Lamb Wave Technique Research Articles

Enhanced Fatigue Crack Detection in Complex Structure with Large Cutout Using Nonlinear Lamb Wave.

The large cutout structure is a key component in the bottom skin of an airplane wing, and is susceptible to developing fatigue cracks under service loads. Early fatigue crack detection is crucial to ensure structural safety and reduce maintenance costs. Nonlinear Lamb wave techniques show significant potential in microcrack monitoring. However, nonlinear components are often relatively weak. In addition, a large cutout structure introduces complex boundary conditions for Lamb wave propagation, making nonlinear Lamb wave monitoring more challenging. This article proposes an integrated data processing method, combining phase inversion with continuous wavelet transform (CWT) to enhance crack detection in complex structures, with phase-velocity desynchronization adopted to suppress the material nonlinearity. Experiments on a large cutout aluminum alloy plate with thickness variations were conducted to validate the proposed method, and the results demonstrated its effectiveness in detecting fatigue cracks. Furthermore, this study found that nonlinear components are more effective than linear components in monitoring closed cracks.

A fatigue crack prediction method based on inductive semi-supervised learning and Lamb-wave monitoring for orthotropic steel bridge deck

Orthotropic steel bridge deck suffers from fatigue cracking due to its orthotropic configuration and cyclic vehicular load. Hence, fatigue crack monitoring and prediction are crucial for addressing this issue. The Lamb-wave technique has potential in monitoring the growth of fatigue cracks, whereas most of the existing signal processing methods show poor performance in the crack prediction. To improve the accuracy and reliability of fatigue crack prediction, an inductive semi-supervised learning (ISL) approach is proposed in conjunction with Lamb-wave monitoring. The presented method is first verified by conducting a fatigue test of orthotropic steel bridge deck loading by three load conditions which would lead to different types of cracks, where lightweight Lamb-wave monitoring devices were adopted. The approach was further applied in field monitoring to validate its effectiveness in real engineering structures. The results demonstrate that the proposed method can recognize the initiation of fatigue cracks by giving a predicted time interval in which the real initiation moment locates. Similar increasing trends are found between the predicted and real crack lengths during the growth of cracks, while a relative fluctuate is existing in the predicted results, and the prediction accuracy of crack lengths can be regarded as 2 mm. For bridge field monitoring, the real fatigue crack length was also well predicted by the proposed method, exhibiting an average error of 0.82 mm in comparison with the real values. In general, the research findings emphasize the adaptability of the proposed method for fatigue crack prediction in practical engineering.

Delamination Depth Detection in Composite Plates Using the Lamb Wave Technique Based on Convolutional Neural Networks.

Delamination represents one of the most significant and dangerous damages in composite plates. Recently, many papers have presented the capability of structural health monitoring (SHM) techniques for the investigation of structural delamination with various shapes and thickness depths. However, few studies have been conducted regarding the utilization of convolutional neural network (CNN) methods for automating the non-destructive testing (NDT) techniques database to identify the delamination size and depth. In this paper, an automated system qualified for distinguishing between pristine and damaged structures and classifying three classes of delamination with various depths is presented. This system includes a proposed CNN model and the Lamb wave technique. In this work, a unidirectional composite plate with three samples of delamination inserted at different depths was prepared for numerical and experimental investigations. In the numerical part, the guided wave propagation and interaction with three samples of delamination were studied to observe how the delamination depth can affect the scattered and trapped waves over the delamination region. This numerical study was validated experimentally using an efficient ultrasonic guided waves technique. This technique involved piezoelectric wafer active sensors (PWASs) and a scanning laser Doppler vibrometer (SLDV). Both numerical and experimental studies demonstrate that the delamination depth has a direct effect on the trapped waves' energy and distribution. Three different datasets were collected from the numerical and experimental studies, involving the numerical wavefield image dataset, experimental wavefield image dataset, and experimental wavenumber spectrum image dataset. These three datasets were used independently with the proposed CNN model to develop a system that can automatically classify four classes (pristine class and three different delamination classes). The results of all three datasets show the capability of the proposed CNN model for predicting the delamination depth with high accuracy. The proposed CNN model results of the three different datasets were validated using the GoogLeNet CNN. The results of both methods show an excellent agreement. The results proved the capability of the wavefield image and wavenumber spectrum datasets to be used as input data to the CNN for the detection of delamination depth.

Locating mutation damage based on the zero-frequency component of nonlinear Lamb waves

Degradation, such as micro-voids, dislocation, persistent bands, and micro-cracks, can give rise to local material nonlinearity and cause early-stage material local damage. The material nonlinearity of a plate can be represented as a distribution function. Depending on whether the nonlinearity distribution function of a plate is smooth or not, early-stage material local damage can be divided into gradual and mutation damage. Gradual damage is usually caused by lattice distortion, and the nonlinearity distribution function is smooth. In contrast, mutation damage is usually induced by a discontinuous interface, and the nonlinearity distribution function is not smooth but stepped. Mutation damage is more harmful than gradual damage. To ensure safety, it is important to locate and evaluate mutation damage. The conventional nonlinear Lamb wave technique has limitations in resolving the location and spatial distribution of mutation damage owing to several reasons. To address these issues, a novel method for locating mutation damage based on the zero-frequency component is proposed in this paper. The theoretical solution of the zero-frequency component generated by the Lamb wave pulse is derived based on certain ideal assumptions. Other complex behaviors of the zero-frequency component can be understood by the contribution of this theory. The region of mutation damage is modeled by enhancing local three-order elastic coefficients, and mutation damage can be located simply and efficiently by using the proposed zero-frequency component-based method. The proposed damage detection based on the zero-frequency component of nonlinear Lamb waves has significant advantages compared to the second harmonic and mixing-wave detection techniques.

Damage assessment using the Lamb wave factorization method

The Lamb wave technique has been widely used for damage detection in plate-like structures. However, for two-dimensional (2D) defects like corrosions or one-dimensional (1D) defects like cracks, conventional Lamb wave-based methodology usually selects the detection algorithm in terms of the damage type, which is restricted if the defect remains unknown. To address the issues, this paper proposes a damage assessment approach based on the Lamb wave factorization method, which is a general method that can adapt to the detection of both 2D and 1D defects. In the process, both the forward-scattered wave across the inspection area and the wave back-scattered from the defect are used for detection, so that the enclosed rich information can be fully exploited. To measure the wave field of defect, a transducer array is firstly set around the inspection area, whose transducers would take turns to excite the Lamb wave while others remain listeners. On the basis, the scattered waves of all directions are then extracted and transformed from the time domain to frequency domain. Under a certain frequency, the inspection area is next visualized by sampling the area and solving the inverse scattering problem using the spectral data at each sampling point. By fusing the results of different frequency together, the final image can be eventually obtained. The method is then numerically investigated and also validated through experiments. The results demonstrate that it can give out the outline description of 2D defect and the size evaluation of 1D defect accurately, thus being an effective tool for damage assessment.

Study on Nonlinear Lamb Wave Test for Invisible Impact Damage on CFRP Laminates

The impact damage imposed on carbon fiber–reinforced polymer (CFRP) materials used in aircraft fuselage may seriously affect flight safety. An ultrasonic testing method can be used to inspect for damage; however, in some cases of invisible or barely visible impact damage, linear ultrasound may not provide a clear indication of the underlying damage. Accordingly, a nonlinear Lamb wave technique was developed in this study to detect invisible impact damage (IID). First, a nonlinear Lamb wave testing platform was set, as well as damage areas with different impact energies. Second, the anisotropic propagation of Lamb waves was studied to determine the wave mode and the distribution of the transducers, and the linear parameters of the Lamb waves were determined. Last, three types of characteristic parameters of nonlinear Lamb waves were obtained for damage detection. As revealed from the results, the linear ultrasonic parameters of A0 mode Lamb waves can be applied to the detection of macro surface cracks, and the frequency shift, relative nonlinearity coefficient (RNC), and fluctuation coefficient of RNCs are highly sensitive to the detection of IID. Thus, a combination of nonlinear S0 Lamb waves and linear A0 Lamb waves can be used for IID and macro surface crack detection, respectively.

Study of concrete de-bonding assessment technique for containment liner plates in nuclear power plants using ultrasonic guided wave approach

In this work, the guided wave de-bonding area-detecting technique was studied for application to containment liner plates in nuclear power plant areas. To apply this technique, an appropriate Lamb wave mode, symmetric and longitudinal dominance, was verified by the frequency shifting technique. The S0 2.7 MHz mm Lamb wave mode was chosen to realize quantitative experimental results and their visualization. Results of the bulk wave, longitudinal wave mode, and comparison experiments indicate that the wave mode was able to distinguish between the de-bonded and bonded areas. Similar to the bulk wave cases, the bonded region could be distinguished from the de-bonded region using the Lamb wave approach. The Lamb wave technique results showed significant correlation to the de-bonding area. As the de-bonding area increased, the Lamb wave energy attenuation effect decreased, which was a prominent factor in the realization of quantitative tomographic visualization. The feasibility of tomographic visualization was studied via the application of Lamb waves. The reconstruction algorithm for the probabilistic inspection of damage (RAPID) technique was applied to the containment liner plate to verify and visualize the de-bonding condition. The results obtained using the tomography image indicated that the Lamb wave-based RAPID algorithm was capable of delineating debonding areas.

Numerical and experimental research on damage shape recognition of aluminum alloy plate based on Lamb wave

The structure health monitoring (SHM) system with Lamb waves technique is studied numerically and experimentally in this paper. A damage shape recognition algorithm (DSRA) is developed for the hole on aluminum alloy plate specimen. The proposed DSRA is established based on the two arrival time difference method (2/ATDM) and Lagrangian optimization method. This method captures the damage shape by describing the coordinates of the reflection point from the piezoelectric ceramic lead zirconate titanate (PZT) transducers to the damage edge. 2/ATDM provides a way to obtain coordinate points by the arrival time which is determined by Lamb waves. And the coordinate points are optimized by the Lagrangian optimization method. A numerical model is established to simulate the proposed experiment process. Its convergence rate of mesh size and time steps is investigated, and the numerical results are verified by these of experiment. Hence, the shape recognition of damage occurring at an arbitrary position and that of irregular damage are studied by the proposed numerical and experiment methods.

Efficient Lamb-wave based damage imaging using multiple sparse Bayesian learning in composite laminates

Lamb wave techniques have been widely used for structural health monitoring (SHM) and nondestructive testing (NDT). To deal with dispersive and multimodal problems of Lamb wave signals, many signal processing methods have been developed. A spatially distributed array of piezoelectric transducers is generally adopted for both transmission and reception of Lamb waves. When imaging the damage in composite laminates, it is necessary to meet the need of processing array signals with high efficiency. In this paper, the multiple sparse Bayesian learning (M-SBL) strategy is employed for damage imaging. Multiple residual signals including damage-reflection waves are decomposed into a sparse matrix of location-based components simultaneously. An appropriate dictionary is designed to match the damage-reflection waves instead of interference waves. The key to success is to obtain the sparse matrix of weighting coefficients through the M-SBL algorithm. Damage imaging can be achieved efficiently using the delay-and-sum (DAS) method with sparse coefficients in time-domain. Results from the experiment in composite laminates demonstrate the effectiveness of the proposed method.

Fiber Bragg Grating-Based Fabry-Perot Interferometer Sensor for Damage Detection on Thin Aluminum Plate

Structural Health Monitoring of engineering structures has become an essential measure for the prevention of catastrophic failures. This study presented a feasibility study of Fiber Bragg Grating-based Fabry-Perot interferometer (FBG-FPI) sensor for damage detection on an aluminum plate, by acoustic Lamb wave technique. In the investigation, a rectangular damage slot was introduced to the plate, at 15 cm from the actuator. Two FBG-FPI sensors were surface-mounted on the aluminum plate for the detection. In the analysis, we observed an additional wave packet with attenuated amplitude and time delay in the time-domain signal for the defect plate. Similar features are observed in the time-frequency spectrograms and they are important signatures that can be used for detecting the defect. The findings show the applicability of FBG-FPI sensor for damage detection on a thin-walled metallic structure.

Application of artificial neural networks for quantitative damage detection in unidirectional composite structures based on Lamb waves

This article provides a quantitative nondestructive damage detection method through a Lamb wave technique assisted by an artificial neural network model for fiber-reinforced composite structures. For simulating damages with a variety of sizes, rectangular Teflon tapes with different lengths and widths are applied on a unidirectional carbon fiber–reinforced polymer composite plate. Two characteristic parameters, amplitude damage index and phase damage index, are defined to evaluate effects by the shape of the rectangular damage in the carbon fiber–reinforced polymer composite plate. The relationships between the amplitude damage index and phase damage index parameters and the damage sizes in the carbon fiber–reinforced polymer composite plate are quantitatively addressed using a three-layer artificial neural network model. It can be seen that a reasonable agreement is achieved between the pre-assigned damage lengths and widths and the corresponding predictions provided by the artificial neural network model. This shows the great potential of using the proposed artificial neural network model for quantitatively detecting the damage size in fiber-reinforced composite structures.

A research on fatigue crack growth monitoring based on multi-sensor and data fusion

Fatigue crack propagation is one of the main problems in structural health monitoring. For the safety and operability of the metal structure, it is necessary to monitor the fatigue crack growth process of the structure in real time. In order to more accurately monitor the expansion of fatigue cracks, two kinds of sensors are used in this article: strain gauges and piezoelectric transducers. A model-based inverse finite element model algorithm is proposed to perform pattern recognition of fatigue crack length, and the fatigue crack monitoring experiment is carried out to verify the algorithm. The strain spectra of the specimen under cyclic load in the simulation and experimental crack propagation are obtained, respectively. The active lamb wave technique is also used to monitor the crack propagation. The relationship between the crack length and the lamb wave characteristic parameter is established. In order to improve the recognition accuracy of the crack propagation mode, the random forest and inverse finite element model algorithms are used to identify the crack length, and the Dempster–Shafer evidence theory is used as data fusion to integrate the conclusion of the two algorithms to make a more accountable and correct judge of the crack length. An experiment has been conducted to demonstrate the effectiveness of the method.

Combination of Phase Matching and Phase-Reversal Approaches for Thermal Damage Assessment by Second Harmonic Lamb Waves.

It is known that measurement and extraction of the tiny amplitude of second harmonic Lamb waves are the main difficulties for practical applications of the nonlinear Lamb wave technique. In this study, phase-reversal approaches and phase matching technique are combined to build up the second-harmonic generation (SHG) of Lamb waves. A specific Lamb wave mode pair, which satisfied phase matching conditions, is selected to ensure the generation of cumulative second harmonic waves. Lamb wave signals with the same frequency but in reverse phase, propagating in the given specimen, are added together to counteract the fundamental waves, and simultaneously to enhance the signals of the second harmonic generated. The obtained results show that the phase-reversal approach can enhance the signals of second harmonic Lamb waves, and effectively counteract that of the fundamental waves. The approach is applied to assess the thermal-induced material degradation in the stainless steel plates. Distinctions of the acoustic nonlinearity parameters under different degraded levels are clearly shown in an improved repeatable and reliable manner, while those of linear wave velocity in the specimens are neglectable. The experimental investigations performed indicate that the proposed approach can be taken as a promising alternative for assessment of material degradation in its early stages.

Damage Detection in a Plate Structure based on FBG sensing Technique under a Single-Mode Lamb Wave

Lamb wave is widely acknowledged as one of the most encouraging tools for damage identification in plate structures, and relevant research has been conducted intensively. However Lamb wave modes have different wave structure, frequency dispersion and attenuation characteristics, which are sensitivity to different types of damages and it is difficult to solve such engineering problems by conventional techniques. Although the single pattern detection method has been researched by piezoelectric wafers, there is little research about FBG sensing detection under single-mode ultrasonic Lamb wave technique currently. So this paper puts forward a single-mode Lamb wave technique for crack detection based on Fiber Bragg Grating sensor, which is used to receive the waves in the plate. First of all, measuring principle of single-mode ultrasonic Lamb technique and demodulation principle of the FBG sensor are introduced. And simulation analysis in the acoustic field is devoted, whose results lay the foundation for the damage detection in the plate. Then, the experimental system is built by a single-mode Lamb wave excitation, and the feasibility of fiber Bragg grating sensors in single-mode excitation method is verified by experiments.

Investigating the critical aspects of evaluating the material nonlinearity in metal plates using Lamb waves: Theoretical and numerical approach

The present study focuses on critical analysis of various aspects related to the evaluation of amplitude based material nonlinearity parameter γamp through the numerical simulations and theoretical justifications. Two different materials with distinct nonlinearities are interrogated using Lamb waves in the numerical simulations. The effects of input force amplitude, number of cycles in the tone burst, tone burst windowing functions, material model parameters, excitation frequency, and wave propagation distance on γamp are studied in detail. Also, γamp estimated for the data obtained from the numerical simulations considering S0-S0 mode pair at low frequencies and resonant S1-S2mode pair at higher frequencies are compared with the physics based material nonlinearity parameter γphy. The difference between the results is marginal. Thus, the nonlinear Lamb wave technique can be effectively used even at low frequencies to estimate the actual material nonlinearity of the (metallic) plate materials with fair accuracy using the proposed nonlinearity models.

Active detection of block mass and notch-type damages in metallic plates using a refined time-reversed Lamb wave technique

A recently proposed refined time-reversed Lamb wave method for baseline-free damage detection is tested experimentally for detecting block mass and notch-type damages in isotropic plates. The experimental results were compared with finite element simulations. The frequency of best reconstruction has been determined experimentally for the actuator–plate–sensor system by performing the time reversal process for a range of frequency, which is found to be very different from the sweet spot frequency exciting a single mode, hitherto recommended for improving the performance of the time reversal process-based techniques. It is shown that the damage indices (DIs) computed by using the conventional main wave packet of the reconstructed signal are less sensitive to the presence of damage, which is consistent with some recently reported experimental results by other groups. The present method with extended wave packet shows excellent sensitivity to damage for both block mass and notch-type damages and also ensures a low threshold for the undamaged case when used at the best reconstruction frequency. The refined DIs reflect the true severity of damage. It was observed that a putty on the plate has no significant change in the DIs in the present method, whereas a baseline method would identify it as a damage due to very significant scattering by the putty.

Experimental assessment of the influence of welding process parameters on Lamb wave transmission across ultrasonically welded thermoplastic composite joints

One of the advantages of thermoplastic composites relative to their thermoset counterparts is the possibility of assembling components through welding. Ultrasonic welding in particular is very promising for industrialization. However, uncertainty in the fatigue and fracture behaviour of composites is still an obstacle to the full utilisation of these materials. Health monitoring is then of vital importance, and Lamb wave techniques have been widely recognised as some of the most promising approaches for that end. This paper presents the first experimental study about the influence of welding travel on the transmission of Lamb waves across ultrasonically welded thermoplastic composite joints in single-lap configuration. The main aim of this research is to start to understand how guided waves interact with the internal structure of ultrasonic welds, so that benign, manufacturing-related structural features can be distinguished from damaging ones in signal interpretation. The power transmission coefficient and the correlation coefficient proved to be suitable for analysing the wave propagation phenomena, allowing quantitative identification of small variations of weld-line thickness and intermolecular diffusion at the weld interface. The conclusions are used to develop a tentative damage detection criterion which can later on assist the design of a Lamb wave based structural health monitoring system for thermoplastic composite structures. The Lamb wave test results are backed up by phased-array inspections, which also provide some extra insight on the internal structure of ultrasonic welds.

Finite Element Modelling of Lamb Waves Propagation in 3D Plates and Brass Tubes for Damage Detection

Structural health monitoring (SHM) is becoming very significant for preventing catastrophic failures and uninterrupted operation. Due to continuous developments in SHM Lamb wave technique, finite element simulation is emerging as an initial step to be performed to visualize the potential solution to problem. The present study focus on the simulation of Lamb wave response using finite element method and its application to crack detection and identification in 3D aluminium plates and brass tubes using commercially available finite element package ABAQUS. Phase velocity and group velocity dispersion curve are initially plotted for aluminium and brass material. Subsequently simulation of distinct specimens with and without presence cracks is performed. Simulation results were validated and compared with actual results and were found to be in reasonably good agreement. A damage index parameter i.e. amplitude ratio is defined to notice the effect of crack dimensions variation. Interaction of Lamb waves with rectangular, semi-elliptical and semi-circular cracks (shallow to deep) is studied in detail. Also the application of signal processing techniques such as Spectrogram analysis, Fourier transform and Hilbert transform is also reported in this paper.

Mechanical state assessment using lamb wave technique in static tensile tests

The paper deals with the investigation of Lamb wave ultrasonic technique for damage (or mechanical state) evaluation of AA7068T3 specimens in the course of tensile testing. Two piezoelectric transducers (PZT), one of which is used as an actuator and the other as sensor, were adhesively bonded on the specimen surface using epoxy. Two frequencies of testing signals (60 kHz and 350 kHz) were used. The set of static tensile tests were performed. The recorded signals were processed to calculate the informative parameters in order to evaluate the changes in stress-strain state of the specimens and their microstructure.

Lamb Wave Based Ultrasonic Technique for AA2024 Fatigue Evaluation

Experimental results of Lamb wave technique investigation for evaluation of fatigue state of AA2024T3 specimens under cyclic loading conditions are presented. Analysis of acoustic signal data obtained by the piezoelectric transducers network was done through the calculation of two parameters: maximum envelope and 2nd central moment. Understanding of relations between acoustic signals features and emergent damages will provide the ability to determine the state of the structure and evaluate the defects, therefore assume the preventative measures and avoid accidents.