Engineering Technology Open Access Journal - Juniper Publishers
Large-scale structures and infrastructures including
buildings, bridges, dams, aircraft, rails are subject to damage and
deterioration throughout their lifecycle [1,2]. Structural Health
Monitoring (SHM) is a multi-discipline field for damage identification
and disaster mitigation of structures at an early stage in aerospace,
civil and mechanical engineering [2-5]. Generally, SHM systems involve
the implementation of sensors, smart materials, data transmission,
computational power, and post-processing techniques [6]. SHM systems
differentiate from traditional damage detection systems because it
integrates automated health assessment analytics with data sensing, from
which a more efficient structural condition valuation can be formulated
[7]. The complexity of the systems can be classified into four levels:
detection, localization, the extent of damage, and prognosis of a
remaining lifetime. In simple terms, they begin from only detecting the
presence of damage, to characterize the severity and predict the
remaining lifetime [7,8].
SHM can be categorized in many categories, for
instance, sensor parameters, sensor types, active or passive, etc.
Nevertheless, most relevantly they can be differentiated in local and
global methods [6]. Local methods usually implement Nondestructive
evaluation (NDE) methods (i.e., ultrasound, magnetic inspection,
acoustic emission eddy current, etc.) to extract imperfections features
in the vicinity of the potential damage area. They are highly sensitive
and are able to find small defects. On the other hand, global methods,
which are vibration-based, operate under the statement that damages
influence the behaviour of the whole structure in terms of time and
space. Thus, it extracts potential damage through changes in stiffness,
mass or energy [6,9]. In both approaches, sensors are imperative
elements for data extraction. Usually, contact sensors such as strain
gauges, accelerometers, fibre optics, and linear variable differential
transformers to name a few, are widely deploy for structural health
monitoring. However, they require installation, which is often
time-consuming, costly and in many cases not achievable as the
structures are hard to access. Besides, as the time pass, this sensor
also requires periodical maintenance and potential replacement producing
extra costs. Moreover, contact methods can generate extra mass loading
which is counterproductive in lightweight structures.
Alternatively, non-contact methods have the potential
to eliminate the challenges of contact-based sensors. Besides, remote
data collection can be achieved in both local and global methods
[10,11]. With the advent of technology, more tools are being applied for
contactless sensing which is overtaking traditional contact sensing.
This paper reviews the emergent approaches on non-contact methods and
tools i.e., vision-based, wireless, embedded sensors, guided waves, etc.
A literature review of non-contact methods and tools is the aim of this
paper. A detailed description of the work principles of tools and
sensors is not attempted rather the purpose of this work is to summarize
the state of the art of non-contact methods and how new technologies
are been employed in Structural Health Monitoring.
This document is presented as follows; the
methodology undertaken to select the papers reviewed is presented in
section 2. The specific classification and descriptive usage of the
contactless methods are discussed in section 3. Finally, conclusions are
presented.
In this review paper, the methodology employed was
undertaken according to the following steps. First, the literature was
collected from the SCOPUS database due to it indexes the largest number
of journals and is commonly used in engineering fields [12,13]. The
initial search was performed on the 21st of January 2021 with the
keywords “structural health monitoring” and with the aim of obtaining
exclusively the non-contact literature, the specific query was:
TITLE-ABS-KEY ("structural health monitoring" AND non-contact* OR
noncontact* OR contactless). The boolean operators (AND, OR, *) are used
to include entirely the non-contact literature and to incorporate
potential literature with different spellings of non-contact. An initial
623 results were obtained, a further limit was imposed on only English
language documents. The search was not limited to a time frame,
resulting in 608 documents from 1994 to 2021 plotted in Figure 1. Then,
the 608 articles were browsed and 92 irrelevant documents (e.g., medical
fields) were excluded and subsequently were classified according to the
main method/tool, Table 1 summarizes it.
The classification previously exposed in Table 1 is
now depicted in Figure 2 for illustration proposes. The 516 papers were
classified based on their main method or tool. Nevertheless, in many
methods exits and overlapping effect. For instance, in vision-based, SHM
approaches are vibration-based which are also shown in the
classification. Additionally, for example in wireless tools,
displacement-based methods are utilized. Thus, this classification was
done with the aim of collecting the majority and most relevant methods
and tools according to the author.
In the last decades with the rise of powerful
computers and digital cameras, vision-based and image base as a means of
structural health monitoring has gained attention [1]. Vision-based
methods have the advantage of remote sensing, and more data is acquired
as opposed to the contact methods which data is obtained in point-wise
measurements. As depicted in Table 1 the vast majority of the studies
for non-contact methods is based on vision-based i.e., camera, video
etc. A complete literature review is not attained as it should be done
solely. However, many promising approaches are presented below.
For instance, a video-based approach was reported in
Yang et al. [14]. A vibration-based approach to acquired modal data
(i.e., natural frequencies, damping radio, mode shapes) through a
digital camera was investigated. Additionally, the blind source
separation (BBS) method was applied as a post-processing technique for
unsupervised data extraction. The method was experimentally tested with a
small-scale building and a cantilever; both were stimulated through a
hummer and the data was read. Moreover, a high concordance was found
from cross-validating the data from traditional accelerometers attached
to the structure.
Ribeiro et al. [15] studied the applicability of the
video-based system for dynamic measurements. High-speed cameras were
in-field deployed for acquiring displacement data of railway bridges.
The data was positively compared with traditional LVDT measurements.
Winkler & Hendy [16] achieved displacement measurements of London’s
Docklands railway bridges using digital cameras and digital image
correlation technique.
The usage of high-speed cameras was also reported in
Baqersad, Niezrecki & Avitabile [17]. Displacement measurements of
wind turbines are obtained from a video-based approach.
Three-dimensional point tracking along with digital image correlation
(DIC) was employed for extracting the data. It was further analyzed in a
finite element model for obtaining strain measurements and contrasting
them to data acquired from traditional strain-gauges. The results showed
a high agreement between the contact and the no-contact method.
Digital image correlation (DIC) is used as a means of
health monitoring of bridges in Nonis et al. [18]. The system used a
digital camera for periodically image acquisition. The images are
processed and strain measurements are derived. It was reported that
cracks, spall, and bridge deformation were successfully identified.
Similarly, Peddle et al. [19] reported DIC technology deployment to
measure in-field displacement data of two bridges. A great correlation
was found when compared with traditional linear variable differential
transformers (LVDT). DIC implementation has been also used for
structural health monitoring of rotating structures. For instance,
Baqersad et al. [20] reported modal analysis throughout digital image
correlation (DIC) using digital cameras. Moreover, finite element
analysis and a conventional modal analysis with attached accelerometer
were performed. The three data were cross-validated and high accuracy
were determined. Recently, Khadka et al. [10] evaluated the
implementation of digital image correlation cameras on Unmanned Aerial
vehicles for vibration monitoring of rotating wind turbines. A
small-scale wind turbine was experimentally tested. The system was
capable to remotely obtain the dynamic characteristics and measure the
deformation.
Unmanned Aerial Vehicles (UAVs) are a promising
technology that allows remote sensing. They can overcome the limitations
of stationary cameras. The implementation of UVAs in structural health
monitoring has gained attention in the last decade. For instance,
Reagan, Sabato & Niezrecki [21] presented a feasibility study of the
usage of digital image correlation with UVA of bridges. The system was
capable to detect changes with an uncertainty of 10-5m. In
the same manner, Ellenberg et al. [22] reported a study of UVAs
implementation to obtain deformation measurements of bridges. Optical
metrology and an X-Box Kinect system were studied. The systems were
tested on a bridge component to attempt deformation measurements. The
findings suggest that the RGB camera could detect cracks from different
distances. Previously Abdelbarr et al. [23] had proved the accuracy of
RGB cameras for structural health monitoring. Yoon, Shin & Spencer
[24] reported structural displacement measurement using a UAV system.
The above techniques employ the usage of digital
cameras as a means of acquiring structural data to be processed.
However, this data alone does not mean anything without being processed.
Thus, computer algorithms are widely employed for identifying potential
damage [25]. Often the vibrations modes are too small to be identified
in non-contact image-based approach. For instance, Civera, Zanotti
Fragonara & Surace [26] investigated the applicability of video
magnification for damage characterization in deflection shapes. The
named, phase-based motion magnification (PBMM) algorithm, restores the
post-processed source obtaining a good signal-to-noise ratio. The method
was tested on a damaged beam finding that the modal data was
successfully obtained. Artificial intelligence was reported in work by
Rivera-Castillo et al. [27]. Displacement measurements from 2D
photogrammetry were post-processed using AI. Yuan et al. [28] reported
the implementation of machine learning as a tool for data analysis and
augmented reality for improving visual inspections.
Guided waves are a specific type of elastic waves
with high sensitivity to damage due to fast and strong propagation on
paths defined by the material boundaries of the structure [29,30], This
technique is discussed below, moreover, Lamb waves, which are a type of
guided waves, are also presented.
In Masserey & Fromme [31] high-frequency guided
waves technique was reported as a means of fatigue crack growth
monitoring. Guided ultrasonic wave, unlike bulk ultrasonic technique,
have a high sensitivity to detect small damages. An aluminium specimen
including a fastener hole with an induced fatigue crack was
experimentally tested. A wedge transducer attached to the structure were
used for guided wave generation and the response was measured
throughout noncontact laser interferometry. The presence of damage is
detected due to the changes in the guided wave signal response.
Additionally, the wave propagation and response were numerically
simulated using a three-dimensional finite difference code to validate
the experimental data. Similarly, Chan, Masserey & Fromme [32]
reported the usage of high-frequency guided waves to detect hidden
damage in aircraft structure. The exact approach previously explained
was capable to detect fatigue crack growth in the 2nd layer of a multilayer structure.
In the same manner, Rizzo, Han & Ni [33] reported
a guided ultrasonic wave approach for health monitoring of immersed
structures. This method aimed to present a non-contact in-situ
technique for underwater structures i.e., ships, submarines, and
underwater pipes. The proposed system includes the usage of a Q-switched
Nd:YAG pulsed laser for guided wave generation and two transducers for
data acquisition. An aluminium plate with two induced damage i.e., notch
and a drilled circle was used for the experiments. The plate was
submerged into a water pool along with the two non-contact transducers
and through the usage of optical lenses (mirror and focusing), guided
wave generation was achieved in a non-contact manner. Although a high
sensitivity and changes in the response of GW, due to the damage,
controversial results were reported. However, in a subsequent work
presented by Pistone, Li & Rizzo [34] the guided wave propagation in
immersed media was numerically simulated with Finite Element Analysis
and the same experiment previously explained was carried out. The
findings suggest that this technique can detect cracks and holes in a
non-contact approach in immersed media.
Guided wave propagations offer a good alternative to
characterize damage in structures. Many applications as those mentioned
above have been reported for metallic materials. However, in composite
materials, there are not many studies reported, mainly because the
behaviour of the guided waves in composite structures is a complex
problem [35]. A deeper understanding led to work by Aizawa et al. [36]
where the scattering behaviour of guided waves in composite materials
was studied. First, a three-dimensional (3D) finite element analysis was
generated to understand the interaction of the guided wave in composite
plates with delamination damage. The influence of the delamination size
was a systematic study in the FE simulations. Then two CRFP specimens,
with induced impact damage, were experimentally tested. An attached
piezoelectric transducer and a non-contact laser interferometer for
generation and measurement of the waves was employed. High accordance
was found in both data, moreover, it was concluded that the delamination
geometry (i.e., size and depth) has a strong influence on guided wave
response.
Similarly, implementation of guided waves for health
monitoring in composite materials was reported by Sherafat et al. [37]. A
composite skin-stringer joint structure composed of three CFRP plates
bonded together was tested. The system, in this case, utilizes two
piezoceramic transducer and a non-contact 3-D laser Doppler vibrometer
(LDV) for plane guided waves generation and measurement respectively.
Two bonding conditions, bond and unboned (damage and undamaged) were
investigated with the A0 and S0 mode signals. The damage
characterization included changes in reflection, transmission in the
guided waves as a function of frequency. In the A0 mode not clear
changes in the parameters were founded, however, clear changes in S0
parameters were confirmed in the experimental tests.
Lamb waves
Lamb waves can predictably propagate in plate-like
structures, thus they are widely employed for such structures [38]. In
the study presented by Mallet et al. [39] lamb waves propagation for
means of damage detection in structures is investigated. A non-contact
approach is attained by laser vibrometer measurements of the guided
waves. This system is tested for damage detection in aluminium plates
with two different severities of damage. The first plate had a
rectangular slot in the centre and the second had a hole in the centre
to simulate artificial damages in metallic structures. The results were
further validated with numerical simulations and experimental tests with
a piezoceramic transducer. Similarly, Leong et al. [40], presented the
same approach to characterize cracks in metallic structures with the use
of lamb guided waves and a commercial laser vibrometer. An aluminium
plate previously drilled in the centre, simulating fatigue crack, was
tested. Overall, both methods showed rapid damage detection and
characterization.
The usage of lamb waves was also reported in Lee,
Kang & Park [41] which guided waves to localize and quantified
damage was investigated. A non-contact scanning laser source system was
implemented to achieve lamb wave propagation on plates structures. The
structural response was measured throughout an embedded piezoelectric
sensor. 3-D flaw images were constructed to visualize the wave
propagation. Fatigue Cracks were successfully identified due to the
scattering of lamb waves affected by the damage.
The usage of Lamb waves has not been only used in
metallic structures. They have been exploited for composite materials as
the lamb wave generation can propagate long distance and their
velocities are sensitive to the in-plane stiffness of the laminates,
however, the implementation of the methods is difficult [42].
A need to understand the propagation of Lamb Waves
led to work by Voß et al. [43]where numerical modelling of non-contact
testing was developed to study the interaction between Lamb Waves and
composite materials. The study developed a numerical simulation model of
lamb waves propagation in multi-layer CFRP laminates throughout Finite
Elements Analysis. Additionally, several experimental validations were
carried out with a CFRP specimen in which a piezo transducer was
embedded to generate the guided waves. The cross-validation contributes
to a better understanding of the interaction.
Similarly, in Gao et al. [44] laser-induced lamb
waves generation was implemented as the main method for damage detection
in composite laminates. The method interprets the responses affected by
the damage throughout an algorithm called sparse imaging which is based
on the assumption that few damage locations are presented on the
structure. The experimental section was carried out on CFRP laminate
with an attached magnet on both sides to simulate delamination. The
system characterized the damage with high accuracy.
A different approach is presented in Wang et al. [45]
where lamb waves were applied for damage detection in pipelines. The
propagation of helical waves was previously modelled in a finite element
analysis to validate the performance of the method. Helical waves,
which can generate better results, were generated throughout a
non-contact electromagnetic acoustic transducer (EMAT). The novel design
was experimental tested on a pipeline where a pitch-catch system was
employed to validate the design. Both experimental and simulation showed
potential applications for Helical waves, however further study should
be conducted to register damage in structures.
As mentioned before, vibration-based techniques are
global approaches to detect potential damage. Moreover, they are the
most widely applied method [46]. In these sections, only radar-based
methods are discussed.
In radar systems, a known frequency radio signal is
transmitted and subsequently reflected onto the object and captured by
the system again for data processing [47]. Radar technology has been
employed in many remote sensing applications in SHM [48]. For instance,
in Ochieng, Hancock & Roberts [49] the state of the art of
ground-based radar applications for in-field monitoring of wind turbines
was presented. Moreover, in-field experiments with ground-based radar
to measure blade tip deflection was employed. The signals were measured
in a time-domain approach to obtain changes in the blade deflection.
Radar sensing has many advantages, for instance, it can work up to a few
kilometres or propagate through non-conducting materials.
The high cost of damage presented in wind turbines
(develop more) [50] has also led to work by Nikoubin et al. [51] where a
low-cost portable radar sensor was originally utilized to acquired
Doppler signatures from which blade’s physical features can be
determined. This system was employed on in-field experiments where
Doppler signatures with different angles and locations were obtained and
compared. Additionally, Munoz-Ferreras et al. [52] reported the same
approach with two designed radar prototypes that operate at the C and K
bands for in-field acquisition experiments. Moreover, in Munoz-Ferreras
et al. [53] simulations of the exact experimental set-up were performed.
The simulated results validated the preliminary experimental data,
concluding that Doppler information has a great potential for real-time
monitoring applications of wind turbines.
For instance, in Moll et al. [54] a non-contact
mechanical vibration sensing was reported. The proposed method employs a
millimetre-wave doppler radar sensor to measure mechanical vibration in
non-conducting materials. MM-wave radiation is capable to penetrate
barriers such as foams, ceramics, plastics etc. The time-series
measurement is used to assess structural defects. Consequently, the
system was tested in a laboratory setup to measure vibration data from a
structure behind an 80mm thick polystyrene foam. Good reliability and
repeatability were found when a 20mm crack was detected in various
experiments.
In Rice et al. [55] another radar technology for
vibration-based monitoring was reported. The investigation was conducted
with a low-cost wireless radar sensor to obtain dynamic structural
response data. The sensor uses dual measurement modes (i.e., periodic
and non-periodic) the arctangent demodulated interferometry and the
nonlinear vibrometer modes were utilized to generate sub-millimetre
accuracy. The system was tested in three laboratories set-ups to
evaluate the accuracy. Although experimental in-field data was not
acquired, this low-cost sensor presented high accuracy and feasibility
in the measurements for both modes and future applications in SHM.
Bennett & Rutz [56] presented another radar
technology for bridges health assessment. The named Image by
Interferometric Survey (IBIS) technology is capable to monitor
deflections with a high precision i.e., 1/100mm, making it a great
option for non-contact measurement applications. The proposed system was
experimentally tested on laboratory and in-field set-up. The former was
conducted to measure the accuracy of the method with cables and the
later was performed in a cable-stayed bridge. Additionally, a contact
accelerometer was utilized to cross-validate the measurements. This
interferometric radar was capable to monitor structural deflections and
vibrations.
Ultrasound is a Nondestructive test method, however,
is widely employed in structural health monitoring in local approaches
[57]. Early-stage damage sometimes is difficult to detect as these
fatigues produce nonlinear characteristics within the structure. A need
to detect early-stage damage led to work by Liu et al. [58], which
investigated nonlinear wave modulation spectroscopy (NWMS) to detect
early fatigue cracks by exploiting nonlinear ultrasonic signatures. A
fully non-contact technique is proposed by the implementation of a pulse
laser beam for ultrasonic wave generation, and a laser Doppler
vibrometer for ultrasonic wave detection. This method, unlike usual
nonlinear techniques, exploits a feature called sideband peak count
(SPC) as a means to identify potential damage. The peak variations
showed in SPC determines the presence of the fatigue cracks. The system
was tested with three aluminium plates and aircraft fitting-lugs.
Resulting in a robust technique to detect material defects in metallic
materials. (The finding suggest a very robust technique)
The same system, pulse laser and laser vibrometer
were reported in An, Kwon & Sohn [59]. This fully non-contact
ultrasonic wavefield imaging ultrasonic system is used to detect surface
cracks in plate-like structures with special complexities.
Additionally, a frequency-wavenumber (f-k) algorithm is implemented to
extract crack ultrasonic features. The f-k algorithm enables to extract
only cracks features without the necessity of baseline data from the
undamaged system. The system was numerically and experimentally tested
in two aluminium specimens, asymmetrically and vertical stiffened
plates. (This image demonstrated a robust technique, In the same manner,
imaging was reported in).
In Flynn & Jarmer [60] laser doppler vibrometry
(LDV) was implemented to measure and visualize ultrasonic signature
responses to characterize hidden defects in plate-like structures. The
single-tone ultrasonic waves are generated throughout an attached
piezoelectric transductor in the structure. The working principle of the
method is that single-tone waves are steady thus extracting
time-invariant properties of the wave that are indicative of damage is
faster. Furthermore, the method exploits the wavenumber property of the
waves from which damage can be detected. This approach was tested with
an aluminium plate with three corrosion spots and two composite
specimens with a high-speed projectile impact and two slow-speed impact
damages respectively. The data acquired processed with the attributes of
the waves clearly showed the spots of the damages in the three
specimens.
Ultrasound system was also reported in Lee et al.
[61], in which mechanical impedance was studied for monitoring pipelines
in nuclear power plants. Pulse laser beam and laser Doppler vibrometer
is also implemented to enable health monitoring of pipelines under high
temperatures. In this study, a statistics tool named outlier analysis,
which enables autonomous damage detection, is implemented for data
processing. The chemical corrosion in an elbow pipeline was successfully
detected in a lab-scale experiment.
Acoustic emission is also an NDE technique, which is
commonly known as the most simples method to deploy yet difficult to
implement [62]. The necessity to obtain vibration measurements lead to
work by Jiang, Zhang & Maxwell [63]. The feasibility to obtain modal
parameters measurements through infrasound measurements was
investigated. A cascading pre-processing technique was employed for
identifying low-frequency modal properties. The method was tested with a
small-scale structure and a microphone. Also, in Lobo-Aguilar et al.
[11] infrasound approach was reported. A single microphone was used as a
means of a noncontact method to capture dynamic properties on bridge
structures. The method was validated with the data obtained from
traditional accelerometer sensor. Besides, both methods deployed machine
learning-based extraction technique to increase the signal-to-noise
ratio. These techniques successfully demonstrated the applicability of
infrasound in SHM.
In a study by Arora, Wijnant & De Boer [64]
damage detection and localization were accomplished using an
acoustic-based method. The proposed technique combines acoustic
emissions and vibration signatures to acquire vibro-acoustic responses
as a means of damage characterization. In experimental studies, an
aluminium with fixed-fixed boundary conditions was studied. The system
consists of a loudspeaker which emits an acoustic field and a microphone
to measure the pressure response of the plate. First, the undamaged
eigenvalue and eigenvector data was obtained from the acoustic pressure
response and subsequently a crack was introduced and the eigendata was
obtained. The changes in the natural frequencies are used to determine
damage. Moreover, the flexibility matrices, derived from eight data,
determine the exact location of the damage (non-contact method).
Similarly, damage detection with acoustic emission is
presented in Poozesh et al. [65]. Sound radiations are used as the main
method to characterize and localize damage in wind turbine blades. The
working principle is that sound radiation characteristics variates when
structural damage is present i.e., cracks, delamination, holes, etc. The
experiments carried out in the study enclosed an acoustic microphone
array with 62 microphones and an acoustic camera to characterize the
radiation. The data acquired was further analyzed with a CLEAN
algorithm, which unlike traditional beamforming, produces higher spatial
resolution. This non-contact method effectively detected and located
holes an cracks within the structure.
In another study by Qiu & Lau [66] a hybrid
acoustic-laser based method is presented to characterize damage in FRP
concrete specimen. The method encloses a loudspeaker, laser,
photoreceiver, laser and a computer. Experimentally a CFRP-retrofitted
concrete specimen and an FRP-reinforced concrete with an artificial
defect were constructed. This technique evaluates damage throughout the
following process: acoustic waves, emitted by the loudspeaker, excite
the surface specimen. The laser is used to characterize the vibration
and the photoreceiver captures the laser reflected response. The
measurement response, through Fourier transform, a frequency domain
spectrum of damaged and undamaged states is acquired. Comparison between
both data was effectively used to indicate the presence of damage.
Magnetic methods are widely used in many ways to
evaluate structures, many magnetic properties of the materials and
transducer are exploited to acquire reliable data [67]. In Christopoulos
et al. [68] an inductive sensing method to measure strain in composite
materials was presented. Magnetostrictive wires were embedded in
carbon/epoxy specimens to act as structural and sensor elements. These
specimens were tested under tensile experiments to study inductive
variations and their relation to the strain. Four types of non-contact
transducer/sensor (i.e., coaxial coils, c-shaped inductive, circular
coil Hall, and c-shaped inductive Hall.) were constructed to acquire
experimental strain measurements. The experimental data showed a minimum
detectable strain value of 0.25mStrain with a high resolution of
0.1mStrain. (High sensitivity embedded small size and does not increase
the weight in the structure)
A similar approach was presented in Coatney et al.
[69]. Where nano magnetostrictive particles were embedded in a composite
structure for nondestructive damage detection. Terfenol-D
magnetostrictive powder was embedded in a CFRP sample as a means of
damage characterization. Experimentally the specimen was tested under
tensile stress and with the usage of a non-contact magnetic field
sensor, fluctuations in magnetization flux density were captured. The
load and fatigue cycles produce clearly variations in the magnetic field
due to Terfenol-D particles, which is an indicator of early-stage
damage detection (The specimen reduced its strength with the inclusion).
Similarly, in Zagrai & Akan [70]
magneto-mechanical impedance (MMI) method was reported as a means to
obtain structural dynamic responses and diagnosis in metallic
structures. The approach compromises the usage of a non-contact
magneto-elastic active sensor (MEAS), with two different configurations,
to emit electromagnetic and elastic waves. First, an aluminium beam
with free-free boundary conditions was tested to identify a structural
dynamic response. The MEAS sensors were placed 1mm away from the beam,
and through and impedance analyzer the impedance variations were
obtained and the dynamic responses characterized through the software
LabVIEW. Moreover, the system was tested on three different structures
evaluation scenarios i.e., loose bolts, adhesive deterioration, and
cracks in honeycomb panels. These scenarios change the mechanical
properties of the structure and therefore the inductance peaks in the
dynamic response can be exploited for damage evaluation.
In another study presented by Chen et al. [71]
magnetic field interference measurements are investigated as a means of
monitoring scour in bridges. The method incorporates smart rock usage
containing strong magnets in their structure. Although the study
primarily presents the feasibility of the smart rock’s magnetic field
measurements through a magnetometer, the potential field application is
revealed. The smart rocks would be placed underneath the sensitive zones
of the bridge piers, thus, when a scour events occurs, the wholes,
started by the flood, increase and eventually the smart rocks will
automatically roll down to the bottom of the whole. Thus, damage
detection would be characterized by tracking the movement of smart rocks
through a magnetic field with, for instance, high precision global
positioning system.
In the work presented by Giri & Kharkovsky [72] a
novel approach to detect surface cracks in concrete was presented. The
non-contact system consists of a laser displacement sensor (LSD), a
scanner and a control centre. The LSD, mounted on the scanner, performs
raster scanning over concrete specimens. Two concrete specimens were
used to test the system i.e., cylindrical and concrete slab. Damage
characterization is achieved through the triangulation principle onto
the specimen surface. The effects of the specimen's geometry were
further analyzed with different incident angles. The readings
demonstrated this method is a robust technique to detect cracks in
concrete and other nonconducting materials.
Laser displacement sensor (LSD) was equally
implemented as means of damage detection in Lee & Kim [73]. The
non-contact system encloses a single LSD installed on wind towers to
characterize damage in the rotating blades. A multi-sensing approached
to characterize blade deflection due to bolt loosening, nacelle tilting
and, mass loss-damage was proposed. Moreover, the effects of the
temperature on the data monitored were analyzed. Overall, the results
showed feasibility to characterize such damages. Besides, the system
showed a relative easy damage evaluation from the field experiments.
Rodrigues, Félix & Figueiras [74] developed a
hybrid system to measure bridge deflections. The non-contact system
encloses a hydrostatic liquid levelling with a fibre optic engaged for
displacement variations measurements. The fibre-optic-based transducers
were installed along the bridge in crucial locations to obtain vertical
displacements through liquid’s level changes; these changes are measured
throughout a fibre optic sensor placed in the transducer system.
Laboratory tests were executed to study the prototype performance.
Additionally, field tests in the Leziria bridge were performed obtaining
a high sensitivity with an error of less than 0.2%. (Robust system,
capable to read in environment conditions )
Similarly, Li et al. [75] proposed a multi-target
method for 3-D non-contact displacement measurements. The system
encompasses a frequency modulation continuous wave (FMCW) radar sensor.
Mathematical and analytical modelling was developed to further analyzed
the working principle of the technique. Moreover, the radar prototype
system was constructed with a data acquisition card (DAQ). Outdoors
experiments were conducted to test the feasibility of the new system.
Although no structural damage was investigated with the system, it
showed high accuracy and potential use in structural heal monitoring.
In another recent study, Pang, Chen, Yu, et al. [76] investigated the use of laser speckle optical sensor (LSOS) for in-situ
strain measurements. This fully non-contact method replaces traditional
contact methods i.e. resistive gauges, fibre optic, and extensometers.
The LSOS was modified with a field-of-view subsystem to extend sensor
gauge length. The method was validated through field test for strain
monitoring of rail tracks. Data comparison between strain gauge and
laser speckle confirms the high accuracy and the robustness of the
proposed method, moreover, contact sensors can be replaced for LSOS
sensors where mirror surfaces or transparency materials are not
utilized. (Finally, the outcomes suggest a strong sensor capable to be
used for strain-based and other applications).
In the work by Yang & Oyadiji [77] a fibre optic
sensor was developed for structural health monitoring applications. The
sensor was modified with multiple layers of transmitters for large
amplitude vibration measurements. Better read range and sensitivity was
achieved with two-layers of transmitters. This non-contact sensor was
tested to measure dynamic displacement in small scale cantilevers. The
experiment validated the information with a contact accelerometer and
non-contact laser sensor. The data suggest an extremely high concordance
with conventional techniques. Moreover, the fibre optic sensor data is
less noisy and free from electromagnetic interference.
In the work presented by García et al. [78] different
configurations of the optical sensor were tested to measure the tip
clearance (TC) in turbines. Four configurations of optical fibres were
built and tested to obtain at least 30um of precision. Three
configurations were tested further in the turbine in a wind tunnel,
resulting in the third and fourth configuration have the best precision.
Although the third configuration showed the best precision, 25um, the
maximum working temperature is 60C limiting its applicability. Finally,
the fourth configuration, capable of working at 350C, showed a precision
of 28um making it suitable for tip clearance and vibration frequency
measurements in structural health monitoring applications.
Similarly, Dhawan, Dikshit & Kawade [79]
developed a two-dimensional fibre optic position sensor. The method is
capable to produce vibrations measurements in a 2-D plane for structural
health monitoring applications. The system includes a CCD camera where
the data measurements are collected and further analyzed. The working
principle is that the axial and the lateral changes are measured through
the change in peak intensity and the centroid of image spot at CCD
camera respectively. Although reliable measurements were acquired, this
non-contact method should be further tested in field application.
Infrared thermography or thermal imaging is
considered a non-destructive examination method which allows observing
the heat patterns on an object surface [80]. In a study by Mulaveesala
et al. [81] defects in reinforcement concrete structures (RCS) are
characterized throughout Thermal Nondestructive Testing (TNDT). A
non-contact thermal wave imaging method was implemented to expose
corrosion in reinforcement bars (rebar) within the concrete. This active
technique implemented a frequency modulated thermal wave imaging
(FMTWI) method to control two halogens lamps to generate thermal waves,
and an IR camera to capture the temperature distribution in the sample.
Phase based and correlation-based post-processing approaches were chosen
to reveal subsurface features i.e., corrosion. Both processing
approaches clearly indicate the amount of corrosion.
In Hwang, An & Sohn [82] continuous laser
thermography is proposed as a newly damage visualization method of wind
turbine blades. The fully non-contact thermography is capable of
detecting surface and subsurface damage under rotating condition. The in-situ
apparatus includes a line laser beam for thermal waves generation and
an infrared (IR) camera for capturing the thermal responses. The working
principle is that the obtained images from the IR camera are
post-processed with a damage imaging algorithm. The statistical pattern
recognition algorithm recognizes internal delamination throughout,
first, a collection of thermal responses for each blade are built, then
system continuously produces thermal images for comparison, once an
abnormality is detected, the algorithm removes the noises and clearly
shows the exact defect location.
Better post-processing techniques led to work by Pena
& Rapun [83] which a post-processing technique was exploited for
detecting defects and inclusions in two-dimensional plates. The study
combined active infrared thermography and topological derivatives as a
post-processing tool for damage detection in aluminium plates. The
method is capable to process time-harmonic thermographs capable to
detect interior defect with no prior knowledge about the size or shape
of the defects. Moreover, the mathematical tool is extremely robust
concerning noise.
Higuera et al. [84] investigated a steady active
thermographic method which incorporates a post-processing algorithm
capable of detecting defects and inclusions from synthetic thermographs.
The mathematical tool, topological derivatives, as opposed to
traditional algorithm approaches, does not reduce the physical
information obtained from thermal imaging, generating a robust damage
detection method capable of identifying and locating internal flaws of
diverse sizes and shapes. The method is also capable to process noisy
thermographs.
A bio-inspired wireless sensor is reported in Tata et
al. [85]. The proposed technology encloses an antenna for strain
measurements. Printed on a flexible substrate, the patch antenna
functions as both, transducer and as the broadcasting device. Although
essentially the sensor is contact based i.e., embedded, the data
acquisition procedure is a wireless non-contact method. Furthermore, the
backscattering principle was utilized to interrogate the strain data
from the antenna attached to a cantilever exposed to mechanical loads.
The electromagnetic resonant cavity, generated by the patch antenna,
radiates specific known resonance frequencies which are distorted when
elongation is present. Moreover, the reflection coefficient (S11)
presents changes in its frequency for different strain percentages which
is the principal method to evaluate the state of the structure.
Similarly, wireless strain-based technology was
presented in Zhang & Bai [86]. A passive RFID tag was embedded in
truss elements to assess the overall structural condition. The working
principle was that a brittle bar is connected to the tag
short-circuiting the chip and changing the impedance. This brittle bar
is designed to break out when a strain threshold previously calculated
is exceeded. Once the pre-set brittle bar is broken the RFID tag starts
data broadcasting throughout a non-contact RFID reader. Additionally,
building information modelling (BIM) is introduced to the method in
order to identify and highlight the failing truss element (yielding and
bulking added to the method to bring a more graphical way to help
decision-makers to identify the truss element which is under strain.
identifying the truss element).
A study by Abedin & Mehrabi [87] presented a
novel approach to investigate the accuracy of wireless sensors in
structural condition assessment in girder bridges. Moreover,
self-powered wireless sensor suitability was investigated for SHM
applications. Energy harvesting through solar and thermal gradients are
broadly employed. However, vibration-based energy, generated from the
bridge under live loads, was examined to discover whether they create
enough energy to power the sensors. Additionally, stress/strain
vibrations were analyzed as a means for the damage detection method.
Thus, laser vibrometer was utilized to assess wireless sensor accuracy
and finite element analysis was realized to validate the field data. The
findings suggest that first, non-contact laser vibrometer is an
effective and economical method. And that the vibration generated under
normal loads is enough to power the wireless sensors.
In Zahedi, Yao & Huang [88] a fully wireless
passive technology for structural health monitoring is demonstrated. The
ultrasound-based system includes a wireless interrogator, wireless
actuator and an embedded sensor mounted on the structure. The system
exploits the amplitude modulation and demodulation to produce a passive
pitch-catch system. The ultrasound signal is generated wirelessly
throughout the interrogator. Then, the signal is received by the
actuator which transforms the signal a generates the ultrasound. The
results demonstrated a 0.5m reading range.
A studied by Amies et al. [89] incorporated radio
frequency (RF) technology to gauge floor displacements in civil
structures after earthquakes. The novel method encloses several RF
transceivers embedded to fixed locations nodes in the structure.
Frequency-modulated continuous wave (FMCW) radar through a non-line of
sight (NLOS) technique emits and reflects signals which are computer
analyzed to measure the transceivers displacement. Displacement data is
used to calculate interstorey drift ratios (IDRs) which are used to
study the stress and hence the condition of the structure.
In Iervolino & Meo [90] another wireless
approached is presented to detect barely visible impact damage (BVID),
delamination and cracks. A spiral passive electromagnetic sensor (SPES)
is investigated for damage characterization in composite materials. The
2-D sensor is specially designed and fabricated to resonate at a
specific frequency. Experimentally, the sensor was investigated on two
specimens, conductive (CFRP) and non-conductive (GFRP) composite
materials. Different samples were fabricated and their resonant
frequency obtained. Two types of damage (i.e., drilled holes and
impacts) were introduced to the samples. Through the usage of a spectrum
analyzer, resonant frequencies of the damage samples were obtained and
compared. The clear variation of the frequency showed in the analyzer
makes the approach feasible and reliable.
Overall, microwave techniques have been tested in
nondestructive evaluation. However, it has been mostly employed in
cemented based and metallic based. Structural health monitoring in many
cases is challenging as the structures often perform in harsh
environments and conditions. Moreover, the SHM method must be capable to
detect minimal structural changes before failure occurs [91]. For
instance, in the aero industry, gas turbine components operate in very
high temperatures and health monitoring is extremely essential. This
necessity has led to the work by the National Aeronautics and Space
Administration (NASA) reported in [91]. NASA developed two new
non-contact microwave sensing technology for rotating blades in gas
turbine engines. Microwave based blade vibration sensor was utilized to
perform frequencies and vibration measurements. They were compared with
previous data gathered from capacitive sensors, showing high accuracy
and reliable readings. (Both technologies have the potential to
withstand harsh environments and produce highly accurate measurements.
Microwave’s vibration sensing it’s a worthy technology as it can stay at
high temperatures. The technology is under evaluation, but they have
developed this technology)
Similarly, Li et al. [92] presented a microwave
imaging method to detect delamination of wind turbine composite blades.
Delamination is the most critical failure mode for composite materials
and especially in fibre-reinforced composites [93]. An open-ended
waveguided technique was implemented as the method for obtaining
microwave imaging of T-joints in wind turbines. Glass-fibre reinforced
polymer (GFRP), widely employed for wind turbine components, was
utilized for delamination test. A highly accurate delamination
characterization i.e., existence and extent was achieved during the
experiments. This new approach could be further taken for health
assessment un other parts of the wind turbines.
Nadakuduti, Chen & Zoughi [94] presented a
microwave method for crack detection in cement-based materials. A
non-contact near field microwave method is employed to characterized
surface-breaking cracks, its width and depth. The project presented two
studies of surface-breaking cracks for mortar and hardened cement
samples. The successful crack detection method was accomplished using an
open-ended rectangular waveguided probe. Cracks characterization i.e.
width and depth were effectively reported throughout the measurements.
This method could be extremely useful as depth characterization and
damage evaluation can be easily evaluated in cement structures for
instance, after seismic events.
Gentile & Cabboi [95] evaluated the use of
microwave remote sensing for vibration response measurements on
cable-stayed bridges. This radar technology utilized microwave
interferometers to performs dynamic and static measurements under
operational conditions. Contact accelerometers were employed to validate
the data acquired from the non-contact technique. Two cable-stayed
bridges were analyzed during the tests; periodic measurements on the
cables to obtain local natural frequencies and damping ratios is the
technique to evaluate deflections and structure condition. Based on the
comparison between both data and its high accuracy is suggested that
microwave remote sensing is a quite consistent technique for condition
assessment on cable-stayed bridges in SHM applications.
Magnetic Induction Tomography is an ideal technique
to be applied for contactless applications [96]. A study by Renner,
Fischer & Marschner [97] presented a new tomography imaging approach
for in-situ and non-contact applications. Magnetic Induction
Tomography (MIT) is proposed to evaluate the condition of the
fibre-reinforced composite. This contactless technology is capable to
produce 2D or 3D inhomogeneity images from where damage can be localized
and detected. MIT differs from conventional techniques as it can
produce 3D spatial interior images. A further study by Renner, Marschner
& Fischer [98] was conducted to evaluate MIT for conductive
fibre-reinforced composites. This method is proposed as an autonomous
tool in SHM of conductive composites (too much data collected).
Another study by Park et al. [99] similarly employed
additional algorithms to improve non-contact tomography methods.
Difference Hilbert Back Projection (DHB) algorithm was implemented to
improve the tomography imaging accuracy of plate structures
imperfections. Pulse laser and air-coupled transducers were used as the
main non-contact detection method. The automatic detection system
includes a robotic arm with a hybrid technology containing the laser and
the air transducer for image acquisition. Overall, the technique was
found successfully to predict faults in large plate structures. However,
it has clearly stated that there is space for improvements in image
quality and DHB algorithm.
Gupta et al. [100] developed and validated an
electrical capacitance tomography (ECT) method to characterize
subsurface composite damage. Planar array electrodes configuration,
unlike conventional circular arrays, was implemented to obtain a
volumetric distribution of the specimens. The portable method was tested
in two different scenarios. First 3-D PLA specimens with internal voids
of different configuration and CFRP specimens after an induced hammer
impact were investigated. Throughout mapping change in electrical
permittivity, the method was capable of identifying the
delamination-like and delamination damage in both procedures. Although
the image quality resolution is not desirable the delamination on the
subsurface was identified. Moreover, the data were further compared with
a C-scan finding high accuracy.
Strain based methods are widely used to assess the
condition of the structures as they produce key data from the
structures. Many sensors have been developed throughout the years. This
sensor has some drawback as they must be attached to the structure and
have to be maintenance etc. Some structures are hard to access for such
installations. Thus, other technologies have been used to overcome these
drawbacks.
In a work, by Jo et al. [101] strain measurements
were accomplished using light detection and ranging (LiDAR) as a
non-contact method. This 3D laser technology was used to obtain 3D shape
information data for a steel plate. The data were evaluated using
regression analysis and the strain was calculated using a finite element
analysis (FEA) simulation. Also, the obtained strain measurements were
compared to measurements obtained with contact strain gauges sensors.
The findings suggest that data from LiDAR were quite similar to the
strain gauges sensors. Thus, this non-contact technique can be an
effective tool in structural health monitoring applications.
A similar approach was described in Pang et al. [102]
where a laser speckle imaging system (LSIS) was used to obtain strain
measurements in fastener holes. Additional digital image correlation
(DIC) algorithms were used to optimize the performance of LSIS
technology. Uniaxial tensile stress was performed on an aluminium alloy
specimen as it is widely used in fuselage structures. In addition, an
extensometer was utilized in the test to validate the LSIS performance.
The measurements showed high consistency with previous FEA simulation.
The data obtained from both approaches were extremely correlated. (Thus,
this approach seems quite practical for structural health monitoring
applications).
In Christopoulos, Hristoforou & Tsamasphyros
[103]strain-based magnetic sensing capabilities were investigated. An
epoxy polymer matrix dispersed with ferromagnetic particles (iron) was
used to study the sensitivity of magnetic properties exposed to tensile
stress. The composite material was exposed to an external mechanical
load. The obtained elongation produced changes in the sample geometry
and its magnetic properties. The alteration in the magnetic properties
is observed in variations in the magnetic resistance (reluctance). The
non-contact method used a Hall sensor to measure reluctance
fluctuations. The proposed method found a strong relationship between
strain and reluctance which can be further exploited in SHM applications
where iron materials are employed.
3.14. Spectroscopy
Withey et al. [104] investigated non-contact strain
measurements using photoluminescence spectroscopy. A polymeric coating
embedded with single-walled carbon nanotubes (SWCNTs) was applied to a
substrate. Strain applied to the substrate is transmitted to the coating
producing shifts in SWCNT fluorescent spectra due to electronic
changes. These fluctuations are measure optically with a non-contact
spectrometer. The fluorescence peaks are large enough to measure strain
in structural health monitoring applications using SWCNTs as nanoscale
sensors. The proposed method, strain painting, although under complex
working principles, its deployment is quite simple and versatile.
(Complexity discussed of the principle, the laboratory should see in
real word but suitable for practical applications however see the 87 for
steel, also many instruments required).
In a study by Hanhan et al. [105] portable spectroscopy is proposed for in-situ
and non-contact stress detection. This technique explores the
piezospectroscopic effect of certain photo-luminescent materials. For
instance, alumina-containing materials under laser excitation, emit
spectral peaks. These spectral emissions are sensitive to stress and
strain. The photo-luminescent mapping and analysis instrumentation was
designed to be a portable piezospectroscopic system (PPS). They tested
an alumina nanocomposite coating sample with the PPS, the measurements
were compared against a FEM simulation data. The experiment showed
potential applications for non-contact structural health monitoring.
A deeper damage characterization could be achieved
with the combination of several methods or sensors. Combination of
non-contact methods or combining non-contact and contact techniques can
greatly enhance the reliability and accuracy of the procedure. However,
this approach is only justifiable if the benefits are correctly balanced
with additional time, cost and complexity generated [67].
Khan et al. [106] presented a hybrid non-contact and
contact method for damage assessment of concrete masonry walls subjected
to cycling loads. The multi-sensing approach combined infrared
thermography (IRT), acoustic emission (AE) and ultrasonic method (UT).
The Infrared thermography non-contact method was capable to detect the
presence of moisture in the porous wall which appears in the form of
temperature fluctuation on the surface. AE was proven to be a suitable
method to monitor damage progression when active ultrasonic methods
confirm the existence of cracks. This efficient method utilized
cross-validation within the above methods to validate damage
progression.
A work by Vakhguelt, Kapayeva & Bergander [107]
incorporated a mixture of non-contact and contact ultrasonic methods for
condition assessment for boiler tubes. Overheating and wall thinning
are two major issues in boiler tubes failures. EMAT (Electro-Magnetic
Acoustic Transducer) was used as a non-contact ultrasonic technique to
evaluate the wall thickness. Standard ultrasonic measurements were
obtained to compare the reliability of the non-contact measurements. A
further correlation between wall thickness and overheating was attempted
for the overall method (Economic advantages see in the paper).
In a study by Alamdari et al. [108] three different
non-contact sensing techniques were examined to monitor the integrity of
a cable-stayed bridge. Namely laser scanning, robotic total station and
digital levelling were deployed to acquire displacement profiles at
four discrete points. Although the data gathered from the three sensor
techniques is very consistent and sufficient to identify the changes in
the structure, damage localization and characterization are only
possible with multiple measurements points. Nevertheless, this
multi-sensing approach verified that changes in the displacement
profiles between undamaged and damaged state are a reliable damage
detection method (much sensors, need more measurement points).
Lai et al. [109] presented a combination of
full-field infrared thermography (IRT) and laser shearography. Both
non-contact methods were used to detect flaws between carbon
fibre-reinforced polymer (CFRP) and concrete materials. CFRP is used to
rehabilitate concrete structures. Imperfections in such materials
interfaces can be critical for the overall bond strength. Thus, the IRT
technique was implemented to detect surface flaws due to a distinct rate
of heat diffusion and shearography method to measure the mechanical
response of surface displacement through the application of thermal
stresses. The experiments were carried out on 6 CFRP-concrete samples
with 17 different flaws. Field data were compared after opening the
samples resulting in, infrared thermography achieving 93% of accuracy
whereas shearography 90.5%, however, both techniques tend to
underestimate and overestimated the measurements respectively. (However,
both methods could be combined and further algorithm could be used to
achieve better accuracy for structural health monitoring)
In the study presented by Chen et al. [110] a hybrid
method is proposed as a means to characterize structural defects. The
combined method merges Finite Element Analysis (FEA) simulations and
optical shearography. Finite Element simulations are used to simulate
different loading scenarios to obtain deformation data and a prediction
algorithm to determine shearographic fringes patterns. Experimentally an
acrylic sample is exposed to the same loading scenarios, and real-time
patterns are obtained and compared with the predicted fringes patterns
thus the abnormalities are detected. Besides, the shearographic patterns
are also projected to the sample to improve the method and make it more
obvious.
This document reviewed the most relevant methods and
tools that exhibit many different contactless methods taken for
structural health monitoring in the last 25 years. The most important
technique was discussed including vision-based, radar, laser, embedded,
wireless, hybrid sensing among others. There is a clear trend in
utilizing vision-based tools like the computer become more powerful and
algorithms (i.e., artificial intelligence, deep learning, neural
network) are capable to accurately post-process the data. Global methods
are undoubtedly the more applied method used with different types of
sensors and tools deployed. Mainly because the vicinity of the potential
damage is not needed beforehand. However, small-scale damage might not
be detected in these vibration-based approaches. Thus, local methods
(e.g., strain-based,) are preferred when high sensitivity is essential.
For these particular cases, the wireless embedded sensor seems to be the
most feasible techniques. Additionally, hybrid sensing has the
potential to detect damage in a more accurate approach, however, its
implementation needs to be considered as an extra cost and massive data
would be generated. Also, there is still room for improvement in all
contactless approaches. To conclude non-contact methods are being widely
employed to characterize many defects (e.g. cracks, delamination,
spalling) in metallic, concrete and composite structures, nevertheless,
the chosen technique should be carefully chosen as early damage
detection is imperative.
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