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The Lamb wave-based damage imaging technique offers a novel approach for structural health monitoring. However, enhancing the accuracy of damage detection continues to pose a significant challenge. To improve the precision and reliability of defect detection and localisation in composite plates, this paper introduces and investigates the Empirical Mode Decomposition-based Adaptive Time Reversal Method (EMD-ATRM). This method integrates adaptive Tukey window inverse filtering with a data-driven advanced technique, empirical mode decomposition, to effectively mitigate noise and accurately extract the primary modes. Moreover, the enhanced time reversal method is coupled with the Improved Reconstruction Algorithm for Probabilistic Inspection of Damage (IRAPID) to achieve precise computation of damage index values and efficient execution of time-reversed imaging. Experimental results demonstrate that, compared to traditional Time Reversal Method (TRM), EMD-ATRM exhibits superior defect localisation accuracy, clearer damage images, a reduced false alarm rate, and enhanced capability in identifying damage paths and regions. This study not only provides innovative methods and tools for the structural health monitoring of composite materials but also highlights the potential applications of EMD-ATRM in industrial settings, guiding future research directions. [ABSTRACT FROM AUTHOR]

The stiffened composite panels are widely used in various engineering structures, but their nondestructive testing methods face certain limitations. The traditional wave field imaging method faces difficulties when applied for damage detection in complex composite structures. An improved adjacent wave subtraction (AWS) method is proposed in this research to visualize the multiple damage in stiffened composite panels. The method is based on the concept that the Lamb wave signals from two adjacent scanning points at healthy area are very similar and the anomalous wave, caused by the structural discontinuities including the damage, has different signal packets at any two adjacent scanning points. The ${S_0}$ mode Lamb wave signals are used in the proposed AWS method due to their faster speed in low-frequency domains. A damage index is proposed to show the signal difference of any two adjacent points, which can indicate the damage locations. A robust time window is used to enhance the anomalous wave signals and improve the damage imaging results. The prosed method is proven to be effective for damage detection in stiffened composite panels with numerical simulations and experiments. [ABSTRACT FROM AUTHOR]

The existing guided wavefield damage imaging theory is mainly Fourier transform-based wavenumber domain analysis, which essentially processes signals in a global sense and easily loses local information of structural damage. The current research on wavefield damage imaging methods focuses on flat plate-type structures, with few studies involving composite curved panels. By utilizing the ability of two-dimensional continuous wavelet transform (2D CWT) to amplify the singular components of the signal, it is introduced into spatial domain wavefield analysis to generate 2D CWT wavefields in composite curved panels. Furthermore, a damage imaging algorithm is constructed based on 2D CWT wavefield energy fusion. The results show that the algorithm can accurately image damage in composite curved panels. The novelty of this paper lies in conducting a spatial domain analysis of the guided wavefield for the purpose of damage imaging in composite curved panels. [ABSTRACT FROM AUTHOR]

Copyright of Acta Materiae Compositae Sinica is the property of Acta Materiea Compositae Sinica Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Carbon fiber reinforced plastic (CFRP) is a composite material known for its high strength-to-weight ratio, stiffness, and corrosion and fatigue resistance, making it suitable for its use in structural components. However, CFRP can be subject to various types of damage, such as delamination, matrix cracking, or fiber breakage, requiring nondestructive evaluation to ensure structural integrity. In this context, damage imaging algorithms are important for assessing the condition of this material. This paper presents signal and image processing methods for delamination characterization of thin CFRP plates using eddy current testing (ECT). The measurement system included an inductive ECT probe with three coil elements, which has the characteristic of allowing eddy currents to be induced in the specimen with two different configurations. In this study, the peak amplitude of the induced voltage in the receiver element and the phase shift between the excitation and receiver signals were considered as damage-sensitive features. Using the ECT probe, C-scans were performed in the vicinity of delamination defects of different sizes. The dimensions and shape of the ECT probe were considered by applying the erosion method in the damage imaging process. Different thresholding approaches were also investigated to extract the size of the defective areas. To evaluate the impact of this application, a comparison is made between the results obtained before and after thresholding using histogram analysis. The evaluation of damage imaging for three different delamination sizes is presented for quantitative analysis. [ABSTRACT FROM AUTHOR]

This paper presents a damage sparse imaging method using multipath-scattered Lamb waves. It leverages a large number of echoes and reverberations in the recorded signal that may be usually ignored in conventional methods. First, reflections of Lamb waves at free edges are viewed as waves transmitted from a virtual transducer which is located at the mirror point of the actual one. On this basis, an optimized transducers-layout strategy is proposed based on the multipath propagation model of the Lamb wave. Benefiting from that, the direct damage-scattered wave and several waves scattered by both the damage and edges could be separately identified in the time domain, and further, each wave could be matched with a sensing path (either actual or virtual) in the expanded sensor network. Subsequently, a dictionary is constructed from the Lamb wave propagation and scattering model. By solving the sparse reconstruction problem, the pixel value of each point in the region of interest is obtained, and the whole area can be finally visualized. The proposed method is validated using experiments conducted on an aluminum plate with simulated damages. Results show that the damages can be correctly detected and accurately localized with only a single transmitter–receiver pair. [ABSTRACT FROM AUTHOR]

Photonic synapses integrate sensing and processing within a single device, making them promising candidates for emulating the visual perception of a biological retina. Most retinomorphic photonic synapses achieve image pre‐processing by differentially responding to red, green, and blue (RGB). However, the impact of invisible ultraviolet (UV) light on the retina remains insufficiently explored, hindering the perception of the full spectrum by retinomorphic devices. Herein, a photonic synapse is constructed with strong UV absorption of Poly[(9,9‐dioctylfluorenyl‐2,7‐diyl)‐co‐(4,4′‐(N‐(4‐sec‐butylphenyl) diphenylamine)] (TFB) as photosensitive layer. The device exhibits synaptic properties of long‐term memory (LTM) and short‐term memory (STM) at different UV radiation stages. Extracting the electrical conductance of the device under UV radiation generates patterns of different resolutions, facilitating the simulation of retinal damage's impact on object perception. Moreover, an electronic eye system, incorporating the photonic synapse under UV radiation, successfully replicates pupil constriction and eye‐closing behaviors akin to those observed in a real biological eye. This result underscores the authenticity of retinomorphic devices, expending a novel concept for the future development of visuomorphic computing. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Applied Mechanics is the property of Chinese Journal of Applied Mechanics Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The damage imaging method based on Lamb wave beamforming has been widely used in the field of SHM. The DAS method has a high imaging efficiency, but its ability to suppress interference signals is weak, resulting in low imaging resolution and signal-to-noise ratio. Drawing inspiration from the adaptive weighted MVDR damage imaging method, this paper constructs a neural network based on FCNN, with the images generated by the MVDR method as the target. By training the model, the mapping relationship between delayed channel input data and adaptive weighting factors is established, thereby improving the resolution and signal-to-noise ratio of Lamb wave damage imaging and achieving rapid imaging of damage. To verify the effectiveness and imaging performance of the FCNN method, imaging of two types of damage in aluminum plates is conducted through simulation and experiments, and the imaging results are compared and analyzed with DAS and MVDR. The results show that the imaging quality and the quantitative indicators of the FCNN method have not yet reached the performance level of the MVDR, but compared with DAS, FCNN has a significantly narrower main lobe width and lower sidelobe level. Furthermore, its quantitative indicators such as API, SNR, and FWHM are better than DAS. The proposed adaptive Lamb wave beamforming method based on FCNN combines high resolution and signal-to-noise ratio, as well as the advantage of rapid imaging, providing reference and support for real-time SHM based on Lamb waves.

An integrated system is proposed to visualize subsurface barely visible impact damage (BVID) in composite structures using three-dimensional (3D) digital image correlation (3D DIC). This system uses a pair of digital cameras to record video frames in the field-of-view (FOV) of the structure's surface, capturing the wavefield generated via chirp excitation in the near-ultrasonic frequency range. Significant pitfalls of previous efforts of damage imaging using two-dimensional DIC have been largely mitigated. First, 3D DIC enables capturing out-of-plane displacements, which are much larger in amplitude versus in-plane displacements that a single camera would be limited to sensing, thus increasing the signal-to-noise ratio. This enhancement in turn increases the sensitivity of the stereo-camera system. Second, a total wave energy (TWE) damage imaging condition is proposed to visualize the local damage region. The monogenic signal obtained via Reisz transform (RT) is employed to compute the instantaneous amplitude, with which the local wave energy can be calculated spatially over time. Since a high displacement amplitude and thus high wave energy will occur in the damage region due to the local resonance, the proposed TWE imaging condition can relax the Nyquist sampling requirement, unlike guided-wave-based structural health monitoring techniques which require fully reconstructing the wavefield and wave modes through sampling that satisfies the Nyquist criterion. As such, a much lower camera frame rate is adequate for the proposed system. Consequently, the maximum spatial resolution of the camera for a given FOV can be achieved at the expense of a reduced frame rate. With the maximized pixel resolution and reduced frame rate for employing the TWE imaging condition, composite structures can be inspected or monitored with a larger FOV. As a result, there is no longer any need to apply signal enhancement techniques, such as sample interleaving, image stitching, or averaging, to increase the effective performance of the camera. Rather than needing thousands of repeated videos for minimizing the incoherent noise, only a single stereo-video with a few seconds of sampling duration is necessary for damage imaging. The use of a powerful piezo-shaker also increases the wave signal amplitude and further enhances sensitivity without permanent adhesion. To demonstrate this stereo-camera concept with the TWE imaging condition, the system was used to image damage in two carbon fiber reinforced polymer composite honeycomb panels, which had been subjected to low-velocity impacts (2 J). For each panel, two excitation configurations were used to verify the robustness of the system. Initial damage maps produced for a 100 × 100-mm FOV using a three-second stereo-video show accurate damage imaging ability that is independent of excitation location and comparable to benchmark damage images computed from laser Doppler vibrometer data and those gathered from ultrasonic and X-ray computerized tomography scans. This efficient and reliable integrated system demonstrated high potential for in-time damage inspection on composite aircraft and other critical structures. [ABSTRACT FROM AUTHOR]

In guided-wave-based damage-imaging algorithms, damage reconstruction typically involves comparing the signals with and without a defect. However, in many cases, defect-free data may not be available. Therefore, in this study, baseline and baseline-free approaches were used for damage imaging, exploiting not only the amplitude of the signal as the feature but also five additional features, namely, the amplitude of the sparse signal after deconvolution, the amplitude of the coefficients at the excitation frequency from the re-assigned short-time Fourier transform, the time of flight determined from cross-correlation, kurtosis in the time domain, and kurtosis in the frequency domain. For this study, three different plates with different types of defects were considered: a metallic plate with a notch-type artificial defect, a pultruded type of composite plate with an impact defect, and a laminate composite plate with plexiglass serving as an added mass damper artificial defect. The Reconstruction Algorithm for Probabilistic Inspection of Damage (the RAPID algorithm) was used to characterize the defects on the three plates, and the defect parameters were then quantified by creating an ellipse after thresholding. [ABSTRACT FROM AUTHOR]

In this research, to solve the problem of the ultrasonic guided wave inspection of a U-shaped boom, an improved periodic permanent magnet electromagnetic acoustic transducer (PPM EMAT) is proposed for defect detection for a U-shaped boom. The acoustic field distribution range of a traditional PPM EMAT is approximately ±20°, and the energy distribution is relatively concentrated. By adjusting the tilt angle between adjacent magnets and coils of a traditional PPM EMAT, an improved PPM EMAT is proposed. The acoustic field distribution range of the improved PPM EMAT is approximately ±30°, and the energy distribution in this range is relatively uniform. The simulation and experimental results show that the improved PPM EMAT has superior frequency response characteristics and acoustic field directivity, which is suitable for detecting large and complex structures. Furthermore, based on the traditional PPM EMAT and the improved PPM EMAT array, combined with the reconstruction algorithm for the probabilistic inspection of damage (RAPID), the damage locations of the double-hole defects of a U-shaped boom are studied. It is shown that the imaging results for defect location using the improved PPM EMATs are better than those found using the traditional PPM EMATs. [ABSTRACT FROM AUTHOR]

This paper presents a baseline-free damage imaging technique using a parallel array of piezoelectric sensors and a control board that facilitates custom combinations of sensor selection. This technique incorporates an imaging algorithm that uses parallel beams for generation and reception of ultrasonic guided waves in a pitch–catch configuration. A baseline-free reconstruction algorithm for probabilistic inspection of defects (RAPID) algorithm is adopted. The proposed RAPID method replaces the conventional approach of using signal difference coefficients with the maximum signal envelope as a damage index, ensuring independence from baseline data. Additionally, conversely to the conventional RAPID algorithm which uses all possible sensor combinations, an innovative selection of combinations is proposed to mitigate attenuation effects. The proposed method is designed for the inspection of lap joints. Experimental measurements were carried out on a composite lap joint, which featured two dissimilar-sized disbonds positioned at the lap joint's borderline. A 2D correlation coefficient was used to quantitatively determine the similarity between the obtained images and a reference image with correct defect shapes and locations. The results demonstrate the effectiveness of the proposed damage imaging method in detecting both defects. Additionally, parametric studies were conducted to illustrate how various parameters influence the accuracy of the obtained imaging results. [ABSTRACT FROM AUTHOR]

Electromechanical impedance (EMI) measurement, using piezoelectric transducers (PZTs) in the high-frequency range is a potential method for assessing the health of lightweight structures. The major objective of this work is to comprehend how different actuators react to damage in additively manufactured (AM) polymer structures. A novel frequency-range selection technique was suggested based on the maxima of the standard deviation of the impedance frequency spectra gathered for the referential and damage cases. A 3D-printed acrylonitrile butadiene styrene (ABS) plate was used for the investigation, where two PZT and one macro fiber composite (MFC) actuator were glued to the surface. Small magnets were used to simulate damage and were positioned at increasing distances from each transducer as EMI measurements were made using the MFC and 1 PZT. This served both in studying the transducers' sensitivity to damage and selecting the proper frequency range for damage detection utilizing the standard-deviation approach. The EMI-acquired data from the MFC actuator displays damage-sensitive peaks in a low-frequency band (0–58 kHz ), while the PZT shows a good sensitivity in a higher frequency range (94–304 kHz ). In order to evaluate the PZT and MFC actuators' sensitivity to damage in the 3D-printed ABS plate, impact damage is also generated in the plate's center. The impedance-based damage indices obtained from different types of PZTs (2 PZTs and 1 MFC) were projected to the same base level and then fused—for the first time—for impact-damage localization and further added magnetic mass damage localization. The obtained damage index values of impedance are encouraging for the evaluation of AM polymer structures with a 4.48 mm positional error from a real location by fusing data in the different frequency ranges for PZTs and MFC. The damage localization error increases significantly to the new location beyond the damage sensitivity range of the PZT2 and MFC for the added magnetic mass on the 3D printed structure. [ABSTRACT FROM AUTHOR]

The influence of the wavelength difference between the laser source and the phase-shifted fiber Bragg grating (PS-FBG) on the intensity of the power demodulation system based on an adjustable laser source was studied experimentally, and the optimum of the output laser wavelength was determined. Then, the research on time-frequency imaging damage identification based on smooth pseudo-Wigner-Ville distribution was carried out. The Time of Flight of the acoustic wave signal was calculated and time compensation was made according to the Wigner-Ville distribution and the Lamb wave dispersion curve. The ultrasonic waves before and after damage were measured with spatially arranged PS-FBGs. The difference signals were processed in a window, and then the time-frequency energy of the normalized difference signal was imaged to assess the damage detection and location. Although the mode and group velocity of ultrasound measured by each fiber grating were different, the accurate location and identification of artificial damage in an aluminum alloy plate was realized by using only three PS-FBGs and a smooth Wigner time-frequency imaging method.

Traditional Lamb wave inspection and imaging methods heavily rely on prior knowledge of dispersion curves and baseline recordings, which may not be feasible in the majority of real cases due to production uncertainties and environmental variations. In order to solve this problem, a two-step Lamb wave strategy utilizing adaptive multiple signal classification (MUSIC) and sparse reconstruction of dispersion reconstruction is proposed. The multimodal Lamb waves are initially reconstructed in the f-k domain using random measurements, allowing for the identification and characterization of multimodal Lamb waves. Then, using local polynomial expansion and derivation, the phase and group velocities for each Lamb wave mode could be computed. Thus, the steering vectors of all potential scattering Lamb waves for each grid in the scanning area can be established, thereby allowing for the formulation of the MUSIC algorithm. To increase the precision and adaptability of the MUSIC method, the local wave components resulting from potential scatters are extracted with an adaptive window, which is governed by the group velocities and distances of Lamb wave propagation. As a result, the reconstructed dispersion relations and windowed wave components can be used to highlight the scattering features. For the method investigation, both a simulation and experiment are carried out, and both the dispersion curves and damage locations can be detected. The results demonstrate that damage localization is possible without theoretical dispersion data and baseline recordings while exhibiting a considerable accuracy and resolution. [ABSTRACT FROM AUTHOR]

• A tailor-made cylindrical concrete implantable module (CCIM) was proposed for damage perception in plate-like concrete structures. • The CCIM can be directly implanted into inspected structure to transmit and receive probing stress waves using pulse-echo manner, which allows conveniently removing and updating the CCIM when the devices failed to work. • A CCIM-based multiple signal classification (MUSIC) algorithm is proposed to realize two-dimensional damage visualization in a fusion strategy manner. In this research, a tailor-made cylindrical concrete implantable module (CCIM) was proposed for damage imaging in concrete structures. The CCIM can be directly implanted into inspected structure to transmit and receive probing stress waves, which allows conveniently removing and updating CCIM when devices failed to work. Moreover, a CCIM-based multiple signal classification (MUSIC) algorithm is proposed to realize two-dimensional damage visualization. Based on meso-level finite element simulation, considering concrete as a three-phase composite material, the stress wave propagation characteristics can be revealed and the effectiveness of CCIM-based MUSIC imaging method has been investigated. To verify the proposed method experimentally, a pair of CCIMs were fabricated and implanted into two concrete specimens with different configurations. The results could effectively pinpoint damage location within inspected area. The proposed hardware and algorithm has great potential to overcome the disadvantage of short service period and could be applied for damaging imaging in concrete structures. [ABSTRACT FROM AUTHOR]

• A Lamb wave based damage imaging method for variable thickness plates is proposed. • Damage localization is achieved in variable thickness aluminum plates. • A prediction model for scattering signals in variable thickness plates is developed. The researches on Lamb wave based damage localization for constant thickness plates have been widely investigated in the field of structural health monitoring, while the issue of Lamb wave based damage imaging in variable thickness plates is rarely addressed. This is because the Lamb wave propagation characteristics in plates with varying thickness is more complex than that with constant thickness. In this study, a Lamb wave based damage imaging method using a sensor array is proposed for damage localization in variable thickness plates. In the process of point-by-point imaging within the interested imaging area, a signal back-propagation operator based on a Lamb wave propagation model can deal with the problem of dispersion compensation for Lamb waves propagating in variable thickness plates. The Lamb wave propagation model, which is based on the assumption that Lamb waves propagating in a variable thickness plate can be seen as that propagating in a sequence of short and constant thickness plates with different thicknesses, can predict Lamb wave response waveform in variable thickness plates. Numerical simulations and experiments on aluminum plates with linearly varying thicknesses are implemented, and the imaging results validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The main goal of this study was non-destructive evaluation of wooden elements using ultrasonic waves. The inspection was carried out on wooden beams from a historical object. Elastic wave signals were processed by ultrasonic transmission tomography to obtain imaging of the internal structure of tested elements without disturbing their state and integrity. The focus was on the influence of wood anisotropy on the propagation of ultrasonic waves. A novel method of determining the position of the cross-section pith was proposed. The study presented that the proposed imaging approach was capable to assess the technical condition of historic wooden beams by determining the degree of wood damage and the location of discontinuities, scratches or fibrosis in the tested cross-section. [ABSTRACT FROM AUTHOR]

The amplitude and the phase information are both important for damage localization in Lamb wave–based structural health monitoring and non-destructive testing. Most previous studies in Lamb wave imaging are only based on either the amplitude or phase of the signal at the time of flight. In this study, a post-processing technique for Lamb wave phased array imaging is proposed for isotropic plates, which simultaneously utilizes both the amplitude and phase information within a small neighborhood centered at the time of flight. In the proposed imaging algorithm, a modified virtual time reversal is firstly implemented to compensate for dispersion and the amplitude decrease caused by wave diffusion. Then the waveform covariance between any two processed wave packets, which contains information of both amplitude and phase, is used as the indicator of the presence of damage. Finally, adaptive weights based on minimum variance are introduced to weight and sum the waveform covariance for damage imaging. Based on a uniform circular array, experimental results on an aluminum plate with three defects verify that the proposed algorithm is capable of localizing multiple defects, suppressing background noise and main lobe width. [ABSTRACT FROM AUTHOR]

Structural health monitoring (SHM) techniques are widely used in industry applications to guarantee the integrity of several types of components. Ultrasonic guided wave (GW) methods for damage imaging typically use baseline signals from the undamaged component, which are often affected by real operational conditions and may not always be available. This article proposes a baseline-free damage imaging algorithm based on spatial frequency domain virtual time reversal (SFD-VTR). Virtual time reversal (VTR) is an alternative to traditional time reversal as it reduces the burden of physically back-propagating re-emitted signals by applying signal operations between the transmitted and received waveforms. However, VTR relies on the reconstruction of the emitted signal in the time domain, which involves significant data manipulation causing sampling errors of reconstructed signals. These errors are largely manifested in nonstationary transient phenomena, such as GW propagation and may lead to poor damage detection. Novel SFD-VTR damage indices were here proposed to enhance defect detection as they do not require the time domain reconstruction of re-emitted signals. Therefore, this work develops a new baseline-free algorithm for damage detection based on a mathematical model of acoustic emission wave propagation for a network of emitter-receivers. The algorithm was validated in aluminum and composite specimens, and it was able to localize material flaws with a maximum localization error of ∼6 mm and ∼2 mm for the aluminum and composite samples, respectively, proving to be a promising alternative to SHM systems. Besides, this new mathematical model optimized the traditional methodologies by excluding signal emissions from the setup, and digital signal processing steps. [ABSTRACT FROM AUTHOR]

• A Lamb wave imaging method via dual-frequency fusion is proposed. • This method effectively compensates for the grating lobe effect. • This method improves positioning accuracy with higher excitation frequencies. In Lamb wave imaging based on a phased array, higher frequencies narrowband excitation pulses enable more precise damage detection and localization. However, due to the size constraints of individual transducer elements, the spacing between array elements may exceed half the wavelength of the excitation signal. This can lead to a grating lobe effect. To overcome this limitation, a Lamb wave imaging method via dual-frequency fusion for grating lobe effect compensation is proposed in this study. Analyses indicate that the grating lobe effect may introduce artifacts or distortions in the imaging results. This method utilizes two frequencies of narrowband excitation pulses for imaging and subsequently fuses the results. By doing so, the imaging artifacts caused by the grating lobes produced by high-frequency narrowband excitation pulses are effectively compensated. The proposed method is validated through simulations and experiments on an aluminum plate, showing superior accuracy, contrast, and imaging quality. [ABSTRACT FROM AUTHOR]

• A global–local approach for damage localization and imaging in beam structures is formulated. • Damage-induced relative natural frequency change curves are derived analytically and then used for global damage localization. • A TKEO-wavelet-wavefield analysis method is created for local damage imaging in the spatial domain. • The global–local approach offers high accuracy and efficiency in damage imaging by reducing wavefield measurements by 80%. The guided wavefield-based damage imaging methods have been the subject of extensive research. It is commonly recognized that these methods are time-consuming due to measurements of high-resolution guided wavefields. To address this challenge, this paper introduces a global–local damage localization and imaging approach in beam structures. Firstly, a global damage indicator is developed to identify possible damage locations through the analysis of relative natural frequency change curves. Subsequently, inspections of these possible damage locations are conducted using guided wavefields. To process the laser-measured wavefields, wavelets are employed in conjunction with a Teager-Kaiser energy operator (TKEO), resulting in the generation of TKEO-wavelet-wavefields. The multi-scale property of the TKEO-wavelet-wavefields helps minimize measurement noise and enhance the detection of damage-related wavefield anomalies, thereby improving the accuracy of the inspection process. Experimental results demonstrate that the global–local approach exhibits high accuracy and efficiency in damage imaging, while reducing wavefield measurements by 80%. [ABSTRACT FROM AUTHOR]

The Lamb-wave-based damage imaging via beamforming techniques, which can visualize the location of damage in the structure intuitively, is one of the most promising methods in the field of structural health monitoring (SHM). However, transducer array position errors are inevitable in practical application, which may lead to serious degradation in imaging performance. In this study, it is shown that the uncertainty of the steering vectors led by the imprecise position of transducers in an array can be suppressed by the doubly constrained robust Capon beamformer (DCRCB). After the unwanted side lobes are restrained by the DCRCB-based coherence factor (CF) weighting, an effective adaptive beamforming damage imaging method robust to transducer position errors is proposed. The numerical simulation and imaging experiment of damage on an aluminum plate are carried out to verify the effectiveness of the proposed algorithm. The results show that the proposed Lamb wave damage imaging method performs better than the reported beamforming ones in literature in terms of resolution, contrast, and robustness to transducer position errors. [ABSTRACT FROM AUTHOR]

This paper proposes a phase-reversal method (PRM) for damage imaging in plate structures. The PRM is a novel Lamb-wave-based method that mainly focuses on phase spectrum information of scattering waves reflected from a defect. The PRM reverses the phase angle along the propagation path by using the inverse Fourier transform first, and then the reversal reconstruction of the wave field in the frequency domain is performed for damage imaging. The proposed method analyzes the scattered wave field without using the baseline data and structural parameters. Moreover, dispersion characteristics and anisotropy are not involved in the process of damage positioning, thus making the PRM suitable for damage monitoring of composite laminates. To improve the PRM accuracy further, a combined addition and multiplication method of the correlation coefficient (CAMM) is proposed, which can reduce the effects of phase and noise artifacts and distortion. The results of the finite element simulations and experiments show that the combination of the PRM and CAMM methods can accurately locate damage in composite structures. Therefore, the PRM and CAMM methods have great application potential in damage imaging in composite laminates. [ABSTRACT FROM AUTHOR]

In this paper, a damage quantification strategy relying on post-processing of Lamb wave based damage localization results is presented. This method is able to predict the upcoming sizes of a delamination after a training step. Inputs of the proposed method are localization index maps produced by damage localization algorithms and representing the presence likelihood of a damage over the structure under study. The area covered by a high localization index around the estimated damage location are then extracted from these spatial probability maps. A data-driven model representing the mathematical relationship between this quantification feature and the actual size of the damage is finally inferred and used to predict future damage size. The proposed method is successfully validated on experimental data coming from CFRP plate samples equipped with piezoelectric transducers. Delaminations induced by fatigue testing and laser shock are studied. The sensitivity of the method to input frequency and damage localization algorithms parameters is assessed and a method to automatically select its own parameters is proposed. Furthermore, it is demonstrated that a model can be confidently learned on a given CFRP plate sample and transferred to predict damage size on another similar CFRP plate sample. [ABSTRACT FROM AUTHOR]

The electromechanical impedance (EMI) method has shown its damage detection capability for lightweight structures due to its damage sensitivity. In this paper, a new technique based on the uniform sensor network for multiple damage localization was proposed. The EMI-based damage indices were obtained from several piezoelectric transducers and fused for multiple-damage localization for the first time in literature. In the proposed approach, the sensor sub-network selection employs the vertices of a triangle based on the calculated sensing region radius. The method employs sub-networks to allow multiple damage sites localization without prior information about the number of damage sites to be found. These sub-networks approaches were applied to detect and localize the two and three damaged sites simultaneously. The glass fiber reinforced polymer (GFRP) and 3D-printed acrylonitrile butadiene styrene (ABS) plates were used for the investigation, with surface-bonded piezoelectric transducers (PZTs). Magnets were used to simulate multiple-damage positions, and drilled holes were used as more realistic multiple-damage. In the investigated cases the EMI data displays damage-sensitive peaks in a frequency range of 1 kHz to 200 kHz. The results show successfully the detection and localization of multiple-damage sites in additively manufactured (AM) polymer and fiber-reinforced composite plates. It was observed that the damage localization error increases significantly with the new damage introduced in the structures. [ABSTRACT FROM AUTHOR]

Copyright of Acta Materiae Compositae Sinica is the property of Acta Materiea Compositae Sinica Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper proposes a phase-reversal method (PRM) for damage imaging in plate structures. The PRM is a novel Lamb-wave-based method that mainly focuses on phase spectrum information of scattering waves reflected from a defect. The PRM reverses the phase angle along the propagation path by using the inverse Fourier transform first, and then the reversal reconstruction of the wave field in the frequency domain is performed for damage imaging. The proposed method analyzes the scattered wave field without using the baseline data and structural parameters. Moreover, dispersion characteristics and anisotropy are not involved in the process of damage positioning, thus making the PRM suitable for damage monitoring of composite laminates. To improve the PRM accuracy further, a combined addition and multiplication method of the correlation coefficient (CAMM) is proposed, which can reduce the effects of phase and noise artifacts and distortion. The results of the finite element simulations and experiments show that the combination of the PRM and CAMM methods can accurately locate damage in composite structures. Therefore, the PRM and CAMM methods have great application potential in damage imaging in composite laminates.

The full wavefield detection method based on guided waves can efficiently detect and locate damages relying on the collection of large amounts of wavefield data. The acquisition process by scanning laser Doppler vibrometer (SLDV) is generally time-consuming, which is limited by Nyquist sampling theorem. To reduce the acquisition time, full wavefield data can be reconstructed from a small number of random sampling point signals combining with compressed sensing. However, the random sampling point signals need to be obtained by adding additional components to the SLDV system or offline processing. Because the random sparse sampling is difficult to achieve via the SLDV system, a new uniform sparse sampling strategy is proposed in this paper. By using the uniform sparse sampling coordinates instead of the random spatial sampling point coordinates, sparse sampling can be applied to SLDV without adding additional components or offline processing. The simulation and experimental results show that the proposed strategy can reduce the measurement locations required for accurate signal recovery to less than 90% of the Nyquist sampling grid, and the damage location error is within the minimum half wavelength. Compared with the conventional jittered sampling strategy, the proposed sampling strategy can directly reduce the sampling time of the SLDV system by more than 90% without adding additional components and achieve the same accuracy of guided wavefield reconstruction and damage location as the jittered sampling strategy. The research results can greatly improve the efficiency of damage detection technology based on wavefield analysis. [ABSTRACT FROM AUTHOR]

This article presents a multipath Lamb wave imaging method that leverages the extra reflections present in the recorded ultrasonic waveforms for structural prognosis. Under the ray acoustic approximation, an edge behaves like a mirror, which changes the propagation path of a wave and provides more views of the damage than can be obtained from direct scattering. To accommodate for these extra reflections, the scattering path of each wave in the residual signal is simplified as a direct scattering path from an actual or virtual transmitter (created by edge mirroring) to the damage, and then back to an actual or virtual receiver (created by edge mirroring). On this basis, the Gaussian distribution function is introduced to quantify the probabilities at each spatial node in relation to all possible damage loci. Through fusing the images obtained from all individual wave packets, the structure could be inspected with far fewer transducers compared to conventional elliptical imaging. Experimental results from carbon fiber-reinforced polymer laminates and aluminum plate are provided to illustrate the effectiveness of the imaging method, where damage is correctly detected and accurately localized even with a single transmitter–receiver pair. [ABSTRACT FROM AUTHOR]

A key to successful damage diagnostics and quantification is damage imaging through ultrasonic guided wave tomography. We propose the implementation of least-squares reverse-time migration in a circular array for damage imaging in an aluminum plate. The theory of least-squares reverse-time migration is formulated for guided wave applications along with the summary of an efficient optimization algorithm: the conjugate gradient method. Numerical simulation and laboratory experiments are used to evaluate its performance with a circular array setup. In order to improve the data processing efficiency, the concept of using a limited number of actuators but a relatively large number of sensors is tested. Studies are conducted on three numerical cases, including a rectangular-shaped damage site, a complex-shaped damage site, and six other damage sites varying in size. As an inversion-based method, least-squares reverse-time migration shows significantly improved shape reconstruction with the amplitude quantification capability, compared to conventional reversetime migration. Our experimental data are generated by piezoelectric wafers as actuators, measured by a scanning laser Doppler vibrometer to form a circular array on an aluminum plate, with a rectangular notch located in the inner region of the array. The damage images using experimental data show consistency in both the simulations using Born scattering and in altered material properties in the damaged region. According to the comparison, least-squares reverse-time migration for guided wave tomography is a promising technology to provide high-resolution large area damage imaging for plate-like structures. [ABSTRACT FROM AUTHOR]

A novel method combining the time-reversal method (TRM) with wavelet analysis was proposed for damage imaging in mesoscale concrete modeling. The damage was imaged by the convergence of time-reversed wave signals after wavelet analysis. Through numerical study, three concrete models of different damage sizes were built with randomly distributed aggregate particles. The time-reversal process was simulated using the reverse damage-scattered ultrasonic wave signals as excitations recorded by the sensors. Then, the wavelet analysis was employed to extract certain frequency component, which can enhance detection precision and the signal-to-noise ratio. The damage imaging showed clearly the location of the defect. The results from experimental testing also demonstrated that this detection technique is an efficient and effective method for damage imaging in mesoscale concrete. [ABSTRACT FROM AUTHOR]

Air-coupled ultrasonic Lamb wave damage imaging is a method for rapid, non-contact damage detection of plate specimens. However, the current technique based on Lamb waves has limitations regarding accuracy and quality of imaging. To address this issue, an improved bilateral boundary-enhanced reconstruction algorithm for the probabilistic inspection of defects (BBERAPID) is proposed. This algorithm optimizes the probability distribution near the damage boundary to enhance the accuracy of damage imaging. The skewed bilateral boundary distribution algorithm can improve the probability distribution of edges on both sides of the damage and alleviate the problem of abnormal boundary expansion. In addition, a new damage index (DI) calculation method is proposed to accelerate the DI trend near the damage. The new DI can improve the fineness of the damage boundary, thus better distinguish the healthy area from the damage area. Traditional DI has the problem of abnormal distribution at the damage boundary, which BBERAPID solves. The probability distribution near the damage is optimized to improve the quality and accuracy of damage imaging. Experimental studies are performed using composite plates to validate the proposed method further. The effectiveness and accuracy of the proposed BBERAPID algorithm for detecting damages in composite plates are verified by comparing it with existing imaging methods through experimental validation. The proposed non-contact air-coupled Lamb wave damage imaging method is suitable for rapidly and accurately characterizing defects in composite plates. [ABSTRACT FROM AUTHOR]

• An ultrasonic guided waves imaging method based on particle swarm optimization is proposed, and the damage location of composites is realized by target optimization. • The fitness function for damage imaging is designed according to the difference between the time of flight of the scattering signals and the time of flight of the particles. • The proposed method can effectively detect the crack damage of composites, reduce the imaging artifacts and improve the damage localization accuracy. The anisotropy of composites aggravates the dispersion and multimodal characteristics of ultrasonic guided waves propagating in them. At present, most damage imaging methods are prone to inaccurate positioning, artifacts and false imaging when used in composites damage detection. Therefore, an ultrasonic guided waves imaging method based on particle swarm optimization (PSO) is proposed in this paper, and the damage location of composites is realized by target optimization. The fitness function for damage imaging is designed according to the difference between the time of flight (ToF) of the scattering signals and the ToF of the particles. The fitness function is used to evaluate the population, and the particle swarm is finally converged to the damage location through iteration. Damage imaging is realized by drawing the binary histogram of particles position. The experimental results show that the proposed method improves the damage location accuracy compared with the elliptic imaging method and the velocity anisotropy probability imaging method. Compared with the imaging method based on genetic algorithm, the proposed method has faster convergence speed and stronger robustness. [ABSTRACT FROM AUTHOR]

Lamb waves have multimodal and dispersion effects, which reduces their performance in damage localization with respect to resolution. To detect damage with fewest sensors and high resolution, a method, using only two piezoelectric transducers and based on orthogonal matching pursuit (OMP) decomposition, was proposed. First, an OMP-based decomposition and dispersion removal algorithm is introduced, which is capable of separating wave packets of different propagation paths and removing the dispersion part successively. Then, two simulation signals, with nonoverlapped and overlapped wave packets, are employed to verify the proposed method. Thereafter, with the proposed algorithm, the wave packets reflected from the defect and edge are all separated. Finally, a sparse sensor array with only two transducers succeeds in localizing the defect. The experimental results show that the OMP-based algorithm is beneficial for resolution improvement and transducer usage reduction.

In this paper, a damage imaging method for 2-D concrete structures is proposed by employing embedded tubular piezoceramic transducers. The proposed method can image the damages when few numbers of transducers are used or less experimental data is collected. First, the time difference of arrival-based delay and sum (DAS) imaging method is adopted to improve the damage localization accuracy for concrete structural health monitoring. Compared with the conventional DAS imaging algorithm, the proposed method increases the potential number of combinations between the response signals induced by the damage in each transmitter and sensor pair, improving the signal to noise ratio of the imaging map and enhancing the performance of the defect detection and location. Second, to enable the proposed method applicable to a 2-D concrete structure (such as cement concrete pavement and shear walls), embeddable tubular lead zirconate titanate (PZT) transducers rather than conventional PZT patches are used. The new tubular PZT transducers are able to generate radially uniform stress waves in a planar concrete structure. Due to the special construction of the tubular PZT transducers, the detection aperture is significantly improved. Therefore, a few transducers are needed in contrast with the conventional PZT patches. The experimental results conducted on a concrete slab with eight embedded tubular PZT transducers demonstrate that the proposed method can predict the defect accurately and efficiently even with few transducers and less experimental data.

Nondestructive evaluation of carbon fiber reinforced material structures has received special attention in the last decades. Usage of Ultrasonic Guided Waves (UGW), particularly Lamb waves, has become one of the most popular techniques for damage location, due to their sensitivity to defects, large range of inspection, and good propagation in several material types. However, extracting meaningful physical features from the response signals is challenging due to several factors, such as the multimodal nature of UGW, boundary conditions and the geometric shape of the structure, possible material anisotropies, and their environmental dependency. Neural networks (NN) are becoming a practical and accurate approach to analyzing the acquired data using data-driven methods. In this paper, a Convolutional-Neural-Network (CNN) is proposed to predict the distance-to-damage values from the signals corresponding to a transmitter-receiver path of transducers. The NN input is a 2D image (time-frequency) obtained as the Wavelet transform of the acquired experimental signals. The distances obtained with the NN are the input of a novel damage location algorithm which outputs a bidimensional image of the structure’s surface showing the estimated damage locations with a deviation of the actual position lower than 15 mm.

Lamb wave-based damage imaging is a promising technique for aircraft structural health monitoring, as enhancing the resolution of damage detection is a persistent challenge. In this paper, a damage imaging technique based on the Time Reversal-MUltiple SIgnal Classification (TR-MUSIC) algorithm is developed to detect damage in plate-type structures. In the TR-MUSIC algorithm, a transfer matrix is first established by exciting and sensing signals. A TR operator is constructed for eigenvalue decomposition to divide the data space into signal and noise subspaces. The structural space spectrum of the algorithm is calculated based on the orthogonality of the two subspaces. A local TR-MUSIC algorithm is proposed to enhance the image quality of multiple damages by using a moving time window to establish the local space spectrum at different times or different distances. The multidamage detection capability of the proposed enhanced TR-MUSIC algorithm is verified by simulations and experiments. The results reveal that the local TR-MUSIC algorithm can not only effectively detect multiple damages in plate-type structures with good image quality but also has a superresolution ability for detecting damage with distances smaller than half the wavelength.

It is highly probable for the structures of carbon fiber reinforced plastics (CFRP) to suffer from invisible impact damage, for which the identification of such damage is of great significance. For the purpose of damage localization, this paper proposes a minimum variance distortion-less response (MVDR) algorithm that employs linear array sensor. In addition, a near field signal model based on active Lamb wave is established and the propagation of Lamb wave is investigated in composite laminates through the method of simulation. Moreover, a damage imaging system is also set up for composites to verify the effectiveness of the MVDR algorithm. Besides, in the study, wavelet transform is used as well to extract narrowband signals and promote signal-to-noise. It is shown by the results that the proposed algorithm can accurately identify the location of damage through the method of imaging. It is concluded that the maximum error of damage identification is 1.2 cm and MVDR algorithm has great potential in the field, damage imaging of composite materials. As a result, it provides a novel idea for damage imaging of composite materials. [ABSTRACT FROM AUTHOR]

Estimation of damage position and extent in the inspected structure is among the emerging problems of active structural health monitoring (SHM) with elastic guided waves. Unlike conventional non-destructive testing (NDT) techniques, which assume continuous surface scanning, SHM systems operate only with data from a limited number of sensors. Nevertheless, in the case of isotropic (metal) plate-like structures, computational time-reversal techniques have proved to be effective for estimating in situ the location and size of wave sources and/or local scatterers within the SHM concept. With composite plates, the reconstruction procedure faces additional difficulties associated with the complexity of wave phenomena caused by their lamination and anisotropy. In this article, we present an extension of the time reversal technique for the case of composite laminate plate-like structures. This technique relies on the simulation of the reversed guided waves generated by reciprocal surface loads applied at a sparse set of measurement points of a real sensor network. The proposed implementation is based on the far-field asymptotics for guided waves generated in arbitrarily anisotropic laminate waveguides by a prescribed source, which have been derived from the path integral representations in terms of Green's matrix for the structures considered. The performance of this approach has been experimentally tested on cross-ply carbon fiber-reinforced plastic plates showing reliable and adequate results for both active (piezoactuators) and passive (artificial defects) source characterization. [ABSTRACT FROM AUTHOR]

In practical structural health monitoring with Lamb waves, the signal spatial resolution is usually restricted by not only dispersion but also the space duration of excitation waveforms, that is, the initial spatial resolution for the signals before traveling. As a result, the final resolution and accuracy of damage identification could be badly impaired. To overcome this problem, a signal domain transform method is presented in this article. In signal domain transform, the original dispersive Lamb wave signals are transformed from the time to distance domains, with the time–distance scaling on the excitation waveforms particularly modified. Then, both dispersion compensation and initial spatial resolution enhancement can be actualized to efficiently improve the signal spatial resolution. Considering the practical situation that the structural property parameters could be unavailable to theoretically derive the requisite wavenumber relations, signal domain transform with synthetically measured relative wavenumber curves is further explored. After the frequency domain representation and spatial resolution of Lamb wave signals are basically analyzed, the principle and numerical realization of signal domain transform are investigated. Hereafter, the synthetic measurement of relative wavenumber curves for signal domain transform is discussed and preliminarily validated in an aluminum plate. Finally, signal domain transform is applied for high-resolution imaging of adjacent multiple damages. The efficiency of signal domain transform and signal domain transform–based imaging methods has been well demonstrated by the experimental study on a glass fiber–reinforced composite plate with unknown material parameters. [ABSTRACT FROM AUTHOR]