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This paper offers a comprehensive critical appraisal and experimental comparison of leading linear baseline-free techniques applied in guided wave-based structural health monitoring (GWSHM). The paper extensively examines the most popular linear baseline-free techniques, namely Time Reversal (TR), Virtual Time Reversal (VTR), Instantaneous Baseline (IB), and reciprocity-based methods. Detailed discussions on the principles, strengths, and limitations of each technique provide a thorough understanding of their capabilities and challenges. Critical factors affecting performance that influence the performance of baseline-free techniques in damage detection and localization is the main focus of the paper. These factors encompass varying environmental conditions such as temperature fluctuations, geometric and structural complexities, and diverse damage scenarios. The research reported conducts experimental comparisons among VTR, IB, and reciprocity-based techniques as related to the challenging case of composite materials, considering single and dual Barely Visible Damage (BVID) scenarios, temperature variations, boundary reflections, and structural complexities like stiffeners. The results demonstrate that the investigated baseline-free techniques are capable of identifying and localizing damages, albeit with differing capabilities.
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This article presents a method to use the dispersive behavior of ultrasonic guided waves and neural networks to determine the isotropic elastic constants of plate-like structures through dispersion images. Therefore, two different architectures are compared: one using convolutions and transfer learning based on the EfficientNetB7 and a Vision Transformer-like approach. To accomplish this, simulated and measured dispersion images are generated, where the first is applied to design, train, and validate and the second to test the neural networks. During the training of the neural networks, distinct data augmentation layers are employed to introduce artifacts appearing in measurement data into the simulated data. The neural networks can extrapolate from simulated to measured data using these layers. The trained neural networks are assessed using dispersion images from seven known material samples. Multiple variations of the measured dispersion images are tested to guarantee the prediction stability. The study demonstrates that neural networks can learn to predict the isotropic elastic constants from measured dispersion images using only simulated dispersion images for training and validation without needing an initial guess or manual feature extraction, independent of the measurement setup. Furthermore, the suitability of the different architectures for generating information from dispersion images in general and an image-to-regression visualisation technique, are discussed.
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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.
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With the rapid demand for high-performance energy storage systems, lithium-ion batteries (LiBs) have emerged as the predominant technology in various applications. However, ensuring the safety and reliability of these batteries remains a critical challenge. Ultrasound-based detection, as a non-destructive and effective method for monitoring the internal state of LiBs, has gradually emerged as a valuable tool to enhance battery safety, reliability, and performance. This paper provides a review of recent advancements in the field of acoustic detection for LiBs, delving into the fundamental principles and mechanisms governing the propagation of acoustic signals within these batteries. This paper reviews the correlation between these acoustic signals and the operational status of the battery, as well as the association with internal side reactions during abnormal conditions. The strengths and limitations of current ultrasound-based detection methods are emphasized, offering insights to guide researchers, engineers, and industry professionals in advancing the field. The review aims to foster the development of robust ultrasound-based detection solutions for the next generation of energy storage systems.
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Guided ultrasonic waves can be employed for efficient structural health monitoring (SHM) and non-destructive evaluation (NDE), as they can propagate long distances along thin structures. The scattering (S0 mode) and mode conversion of low frequency guided waves (S0 to A0 and SH0 wave modes) at part-thickness crack-like defects was studied to quantify the defect detection sensitivity. Three-dimensional (3D) Finite Element (FE) modelling was used to predict the mode conversion and scattering of the fundamental guided wave modes. Experimentally, the S0 mode was excited by a piezoelectric (PZT) transducer in an aluminum plate. A laser vibrometer was used to measure the out-of-plane displacement to characterize the mode-converted A0 mode, employing baseline subtraction to achieve mode and pulse separation. Good agreement between FE model predictions and experimental results was obtained for perpendicular incidence of the S0 mode. The influence of defect depth and length on the scattering and mode conversion was studied and the sensitivity for part-thickness defects was quantified. The maximum mode conversion (S0-A0 mode) occurred for ¾ defect depth and the amplitude of the mode-converted A0 and scattered S0 modes mostly increased linearly as the defect length increased with an almost constant A0/S0 mode scattered amplitude ratio. Similar forward and backward scattering amplitude was found for the mode converted A0 mode. The mode conversion of the S0 to SH0 mode has the highest sensitivity for short defects, but the SH0 mode amplitude only increased slightly for longer defects. Employing the information contained in the mode-converted, scattered guided ultrasonic wave modes could improve the detection sensitivity and localization accuracy of SHM algorithms.
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Zero-Group-Velocity (ZGV) Lamb waves in elastic plates had been conducted extensive theoretical and experimental researches in the field of ultrasonic nondestructive testing. The ZGV modes in complex structures had been studied theoretically, but less attention had been paid to their experimental investigation. This paper reports the experimental observation of Zero-Group-Velocity Feature Guided Waves (ZGV-FGWs) in a welded joint using the pitch-catch measurement technique with air-coupled ultrasonic transducers. Firstly, for the elastic plate, it is verified that the received time-domain signal using the pitch-catch measurement method with air-coupled ultrasonic transducers is indeed ZGV Lamb waves. Subsequently, we applied the same pitch-catch measurement method with air-coupled ultrasonic transducers to receive time-domain signals at different excitation frequencies in the welded joint. It is observed that the received time-domain signals in the welded joint oscillate for extended periods of time. By performing short-time Fourier transforms on the received time-domain signals, we analyze the frequency content of the received time-domain signals at different excitation carrier frequencies. By analyzing the spectral amplitude variations of these signals at different excitation carrier frequencies, it can be demonstrated that the spectral amplitude corresponding to the resonance frequency is the largest. These findings collectively affirm that the received time-domain signals in the welded joint exhibit ZGV characteristics, identified as ZGV-FGWs. Consequently, from an experimental perspective, the presence of ZGV-FGWs in the welded joint is verified. Moreover, the experimentally determined resonance frequency of ZGV-FGWs concurs with the results obtained through simulation. This study confirms the feasibility of using the pitch-catch measurement method with air-coupled ultrasonic transducers to excite ZGV-FGWs in a welded joint and provides a reference for future experimental investigations of ZGV-FGWs in complex structures.
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This study aimed to assess the delamination detection in FMLs via the finite element (FE) simulations of Lamb wave propagation. An FE model of an FML specimen with [Al/902/Al/902/Al] layup was developed. Delamination damage of 10 and 25 mm diameters was induced between different layers of the FML specimen. The fundamental antisymmetric Lamb wave mode (A0) at 60 kHz and the fundamental symmetric Lamb wave mode (S0) at the frequency of 206 kHz were propagated on the developed FE models. The Lamb wave phase velocity was obtained from the FE models and compared with those obtained from the Lamb wave propagation tests. The sensitivity of the A0 and S0 Lamb wave modes to the delamination and its diameter were examined. The inverse Lamb wave propagation problem was then solved, and the elastic modulus of the FML specimen was estimated in the intact and delamination regions. It was observed that the phase velocity of the S0 Lamb wave mode had a higher sensitivity to the delamination damage compared to that of the A0 Lamb wave mode. The phase velocity of the A0 Lamb wave mode was more sensitive to the delamination diameter. The capability of the proposed simulated Lamb wave propagation method as a virtual lab for detecting delamination in the FMLs was confirmed.
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This study aimed to address the challenges encountered in traditional bulk wave delamination detection methods characterized by low detection efficiency. Additionally, the limitations of guided wave delamination detection methods were addressed, particularly those utilizing reflected waves, which are susceptible to edge reflections, thus complicating effective defect extraction. Leveraging the full waveform inversion algorithm, an innovative approach was established for detecting delamination defects in multi-layered structures using ultrasonic guided wave arrays. First, finite element modeling was employed to simulate guided wave data acquisition by a circular array within an aluminum-epoxy bilayer structure with embedded delamination defects. Subsequently, the full waveform inversion algorithm was applied to reconstruct both regular and irregular delamination defects. Analysis results indicated the efficacy of the proposed approach in accurately identifying delamination defects of varying shapes. Furthermore, an experimental platform for guided wave delamination defect detection was established, and experiments were conducted on a steel-cement bilayer structure containing an irregular delamination defect. The experimental results validated the exceptional imaging precision of our proposed technique for identifying delamination defects in multi-layered boards. In summary, the proposed method can accurately determine both the positions and sizes of defects with higher detection efficiency than traditional pulse-echo delamination detection methods.
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This study investigates viscoelastic guided wave properties (e.g., complex-wavenumber-, phase-velocity-, and attenuation-frequency relations) for multiple modes, including different orders of antisymmetric, symmetric, and shear horizontal modes in viscoelastic anisotropic laminated composites. To obtain those frequency-dependent relations, a guided wave characteristic equation is formulated based on a Legendre orthogonal polynomials expansion (LOPE)-assisted viscoelastodynamic model, which fuses the hysteretic viscoelastic model-based wave dynamics and the LOPE-based mode shape approximation. Then, the complex-wavenumber-frequency solutions are obtained by solving the characteristic equation using an improved root-finding algorithm, which leverages coefficient matrix determinant ratios and our proposed local tracking windows. To trace the solutions on the dispersion curves of different wave modes and avoid curve-tracing misalignment in regions with phase-velocity curve crossing, we presented a curve-tracing strategy considering wave attenuation. With the LOPE-assisted viscoelastodynamic model, the effects of material viscosity and fiber orientation on different guided wave modes are investigated for unidirectional carbon-fiber-reinforced composites. The results show that the viscosity in the hysteresis model mainly affects the frequency-dependent attenuation of viscoelastic guided waves, while the fiber orientation influences both the phase-velocity and attenuation curves. We expect the theoretical work in this study to facilitate the development of guided wave-based techniques for the NDT and SHM of viscoelastic anisotropic laminated composites.
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Structural health monitoring (SHM) of in-service structures is becoming increasingly important. The fundamental shear horizontal (SH0) guided wave mode in plate-like structures shows great potential in damage detection due to its non-dispersive and in-plane vibration properties. In order to generate SH0 waves, a practical Lorentz force-based electromagnetic acoustic transducer (EMAT) was introduced in this study using the flexible circumferential printed circuit (CPC). The designed principle of CPC-EMAT was similar to that of the circumferential magnet array (CMA)-based EMAT. However, the structure of the CMA-EMAT is complex, and it is difficult to assemble for generating high frequency and uniformly distributed omnidirectional SH0 waves. Firstly, the performance of the CMA-EMAT with different numbers of magnets was investigated by finite element simulations. Then, the CPC was proposed to replace the CMA with an optimized designed on its size. The CPC-EMAT is easier to fabricate compared to the CMA-EMAT. Finally, experimental tests were conducted for systematic validations on the transducer properties. Simulation and experimental results show that the CPC-EMAT can successfully generate the desirable and acceptable omnidirectional SH0 waves. The proposed CPC-EMAT is anticipated to find widespread application in SH-typed guided wave-based SHM.
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Health monitoring of structures using ultrasonic guided waves is an evolving technology with potential applications in monitoring pipelines, civil bridges, and aircraft components. However, the sensitivity of guided waves to external parameters affects the reliability of monitoring systems based on them. These influencing factors and experimental related factors cannot be perfectly modeled, which give rise to the discrepancy between numerical simulations and experimental measurements. Therefore, it is important to address this inevitable discrepancy and generate close-to-experiment simulations. In this work, we present a deep learning-based Digital Twin framework containing multi-fidelity modeling to reduce the discrepancy between measurements and simulations and a deep generative model to generate close-to-experiment guided wave responses by harnessing the vital characteristics of the two sources. These realistic simulations (close to experiment) can then be used in assessing the reliability of health monitoring system by generating probability of detection curves. Furthermore, they can also be used for augmenting the training data for a machine learning algorithm. We use a measurement dataset corresponding to crack propagation and simulations to validate the proposed framework. The results show that the discrepancy is indeed reduced to a great extent, furthermore, we also show that this framework enables the computation of probability of detection from close-to-experiment data as a direct consequence of rapid generation of realistic simulations.
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In this article, the practical issues connected with guided wave measurement are studied: (1) the influence of gluing of PZT plate actuators (NAC2013) on generated elastic wave propagation, (2) the repeatability of PZT transducers attachment, and (3) the assessment of the possibility of comparing the results of Laser Doppler Vibrometry (LDV) measurement performed on different 2D samples. The consideration of these questions is crucial in the context of the assessment of the possibility of the application of the guided wave phenomenon to structural health-monitoring systems, e.g., in civil engineering. In the examination, laboratory tests on the web of steel I-section specimens were conducted. The size and shape of the specimens were developed in such a way that they were similar to the elements typically used in civil engineering structures. It was proved that the highest amplitude of the generated wave was obtained when the exciters were glued using wax. The repeatability and durability of this connection type were the weakest. Due to this reason, it was not suitable for practical use outside the laboratory. The permanent glue application gave a stable connection between the exciter and the specimen, but the generated signal had the lowest amplitude. In the paper, the new procedure dedicated to objective analysis and comparison of the elastic waves propagating on the surface of different specimens was proposed. In this procedure, the genetic algorithms help with the determination of a new coordinate system, in which the assessment of the quality of wave propagation in different directions is possible.
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Ultrasonic guided wave (UGW) inspection is an emerging non-destructive testing(NDT) technique for rail flaw detection, where weak UGW signals under strong noise backgrounds are difficult to detect. In this study, a UGW signal identification model based on a chaotic oscillator is established. The approach integrates the UGW response into the critical state of the Duffing system to serve as a disturbance control variable. By evaluating the system's motion state before and after introducing the UGW response, identification of UGW signals can be realized. Thus, the parameters defining the critical state of Duffing oscillators are determined by Ke. Moreover, an electromagnetic transducer was specifically devised to enable unidirectional excitation for UGWs targeted at both the rail base and rail head. Experimental studies showed that the proposed methodology effectively detected and located a 0.46 mm notch at the rail base and a 1.78 mm notch at the rail head. Furthermore, Ke was directly proportional to the notch size, which could be used as a quantitative index to characterize the rail flaw.
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The multimodal and dispersive character of ultrasonic guided waves (UGW) offers the potential for non-destructive evaluation of fiber-reinforced composite (FRC) materials. In this study, a methodology for in situ stiffness assessment of FRCs using UGWs is introduced. The proposed methodology involves a comparison between measured wave speeds of the fundamental symmetric and antisymmetric guided wave modes with a pre-established dataset of UGW speeds and translation of them to corresponding stiffness properties, i.e., ABD-components, in an inverse manner. The dispersion relations of guided waves have been calculated using the semi-analytical finite element method. First, the performance of the proposed methodology has been assessed numerically. It has been demonstrated that each of the independent ABD-components of the considered laminate can be approximated with an error lower than 10.4% compared to its actual value. The extensional and bending stiffness properties can be approximated within an average error of 3.6% and 9.0%, respectively. Secondly, the performance of the proposed methodology has been assessed experimentally. This experimental assessment has been performed on a glass fiber-reinforced composite plate and the results were compared to mechanical tensile and four-point bending tests on coupons cut from the plate. Larger differences between the estimated ABD-components according to UGW and mechanical testing were observed. These differences were partly attributed to the variation in material properties across the test plate and the averaging of properties over the measurement area.
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Ice detection poses significant challenges in sectors such as renewable energy and aviation due to its adverse effects on aircraft performance and wind energy production. Ice buildup alters the surface characteristics of aircraft wings or wind turbine blades, inducing airflow separation and diminishing the aerodynamic properties of these structures. While various approaches have been proposed to address icing effects, including chemical solutions, pneumatic systems, and heating systems, these solutions are often costly and limited in scope. To enhance the cost-effectiveness of ice protection systems, reliable information about current icing conditions, particularly in the early stages, is crucial. Ultrasonic guided waves offer a promising solution for ice detection, enabling integration into critical structures and providing coverage over larger areas. However, existing techniques primarily focus on detecting thick ice layers, leaving a gap in early-stage detection. This paper proposes an approach based on high-order symmetric modes to detect thin ice formation with thicknesses up to a few hundred microns. The method involves measuring the group velocity of the S1 mode at different temperatures and correlating velocity changes with ice layer formation. Experimental verification of the proposed approach was conducted using a novel group velocity dispersion curve reconstruction method, allowing for the tracking of propagating modes in the structure. Copper samples without and with special superhydrophobic multiscale coatings designed to prevent ice formation were employed for the experiments. The results demonstrated successful detection of ice formation and enabled differentiation between the coated and uncoated cases. Therefore, the proposed approach can be effectively used for early-stage monitoring of ice growth and evaluating the performance of anti-icing coatings, offering promising advancements in ice detection and prevention for critical applications.
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Although guided waves offer great potential for monitoring various structures, interpreting signals from piezoelectric sensors remains a challenging task. One main reason is the significant influence of environmental conditions on the wave propagation. A lot of research has already been done on the influence of temperature effects and recently more attention has been shifted towards loads. While previous publications have mainly focused on uni- or bi-directional loads, this publication expands the developed models to include bending loads. After reviewing the analytical basis of acoustoelasticity, the derived equations are expanded to nonhomogeneous elastic bending loads using the partial wave method. The analysis is completed using recent results developed by C. Hakoda and C. J. Lissenden (2018) [1], that gave more physical insight in the propagation of guided waves in various frequency-bands. The focus of the experimental analysis is around the fundamental S0- and A0-Modes of Lamb waves. To validate the analytical results an aluminum plate is instrumented using piezoelectric transducers and loaded with varying bending loads. The experimental results are in good agreement with the analytical theory and demonstrate the influence of bending prestress on guided wave propagation. Based on these results an innovative measurement method for bending loads is developed, that is robust to small temperature changes.
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We propose an innovative deep learning (DL) regression strategy combined with guided wave modes to address inverse acoustic scattering problems effectively. This approach allows for accurate recovery of heterogeneous defect fields at the interfaces of composite laminates. The neural network (NN) model's training process employs stochastic Gaussian fields as output, which are linked to the interfacial defect fields of the physical problem. Our method assumes prior knowledge of the material geometrical properties of the constituent layers. To model the interfaces, we utilize the Quasi-Static Approximation, a technique generating position-dependent interfacial stiffness matrices containing uncoupled normal and tangential springs. We validate our approach by assessing its performance in handling noisy input data and reduced models, as well as accounting model errors at the composite interface. The obtained results show that the proposed method has a remarkable generalization capability, allowing it to recover diverse defect field profiles with accuracy. Moreover, it exhibits robustness concerning noisy data and model errors. Lastly, thanks to the guided wave modes approach, the presented methodology not only maintains its capability to recover heterogeneous defect fields potentially in real-time but also extends the range of inspection to encompass a significantly larger structural area.
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The excitation of acoustic waves by a unidirectional transducer, integrated in a piezoelectric cylindrical tube or disk, can lead to a time-independent torque. This phenomenon, demonstrated earlier in experiments and analyzed with coupling-of mode theory, is explained in detail, starting on the level of lattice dynamics of a piezoelectric crystal. Expressions are derived for the stationary torque in the form of integrals over the volume or surface of the piezoelectric, involving the electric potential and displacement field associated with the acoustic waves generated by the transducer. Simulations have been carried out with the help of the finite element method for a tube made of PZT for two cases: A pre-defined potential on the surface of the tube and metal electrodes buried in the piezoelectric. The displacement field and electric potential of the high-frequency acoustic waves (between 200 and 300 kHz) were computed and used in the evaluation of the integrals. The attenuation due to various loss channels of the acoustic waves in the system has been analyzed in detail, as this plays a crucial role for the efficiency of torque generation. It is conjectured that time-reversal symmetry, present in the absence of attenuation, prohibits the generation of a static torque at least in the linear limit. A qualitative comparison is made between the simulations and earlier experiments. Discrepancies are attributed to lack of knowledge of the relevant material constants of the piezoelectric and to a simplified modeling of the electrode geometry in the cylindrical tube, which was necessary for reasons of numerical accuracy.
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In offshore reinforced concrete (RC) structures, the phenomenon of rebar corrosion is widespread, seriously threatening the durability of the structures. However, the issue of rebar corrosion detection especially for the early corrosion situation is also challengeable. It is of great significance to use ultrasonic guided waves (UGWs) for monitoring the situation of the rebar corrosion entire process. In this paper, a mechanical model was used to establish the relationship between different rebar corrosion expansion states and layer-surface contact pressures in the layered RC components with radial cracks. Based on this model, a soft pressure-dependent contact 2D model in Abaqus was used to simulate the local corrosion layer. A linear and nonlinear signal joint analysis (LNSJA) method using PZT-based UGWs was proposed to monitor rebar corrosions, and an LNSJA-based rebar corrosion damage index (RCDI) for corroded RC components was proposed. The proposed method which can effectively detect both the micro- and macro-thickness as well as local area of rebar corrosion layer was validated by the relevant experiment and finite element analysis (FEA).
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Circumferential Shear Horizontal (CSH) guided waves provide an effective method for detecting defects like axial cracks and corrosion in pipes. Periodic Permanent Magnet Electromagnetic Acoustic Transducers (PPM EMATs) are typically used to generate CSH guided waves. However, there is an offset problem to which little attention has been paid. The offset problem refers to the offset of the center (position of maximum energy) of the operating region caused by the variation in the peak frequency of the spatial spectra of PPM with 2 or fewer cycles. Furthermore, the excitability of guided waves is one of the factors that needs to be considered when selecting the excitation parameters of EMATs, but there are still some studies that have not sufficiently addressed this issue. In this paper, the offset problem and the excitability of CSH guided waves were investigated. Firstly, by obtaining the operating regions corresponding to PPM with different cycles, the cause and influences of the offset problem were studied. The results show that the offset in the peak frequency of the spatial spectrum of PPM is the fundamental reason causing the offset problem, and it not only leads to incorrect prediction of the excitation efficiency of guided waves but also affects the selection of the excitation parameters of EMATs. Secondly, finite element simulations and experiments were performed to assess the influence of the excitability on the excitation efficiency of the CSH0 and CSH1 modes in pipes. By analyzing the simulation and experimental results of 2-cycle PPM, as well as the simulation results for PPM with 1 to 5 cycles, the impact of the excitability on the CSH1 mode was confirmed from two perspectives. The final conclusion indicates that an accurate prediction of the amplitudes of CSH guided waves with different modes is only possible through a comprehensively consideration of the operating region of EMAT and the excitability of guided waves.