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The complex design of composite structures makes it very difficult for conventional visual inspection techniques to detect defects in these materials. Therefore, numerous types of nondestructive testing and structural health monitoring techniques have been developed for damage identification in composite structures, among which ultrasonic guided waves, particularly Lamb waves, have gained much popularity. In recent years, apart from piezoelectric pointwise measurements, laser Doppler vibrometry has been used for full wavefield measurements of propagating Lamb waves. Damage imaging can be done with animations of Lamb waves interacting with defects. In this work, two end-to-end deep learning-based models of many-to-one sequence prediction were developed to perform pixel-wise image segmentation. A large dataset of full wavefield images resulting from the interaction with delamination of random size, shape, and location was utilised to train the proposed deep learning models. The main goal of this work is to investigate the feasibility of implementing deep learning methods for delamination identification in composite laminates by only utilising the animations of Lamb waves. The elaborated models worked well on the numerically generated test data and have also shown good performance on the real-world experimental data. These methods can enable the automation of delamination identification and to create damage maps without the intervention of the user. [ABSTRACT FROM AUTHOR]

Ultrasonic guided wave is a promising technique for structural health monitoring and nondestructive testing. However, due to the anisotropy and complexity of composite materials, the imaging performance of numerous signal processing methods deteriorates with significant artifacts and unsatisfactory accuracy. To obtain a better damage imaging performance of Lamb waves in noisy and noise-free conditions, a weighted delay-and-sum (DAS) imaging method based on denoising autoencoder (DAE) learning is developed for complex composite structures. The traditional DAS formulation is modified to be more compatible with anisotropic materials. The DAE with feature learning capability is then employed to extract potentially efficient features and remove noise from ultrasonic signals. Several verification experiments conducted on flat or curved and stiffened composite structures have confirmed the ability of the DAE-DAS method to suppress artificial noise and to intensify singularities induced by the anomalies. By comparing with the unweighted DAS methods and the weighted DAS method without feature extraction, the proposed algorithm has satisfactory robustness to achieve higher localization accuracy and fewer artifacts. [ABSTRACT FROM AUTHOR]

The formation of dendrite affects the cycling life of a battery and lead to malfunctions such as internal short-circuiting and thermal runaway events. However, existing methods to observe dendrite formation, such as X-ray computed tomography and scanning electron microscopy are either prohibitively complicated or unsuitable for long-term, in-situ monitoring. In this study we present a method which uses the fundamental shear-horizontal mode (SH0*) guided ultrasonic waves to independently monitor the status of the electrodes in a symmetric aqueous zinc-ion battery. Experimental measurements show that the velocity and attenuation of the ultrasonic wave on the opposing electrodes vary in the opposite senses during the cycling. While the velocity and attenuation changes can be partially reversed, a monotonic drift can also be observed with increasing number of cycles. Coupled with optical microscopy, the partially reversible oscillations can be associated with zinc stripping/plating. The irreversible drifting can be associated with the formation of 'dead' zinc dendrite. The technique shows clear sensitivity to the formation of dendrite, especially in the early stages (∼ 10 cycles) of charging and discharging processes. This work should inspire future research to enable quantitative assessment of the technique sensitivity and to improve its resolution. [Display omitted] • Dendrite formation on electrode surfaces is a key degradation process in batteries. • A novel technique for in-situ monitoring of dendrite formation is presented. • Properties of guided ultrasonic waves are affected by the dendrites. • Technique delivers quantitative insights into battery degradation processes. [ABSTRACT FROM AUTHOR]

[Display omitted] • Instantaneous phase characteristics of guided waves contain a rich source of information for defect characterisation. • Gaussian process regression technique is capable of predicting the real defect depth with a large-scale simulated dataset. • Gaussian process regression can successfully estimate the depth of wide defects (≥100% of wavelength) in practice. Ultrasonic Guided Waves (UGW) offer the possibility of inspecting a strip across a structure rather than just the point under a traditional bulk wave transducer. This can increase the rate of inspection and enable inspection under obstructions. This paper investigates the instantaneous phase characteristics of the shear horizontal guided waves for various defect depths and widths. The Gaussian process regression is then evaluated for estimating the minimum remaining wall thickness between a pair of transducers. A Gaussian process regression model is built using the fusion of large-scale simulated and low-scale real experimental data. For this purpose, a more precise model of an electromagnetic acoustic transducer is initially built by integrating both electromagnetic and elastic wave fields. Then the simulated data set is built after having been calibrated using a genetic algorithm. The examination of an unseen simulated evaluation data set shows that 96 % of data has an error during thickness gauging of less than 10 per cent of wall thickness. Finally, an experimental testing data set containing three different defects with depths of 3.7, 5.7 and 9.2 mm was examined, resulting in a good depth prediction of large defects with less than 1 mm error for defects wider than one wavelength. [ABSTRACT FROM AUTHOR]

In view of the high sensitivity to microstructure evolution of higher harmonics generated by the nonlinear ultrasonic method, the tensile damage in the stainless steel AISI 316L was evaluated by nonlinear ultrasonic Lamb wave. The effect of different degree of tensile deformation on nonlinear ultrasonic response in 316L was analyzed by considering the microstructure evolution and the test results. First, the power-law relation of nonlinear ultrasonic parameter and plastic strain is proposed. Meanwhile, martensitic transformation and the increasing of dislocation density can be observed in the micrographs of specimens with the increase of plastic deformation. Then, the same variation tendency of intergranularly averaged Kernel Average Misorientation (KAM), as well as the relative nonlinear ultrasonic parameter, demonstrated that the nonlinearity due to tensile damage is controlled by the evolution of microstructure that directly affects higher order elastic constant of stainless steel 316L. Furthermore, based on continuous damage mechanics, the method quantitatively characterizes the degradation of mechanical properties was proposed with a functional relation of damage variable and relative nonlinear parameter. The method proposed in this study provides a theoretical basis for online monitoring of the damage status of in-service equipment. It is of great significance for residual life assessment, structure integrity assessment, and service life extension of equipment. • A non-destructive method using nonlinear ultrasonic Lamb wave to detect tensile damage is introduced for AISI 316L. • The power-law relation of nonlinear ultrasonic parameter and plastic strain is observed. • The method quantitatively characterizes the degradation of mechanical properties is proposed with nonlinear parameter. • The effects of different degrees of tensile test on the evolution of the microstructures are examined. [ABSTRACT FROM AUTHOR]

• Spectral FEM within the bi-potential framework is developed for modeling CAN. • A semi-explicit algorithm is proposed to facilitate high computational efficiency. • Contact force can be calculated by bi-potential method without defined parameters. • Computational efficiency of the proposed method is much higher than that of FEM. • The proposed method can capture classical contact acoustic nonlinearity features. Nonlinear ultrasonic guided waves are of great importance in structural health monitoring, since they have both the large-area inspection capability of guided waves and the desirable sensitivity to incipient defects from nonlinear ultrasonic features. Efficient numerical methods play a key role in investigating the nonlinear features of guided waves. In this work, a time domain spectral finite element method (TDSFEM) combined with the bi-potential contact theory is developed to capture the nonlinear interactions between guided waves and breathing cracks. The bi-potential approach has better accuracy than the conventional penalty method, since there is no any user-defined parameter for computation in the former method while the latter one requires a user-experience-based penalty factor. In addition, a semi-explicit algorithm is proposed to integrate the wave equation, which can take full advantage of the diagonal mass matrix of TDSFEM while not sacrificing numerical stability. Numerical verifications against ANSYS show that the computational efficiency of the bi-potential method-based TDSFEM is much higher than that of the FEM via the penalty method. Numerical case studies are then performed to investigate the nonlinear interactions between Lamb waves and breathing cracks. Results show that the proposed method can successfully capture the classical nonlinear features, such as higher harmonic generation and zero frequency (DC) response. Moreover, the influence of the length and gap of a breathing crack on the contact acoustic nonlinearity (CAN) is investigated. As an efficient numerical approach, the bi-potential method-based TDSFEM may be a good tool for investigating the CAN. [Display omitted] [ABSTRACT FROM AUTHOR]

In ultrasonic guided wave inspections, incident waves propagate as a finite-bandwidth wave packet. During propagation, the shape of the wave packet is distorted because of dispersion even if there are no viscous or scattering effects. Although the presence of distortion is well known, how the wave packet is distorted has not been sufficiently investigated. We use the method of multiple scales (MMS), a perturbative scheme, to investigate the dispersion of the Lamb waves comprising the finite-bandwidth wave packet. Solutions obtained by the MMS to order O (ε 2) show that the shape of an input wave-packet remains invariant during propagation along the waveguide. The wave packet propagates with a group velocity obtained from a classical analysis. The O (ε 3) -order MMS solutions exhibit a symmetric distortion of the shape, whereas the O (ε 4) -order MMS solutions feature symmetric and anti-symmetric distortion. For the derivation of the O (ε 3) - and O (ε 4) -order MMS solutions, the Fourier transform of the wave-packet shape is introduced. The proposed MMS solutions were verified by comparing them with the numerical time-domain solutions constructed from the classical frequency-domain solutions. The strength of the distortion depends on propagation mode, input frequency, and shape of the input wave packet. Because the wave-packet distortion induces a shift and reduction of the peak, the propagation velocity is different from the group velocity. For long-distance inspections, the proposed method provides the precise propagation velocity and details of the propagation-mode selection. • The method of multiple scales is applied to analysis of the dispersion. • The strength of the distortion depends on propagation mode, input frequency, and shape of the input wave packet. • Using the MMS, we obtained insights into distorting the shape of the wave packet. [ABSTRACT FROM AUTHOR]

• Guided ultrasonic wavefield measurements performed on quasi-isotropic CFRP laminate. • Scattering at artificial, ellipse delamination, located at an asymmetric depth. • Wave trapping on top of delamination and forward scattered wave verified. • Numerical, Finite Element simulations validated from experiments. • Parameter study of guided wave scattering at different delamination shape and depth. Carbon fibre composite laminates are increasingly being used for aerospace structures due to their low weight and improved mechanical performance. Impact damage can cause delaminations below the visible surface of the structure due to limited interlaminar strength. Guided ultrasonic waves can detect and characterize delaminations in composite laminates. The scattering of the A 0 Lamb wave mode at an artificial delamination, located at an asymmetric depth in a quasi-isotropic laminate, was investigated. Full field non-contact laser measurements were used to visualise wave trapping and scattered waves. A three-dimensional finite element model was developed and validated against the experiments. The influence of delamination shape and depth on guided wave scattering were studied. Small variations in delamination shape significantly affected the interference pattern on top of the delamination, but had limited effect on the scattered wave outside the delamination. Delamination depth was found to strongly influence the angular direction and amplitude of scattered waves. Implications for structural health monitoring were discussed. [ABSTRACT FROM AUTHOR]