2017, 17, 1123
22 of 33
MWT is capable of determining the presence of the fiber clumping in the cement-based composite
Figure1%
21. and
MWT
measurement
(a) and
surface
temperature
variation
with different
structures:
2%
steel fibers setup
are shown
tospecimen
have higher
surface
temperature
difference
compared
steel
fiber
contents
(b)
[73].
Reprinted/reproduced
with
permission
from
Springer.
to the sample made with 3% fiber content.
4.9. Advanced
Advanced Signal
Signal and
and Image
Image Processing
Processing Methods
Methods
4.9.
Microwave lock-in
lock-in thermography
didi
Bari
[74].
A
Microwave
thermography has
hasbeen
beendeveloped
developedby
byscientists
scientistsatatPolitecnico
Politecnico
Bari
[74].
function
generator
was
used
to
control
the
power
by
switching
the
oven
off/on.
The
frequency
of
A function generator was used to control the power by switching the oven off/on. The frequency
excitation
was
0.10.1
Hz.Hz.
As As
shown
in Figure
22a,22a,
the IR
was was
positioned
at 15at
cm15from
the oven
of
excitation
was
shown
in Figure
thecamera
IR camera
positioned
cm from
the
to
allow
it
to
focus
on
and
frame
the
whole
specimen.
The
dimensions
of
the
specimen
were
76
mm
oven to allow it to focus on and frame the whole specimen. The dimensions of the specimen were
in length,
mm in
and
8 mmand
in thickness.
Due to the Due
low heat
diffusion
velocity
andvelocity
thermal
76
mm in 76
length,
76width
mm in
width
8 mm in thickness.
to the
low heat
diffusion
conductivity,
a strong driftainstrong
the temperature
over
time is noted.
Moreover,
thisMoreover,
setup can
and
thermal conductivity,
drift in the evolution
temperature
evolution
over time
is noted.
avoid
damage
due
to
possible
microwave
leakage.
To
obtain
the
amplitude
and
the
phase
this setup can avoid damage due to possible microwave leakage. To obtain the amplitude and
the
information,
Fast Fourier
Transform-based
algorithms
were were
used used
to process
the thermal
image
data
phase
information,
Fast Fourier
Transform-based
algorithms
to process
the thermal
image
which
acquires
thermal
images
frame
by frame
overover
time.time.
Figure
22b shows
the phase
image
and
data
which
acquires
thermal
images
frame
by frame
Figure
22b shows
the phase
image
Figure
22c
shows
amplitude
image.
In
the
experimental
results,
the
problem
of
the
specimen’s
edges
and Figure 22c shows amplitude image. In the experimental results, the problem of the specimen’s
was observed.
Due toDue
the to
interaction
between
the specimen
geometry
and the
electromagnetic
field,
edges
was observed.
the interaction
between
the specimen
geometry
and
the electromagnetic
a
high
temperature
was
exhibited
near
the
edge
of
the
specimen.
Nevertheless,
the
authors
could
field, a high temperature was exhibited near the edge of the specimen. Nevertheless, the authors could
clearlyidentify
identifythe
thedamage
damagearea
areainin
the
captured
thermograms.
In addition,
quantitative
analysis
of
clearly
the
captured
thermograms.
In addition,
quantitative
analysis
of the
the damaged
showed
good agreement
defect
area
resultswith
obtained
with
damaged
areasareas
showed
a goodaagreement
betweenbetween
the defectthe
area
results
obtained
microwave
2) and X-ray scanning
2).
2
2
microwave
thermography
(1693
mm
(1385
mm
thermography (1693 mm ) and X-ray scanning (1385 mm ).
4.5
4
3.5
3
2.5
2
1.5
(a)
(b)
(c)
1
Figure
experimental
set-upused
usedfor
forrelay
relay(a),
(a), lock-in
lock-in phase
image
(c)(c)
[74].
Figure
22. 22.
TheThe
experimental
set-up
phaseimage
image(b)
(b)and
andamplitude
amplitude
image
[74].
In 2014, Palumbo et al. investigated MWT for quantitative evaluation of damaged areas in CFRP
In 2014, Palumbo et al. investigated MWT for quantitative evaluation of damaged areas in
through experiments and numerical simulations [75]. Damaged CFRP samples were inspected by
CFRP through experiments and numerical simulations [75]. Damaged CFRP samples were inspected
microwave pulsed thermography. The dimensions of the four sandwich tested specimens were 76 ×
by microwave pulsed thermography. The dimensions of the four sandwich tested specimens were
76 mm2 with 8 mm thickness. Non-linear heating behavior was characterized and the undamaged
76 × 76 mm2 with 8 mm thickness. Non-linear heating behavior was characterized and the undamaged
area exhibited a higher slope during the heating and cooling phases. A new approach was proposed
area exhibited a higher slope during the heating and cooling phases. A new approach was proposed
to process the obtained thermographic data. Numerical simulations were carried out to assess the
to process the obtained thermographic data. Numerical simulations were carried out to assess the
sensitivity. An IR camera was located at 150 mm from the samples under test. To acquire the heating
phase and subsequent cooling phase, the IR camera recorded for 7 s at 100 Hz. This proposed
technique offers advantages in term of testing time (only 2 s of heating and a very fast data processing).
In Figure 23a, X-ray images of the specimens under test are provided for comparison with the MWT
results. As shown in Figure 23b, Tmax analysis can be used to quantitatively indicate damaged areas
located at a greater depth. The authors proposed a new algorithm based on the non-linear heating and
cooling thermal behavior of damaged and undamaged areas for the quantification of damaged areas.
The image after the data binarization is shown in Figure 23c. The location and size information of the
damaged area can be obtained from these measured results. Quantitative analysis of the damaged areas
shows a good agreement between results obtained with microwave thermography (784.3 mm2 with
technique offers advantages in term of testing time (only 2 s of heating and a very fast data
processing). In Figure 23a, X-ray images of the specimens under test are provided for comparison
with the MWT results. As shown in Figure 23b, Tmax analysis can be used to quantitatively indicate
damaged areas located at a greater depth. The authors proposed a new algorithm based on the nonlinear heating and cooling thermal behavior of damaged and undamaged areas for the quantification
Sensors 2017, 17, 1123
23 of 33
of damaged areas. The image after the data binarization is shown in Figure 23c. The location and size
information of the damaged area can be obtained from these measured results. Quantitative analysis
of slope),
the damaged
areas mm
shows
a good
agreement
between(779.3
results
obtained
withofmicrowave
2 ) and
2 ). The size
heating
X-ray (769.4
lock-in
thermography
mm
the minimum
thermography (784.3 mm2 with heating
slope), X-ray (769.4 mm2) and lock-in thermography (779.3
3
resolvable
defect
was
2
×
2
×
0.5
mm
,
with
a
depth
of
1.3
mm.
mm2). The size of the minimum resolvable defect was 2 × 2 × 0.5 mm3, with a depth of 1.3 mm.
Figure 23. X-ray images of three samples (a), Tmax maps during all acquisition sequence (b), and binary
Figure 23. X-ray images of three samples (a), Tmax maps during all acquisition sequence (b), and binary
images obtained by Tmax maps (c) [75]. Reprinted/reproduced with permission from Springer.
images obtained by Tmax maps (c) [75]. Reprinted/reproduced with permission from Springer.
Usamentiaga et al. proposed an artificial neural network for automatic energy estimation of
impact damages
fiber composite
materials,
the data for
acquisition
timeenergy
requiredestimation
for each of
Usamentiaga
etinal.carbon
proposed
an artificial
neuralbut
network
automatic
inspection
area
was
at
least
30
s
[76].
Three
specimens
were
measured:
specimen
1
was
a
carbon
impact damages in carbon fiber composite materials, but the data acquisition time requiredfiber
for each
composite
of 12 plies
mm in
thickness. were
Specimens
2 and 3 specimen
were composite
inspection
areamade
was up
at least
30 s with
[76]. 2.5
Three
specimens
measured:
1 waspanels
a carbon
with two stiff facings made of carbon fiber and a low density material bonded between them. These
fiber composite made up of 12 plies with 2.5 mm in thickness. Specimens 2 and 3 were composite
two specimens have two valid sides, side A made up of six plies (1.5 mm in thickness) and side B
panels with two stiff facings made of carbon fiber and a low density material bonded between them.
made up of 12 plies (2.5 mm in thickness). A FLIR SC5000 IR camera was used to acquire infrared
Theseimages
two specimens
have
two valid
sides,ofside
A made
up ofranging
six plies
(1.56 mm
inJ.thickness)
and
side B
for damages
caused
by impacts
different
energy,
from
J to 50
With 12 bits
per
made up of 12 plies (2.5 mm in thickness). A FLIR SC5000 IR camera was used to acquire infrared
images for damages caused by impacts of different energy, ranging from 6 J to 50 J. With 12 bits per
pixel, 320 × 256 pixel thermal images are produced by the FLIR SC5000 and its’ thermal sensitivity
is 0.02 K. To cut down the number of obtained images, the experimental acquisition rate is 50 Hz
while the maximum frame rate is 383 Hz. To improve the signal-to-noise ratio in the thermal images,
a post-processing method was applied. With a Discrete Fourier Transform (DFT), the temperature-time
history of each pixel during the heating period is transformed into the frequency domain and the
phase information can be calculated based on it. As shown in Figure 24, the value below each defect is
the estimated impact energy and the real impact energy is the number in brackets. In their primary
experiment results, the impact energy of nearly half of the defects was estimated with an error of
less than 2.5 J. This percentage increases to 80% when the considered error is 5 J, and nearly 100%
the maximum frame rate is 383 Hz. To improve the signal-to-noise ratio in the thermal images, a postprocessing method was applied. With a Discrete Fourier Transform (DFT), the temperature-time
history of each pixel during the heating period is transformed into the frequency domain and the
phase information can be calculated based on it. As shown in Figure 24, the value below each defect
is
the estimated
impact energy and the real impact energy is the number in brackets. In their primary
Sensors
2017, 17, 1123
24 of 33
experiment results, the impact energy of nearly half of the defects was estimated with an error of less
than 2.5 J. This percentage increases to 80% when the considered error is 5 J, and nearly 100% when
when
the estimated
J. The
results
indicate
artificial
neuralnetwork
network(ANN)
(ANN)isisable
able to
to
the
estimated
error error
is 10 isJ. 10
The
results
indicate
thatthat
an an
artificial
neural
quantitatively
characterize
impact
damages.
quantitatively characterize impact damages.
energy
using
artificial
neural
networks:
specimen
2 front side
(a), specimen
Figure 24.
24. Estimated
Estimatedimpact
impact
energy
using
artificial
neural
networks:
specimen
2 front
side (a),
2 backside2 (b),
specimen
3 front side
(c), side
specimen
3 backside
(d) [76].(d)Reprinted/reproduced
with
specimen
backside
(b), specimen
3 front
(c), specimen
3 backside
[76]. Reprinted/reproduced
permission
from from
Elsevier.
with
permission
Elsevier.
In
summary,the
thepurpose
purpose
of adopting
advanced
processing
methods
is to
In summary,
of adopting
advanced
signalsignal
processing
methods
in MWTinis MWT
to eliminate
eliminate
noise,
increase
the
signal
to
noise
ratio
for
extracting
the
abnormality
information
of
defects,
noise, increase the signal to noise ratio for extracting the abnormality information of defects, enhance
enhance
theofcontrast
ofimages
detection
theaccuracy.
assessment
accuracy.
the
the contrast
detection
andimages
improveand
the improve
assessment
Meanwhile,
theMeanwhile,
inspection time
inspection
timereduced.
can be further reduced.
can be further
5. Discussion
Discussion
Comparison with Other Excitation Sources
5.1. Comparison
a thermal
contrast
betweenbetween
surface/subsurface
defects anddefects
the surrounding
As mentioned
mentionedbefore,
before,
a thermal
contrast
surface/subsurface
and the
material
can
be
produced
by
many
energy
sources.
Some
works
are
focused
on
the
comparison
surrounding material can be produced by many energy sources. Some works are focused on the
between heating
methods.
Formethods.
example,For
Keoexample,
et al. [56]Keo
compared
microwave
infrared
thermography
comparison
between
heating
et al. [56]
compared
microwave
infrared
with CO2 laser with
thermography.
MWT was foundMWT
to be was
morefound
suitable
formore
the detection
defects
thermography
CO2 laser thermography.
to be
suitable of
fordeeper
the detection
while
CO2defects
laser thermography
was
more suitable
formore
the detection
of surface/near
surface
defects
of
deeper
while CO2 laser
thermography
was
suitable for
the detection of
surface/near
in CFRP.defects in CFRP.
surface
According to a literature review [14,30,56,77], a comparison between
between MWT and other
According
thermography excitation
excitationsources
sourceshas
hasbeen
been
provided
Table
3. Due
to use
the of
use
IR camera,
thermography
provided
in in
Table
3. Due
to the
anof
IRan
camera,
most
most
the thermography
methods
can fast
offerinspection,
fast inspection,
non-contact,
full-field,
great sensitivity,
of
theof
thermography
methods
can offer
non-contact,
full-field,
great sensitivity,
high
high
resolution,
and
quantitative
analyses.
As
listed
in
Table
3,
energy
sources
can
be
divided
into:
resolution, and quantitative analyses. As listed in Table 3, energy sources can be divided into:
1.
1.
2.
2.
3.
4.
Flash/lamp:
Flash/lamp:halogen
halogenororIR
IRlamps
lampsare
arecommonly
commonlyemployed
employedfor
foraalong
long period
period in
in large
large inspection
inspection
areas
with
an
x-y
scanner/robot.
In
all
cases,
the
measurement
surface
is
been
illumined
areas with an x-y scanner/robot. In all cases, the measurement surface is been illumined by
by light
light
to
transfer
heat
and
to
propagate
inside
the
specimen
(containing
a
wavelength
range
from
to transfer heat and to propagate inside the specimen (containing a wavelength range from the
the
ultraviolet,
ultraviolet,visible
visible and
and infrared
infrared spectrum).
spectrum).
Laser:
with
lamps,
a
Laser:the
theheat
heatisisintroduced
introducedinto
intothe
thematerial
materialunder
undertest
testbybythe
thelaser.
laser.Compared
Compared
with
lamps,
scan
of
the
inspection
area
is
needed.
a scan of the inspection area is needed.
Mechanical: sound or ultrasound waves are injected by transducers. With waves propagating
through the specimen, heat is produced by slapping and rubbing of the surfaces (mostly in the
defect areas). Compared with optical excitation, non-uniform heating is considerably reduced
and the visibility of sub-surface defects is improved.
Induction: eddy currents are generated by an excitation coil. The penetration depth varies
inversely with the operation frequency. The induction heating is limited to conductive materials.
Sensors 2017, 17, 1123
5.
25 of 33
Compared with mechanical heating, heating non-uniformities have less influence in induction
heating since heat is produced locally.
Microwave: the heat is introduced into the specimen by a time-gated microwave excitation source.
The sub-surface microwave absorbing features can be used for measurements (such as metal
bars/fibers, water-filled areas). By analyzing the time of the thermal images, quantitative defect
information can be extracted (such as depth and size).
Table 3. Comparison of thermography inspection methods with different excitation sources.
Heating Sources
Strengths
Limitations
Flash, lamp
Non-contact, full-field, low cost, methods are mature
Surface heating, impact of surface condition
on heating, heating reflection
Laser
Non-contact, remote heating from a far distance,
high sensitivity, great resolution, quantification, fast
Heating area relies on excitation source,
scanning is required, more suitable for
surface defect detection
Full-field, high resolution, high sensitivity,
quantification, fast, selective heating
Contact, know-how, specimen needs to be
fixed, lack of quantitative information
Non-contact, relatively low-cost of excitation system,
full-field, high resolution, great sensitivity,
quantification, fast, inner heating
Limited to conductive material,
non-uniform heating, complex heating
system, near-field heating, heating area is
limited to the excitation coil
Non-contact, remote excitation, full-field, high
resolution, great sensitivity, quantification, fast,
uniform heating, selective heating
Complex and expensive microwave
excitation system, electromagnetic radiation
Mechanical
Induction
Microwave
5.2. Comparison with Other NDT Methods
Eight major categories of NDT techniques are listed in Table 4. A comparison of these technologies
is provided and an overview of each method given to identify the advantages and limitations of current
NDT techniques.
Table 4. Summary and comparison for MWT with major NDT methods.
NDT Techniques
Strength
Limitation
Ultrasound-echo/Phased
array/Linear array
Great depth, high resolution, many
deployment options
Sound attenuation, coupling for contact testing,
non-sensitive to surface defects
Guide wave
Large areas
Sound attenuation, coupling for contact testing
Acoustic emission
In-service, passive, large areas,
Noise, bad quantitation, non-sensitive
to static defects
Shearography
Non-contact, full-field, fast, high sensitivity
Sensitive to part movement, small
thickness/stiffness, require unique test set-ups,
expensive, hard to quantitatively analyze
Eddy current
Non-contact, low-cost, no surface treatment
Conductive material, scanner required, sensitive
to lift-off, low resolution
Microwave
Non-contact, high resolution, suitable for
dielectric material
Scanner required, near-field, lift-off influence
Microwave thermography
Non-contact, full-field, high resolution,
high sensitivity, quantification, fast,
uniform heating, selective heating
Heating system complex,
electromagnetic radiation
X-ray/Gamma-ray
High resolution, non-contact
X-ray radiation hazards, operation complex,
scanner required
For materials inspection, there is no universally applicable method. Selection of a particular NDT
technique requires more consideration than the detection capabilities. Meanwhile, the application,
portability of equipment, inspection schedule, inspection area, types of materials, accessibility, costs
and expected defects types are also important.
Sensors 2017, 17, 1123
26 of 33
5.3. Shortcomings of MWT
From the MWT literature, it can be found that MWT is not always perfect for quantitative material
detection. There are still many shortcomings in existing studies, which can be mainly summarized
as follows:
1.
Inadequate theoretical studies
Multi-physics coupling mechanisms of metal/composite materials detection with microwave
thermography are not deeply studied. For example, composite materials are typically composed of
a variety of materials, and the microwave heating principles of composite materials are different from
those of conductive and dielectric materials. Meanwhile, the physical processes of MWT for material
evaluation are very complex, which includes microwave heating, heat conduction, and heat diffusion.
For example, microwave heating represents a dielectric loss in glass fiber composite materials, where it
is a volumetric heating method; while microwave heating is Joule heat for conductive materials which
is affected by skin effects, and it is a surface heating method.
2.
Lack of study on excitation signal modulation and corresponding data processing methods
As mentioned above, IR thermography techniques can be subdivided into pulse thermography,
lock-in thermography, pulse phase thermography and step heating thermography [14]. Many scholars
have studied microwave pulse thermography, microwave step heating thermography and microwave
lock-in thermography. However, no researcher has studied pulse phase microwave heating in the
frequency domain. Microwave pulse phase thermography combines the advantages of MPT and MLT
which can inhibit change in the surface emissivity and other negative factors; the pulse width can
bring a stronger contrast and a deeper defect can be detected.
3.
Lack of systematic research on microwave excitation module optimization
Microwave excitation module is an important part of MWT, and the heating effect is directly
reliant on it. Furthermore, the subsequent thermal imaging is directly affected by rapid and uniform
heating. British and Polish researchers have investigated waveguides as excitation modules [57,72];
French scholars have studied the pyramidal horn antenna as an excitation module [56]; South Korean
scholars have studied the coaxial setup as excitation module [69]. However, the advantages and
disadvantages of these microwave excitation modules are not thoroughly studied, which results in is it
being difficult to achieve the optimal detection ability with MWT systems.
4.
Lack of internal properties characterization and defect quantification methods
Temperature variation from the infrared camera is a result of joint action by the surface properties
of materials (emissivity), internal thermal properties (thermal conductivity, diffusivity, interlayer
reflection coefficient), electrical properties (conductivity and permittivity) and other factors. How to
extract these features from the surface temperature response and to further quantitatively characterize
the material properties is important and difficult in the current studies. Existing studies did not
provide an effective method for property characterization and defect quantification.
5.
Lack of automatic separation and damage area quantification methods
Some scholars have studied several prefabricated macroscopic defects in composite materials
(lamination defects, cracks and debonding, etc.), and experimental empirical formulas have been
established; but there is a lack of related research on automatic separation of different defects and
damage area quantification. The data acquired with MWT is an image sequence or a three-dimensional
matrix. Matrix analysis method is theoretically possible to achieve fast imaging, automatic separation
and damage area quantification. However, existing studies employed advanced matrix decomposition
methods for MWT data processing.
Sensors 2017, 17, 1123
27 of 33
6. Trends
1.
Multiple physics and new physics
The physical properties of the specimens are different which results in the physics of MWT
being different. For example, composites are multi-layered and their parameters are anisotropic
as a result of fiber reinforcement. In addition, several composite materials are often included in
a composite structure (such as a sandwich structure). Hence, the physics of metals differ from those
of composites. Furthermore, the effects of the electromagnetic field, microwave propagation and
other multiple-physical field also need to be investigated, such as thermal pattern interpretation [78]
in thermal optical flow [79], and the spatial-, time-, frequency-, and sparse-pattern domains. Thus,
multiple physics and new physics-based MWT methods are required for materials evaluation.
2.
Computer simulation and modeling
Over the last several years, computer modeling and simulation (such as method of moments
or MoM and finite element method or FEM) have been employed for understanding the physics
during MWT measurements (such as microwave radiation and propagation, heat generation and
diffusion). In the past, researchers have investigated three different approaches to resolving the
electromagnetic phenomena of microwave propagation and heating processes. Firstly, time-domain
solvers have been applied to microwave heating problems [80]. These use a time-marching algorithm
to predict the electric and magnetic fields at the next time step. Secondly, frequency-domain methods
have been investigated [81], where the numerical solution strategy uses a particular frequency to
predict the electric and magnetic fields. Lastly, a method that combines an efficient time-domain
solver with the power of a frequency-domain solver, has been used to predict the power distribution
generated in a lossy medium during microwave heating [82]. Moreover, the operational frequency and
radiation pattern of microwave excitation system can be optimized with simulation and modeling for
better detection performance. In addition, the influence of materials’ properties (such as conductivity,
dielectric, size and shape) can be investigated with simulation and the total cost of experiments will be
reduced. What’s more, the parameters of defects (such as location, size, orientation and shape) can be
examined. For composite materials, the influence of different fiber orientations in the microwave EM
field can be investigated too. Therefore, simulation and modeling are needed to improve the reliability
and accuracy of MWT systems.
3.
Microwave excitation system optimization
MWT is based on microwave heating. The thermal profile of a material under test is created by
an IR camera after microwave excitation. With MWT, a large amount of microwave excitation systems
can be used to introduce the heat, however, the heating efficiency of microwave excitation systems
is not only dependent on the properties of the microwave system (such as operational frequency,
radiation pattern and power, etc.) but also relies on the physical properties of the material under test
(such as size, shape, conductivity, dielectrics and microwave energy absorbing ability, etc.). Thus,
the optimization of microwave excitation systems is required to improve the ability and sensitivity of
MWT systems.
4.
Signal processing algorithms
To extract useful features from the captured thermal images, advanced signal processing
algorithms have been used. These algorithms includes wavelet transform [83], independent
components analysis (ICA) [84], principal components analysis (PCA) [85,86], pattern recognition [87],
support vector machine [88,89] and Tucker decomposition [90]. With suitable signal processing
algorithms, the inspection results for size and depth identification, subsurface defect detection,
emissivity variation reduction and defect dimension quantification can be significantly improved.
To extract useful features from the captured thermal images, advanced signal processing
algorithms have been used. These algorithms includes wavelet transform [83], independent
components analysis (ICA) [84], principal components analysis (PCA) [85,86], pattern recognition
[87], support vector machine [88,89] and Tucker decomposition [90]. With suitable signal processing
Sensors
2017, 17, the
1123 inspection results for size and depth identification, subsurface defect detection,
28 of 33
algorithms,
emissivity variation reduction and defect dimension quantification can be significantly improved.
Therefore, more advanced signal processing algorithms are needed to further improve the sensitivity
Therefore, more advanced signal processing algorithms are needed to further improve the sensitivity
and quantification ability of MWT systems.
and quantification ability of MWT systems.
5. Intelligent inspection systems
5. Intelligent inspection systems
The efficiency of a MWT system can be improved by implementing an intelligent inspection
The efficiency of a MWT system can be improved by implementing an intelligent inspection
system with artificial intelligence. As various types of defects can be acquired during material
system with artificial intelligence. As various types of defects can be acquired during material
measurement, the treatment for different types of defects is different. Taking a composite material
measurement, the treatment for different types of defects is different. Taking a composite material for
for example, the most common embedded defects are delamination, adhesive debonding and out-ofexample, the most common embedded defects are delamination, adhesive debonding and out-of-plane
plane waviness. These defects are the most typical defects observed during manufacturing which
waviness. These defects are the most typical defects observed during manufacturing which need
need to be identified to improve the manufacturing quality of the composite. Therefore, it is
to be identified to improve the manufacturing quality of the composite. Therefore, it is important
important to classify the defect type with an intelligent inspection system. As computers become
to classify the defect type with an intelligent inspection system. As computers become increasingly
increasingly capable, artificial intelligence methods can be used in MWT to reduce the inspection
capable, artificial intelligence methods can be used in MWT to reduce the inspection time and improve
time and improve the reliability of MWT systems. For example, Moomen et al. employed machine
the reliability of MWT systems. For example, Moomen et al. employed machine learning for feature
learning for feature selection in microwave NDT [91].
selection in microwave NDT [91].
6. Mobile inspection systems
6. Mobile inspection systems
For a large material under test, the MWT needs to be placed in a mobile robot or a vehicle. In
For a large material under test, the MWT needs to be placed in a mobile robot or a vehicle.
Figure 25, a MWT inspection system has been combined with a vehicle [61]. The inspection time of
In Figure 25, a MWT inspection system has been combined with a vehicle [61]. The inspection time
MWT for a large material can be significantly reduced. The whole inspection can be performed
of MWT for a large material can be significantly reduced. The whole inspection can be performed
autonomously. The safety and efficiency of the MWT systems are being improved too. However,
autonomously. The safety and efficiency of the MWT systems are being improved too. However,
lightweight equipment and advanced detection algorithms including compressed sensing are also
lightweight equipment and advanced detection algorithms including compressed sensing are also
required in order to provide automatic inspection capability.
required in order to provide automatic inspection capability.
Figure25.
25.MWT
MWTcombined
combinedwith
withaavehicle
vehicle[61].
[61].Reprinted/reproduced
Reprinted/reproduced with
with permission
permission from
from SPIE.
SPIE.
Figure
7. Conclusions
Conclusions
7.
The basic
basic principles
principles and
and types
types of
of MWT
MWT have
have been
been reviewed
reviewed in
in this
this paper.
paper. MWT
MWT exhibits
exhibits great
great
The
potential, including
including fast
fast heating,
heating, high
high resolution,
resolution, fast
fast inspection
inspection and
and high
high sensitivity,
sensitivity, no
no contact
contact
potential,
requirement
and
better
detectability
for
inner
defects.
Moreover,
the
manufacturing
quality
and
requirement and better detectability for inner defects. Moreover, the manufacturing quality and
reliability of
of materials
materials can
review
of
reliability
can be
be improved
improved to
toprevent
preventfailures.
failures.InInthis
thiswork,
work,a comprehensive
a comprehensive
review
MWT
techniques
for
material
inspection
has
been
reported
based
on
a
detailed
literature
survey.
of MWT techniques for material inspection has been reported based on a detailed literature survey.
Firstly,the
thetheory
theoryofof
MWT
been
presented
MWT
has been
classified
intocategories.
four categories.
Firstly,
MWT
hashas
been
presented
andand
MWT
has been
classified
into four
Then,
the development of MWT has been outlined through case studies. Next, limitations in current MWT
research have been outlined based on detailed comparisons. Finally, some research trends in MWT are
predicted. It is concluded that:
1.
MWT combines the advantages of microwave technology and infrared thermography. A higher
heating efficiency and uniform heating pattern can be expected. A full-field, non-contact, fast
detection can be performed.
Sensors 2017, 17, 1123
2.
3.
29 of 33
MWT can be divided into MPT, MPPT, MST and MLT. In the near future, microwave frequency
modulated thermography and microwave pulsed phase thermography will be achieved.
MWT is a fast and effective non-destructive method for material inspection, especially for
water/defects identification in concrete/composite structures.
Acknowledgments: This work was supported by National Natural Science Foundation of China (61601125
and 61501483), National Key Research and Development Program of China (2016YFF0203400), Natural Science
Foundation of Fujian Province (2016J05152) and Fujian Province Young and Middle Age Education Research Fund
(JA15577).
Conflicts of Interest: The authors declare no conflict of interest.
Abbreviations
AHT
ANN
CFRP
DFT
ECLT
ECPT
ECPPT
ECST
FEM
FRCM
GFRP
LT
MLT
MoM
MPT
MPPT
MST
MT
MUT
MWT
NDT
PMC
PPT
PT
SHM
SHT
ST
VHT
Abnormal heating thermography
Artificial neural networks
Carbon fiber reinforced polymer
Discrete Fourier transform
Eddy current lock-in thermography
Eddy current pulsed thermography
Eddy current pulsed phase thermography
Eddy current step thermography
Finite element method
Fiber-reinforced cement-based mortars
Glass fiber reinforced polymer
Lock-in thermography
Microwave lock-in thermography
Method of moments
Microwave pulsed thermography
Microwave pulsed phase thermography
Microwave step thermography
Modulated thermography
Material under test
Microwave thermography
Nondestructive testing
Polymer matrix composites
Pulsed phase thermography
Pulsed thermography
Structural health monitoring
Surface heating thermography
Step thermography
Volume heating thermography
References
1.
2.
3.
4.
5.
6.
7.
Bakht, B.; Mufti, A. Bridges: Analysis, Design, Structural Health Monitoring, and Rehabilitation; Springer: Cham,
Switzerland, 2015.
Hellier, C. Handbook of Nondestructive Evaluation; Mcgraw-hill: New York, NY, USA, 2001.
Maldague, X.P. Introduction to NDT by active infrared thermography. Mater. Eval. 2002, 60, 1060–1073.
Vergani, L.; Colombo, C.; Libonati, F. A review of thermographic techniques for damage investigation in
composites. Fract. Struct. Integr. Ann. 2014, 8. [CrossRef]
Sun, J.G. Analysis of Pulsed Thermography Methods for Defect Depth Prediction. J. Heat Transf. 2005, 128,
329–338. [CrossRef]
Czichos, H. Handbook of Technical Diagnostics; Springer: Berlin, Germany, 2013; Volume 40, pp. 43–68.
Shalin, R.E.E. Polymer Matrix Composites; Springer Science & Business Media: Berlin, Germany, 2012.
Sensors 2017, 17, 1123
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
30 of 33
Zalameda, J.N.; Burke, E.R.; Parker, F.R.; Seebo, J.P.; Wright, C.W.; Bly, J.B. Thermography inspection for
early detection of composite damage in structures during fatigue loading. Proc. SPIE 2012, 8354. [CrossRef]
Waugh, R.C.; Dulieu-Barton, J.M.; Quinn, S. Modelling and evaluation of pulsed and pulse phase
thermography through application of composite and metallic case studies. NDT E Int. 2014, 66, 52–66.
[CrossRef]
Roche, J.M. Common tools for quantitative time-resolved pulse and step-heating thermography—Part I:
Theoretical basis. Quant. Infrared Thermogr. J. 2014, 11, 43–56.
Maldague, X.P. Theory and Practice of Infrared Technology for Nondestructive Testing; John Wiley Interscience:
New York, NY, USA, 2001.
Castanedo, C.I. Quantitative Subsurface Defect Evaluation by Pulsed Phase Thermography: Depth Retrieval with the
Phase; Université Laval: Québec City, QC, Canada, 2005.
Maldague, X.P.; Marinetti, S. Pulsed phase infrared thermography. J. Appl. Phys. 1996, 79, 2694–2698.
[CrossRef]
Yang, R.; He, Y. Optically and Non-optically Excited Thermography for Composites: A review.
Infrared Phys. Technol. 2016, 75, 26–50. [CrossRef]
Li, T.; Almond, D.P.; Rees, D.A.S. Crack imaging by scanning pulsed laser spot thermography. NDT E Int.
2011, 44, 216–225. [CrossRef]
Wilson, J.; Tian, G.Y.; Abidin, I.Z.; Yang, S.; Almond, D. Pulsed eddy current thermography: System
development and evaluation. Insight Non-Destr. Test. Cond. Monit. 2010, 52, 87–90. [CrossRef]
Riegert, G.; Zweschper, T.; Busse, G. Eddy-current lockin-thermography: Method and its potential. J. Phys.
IV Fr. 2005, 125, 587–591. [CrossRef]
He, Y.; Tian, G.; Pan, M.; Chen, D. Eddy current pulsed phase thermography and feature extraction.
Appl. Phys. Lett. 2013, 103, 084104. [CrossRef]
Yang, R.; He, Y.; Gao, B.; Tian, G.Y.; Peng, J. Lateral heat conduction based eddy current thermography for
detection of parallel cracks and rail tread oblique cracks. Measurement 2015, 66, 54–61. [CrossRef]
He, Y.; Pan, M.; Tian, G.Y.; Chen, D.; Tang, Y.; Zhang, H. Eddy current pulsed phase thermography for
subsurface defect quantitatively evaluation. Appl. Phys. Lett. 2013, 103, 144108. [CrossRef]
He, Y.; Pan, M.; Chen, D.; Tian, G.Y.; Zhang, H. Eddy current step heating thermography for quantitatively
evaluation. Appl. Phys. Lett. 2013, 103, 194101. [CrossRef]
He, Y.; Tian, G.; Pan, M.; Chen, D. Impact evaluation in carbon fiber reinforced plastic (CFRP) laminates
using eddy current pulsed thermography. Compos. Struct. 2014, 109, 1–7. [CrossRef]
Zhang, H.; Gao, B.; Tian, G.Y.; Woo, W.L.; Bai, L. Metal defects sizing and detection under thick coating using
microwave NDT. NDT E Int. 2013, 60, 52–61. [CrossRef]
Qaddoumi, N.N.; Saleh, W.M.; Abou-Khousa, M. Innovative Near-Field Microwave Nondestructive
Testing of Corroded Metallic Structures Utilizing Open-Ended Rectangular Waveguide Probes. IEEE Trans.
Instrum. Meas. 2007, 56, 1961–1966. [CrossRef]
Meredith, R. Engineers’ Handbook of Industrial Microwave Heating; The Institution of Electrical Engineers:
London, UK, 1998.
Wyckhuyse, A.; Maldague, X. A Study of Wood Inspection by Infrared Thermography, Part II: Thermography
for Wood Defects Detection. Res. Nondestruct. Eval. 2001, 13, 13–22. [CrossRef]
Balageas, D.; Lemistre, M.; Levesque, P. Mine detection using the EMIR® method-Improved configuration
using a mobile detection system. In Proceedings of the 7th International Conference on Quantitative Infrared
Thermography (QIRT), Bordeaux, France, 7–11 July 2004.
Swiderski, W.; Hłosta, P.; Szugajew, L.; Usowicz, J. Microwave enhancement on thermal detection of buried
objects. In Proceedings of the 11th International Conference on Quantitative InfraRed Thermography, Naples,
Italy, 11–14 June 2012.
Vinson, J.R. Adhesive bonding of polymer composites. Polym. Eng. Sci. 1989, 29, 1325–1331. [CrossRef]
Yang, R.; He, Y.; Zhang, H. Progress and Trends in Nondestructive Testing and Evaluation for Wind Turbine
Composite Blade. Renew. Sustain. Energy Rev. 2016, 60, 1225–1250. [CrossRef]
Ibarra-Castanedo, C.; Maldague, X. Review of pulse phase thermography. Proc. SPIE 2015, 9485. [CrossRef]
Kylili, A.; Fokaides, P.A.; Christou, P.; Kalogirou, S.A. Infrared thermography (IRT) applications for building
diagnostics: A review. Appl. Energy 2014, 134, 531–549. [CrossRef]
Sensors 2017, 17, 1123
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.
53.
54.
55.
56.
31 of 33
Bagavathiappan, S.; Lahiri, B.B.; Saravanan, T.; Philip, J.; Jayakumar, T. Infrared thermography for condition
monitoring—A review. Infrared Phys. Technol. 2013, 60, 35–55. [CrossRef]
Yang, B.; Zhang, L.; Zhang, W.; Ai, Y. Non-destructive testing of wind turbine blades using an infrared
thermography: A review. In Proceedings of the International Conference on Materials for Renewable Energy
and Environment, Chengdu, China, 19–21 August 2013; pp. 407–410.
Ibarra-Castanedo, C.; Maldague, X. Pulsed phase thermography reviewed. Quant. Infrared Thermogr. J. 2004,
1, 47–70. [CrossRef]
Hung, Y.; Chen, Y.S.; Ng, S.; Liu, L.; Huang, Y.; Luk, B.; Ip, R.; Wu, C.; Chung, P. Review and comparison
of shearography and active thermography for nondestructive evaluation. Mater. Sci. Eng. R Rep. 2009, 64,
73–112. [CrossRef]
Omar, M.A.; Zhou, Y. A quantitative review of three flash thermography processing routines.
Infrared Phys. Technol. 2008, 51, 300–306. [CrossRef]
Ghosh, K.K.; Karbhari, V.M. A critical review of infrared thermography as a method for non-destructive
evaluation of FRP rehabilitated structures. Int. J. Mater. Prod. Technol. 2006, 25, 241–266. [CrossRef]
Vavilov, V.P.; Burleigh, D.D. Review of pulsed thermal NDT: Physical principles, theory and data processing.
NDT E Int. 2015, 73, 28–52. [CrossRef]
Banerjee, D.; Chattopadhyay, S.; Tuli, S. Infrared thermography in material research—A review of textile
applications. Indian J. Fiber Text. Res. 2013, 38, 427–437.
Usamentiaga, R.; Venegas, P.; Guerediaga, J.; Vega, L.; Molleda, J.; Bulnes, F.G. Infrared thermography for
temperature measurement and non-destructive testing. Sensors 2014, 14, 12305–12348. [CrossRef] [PubMed]
Meola, C.; Carlomagno, G.M. Application of infrared thermography to adhesion science. J. Adhes. Sci. Technol.
2006, 20, 589–632. [CrossRef]
Meola, C.; Carlomagno, G.M. Recent advances in the use of infrared thermography. Meas. Sci. Technol. 2004,
15, R27. [CrossRef]
Yang, R.; Zhang, H.; Li, T.; He, Y. An investigation and review into microwave thermography for NDT and
SHM. In Proceedings of the IEEE Far East NDT New Technology & Application Forum, Zhuhai, China,
28–31 May 2015; pp. 133–137.
He, Y.; Yang, R.; Zhang, H.; Zhou, D.; Wang, G. Volume or inside heating thermography using electromagnetic
excitation for advanced composite materials. Int. J. Thermal Sci. 2017, 111, 41–49. [CrossRef]
Meredith, R. Engineers’ Handbook of Industrial Microwave Heating [Book Review]. Power Eng. 1999, 13, 3.
Vrana, J.; Goldammer, M.; Bailey, K.; Rothenfusser, M.; Arnold, W. Induction and Conduction Thermography:
Optimizing the Electromagnetic Excitation towards Application. AIP Conf. Proc. 2009, 1096, 518–525.
Shao, K.; Lavers, J.D. A skin depth-independent finite element method for Eddy current problems.
IEEE Trans. Magn. 1986, 22, 1248–1250. [CrossRef]
Niliot, C.L.; Gallet, P. Infrared thermography applied to the resolution of inverse heat conduction problems:
Recovery of heat line sources and boundary conditions. Revue Générale Thermique 1998, 37, 629–643.
[CrossRef]
Salazar, A. Energy propagation of thermal waves. Eur. J. Phys. 2006, 27, 1349. [CrossRef]
Liu, J.; Yang, W.; Dai, J. Research on thermal wave processing of lock-in thermography based on analyzing
image sequences for NDT. Infrared Phys. Technol. 2010, 53, 348–357. [CrossRef]
Osiander, R.; Spicer, J.W. Time-resolved infrared radiometry with step heating.
A review.
Revue Générale Thermique 1998, 37, 680–692. [CrossRef]
Yang, R.; He, Y.; Gao, B.; Tian, G.Y. Inductive pulsed phase thermography for reducing or enlarging the effect
of surface emissivity variation. Appl. Phys. Lett. 2014, 105, 184103. [CrossRef]
Yang, R.; He, Y. Eddy current pulsed phase thermography considering volumetric induction heating for
delamination evaluation in carbon fiber reinforced polymers. Appl. Phys. Lett. 2015, 106, 234103. [CrossRef]
He, Y.; Yang, R. Eddy Current Volume Heating Thermography and Phase Analysis for Imaging
Characterization of Interface Delamination in CFRP. IEEE Trans. Ind. Inf. 2015, 11, 1287–1297. [CrossRef]
Keo, S.-A.; Defer, D.; Breaban, F.; Brachelet, F. Comparison between Microwave Infrared Thermography and
CO2 Laser Infrared Thermography in Defect Detection in Applications with CFRP. Mater. Sci. Appl. 2013, 4,
600–605.
Sensors 2017, 17, 1123
57.
58.
59.
60.
61.
62.
63.
64.
65.
66.
67.
68.
69.
70.
71.
72.
73.
74.
75.
76.
32 of 33
Cheng, L.; Tian, G.Y.; Szymanik, B. Feasibility studies on microwave heating for nondestructive evaluation
of glass fibre reinforced plastic composites. In Proceedings of the IEEE International Instrumentation and
Measurement Technology Conference, Hangzhou, China, 10–12 May 2011; pp. 1–6.
Foudazi, A.; Donnell, K.M.; Ghasr, M.T. Application of Active Microwave Thermography to delamination
detection. In Proceedings of the IEEE International Instrumentation and Measurement Technology
Conference, Montevideo, Uruguay, 12–15 May 2014; pp. 1567–1571.
Levesque, P.; Deom, A.; Balageas, D. Non destructive evaluation of absorbing materials using microwave
stimulated infrared thermography. In Review of Progress in Quantitative Nondestructive Evaluation; Springer:
Berlin, Germany, 1993; pp. 649–654.
D’Ambrosio, G.; Massa, R.; Migliore, M.D.; Cavaccini, G.; Ciliberto, A.; Sabatino, C. Microwave excitation
for thermographic NDE: An experimental study and some theoretical evaluations. Mater. Eval. 1995, 53,
502–508.
Sakagami, T.; Kubo, S.; Komiyama, T.; Suzuki, H. Proposal for a new thermographic nondestructive testing
technique using microwave heating. Proc. SPIE 1999, 3700. [CrossRef]
Foudazi, A.; Ghasr, M.T.; Donnell, K.M. Characterization of Corroded Reinforced Steel Bars by Active
Microwave Thermography. IEEE Trans. Instrum. Meas. 2015, 64, 2583–2585. [CrossRef]
Pieper, D.; Donnell, K.M.; Ghasr, M.T.; Kinzel, E.C. Integration of microwave and thermographic NDT
methods for corrosion detection. AIP Conf. Proc. 2014, 1581, 1560–1567.
Foudazi, A.; Ghasr, M.T.; Donnell, K.M. Application of active microwave thermography to inspection of
carbon fiber reinforced composites. In Autotestcon; IEEE: Washington, DC, USA, 2014; pp. 318–322.
Keo, S.A.; Brachelet, F.; Breaban, F.; Defer, D. Steel detection in reinforced concrete wall by microwave
infrared thermography. NDT E Int. 2014, 62, 172–177. [CrossRef]
Osiander, R.; Spicer, J.W.M.; Murphy, J.C. Thermal imaging of subsurface microwave absorbers in dielectric
materials. Proc. SPIE 1994, 2245. [CrossRef]
Bowen, M.W.; Osiander, R.; Spicer, J.W.M.; Murphy, J.C. Thermographic Detection of Conducting
Contaminants in Composite Materials Using Microwave Excitation. In Review of Progress in Quantitative
Nondestructive Evaluation; Thompson, D.O., Chimenti, D.E., Eds.; Springer US: Boston, MA, 1995; Volume 14,
pp. 453–460.
Sikora, R.; Chady, T.; Szymanik, B. Infrared thermographic testing of composite materials with adhesive
joints. In Proceedings of the 18th World Conference on Nondestructive Testing, Durban, South Africa,
16–20 April 2012; pp. 1–8.
Lee, H.; Galstyan, O.; Babajanyan, A.; Friedman, B.; Berthiau, G.; Kim, J.; Lee, K. Characterization of
anisotropic electrical conductivity of carbon fiber composite materials by a microwave probe pumping
technique. J. Compos. Mater. 2015, 50. [CrossRef]
Foudazi, A.; Edwards, C.A.; Ghasr, M.T.; Donnell, K.M. Active Microwave Thermography for Defect
Detection of CFRP-Strengthened Cement-Based Materials. IEEE Trans. Instrum. Meas. 2016, 65, 1–9.
[CrossRef]
Osiander, R.; Spicer, J.W.M.; Murphy, J.C. Microwave-source time-resolved infrared radiometry for
monitoring of curing and deposition processes. Proc. SPIE 1995, 2473. [CrossRef]
Swiderski, W.; Szabra, D.; Wojcik, J. Nondestructive evaluation of aircraft components by thermography using
different heat sources. In Proceeding of the QIRT Conference, Dubrovnik, Croatia, 24–27 September 2002;
pp. 78–84.
Foudazi, A.; Mehdipour, I.; Donnell, K.M.; Khayat, K.H. Evaluation of steel fiber distribution in cement-based
mortars using active microwave thermography. Mater. Struct. 2016, 49, 5051–5065. [CrossRef]
Galietti, U.; Palumbo, D.; Calia, G.; Pellegrini, M. Non destructive evaluation of composite materials with
new thermal methods. In Proceedings of the 15th European Conference on Composite Materials, Venice,
Italy, 24–28 June 2012.
Palumbo, D.; Ancona, F.; Galietti, U. Quantitative damage evaluation of composite materials with microwave
thermographic technique: Feasibility and new data analysis. Meccanica 2015, 50, 443–459. [CrossRef]
Usamentiaga, R.; Venegas, P.; Guerediaga, J.; Vega, L.; López, I. Feature extraction and analysis for automatic
characterization of impact damage in carbon fiber composites using active thermography. NDT E Int. 2013,
54, 123–132. [CrossRef]
Sensors 2017, 17, 1123
77.
78.
79.
80.
81.
82.
83.
84.
85.
86.
87.
88.
89.
90.
91.
33 of 33
Pickering, S.; Almond, D. Matched excitation energy comparison of the pulse and lock-in thermography
NDE techniques. NDT E Int. 2008, 41, 501–509. [CrossRef]
Gao, B.; Woo, W.L.; Tian, G.Y. Electromagnetic Thermography Nondestructive Evaluation: Physics-based
Modeling and Pattern Mining. Sci. Rep. 2016, 6, 25480. [CrossRef] [PubMed]
Gao, B.; He, Y.; Woo, W.L.; Tian, G.Y.; Liu, J.; Hu, Y. Multidimensional Tensor-Based Inductive Thermography
With Multiple Physical Fields for Offshore Wind Turbine Gear Inspection. IEEE Trans. Ind. Electron. 2016, 63,
6305–6315. [CrossRef]
Shankar, V.; Mohammadian, A.H. A Time-Domain, Finite-Volume Treatment for the Maxwell Equations.
J. Microw. Power Electromagn. Energy 1990, 128–145. [CrossRef]
Harms, P.H.; Chen, Y.; Mittra, R.; Shimony, Y. Numerical Modeling of Microwave Heating Systems. J. Microw.
Power Electromagn. Energy 1996, 31, 114–121. [CrossRef]
Vegh, V.; Turner, I.W. A hybrid technique for computing the power distribution generated in a lossy medium
during microwave heating. J. Comput. Appl. Math. 2006, 197, 122–140. [CrossRef]
Liu, T.; Zhang, W.; Yan, S. A novel image enhancement algorithm based on stationary wavelet transform
for infrared thermography to the de-bonding defect in solid rocket motors. Mech. Syst. Signal Process. 2015,
62–63, 366–380. [CrossRef]
Cheng, L.; Gao, B.; Tian, G.Y.; Woo, W.; Berthiau, G. Impact Damage Detection and Identification using
Eddy Current Pulsed Thermography through Integration of PCA and ICA. IEEE Sens. J. 2014, 14, 1655–1663.
[CrossRef]
Liang, T.; Ren, W.; Tian, G.Y.; Elradi, M.; Gao, Y. Low energy impact damage detection in CFRP using eddy
current pulsed thermography. Compos. Struct. 2016, 143, 352–361. [CrossRef]
Edis, E.; Flores-Colen, I.; de Brito, J. Quasi-quantitative infrared thermographic detection of moisture
variation in facades with adhered ceramic cladding using principal component analysis. Build. Environ.
2015, 94, 97–108. [CrossRef]
Gao, B.; Woo, W.L.; He, Y.; Tian, G.Y. Unsupervised sparse pattern diagnostic of defects with inductive
thermography imaging system. IEEE Trans. Ind. Inform. 2016, 12, 371–383. [CrossRef]
Wang, H.; Hsieh, S.J.; Peng, B.; Zhou, X. Non-metallic coating thickness prediction using artificial neural
network and support vector machine with time resolved thermography. Infrared Phys. Technol. 2016, 77,
316–324. [CrossRef]
Zou, H.; Huang, F. A novel intelligent fault diagnosis method for electrical equipment using infrared
thermography. Infrared Phys. Technol. 2015, 73, 29–35. [CrossRef]
Gao, B.; Yin, A.; Tian, G.; Woo, W.L. Thermography spatial-transient-stage mathematical tensor construction
and material property variation track. Int. J. Therm. Sci. 2014, 85, 112–122. [CrossRef]
Abdelniser, M.; Abdulbaset, A.; Ramahi, O.M. Reducing Sweeping Frequencies in Microwave NDT
Employing Machine Learning Feature Selection. Sensors 2016, 16, 559.
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