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Guided waves (GW) allow fast inspection of a large area and hence have received great interest from the structural health monitoring (SHM) community. Fiber Bragg grating (FBG) sensors offer several advantages but their use has been limited for the GW sensing due to its limited sensitivity. FBG sensors in the edge-filtering configuration have overcome this issue with sensitivity and there is a renewed interest in their use. Unfortunately, the FBG sensors and the equipment needed for interrogation is quite expensive, and hence their number is restricted. In the previous work by the authors, the number and location of the actuators was optimized for developing a SHM system with a single sensor and multiple actuators. But through the use of the phenomenon of acoustic coupling, multiple locations on the structure may be interrogated with a single FBG sensor. As a result, a sensor network with multiple sensing locations and a few actuators is feasible and cost effective. This paper develops a two-step methodology for the optimization of an actuator–sensor network harnessing the acoustic coupling ability of FBG sensors. In the first stage, the actuator–sensor network is optimized based on the application demands (coverage with at least three actuator–sensor pairs) and the cost of the instrumentation. In the second stage, an acoustic coupler network is designed to ensure high-fidelity measurements with minimal interference from other bond locations (overlap of measurements) as well as interference from features in the acoustically coupled circuit (fiber end, coupler, etc.). The non-sorting genetic algorithm (NSGA-II) is implemented for finding the optimal solution for both problems. The analytical implementation of the cost function is validated experimentally. The results show that the optimization does indeed have the potential to improve the quality of SHM while reducing the instrumentation costs significantly.

Guided wave array-based structural health monitoring (SHM) is a promising solution for diagnosing damage in metal-connected structures. In this field, the reconstruction algorithm for probabilistic inspection (RAPID) is one of the most widely used algorithms for performing damage localization. In this paper, a density clustering RAPID based on an array-compensated damage index is proposed. A new probability distribution function was constructed based on a new damage index, which is adaptive to different elements in the sensor array to compensate for performance variation. Then, the imaging matrix of the RAPID algorithm was density-clustered to obtain the location and degree of damage. Finally, the method was verified by experiments on a stiffened aluminum plate. The experimental results demonstrate that the method achieves damage localization and enables quantitative damage diagnosis.

This paper addresses the challenging issue of achieving high spatial resolution in temperature monitoring of printed circuit boards (PCBs) without compromising the operation of electronic components. Traditional methods involving numerous dedicated sensors such as thermocouples are often intrusive and can impact electronic functionality. To overcome this, this study explores the application of ultrasonic guided waves, specifically utilising a limited number of cost-effective and unobtrusive Piezoelectric Wafer Active Sensors (PWAS). Employing COMSOL multiphysics, wave propagation is simulated through a simplified PCB while systematically varying the temperature of both components and the board itself. Machine learning algorithms are used to identify hotspots at component positions using a minimal number of sensors. An accuracy of 97.6% is achieved with four sensors, decreasing to 88.1% when utilizing a single sensor in a pulse–echo configuration. The proposed methodology not only provides sufficient spatial resolution to identify hotspots but also offers a non-invasive and efficient solution. Such advancements are important for the future electrification of the aerospace and automotive industries in particular, as they contribute to condition-monitoring technologies that are essential for ensuring the reliability and safety of electronic systems.

This study conducted experimental and numerical investigations on piezoelectric wafer active sensors (PWASs) bonded to an aluminum plate to assess the impact of bonding degradation on Lamb wave generation. Three surface-bonded PWASs were examined, including one intentionally bonded with a reduced adhesive to create a defective bond. Thermal cyclic aging was applied, monitoring through laser Doppler vibrometry (LDV) and static capacitance measurements. The PWAS with the initially defective bond exhibited the poorest performance over aging cycles, emphasizing the significance of the initial bond condition. As debonding progressed, modifications in electromechanical behavior were observed, leading to a reduction in wave amplitude and distortion of the generated wave field, challenging the validity of existing analytical modeling of wave-tuning curves for perfectly bonded PWASs. Both numerical simulations and experimental observations substantiated this finding. In conclusion, this study highlights the imperative of a high-integrity bond for the proper functioning of a guided wave-based structural health monitoring (SHM) system, emphasizing ongoing challenges in assessing SHM performance.

The article presents the design concept of a surface acoustic wave (SAW)-based lab-on-a-chip sensor with multifrequency and multidirectional sensitivity. The conventional SAW sensors use delay lines that suffer from multiple signal losses such as insertion, reflection, transmission losses, etc. Most delay lines are designed to transmit and receive continuous signal at a fixed frequency. Thus, the delay lines are limited to only a few features, like frequency shift and change in wave velocity, during the signal analysis. These facts lead to limited sensitivity and a lack of opportunity to utilize the multi-directional variability of the sensing platform at different frequencies. Motivated by these facts, a guided wave sensing platform that utilizes simultaneous tone burst-based excitation in multiple directions is proposed in this article. The design incorporates a five-count tone burst signal for the omnidirectional actuation. This helps the acquisition of sensitive long part of the coda wave (CW) signals from multiple directions, which is hypothesized to enhance sensitivity through improved signal analysis. In this article, the design methodology and implementation of unique tone burst interdigitated electrodes (TB-IDT) are presented. Sensing using TB-IDT enables accessing multiple frequencies simultaneously. This results in a wider frequency spectrum and allows better scope for the detection of different target analytes. The novel design process utilized guided wave analysis of the substrate, and selective directional focused interdigitated electrodes (F-IDT) were implemented. The article demonstrates computational simulation along with experimental results with validation of multifrequency and multidirectional sensing capability.

Acoustic emission (AE) sensors and ultrasonic transducers were characterized for the detection of Rayleigh waves (RW). Small aperture reference sensors were characterized first using the fracture of glass capillary tubes in combination with a theoretical displacement calculation, which utilized finite element method (FEM) and was verified by laser interferometer. For the calibration of 18 commercial sensors and two piezoceramic disks, a 90° angle beam transducer was used to generate RW pulses on an aluminum transfer block. By a substitution method, RW receiving sensitivity of a sensor under test was determined over the range of frequency from 22 kHz to 2 MHz. Results were compared to the sensitivities to normally incident waves (NW) and to other guided waves (GW). It was found that (1) NW sensitivities are always higher than RW sensitivities, (2) differences between NW and RW receiving sensitivities are dependent on frequency and sensor size, (3) most sensors show comparable RW and GW receiving sensitivities, especially those of commonly used AE sensors, and (4) the receiving sensitivities of small aperture (1 mm diameter) sensors behave differently from larger sensors.

Grouted sleeves (GSs) are a type of precast joint that can effectively connect steel rebars with excellent performance. However, the grouting debonding problem, which can occur due to the leakage of the glue plug, can seriously affect the properties of GSs. In this paper, a guided-wave-based structural health monitoring (SHM) method is used to detect debonding in GSs. The axisymmetric longitudinal mode is selected as the incident wave since it is sensitive to axial damage. Eight piezoelectrics (PZTs) are then symmetrically installed to actuate signals. The proposed samples are GSs with four different debonding sizes. First, the relationship between the arrival time of the first wave packet and the debonding size is explored through theoretical derivation. The arrival time decreases linearly with an increasing debonding size. A similar trend is observed when the relationship is verified via a numerical simulation and experimental results. This method will provide a reference for detecting debonding in similar GS multilayer structures.

This study develops a framework for determining the material parameters of layered engineered wood in a nondestructive manner. The motivation lies in enhancing nondestructive evaluation (NDE) and quality assurance (QA) for engineered wood or mass timber, promising construction materials for sustainable and resilient civil structures. The study employs static compression tests, guided wave measurements, and a genetic algorithm (GA) to solve the inverse problem of determining the mechanical properties of a laminated veneer lumber (LVL) bar. Miniature LVL samples are subjected to compression tests to derive the elastic moduli and Poisson’s ratios. Due to the intrinsic heterogeneity, the destructive compression tests yield large coefficients of variances ranging from 2.5 to 73.2%. Dispersion relations are obtained from spatial–temporal sampling of dynamic responses of the LVL bar. The GA pinpoints optimal mechanical properties by updating orthotropic elastic constants of the LVL material, and thereby dispersion curves, in a COMSOL simulation in accordance with experimental dispersion relations. The proposed framework can support estimation accuracy with errors less than 10% for most elastic constants. Focusing on vertical flexural modes, the estimated elastic constants generally resemble reference values from compression tests. This is the first study that evaluates the feasibility of using guided waves and multi-variable optimization to gauge the mechanical traits of LVL and establishes the foundation for further advances in the study of layered engineered wood structures.

In this paper, defect detection and identification in aluminium joints is investigated based on guided wave monitoring. Guided wave testing is first performed on the selected damage feature from experiments, namely, the scattering coefficient, to prove the feasibility of damage identification. A Bayesian framework based on the selected damage feature for damage identification of three-dimensional joints of arbitrary shape and finite size is then presented. This framework accounts for both modelling and experimental uncertainties. A hybrid wave and finite element approach (WFE) is adopted to predict the scattering coefficients numerically corresponding to different size defects in joints. Moreover, the proposed approach leverages a kriging surrogate model in combination with WFE to formulate a prediction equation that links scattering coefficients to defect size. This equation replaces WFE as the forward model in probabilistic inference, resulting in a significant enhancement in computational efficiency. Finally, numerical and experimental case studies are used to validate the damage identification scheme. An investigation into how the location of sensors can impact the identified results is provided as well.

Guided wave Electro Magnetic Acoustic Transducers (EMATs) offer an elegant method for structural inspection and localisation relative to geometric features, such as welds. This paper presents a Lorentz force EMAT construction framework, where a numerical model has been developed for optimising Printed Circuit Board (PCB) coil parameters as well as a methodology for optimising magnet array parameters to a user’s needs. This framework was validated experimentally to show its effectiveness through comparison to an industry built EMAT. The framework was then used to design and manufacture a Side-Shifted Unidirectional Periodic Permanent Magnet (PPM) EMAT for use on a mobile robotic system, which uses guided waves for ranging to build internal maps of a given subject, identifying welded sections, defects and other structural elements. The unidirectional transducer setup was shown to operate in simulation and was then manufactured to compare to the bidirectional transmitter and two-receiver configurations on a localisation system. The unidirectional setup was shown to have clear benefits over the bidirectional setup for mapping an unknown environment using guided waves as there were no dead spots of mapping where signal direction could not be interpreted. Additionally, overall package size was significantly reduced, which in turn allows more measurements to be taken within confined spaces and increases robotic crawler mobility.

The use of thin magnetostrictive patches to generate and detect guided waves within the composite samples is investigated for defect detection. This approach has been implemented using SH0 shear horizontal guided waves in both CFRP and GFRP plates. A magnetostrictive patch transducer was able to generate SH0 waves with known directional characteristics. The synthetic aperture focusing technique (SAFT) was then used to reconstruct images of defects using multiple transmission and detection locations. The results for imaging defects in both types of material are presented.

Ultrasonic flow meters (UFMs) based on transducer arrays offer several advantages. With electronic beam steering, it is possible to tune the steering angle of the beam for optimal signal-tonoise ratio (SNR) upon reception. Moreover, multiple beams can be generated to propagate through different travel paths, covering a wider section of the flow profile. Furthermore, in a clamp-on configuration, UFMs based on transducer arrays can perform self-calibration. In this manner, userinput is minimized and measurement repeatability is increased. In practice, transducer array elements may break down. This could happen due to aging, exposure to rough environments, and/or rough mechanical contact. As a consequence of inactive array elements, the measured transit time difference contains two offsets. One offset originates from non-uniform spatial sampling of the generated wavefield. Another offset originates from the ill-defined beam propagating through a travel path different from the intended one. In this paper, an algorithm is proposed that corrects for both of these offsets. The algorithm also performs a filtering operation in the frequency-wavenumber domain of all spurious (i.e., flow-insensitive) wave modes. The advantage of implementing the proposed algorithm is demonstrated on simulations and measurements, showing improved accuracy and precision of the transit time differences compared to the values obtained when the algorithm is not applied. The proposed algorithm can be implemented in both in-line and clamp-on configuration of UFMs based on transducer arrays.

Structural health monitoring (SHM) systems may allow a reduction in maintenance costs and extend the lifetime of the structure. As a result, they are of interest to the research community. Ideally, the SHM methods should be low cost, while being able to detect and localize small levels of damage reliably and accurately. The fiber Bragg grating (FBG) sensors are light in weight, insensitive to electric and magnetic fields, and can be embedded. The edge filtering configuration for transduction allows the use of FBG for guided wave (GW) sensing. This sensitivity may be further enhanced through their application in the remote bonded configuration. This paper provides a proof-of-concept for the use of remotely bonded FBG for damage localization. In order to improve the computational efficiency, a particle swarm optimization (PSO) based algorithm is developed. The PSO allows a significant improvement in the computation time which makes it better suited for real-time damage localization. The proposed objective function is based on the exponential elliptical approach. First, the suitability of the PSO for damage localization is shown. Then the performance of the chosen objective function is compared with the brute-force algorithm as well as other objective functions found in the literature. The methodology is employed on a simple aluminum plate. The results indicate that indeed the objective function along with the PSO is suitable for damage localization. Also as the objective function is developed taking into consideration the specific challenges with the use of FBG sensors, performs better than the other objective functions as well as the brute force algorithm.

Guided waves are a potent tool in structural health monitoring, with promising machine learning algorithm applications due to the complexity of their signals. However, these algorithms usually require copious amounts of data to be trained. Collecting the correct amount and distribution of data is costly and time-consuming, and sometimes even borderline impossible due to the necessity of introducing damage to vital machinery to collect signals for various damaged scenarios. This data scarcity problem is not unique to guided waves or structural health monitoring, and has been partly addressed in the field of computer vision using generative adversarial neural networks. These networks generate synthetic data samples based on the distribution of the data they were trained on. Though there are multiple researched methods for simulating guided wave signals, the problem is not yet solved. This work presents a generative adversarial network architecture for guided waves generation and showcases its capabilities when working with a series of pitch-catch experiments from the OpenGuidedWaves database. The network correctly generates random signals and can accurately reconstruct signals it has not seen during training. The potential of synthetic data to be used for training other algorithms was confirmed in a simple damage detection scenario, with the classifiers trained exclusively on synthetic data and evaluated on real signals. As a side effect of the signal reconstruction process, the network can also compress the signals by 98.44% while retaining the damage index information they carry.

The sections of pipe bends are hot spots for wall thinning due to accelerated corrosion by fluid flow. Conventionally, the thickness of a bend wall is evaluated by local point-by-point ultrasonic measurement, which is slow and costly. Guided wave tomography is an attractive method that enables the monitoring of a whole bend area by processing the waves excited and received by transducer arrays. The main challenge associated with the tomography of the bend is the development of an appropriate forward model, which should simply and efficiently handle the wave propagation in a complex bend model. In this study, we developed a two-dimensional (2D) acoustic forward model to replace the complex three-dimensional (3D) bend domain with a rectangular domain that is made artificially anisotropic by using Thomsen parameters. Thomsen parameters allow the consideration of the directional dependence of the velocity of the wave in the model. Good agreement was found between predictions and experiments performed on a 220 mm diameter (d) pipe with 1.5d bend radius, including the wave-field focusing effect and the steering effect of scattered wave-fields from defects.

The estimation of Direction of Arrival (DoA) of guided ultrasonic waves is an important task in many Structural Health Monitoring (SHM) applications. The aim is to locate sources of elastic waves which can be generated by impacts or defects in the inspected structures. In this paper, the array geometry and the shape of the piezo-sensors are designed to optimize the DoA estimation on a pre-defined angular sector, from acquisitions affected by noise and interference. In the proposed approach, the DoA of a wave generated by a single source is considered as a random variable that is uniformly distributed in a given range. The wave velocity is assumed to be unknown and the DoA estimation is performed by measuring the Differences in Time of Arrival (DToAs) of wavefronts impinging on the sensors. The optimization procedure of sensors positioning is based on the computation of the DoA and wave velocity parameters Cramér-Rao Matrix Bound (CRMB) with a Bayesian approach. An efficient DoA estimator is found based on the DToAs Gauss-Markov estimator for a three sensors array. Moreover, a novel directive sensor for guided waves is introduced to cancel out undesired Acoustic Sources impinging from DoAs out of the given angles range. Numerical results show the capability to filter directional interference of the novel sensor and a considerably improved DoA estimation performance provided by the optimized sensor cluster in the pre-defined angular sector, as compared to conventional approaches.

One of the axioms of structural health monitoring states that the severity of damage assessment can only be done in a learning mode under the supervision of an expert. Therefore, a numerical analysis was conducted to gain knowledge regarding the influence of the damage size on the propagation of elastic waves in a honeycomb sandwich composite panel. Core-skin debonding was considered as damage. For this purpose, a panel was modelled taking into account the real geometry of the honeycomb core using the time-domain spectral element method and two-dimensional elements. The presented model was compared with the homogenized model of the honeycomb core and validated in the experimental investigation. The result of the parametric study is a function of the influence of damage on the amplitude and energy of propagating waves.

Guided waves (GW) and acoustic emission (AE) -based structural health monitoring (SHM) have widespread applications in structures, as the monitoring of an entire structure is possible with a limited number of sensors. Optical fiber-based sensors offer several advantages, such as their low weight, small size, ability to be embedded, and immunity to electro-magnetic interference. Therefore, they have long been regarded as an ideal sensing solution for SHM. In this review, the different optical fiber technologies used for ultrasonic sensing are discussed in detail. Special attention has been given to the new developments in the use of FBG sensors for ultrasonic measurements, as they are the most promising and widely used of the sensors. The paper highlights the physics of the wave coupling to the optical fiber and explains the different phenomena such as directional sensitivity and directional coupling of the wave. Applications of the different sensors in real SHM applications have also been discussed. Finally, the review identifies the encouraging trends and future areas where the field is expected to develop.

The computer modelling of condition monitoring sensors can aide in their development, improve their performance, and allow for the analysis of sensor impact on component operation. This article details the development of a COMSOL model for a guided wave-based temperature monitoring system, with a view to using the technology in the future for the temperature monitoring of nozzle guide vanes, found in the hot section of aeroengines. The model is based on an experimental test system that acts as a method of validation for the model. Piezoelectric wedge transducers were used to excite the S0 Lamb wave mode in an aluminium plate, which was temperature controlled using a hot plate. Time of flight measurements were carried out in MATLAB and used to calculate group velocity. The results were compared to theoretical wave velocities extracted from dispersion curves. The assembly and validation of such a model can aide in the future development of guided wave based sensor systems, and the methods provided can act as a guide for building similar COMSOL models. The results show that the model is in good agreement with the experimental equivalent, which is also in line with theoretical predictions.

Ultrasonic guided waves provide unique capabilities for the structural health monitoring of plate-like structures. They can detect and locate various types of material degradation through the interaction of shear-horizontal (SH) waves and Lamb waves with the material. Magnetostrictive transducers (MSTs) can be used to generate and receive both SH and Lamb waves and yet their characteristics have not been thoroughly studied, certainly not on par with piezoelectric transducers. A series of multiphysics simulations of the MST/plate system is conducted to investigate the characteristics of MSTs that affect guided wave generation and reception. The results are presented in the vein of showing the flexibility that MSTs provide for guided waves in a diverse range of applications. In addition to studying characteristics of the MST components (i.e., the magnetostrictive layer, meander electric coil, and biased magnetic field), single-sided and double-sided MSTs are compared for preferential wave mode generation. The wave mode control principle is based on the activation line for phase velocity dispersion curves, whose slope is the wavelength, which is dictated by the meander coil spacing. A double-sided MST with in-phase signals preferentially excites symmetric SH and Lamb modes, while a double-sided MST with out-of-phase signals preferentially excites antisymmetric SH and Lamb modes. All attempted single-mode actuations with double-sided MSTs were successful, with the SH3 mode actuated at 922 kHz in a 6-mm-thick plate being the highest frequency. Additionally, the results show that increasing the number of turns in the meander coil enhances the sensitivity of the MST as a receiver and substantially reduces the frequency bandwidth.

Interferometric methods of optical sensing based on the phase shift of the Bloch surface waves (BSWs) and guided waves (GWs) supported by a one-dimensional photonic crystal are presented. The photonic crystal, composed of six SiO2/TiO2 bilayers with a termination layer of TiO2, is employed in the Kretschmann configuration. Under resonance condition, an abrupt phase change is revealed, and the corresponding phase shift is measured by interferometric techniques applied in both the spectral and spatial domains. The spectral interferometric technique employing a birefringent quartz crystal is used to obtain interference of projections of p- and s-polarized light waves reflected from the photonic crystal. The phase shifts are retrieved by processing the spectral interferograms recorded for various values of relative humidity (RH) of air, giving the sensitivity to the RH as high as 0.029 rad/%RH and 0.012 rad/%RH for the BSW and GW, respectively. The spatial interferometric technique employs a Wollaston prism and an analyzer to generate an interference pattern, which is processed to retrieve the phase difference, and results are in good agreement with those obtained by sensing the phase shift in the spectral domain. In addition, from the derivative of the spectral phase shifts, the peak positions are obtained, and their changes with the RH give the sensitivities of 0.094 nm/%RH and 0.061 nm/%RH for the BSW and GW, respectively. These experimental results demonstrate an efficient optical sensing with a lot of applications in various research areas.

In the context of active-sensing guided-wave-based acousto-ultrasound structural health monitoring, environmental and operational variability poses a considerable challenge in the damage diagnosis process as they may mask the presence of damage. In this work, the stochastic nature of guided wave propagation due to the small temperature variation, naturally occurring in the ambient or environment, is rigorously investigated and modeled with the help of stochastic time-varying time series models, for the first time, with a system identification point of view. More specifically, the output-only recursive maximum likelihood time-varying auto-regressive model (RML-TAR) is employed to investigate the uncertainty in guided wave propagation by analyzing the time-varying model parameters. The steps and facets of the identification procedure are presented, and the obtained model is used for modeling the uncertainty of the time-varying model parameters that capture the underlying dynamics of the guided waves. The stochasticity inherent in the modal properties of the system, such as natural frequencies and damping ratios, is also analyzed with the help of the identified RML-TAR model. It is stressed that the narrow-band high-frequency actuation for guided wave propagation excites more than one frequency in the system. The values and the time evolution of those frequencies are analyzed, and the associated uncertainties are also investigated. In addition, a high-fidelity finite element (FE) model was established and Monte Carlo simulations on that FE model were carried out to understand the effect of small temperature perturbation on guided wave signals.

A coherent optical fiber sensor with adequate sensitivity for detecting the acoustic emission (AE) during the propagation of a crack in a ferrous material is presented. The proposed fiber optic sensor is successfully compared in terms of the SNR (Signal to Noise Ratio) and detectable AE energy levels to commercially available AE piezo-transducers sensors and is proven to be an effective and advantageous alternative for sensing and monitoring fatigue damage in structural applications.

This paper proposes a hybrid structural health monitoring (SHM) solution for a smart composite patch repair for aircraft structures based on piezoelectric (PZT) and fibre optic (FO) sensors to monitor the integrity of a the bondline and detect any degradation. FO sensors are used to acquire guided waves excited by PZT transducers to allow the advantages of both sensor technologies to be utilised. One of the main challenges of guided wave based detection methodologies is to distinguish the effect of temperature on the propagating waves, from that of an existing damage. In this research, the application of the hybrid SHM system is tested on a composite step sanded repair coupon under operational condition (temperature variation) representative of an aircraft for the first time. The sensitivity of the embedded FO sensor in recording the strain waves is compared to the signals acquired by PZT sensors under varying temperature. A novel compensation algorithm is proposed to correct for the effect of the temperature on the embedded FO sensor spectrum in the hybrid set-up. The repaired specimen is then impacted with a drop mass to cause barely visible impact damage (BVID). The hybrid SHM system is then used to detect the damage, and its diagnosis results are compared to a PZT only based smart repair solution. The results show promising application of the hybrid solution for monitoring bondline integrity as well as highlighting challenges of the embedding of FO sensors for a reliable and repeatable diagnosis.

This paper presents a new technique for the extraction of high-order wave-damage interaction coefficients (WDIC) through modal decomposition. The frequency and direction dependent complex-valued WDIC are used to model the scattering and mode conversion phenomena of guided wave interaction with damage. These coefficients are extracted from the harmonic analysis of local finite element model (FEM) mesh with non-reflective boundaries (NRB) and they are capable of describing the amplitude and phase of the scattered waves as a function of frequency and direction. To extract the WDIC of each wave mode, all the possible propagating wave modes are considered to be scattered simultaneously from the damage and propagate independently. Formulated in frequency domain, the proposed method is highly efficient, providing an overdetermined equation system for the calculation of mode participation factors, i.e., WDIC of each mode. Case studies in a 6-mm aluminum plate were carried out to validate the WDIC of: (1) a through-thickness hole and (2) a sub-surface crack. At higher frequency, scattered waves of high-order modes will appear and their WDIC can be successfully extracted through the modal decomposition.

This review article is focused on the analysis of the state of the art of sensors for guided ultrasonic waves for the detection and localization of impacts for structural health monitoring (SHM). The recent developments in sensor technologies are then reported and discussed through the many references in recent scientific literature. The physical phenomena that are related to impact event and the related main physical quantities are then introduced to discuss their importance in the development of the hardware and software components for SHM systems. An important aspect of the article is the description of the different ultrasonic sensor technologies that are currently present in the literature and what advantages and disadvantages they could bring in relation to the various phenomena investigated. In this context, the analysis of the front-end electronics is deepened, the type of data transmission both in terms of wired and wireless technology and of online and offline signal processing. The integration aspects of sensors for the creation of networks with autonomous nodes with the possibility of powering through energy harvesting devices and the embedded processing capacity is also studied. Finally, the emerging sector of processing techniques using deep learning and artificial intelligence concludes the review by indicating the potential for the detection and autonomous characterization of the impacts.

Since stringers are often applied in engineering constructions to improve thin-walled structures’ strength, methods for damage detection at the joints between the stringer and the thin-walled structure are necessary. A 2D mathematical model was employed to simulate Lamb wave excitation and sensing via rectangular piezoelectric-wafer active transducers mounted on the surface of an elastic plate with rectangular surface-bonded obstacles (stiffeners) with interface defects. The results of a 2D simulation using the finite element method and the semi-analytical hybrid approach were validated experimentally using laser Doppler vibrometry for fully bonded and semi-debonded rectangular obstacles. A numerical analysis of fundamental Lamb wave scattering via rectangular stiffeners in different bonding states is presented. Two kinds of interfacial defects between the stiffener and the plate are considered: the partial degradation of the adhesive at the interface and an open crack. Damage indices calculated using the data obtained from a sensor are analyzed numerically. The choice of an input impulse function applied at the piezoelectric actuator is discussed from the perspective of the development of guided-wave-based structural health monitoring techniques for damage detection.

Structural health monitoring (SHM) systems help in reducing maintenance cost and avoiding catastrophic failure of the structure. As a result, they have been a focus of research for the past few decades. Ideally, the methods employed should be low cost and able to detect and localize small levels of damage reliably and accurately. This paper describes a guided waves (GW) based two-step technique for damage detection and localization using fiber Bragg grating (FBG) sensors. The FBG sensors offer benefits such as the ability to be embedded and multiplexed as well as being lightweight and insensitive to electric and magnetic fields, and they have long been seen as a promising solution for the GW measurements in structures. Unfortunately, in the conventional wavelength-based interrogation they have very low signal to noise ratio and as a result low sensitivity. Therefore, the FBG sensor is incorporated in the edge filtering configuration. The major challenges in the use of FBG sensors for GW-based detection are their directional sensitivity and passive nature. The passive nature leads to the reduction in the available actuator–sensor (AS) pairs while the directionality makes the signal processing a challenge. The proposed two-step methodology overcomes these shortcomings of FBG sensors. In the first step the amplitude weighted elliptical approach is used to identify the hotspots due to the inadequate number of AS pairs, the elliptical approach is not sufficient for damage localization. Therefore, in order to further localize the damage the edge reflection based ray-tracing approach is implemented in the second step. Through the two step method, the damage is accurately located. The paper provides the proof of concept of the proposed methodology on an aluminum plate with simulated damage. The results indicate, that indeed the two-step methodology allows accurate damage localization and overcomes the possibility of false detections.

Structural Health Monitoring (SHM) of Carbon Fiber Reinforced Polymers (CFRP) has become, recently, in a promising methodology for the field of Non-Destructive Inspection (NDI), specially based on Ultrasonic Guided Waves (UGW), particularly Lamb waves using Piezoelectric Transducers (PZT). However, the Environmental and Operational Conditions (EOC) perform an important role on the physical characteristics of the waves, mainly the temperature. Some of these effects are phase shifting, amplitude changes and time of flight (ToF) variations. In this paper, a compensation method for evaluating and compensating the effects of the temperature is carried out, performing a data-driven methodology to calculate the features from a dataset of typical temperature values obtained from a thermoset matrix pristine plate, with a transducer network attached. In addition, the methodology is tested on the same sample after an impact damage is carried out on it, using RAPID (Reconstruction Algorithm for Probabilistic Inspection of Damage) and its geometrical variant (RAPID-G) to calculate the location of the damage.

The topological derivative tool is applied here in structural health monitoring (SHM) problems to locate small defects in a material plate with complex geometry that is subject to permanent multifrequency guided waves excitation. Compared to more standard SHM methods, based in measuring the time-lag between emitted and received propagative pulses plus some postprocessing, the topological derivative somehow compares the measured and computed (solving the full elasto-dynamic equations) response of the damaged plate, instead of relying on only the time of flight of the wave. Thus, the method profits the knowledge behind the physics of the problem and can cope with scenarios in which classical methods give poor results. The authors of this paper have already used the topological derivative in rectangular plates with constant thickness, but with defects consisting simply in both through slits and inclusions of a different material, and actuators/sensors located near the boundary, which makes very difficult to use standard SHM methods. This is an extension of the method, also considering the much more difficult to analyze case of plates with variable thickness and complex (non-rectangular) planform.

In this paper, a novel hybrid damage detection system is proposed, which utilizes piezoelectric actuators for guided wave excitation and a new fibre optic (FO) sensor based on Fabry-Perot (FP) and Fiber Bragg Grating (FBG). By replacing the FBG sensors with FBG-based FP sensors in the hybrid damage detection system, a higher strain resolution is achieved, which results in higher damage sensitivity and higher reliability in diagnosis. To develop the novel sensor, optimum parameters such as reflectivity, a wavelength spectrum, and a sensor length were chosen carefully through an analytical model of the sensor, which has been validated with experiments. The sensitivity of the new FBG-based FP sensors was compared to FBG sensors to emphasize the superiority of the new sensors in measuring micro-strains. Lastly, the new FBG-based FP sensor was utilized for recording guided waves in a hybrid setup and compared to the conventional FBG hybrid sensor network to demonstrate their improved performance for a structural health monitoring (SHM) application.

In this paper, the guided wave propagation behavior in damaged 30CrMo steel curved plates was investigated experimentally and numerically. The effects of the notch orientation, depth in the curved plate, as well as its radius, on the wave propagation characteristics were mainly analyzed by the amplitude distribution curves and the directivity diagrams of A0/S0 (zero-th order of the symmetric/antisymmetric Lamb wave) modes. An ellipse-based algorithm was compiled to locate the notches in the curved plates. Results show that the normalized S0 wave amplitude in the circumferential orientation was the largest, and it increases as notch depth increases in the axial orientation. The A0 wave amplitude in axial orientation was the largest, while it decreases with the increasing of notch depth in the other orientations. The normalized A0 wave amplitude in axial orientation increases with the increasing of radius. With the increasing of radius, the other normalized A0/S0 amplitudes linearly decreased for the other paths. The ellipse-based algorithm has high notch localization accuracy, and the notch localization error increase from 0.005% to 1.47% with the notch depth decreasing from 5 mm to 1 mm in the curved plates. For the curved plates with different radius, the maximum notch localization error is 1.20%. These satisfactory results demonstrate the effectiveness of the developed algorithm in locating damages in the researched structure.

Structural health monitoring using noninvasive methods is one of the major challenges that aerospace manufacturers face in this decade. Our work in this field focuses on the development and the system integration of millimetric piezoelectric sensors/ actuators to generate and measure specific guided waves. The aim of the application is to detect mechanical flaws on complex composite and alloy structures to quantify efficiently the global structures’ reliability. The study begins by a physical and analytical analysis of a piezoelectric patch. To preserve the structure’s integrity, the transducers are directly pasted onto the surface which leads to a critical issue concerning the interfacing layer. In order to improve the reliability and mitigate the influence of the interfacing layer, the global equations of piezoelectricity are coupled with a load transfer model. Thus we can determine precisely the shear strain developed on the surface of the structure. To exploit the generated signal, a high precision analog charge amplifier coupled to a double T notch filter were designed and scaled. Finally, a novel joined time-frequency analysis based on a wavelet decomposition algorithm is used to extract relevant structures signatures. Finally, this paper provides examples of application on aircraft structure specimens and the feasibility of the system is thus demonstrated.

Acoustic emission (AE) sensors and ultrasonic transducers were characterized for the detection of Rayleigh waves (RW). Small aperture reference sensors were characterized first using the fracture of glass capillary tubes in combination with a theoretical displacement calculation, which utilized finite element method (FEM) and was verified by laser interferometer. For the calibration of 18 commercial sensors and two piezoceramic disks, a 90° angle beam transducer was used to generate RW pulses on an aluminum transfer block. By a substitution method, RW receiving sensitivity of a sensor under test was determined over the range of frequency from 22 kHz to 2 MHz. Results were compared to the sensitivities to normally incident waves (NW) and to other guided waves (GW). It was found that (1) NW sensitivities are always higher than RW sensitivities, (2) differences between NW and RW receiving sensitivities are dependent on frequency and sensor size, (3) most sensors show comparable RW and GW receiving sensitivities, especially those of commonly used AE sensors, and (4) the receiving sensitivities of small aperture (1 mm diameter) sensors behave differently from larger sensors.

The following article presents results of investigating the damage detection in reinforced concrete beams with artificially introduced debonding between the rod and cover, using a non-destructive method based on elastic waves propagation. The primary aim of the research was to analyze the possible use of guided waves in partial circumferential debonding detection. Guided waves were excited and registered in reinforced concrete specimens with varying extents of debonding damage by piezoelectric sensors attached at both ends of the beams. Experimental results in the form of time–domain signals registered for variable extent of debonding were compared, and the relationships relating to the damage size and time of flight and average wave velocity were proposed. The experimental results were compared with theoretical predictions based on dispersion curves traced for the free rod of circular cross-section and rectangular reinforced concrete cross-section. The high agreement of theoretical and experimental data proved that the proposed method, taking advantage of average wave velocity, can be efficiently used for assessing debonding size in reinforced concrete structures. It was shown that the development of damage size in circumferential direction has a completely different impact on wave velocity than development of debonding length. The article contains a continuation of work previously conducted on the detection of delamination in concrete structures. The proposed relationship is the next essential step for developing a diagnostics method for detecting debondings of any size and orientation.

Guided waves (GW) allow fast inspection of a large area and hence have attracted research interest from the structural health monitoring (SHM) community. Thus, GW-based SHM is ideal for thin structures such as plates, pipes, etc., and is finding applications in several fields like aerospace, automotive, wind energy, etc. The GW propagate along the surface of the sample and get reflected from discontinuities in the structure in the form of boundaries and damage. Through proper signal processing of the reflected waves based on their time of arrival, the damage can be detected and isolated. For complex structures, a higher number of sensors may be required, which increases the cost of the equipment, as well as the mass. Thus, there is an effort to reduce the number of sensors without compromising the quality of the monitoring achieved. It is of utmost importance that the entire structure can be investigated. Hence, it is necessary to optimize the locations of the sensors in order to maximize the coverage while limiting the number of sensors used. A genetic algorithm (GA)-based optimization strategy was proposed by the authors for use in a simple aluminum plate. This paper extends the optimization methodology for other shape plates and presents experimental, analytical, and numerical studies. The sensitivity studies have been carried out by changing the relative weights of the application demands and presented in the form of a Pareto front. The Pareto front allows comparison of the relative importance of the different application demands, and an appropriate choice can be made based on the information provided.

Composite materials are widely used in the industry, and the interest of this material is growing rapidly, due to its light weight, strength and various other desired mechanical properties. However, composite materials are prone to production defects and other defects originated during exploitation, which may jeopardize the safety of such a structure. Thus, non-destructive evaluation methods that are material-independent and suitable for a wide range of defects identification are needed. In this paper, a technique for damage characterization in composite plates is proposed. In the presented non-destructive testing method, guided waves are excited by a piezoelectric transducer, attached to tested specimens, and measured by a scanning laser Doppler vibrometer in a dense grid of points. By means of signal processing, irregularities in wavefield images caused by any material defects are extracted and used for damage characterization. The effectiveness of the proposed technique is validated on four different composite panels: Carbon fiber-reinforced polymer, glass fiber-reinforced polymer, composite reinforced by randomly-oriented short glass fibers and aluminum-honeycomb core sandwich composite. Obtained results confirm its versatility and efficacy in damage characterization in various types of composite plates.

The implementation of damage-detection methods for continuously assessing structural integrity entails systems with attractive features such as storage capabilities, memory capacity, computational complexity and time-consuming processing. In this sense, embedded hardware platforms are a promising technology for developing integrated solutions in Structural Health Monitoring. In this paper, design, test, and specifications for a standalone inspection prototype are presented, which take advantage of piezo-diagnostics principle, statistical processing via Principal Component Analysis (PCA) and embedded systems. The equipment corresponds to a piezoelectric active system with the capability to detect defects in structures, by using a PCA-based algorithm embedded in the Odroid-U3 ARM Linux platform. The operation of the equipment consists of applying, at one side of the structure, wide guided waves by means of piezoelectric devices operated in actuation mode and to record the wave response in another side of the structure by using the same kind of piezoelectric devices operated in sensor mode. Based on the nominal response of the guide wave (no damages), represented by means of a PCA statistical model, the system can detect damages between the actuated/sensed points through squared prediction error (Q-statistical index). The system performance was evaluated in a pipe test bench where two kinds of damages were studied: first, a mass is added to the pipe surface, and then leaks are provoked to the pipe structure by means of a drill tool. The experiments were conducted on two lab structures: (i) a meter carbon-steel pipe section and (ii) a pipe loop structure. The wave response was recorded between the instrumented points for two conditions: (i) The pipe in nominal conditions, where several repetitions will be applied to build the nominal statistical model and (ii) when damage is caused to the pipe (mass adding or leak). Damage conditions were graphically recognized through the Q-statistic chart. Thus, the feasibility to implement an automated real-time diagnostic system is demonstrated with minimum processing resources and hardware flexibility.

Ultrasonic non-destructive testing techniques (NDT) based on the application of guided waves are already used for inspection of plate-type structures made of various materials, including composite materials. Air-coupled ultrasonic techniques are used to test such structures by means of guided waves. The objective of this research was development and investigation of air-coupled excitation of a slow A0 Lamb wave mode in thin plastic films by a PMN-32%PT ultrasonic array. It is known that when the velocity of the A0 mode in the film is less than the ultrasound velocity in air no leaky wave is observed in a surrounding air. It opens new possibilities for NDT of composite structures. The influence of the airborne wave may be eliminated by 3D filtering in a wavenumbers-frequency domain. A special filter and corresponding signals processing technique were developed in order to obtain directivity patterns and velocity maps of the waves propagating in all directions. The measured ultrasound velocity values prove that, with the proposed method, it is possible to excite a slow A0 Lamb wave mode and to separate it from other parasitic waves propagating in air. Measurements of the parameters of the slow A0 mode, such as the propagation velocity in the plastic film, may be applied for the material characterization.

A novel lightweight diagnostic film with sensors/actuators and a multiple-path wiring option using inkjet printing was developed. The diagnostic film allows for systematic, accurate, and repeatable sensor placement. Furthermore, the film is highly flexible and adaptable for placement on complex configurations. The film can be attached to the surface of the structure through a uniform secondary boundary procedure or embedded within the composite layup during curing. The surface-mounted film can simply be peeled off for repair or replacement without scratching or damaging the part. The film offers significant weight reduction compared to other available technologies. A set of extreme temperature, altitude, and vibration environment test profiles were carried out following the Radio Technical Commission for Aeronautics (RTCA) DO-160 document to assess the durability and performance of the diagnostic film for onboard application. The diagnostic film was shown to be durable and reliable in withstanding the variable operational and harsh environmental conditions of tests representing the conditions of regional aircraft.

This paper aims to set up a finite element model using piezoelectric elements to realize pipeline structure damage identification analysis. Ultrasonic guided wave propagation characteristics and damage identification of pipeline structures are analyzed by the ABAQUS software. The pulse-echo method using an L(0, 2) mode impulse guided wave with a central frequency of 70 kHz is applied to evaluate different size circumferential cracks. An experiment was performed for the validation of the numerical analysis results. Both of the results show that the proposed FEM model with piezoelectric elements can efficiently reveal the dynamic behaviors, which can be used in much more precise numerical simulations than the equivalent dynamic displacement loading method.

Since mechanical stress in structures affects issues such as strength, expected operational life and dimensional stability, a continuous stress monitoring scheme is necessary for a complete integrity assessment. Consequently, this paper proposes a stress monitoring scheme for cylindrical specimens, which are widely used in structures such as pipelines, wind turbines or bridges. The approach consists of tracking guided wave variations due to load changes, by comparing wave statistical patterns via Principal Component Analysis (PCA). Each load scenario is projected to the PCA space by means of a baseline model and represented using the Q-statistical indices. Experimental validation of the proposed methodology is conducted on two specimens: (i) a 12.7 mm ( 1 / 2 ″ ) diameter, 0.4 m length, AISI 1020 steel rod, and (ii) a 25.4 mm ( 1 ″ ) diameter, 6m length, schedule 40, A-106, hollow cylinder. Specimen 1 was subjected to axial loads, meanwhile specimen 2 to flexion. In both cases, simultaneous longitudinal and flexural guided waves were generated via piezoelectric devices (PZTs) in a pitch-catch configuration. Experimental results show the feasibility of the approach and its potential use as in-situ continuous stress monitoring application.

This paper presents a novel non-destructive testing and health monitoring system using a network of tactile transducers and accelerometers for the condition assessment and damage classification of foundation piles and utility poles. While in traditional pile integrity testing an impact hammer with broadband frequency excitation is typically used, the proposed testing system utilizes an innovative excitation system based on a network of tactile transducers to induce controlled narrow-band frequency stress waves. Thereby, the simultaneous excitation of multiple stress wave types and modes is avoided (or at least reduced), and targeted wave forms can be generated. The new testing system enables the testing and monitoring of foundation piles and utility poles where the top is inaccessible, making the new testing system suitable, for example, for the condition assessment of pile structures with obstructed heads and of poles with live wires. For system validation, the new system was experimentally tested on nine timber and concrete poles that were inflicted with several types of damage. The tactile transducers were excited with continuous sine wave signals of 1 kHz frequency. Support vector machines were employed together with advanced signal processing algorithms to distinguish recorded stress wave signals from pole structures with different types of damage. The results show that using fast Fourier transform signals, combined with principal component analysis as the input feature vector for support vector machine (SVM) classifiers with different kernel functions, can achieve damage classification with accuracies of 92.5% ± 7.5%.

This work proposes a novel hybrid signal processing technique to extract information on disbond-type defects from a single B-scan in the process of non-destructive testing (NDT) of glass fiber reinforced plastic (GFRP) material using ultrasonic guided waves (GW). The selected GFRP sample has been a segment of wind turbine blade, which possessed an aerodynamic shape. Two disbond type defects having diameters of 15 mm and 25 mm were artificially constructed on its trailing edge. The experiment has been performed using the low-frequency ultrasonic system developed at the Ultrasound Institute of Kaunas University of Technology and only one side of the sample was accessed. A special configuration of the transmitting and receiving transducers fixed on a movable panel with a separation distance of 50 mm was proposed for recording the ultrasonic guided wave signals at each one-millimeter step along the scanning distance up to 500 mm. Finally, the hybrid signal processing technique comprising the valuable features of the three most promising signal processing techniques: cross-correlation, wavelet transform, and Hilbert–Huang transform has been applied to the received signals for the extraction of defects information from a single B-scan image. The wavelet transform and cross-correlation techniques have been combined in order to extract the approximated size and location of the defects and measurements of time delays. Thereafter, Hilbert–Huang transform has been applied to the wavelet transformed signal to compare the variation of instantaneous frequencies and instantaneous amplitudes of the defect-free and defective signals.

An optical link, based on a conventional Scotch tape waveguide, for sensing applications requiring rapid on-site assembly is proposed and demonstrated. The flexible waveguide contains an integrated aluminum one-dimensional grating coupler that, when stuck on the radiative surface of a light emitting device, allows light to be coupled in and transmitted through the tape, whose tip end is, in turn, adhered onto the photosensitive surface of a photodetector. The (de)coupling approaches exhibit high alignment tolerances that permit the formation of a free-standing flexible optical connection between surface-normal optoelectronic devices without the need of specialized equipment. As the first demonstration of a sensing application, the proposed optical link is easily configured as a cost-effective intensity-based refractometric sensor for liquid detection, which can be applicable to on-site quality and process control of, for example, beverages.