Lamb Wave Detection Research Articles

Time-Dependent Sensitivity of Structural Reliability Assessment to Multi-Source Uncertainties Using Lamb Wave

Abstract This article investigates the time-dependent sensitivity of structural reliability assessment to multisource uncertainties using Lamb wave. To precisely model the influence of local damage on the structure in the course of damage growth, a surface damage effect model is proposed to obtain the equivalent elasticity modulus, which can be coupled with the structure model. The evolution of the surface damage is modeled using the fatigue crack propagation model. Furthermore, by setting up the component and structure failure criteria, the time-dependent reliability model of the structure under multisource uncertainties from Lamb wave detection and material properties is established. The method of score function is employed to evaluate the sensitivity index, which is defined as the derivative of the reliability with respect to the distribution parameters of uncertain variables. A spatial truss structure is used to demonstrate the overall procedure. Numerical results show that the sensitivities indices are time and damage size dependent. The sensitivity contributions from Lamb wave quantification model and the material properties are comparable when the crack size is relatively small. When the crack grows to a larger size, the reliability assessment result is much more sensitive to uncertainties associated with material properties.

Damage Identification and Localization in an Aluminium Plate Based on Lamb Waves

The article presents a method for identifying and locating damages in an aluminum plate using Lamb waves. For this, a network of PZT wafer type actuators/sensors is used to generate and detect Lamb waves. The damage location algorithm is sketched taking into account the network configuration of PZT sensors. The experimental results confirm the calculation procedure.

Impact of Wedge Parameters on Ultrasonic Lamb Wave Liquid-Level Sensor.

The ultrasonic Lamb wave detection principle can realize the noncontact measurement of liquid level in closed containers. When designing an ultrasonic Lamb wave sensor, it is vital to thoroughly study and select the optimal wedge size at the front of the sensor. In this paper, firstly, we select the best working mode of Lamb waves according to their propagation dispersion curve in aluminum alloy, and we obtain the best angle of wedge through experiments. Secondly, we study the impact of the size of the wedge block on the results, and we obtain the selection method of wedge block parameters. The evaluations show that, when the frequency–thickness product is 3 MHz·mm, the Lamb waves work in the A1 mode, and the experimental effect is the best. At this time, the incident angle of the ultrasonic wave is 27.39°. The wedge thickness should be designed to avoid the near-field area of the ultrasonic field, and we should choose the length as odd multiples of 1/4 wavelength. The rules obtained from the experiment can effectively select the best working mode for ultrasonic Lamb waves, while also providing a basis for the design of the wedge block size in a Lamb wave sensor.

Nonlinear Lamb Wave for Structural Incipient Defect Detection with Sequential Probabilistic Ratio Test

The incipient defect is difficult to be identified by ultrasonic signal analysis. The nonlinear ultrasonic method based on the nonlinear Lamb wave principle is proposed by establishing a nonlinear Lamb wave ultrasonic inspection platform. The optimal Lamb wave parameters are obtained for the incipient fatigue material defects. The aluminum alloy board with 3 mm thickness under the different fatigue tensile cycles is tested. The nonlinear ultrasonic signals are analyzed to obtain second harmonic signals. The intelligent diagnosis method for incipient material degrade is proposed based on the Sequential Probability Ratio Test (SPRT). The sequential probabilistic ratio test (SPRT) algorithm is carried out to classify and identify the second harmonics of four different fatigue damages. The results show that the method about with nonlinear Lamb wave analysis with SPRT is effective and reliable for the incipient material microdefect degradation.

Model averaging and probability of detection estimation under hierarchical uncertainties for Lamb wave detection

Existing quantification models using Lamb waves are generally data-driven models, and the model choice can have a significant impact on the quantification results and the probability of detection (POD). This study develops a general method of model averaging and probability of detection estimation for Lamb wave detection. By treating each of the damage quantification models as a discrete uncertain variable, a hierarchical probabilistic model for Lamb wave detection is formulated in the Bayesian framework. Uncertainties from the model choice, model parameters, and other variables can be explicitly incorporated using the proposed method. The performance of a model can be assessed and averaged using the resulting posterior distributions of the model probability and its associated parameters. To evaluated all the quantities efficiently, the reservable jump Markov chain Monte Carlo method is proposed to evaluate the posterior distributions of the model, model parameters, and the model averaging results in one-pass. The overall method is demonstrated using specimens with naturally developed cracks, and the necessity of the method is verified by cross validation. The robustness of the proposed method is further validated using a naturally developed inclined crack, representing a realistic difference between the lab testing and an actual application. The results indicate that the proposed method is more robust compared with the individual models.

A Sagnac-based interferometer with optimal polarization control for Lamb wave detection

Sagnac-based interferometers are promising devices for laser ultrasound (LU) inspection with the advantages of being robust, low-cost, and easy to integrate. Compared with all-Polarization Maintaining (all-PM) method, non-Polarization Maintaining (non-PM) method is more cost-effective and has greater compatibility, making it more practical in low-frequency ultrasound detection. The initial π/2 phase bias (IPB) and high fringe visibility are crucial for realizing the interferometer's full potential. However, a specific process of obtaining the optimal polarization control for non-PM configuration is still absent, leading to the unpredictable fringe states. In this paper, a novel and specific approach to obtaining optimal interference fringes for non-PM configuration based on the polarization control is proposed. Experimentally, the initial π/2 phase bias and 43.9% fringe visibility (50% is the highest in theory) were obtained. Guided waves of low-frequency A0 mode in aluminum sheets were excited by a Q-switched pulse laser and detected by a non-PM Sagnac-based interferometer to inspect artificial defects on the surface of samples. Such a system provided a cost-effective non-contact detection scheme for out-of-plane Lamb wave which was very difficult to separate from LU signal with complex modes composition using conventional piezoceramics sensors.

Fatigue damage detection from imbalanced inspection data of Lamb wave

The core of structural health monitoring is to provide a real-time monitoring, inspection, and damage detection of structures. As one of the most promising technology to structural health monitoring, the Lamb wave method has attracted interest because it is sensitive to small-scale damage with a long detection range. However, in many real-world structural health monitoring applications, the nature of the problem implies structures work under normal condition in most of its operating phases; therefore, classes of data collected are not equally represented. The predictive capability of damage detection algorithms may significantly be impaired by class imbalance. This article presents a damage detection method using imbalanced inspection data which is collected through Lamb wave detection. Aiming at maximizing detection accuracy, an improved synthetic minority over-sampling technique using three-point triangle (triangle synthetic minority over-sampling technique) is proposed to conduct the over-sampling procedure and increase the number of minority samples. The iterative-partitioning filter is employed to remove the noisy examples which may be introduced by triangle synthetic minority over-sampling technique. Three conventional classification methods, namely, support vector machine, decision tree, and k-nearest neighbor, are used to perform the damage detection. A fatigue crack detection test using Lamb wave is performed to demonstrate the overall procedure of the proposed method. Three damage sensitive features, namely, normalized amplitude, correlation coefficient, and normalized energy, are extracted from signals as datasets. A cross-validation is performed to verify the performance of the proposed method for crack size identification.

Physical-virtual time reversing of nonlinear Lamb waves for fatigue crack detection and quantification

This article presents the investigation of a nonlinear Lamb wave time reversing technique for fatigue crack detection and quantification. A 2D analytical framework is initially presented, modeling Lamb wave generation, propagation, wave crack linear and nonlinear interaction, and reception. This study extends the Time Reversal (TR) techniques into the realm of nonlinear Lamb waves. Due to the structural transfer function variation between the forward and backward transmission process, the Virtual Time Reversal (VTR) algorithm reveals obvious deviation for predicting nonlinear Lamb waves, given that it replaces the backward TR procedure with the forward transfer function. However, this study demonstrates that the difference between the physical nonlinear TR method and the conventional VTR algorithm proves to be sensitive to detect and quantify fatigue cracks. Fatigue tests on a thin aluminum plate with a rivet hole are conducted to induce a fatigue crack. The experimental results further illuminate that the proposed physical-virtual nonlinear Lamb wave TR technique possesses remarkable sensitivity to the nucleation and growth of fatigue cracks. The paper finishes with discussion, concluding remarks, and suggestions for future work.

Heteroepitaxy of flexible piezoelectric Pb(Zr0.53Ti0.47)O3 sensor on inorganic mica substrate for lamb wave-based structural health monitoring

Active Lamb wave detection is an effective and simple monitoring method for structural health monitoring (SHM). Piezoelectric lead zirconate titanate (PZT) ceramics are most commonly used as transducers to excite and receive Lamb wave. However, due to their hardness, thickness and brittleness, PZT ceramics are severely limited in detecting damage on curved surface structures. Herein, we report that flexible PZT film sensor is an excellent candidate for receiving Lamb wave used in Lamb wave-based SHM of aircraft. An improved piezoelectric coefficient d33 (~130 pm V−1) is obtained in epitaxial PZT films grown on flexible inorganic mica substrates via van der Waals heteroepitaxy. Superior stable ferroelectricity and piezoelectricity retain in flexible PZT film after bending 104 cycles under a radius of 8 mm. As proven by experiment and simulation, flexible PZT film is demonstrated as an ultrasonic sensor with high sensitivity to be bonded on the curved aluminum plate for Lamb wave-based damage monitoring. Our work demonstrates that flexible PZT films have enormous potential for real-time light-weight and high-sensitivity receiver sensors for the SHM of aging aircraft.

Impact Damage Detection in Patch-Repaired CFRP Laminates Using Nonlinear Lamb Waves.

Carbon fiber-reinforced polymer (CFRP) laminates, a key composite material, are widely used in aircraft structures and are susceptible to low-velocity impact (LVI) damage from bird strikes, lightning strikes, hail impacts and other situations. Therefore, finding a method that repairs the damaged structure and detects the effect of these repairs under LVI is a very important goal. In this work, the repair effect of LVI damage in CFRP laminates repaired with patches of various sizes is investigated via experimental and numerical nonlinear Lamb wave analyses. An integrated numerical procedure that combines LVI with nonlinear Lamb wave detection is developed to predict the nonlinear Lamb wave behavior in LVI-damaged patch-repaired CFRP laminates. The CFRP laminate damage in the nonlinear Lamb wave simulation is evaluated based on relative acoustic nonlinearity parameters (RANPs). As a result, the integrated numerical procedure is validated with drop-weight impact tests and RAM-5000 SNAP nonlinear ultrasonic detection system. An optimal patch design is established via interpolation to optimize the absorbed energy, delamination surface area, second RANP and third RANP with different patch repair sizes. These parameters exhibit consistent curve fitting trends, indicating that they can be used as important indicators of impact damage. The optimal circular patch design with a radius of 2.5 r has better impact resistance behavior and repair performance.

Local Wavenumber Method for Delamination Characterization in Composites With Sparse Representation of Lamb Waves.

This article presents a quantitative Lamb wave detection method for delamination characterization in composite laminates using local wavenumber features. In contrast to the conventional Fourier transform-based methods, the improved sparse reconstruction method is efficient and able to evaluate the spatial wavenumbers of Lamb waves with limited measurements. To improve the feasibility of the sparse reconstruction method, the analytical solution of the local wavenumbers to the compressed sensing (CS) formulation with considering structural discontinuity is firstly investigated. The estimated wavenumber values for the spatial window located on healthy and damaged regions simultaneously are governed by a nonlinear optimization function. Benefiting from revealing the evolution of local wavenumber slopes, a delamination characterization method is proposed to accurately determine the damage location and depth by wavenumber banalization. Subsequently, the performance of the proposed method on local wavenumber estimation and damage quantification is verified by the simulation data. The parameters are discussed in order to improve the algorithm stability. Finally, the experimental investigation was conducted on a quasi-isotropic carbon fiber reinforced polymer (CFRP) laminate with an induced delamination. Lamb wave was generated and scanned by the Nd:YAG laser spot with spatial intervals of 2 mm. The results verify the sparse reconstruction method for delamination characterization, which shows value of reducing labor cost and testing time.

Lamb Wave-Based Damage Localization Feature Enhancement and Extraction Method for Stator Insulation of Large Generators Using VMD and Wavelet Transform.

Lamb waves are used to locate any damage in the stator insulation structure of large generators. However, it is difficult to extract the features of Lamb wave signals in a strong background noise environment, thus significantly reducing the accuracy with which the damage is located. This paper proposes a method based on variational mode decomposition (VMD) and wavelet transform to enhance and extract the location features of stator insulation damage signals of large motors. First, considering that the characteristics of VMD are sensitive to noise, the Lamb wave detection signal is decomposed, denoised, and reconstructed; the reconstructed signal is then wavelet-transformed to extract the time of flight (TOF) of the damage-scattered wave as the damage location feature; finally, the damage location is determined using the TOF features. The proposed method is experimentally tested and verified under various noise environments. The results show that the VMD and wavelet transform methods can significantly improve the signal-to-noise ratio of Lamb wave detection signals and the accuracy with which the damage is located under strong background noise. This study extends the applicability of Lamb wave-based non-destructive detection of stator insulation damage in complex environments.

Nonlinear Lamb wave analysis for microdefect identification in mechanical structural health assessment

Abstract In order to study the application of ultrasonic Lamb wave in the detection of defective plates, a nonlinear Lamb wave detection system was established. The system was used to detect aluminum alloy plates with different depth cracks and aluminum alloy plates with different tensile load cycles. The acquired time domain waveforms are analyzed by Fast Fourier Transform (FFT), and the influence of two kinds of defects on the nonlinear effects of Lamb waves is obtained. The test results show that for crack defects, the deepening of the defects will increase the ultrasonic nonlinear effect of the test piece. When the crack depth exceeds 4 mm, the non-linear effect of crack defects does not increase. For fatigue crack defects, the occurrence of crack defects will also exacerbate the nonlinear effect of the test piece, but when the test piece is fatigue fractured, its macro defects have a smaller effect on nonlinearity.

Fatigue-Crack Detection and Monitoring through the Scattered-Wave Two-Dimensional Cross-Correlation Imaging Method Using Piezoelectric Transducers.

Piezoelectric transducers are convenient enablers for generating and receiving Lamb waves for damage detection. Fatigue cracks are one of the most common causes for the failure of metallic structures. Increasing emphasis on the integrity of critical structures creates an urgent need to monitor structures and to detect cracks at an early stage to prevent catastrophic failures. This paper presents a two-dimensional (2D) cross-correlation imaging technique that can not only detect a fatigue crack but can also precisely image the fatigue cracks in metallic structures. The imaging method was based on the cross-correlation algorithm that uses incident waves and the crack-scattered waves of all directions to generate the crack image. Fatigue testing for crack generation was then conducted in both an aluminum plate and a stainless-steel plate. Piezoelectric wafer transducer was used to actuate the interrogating Lamb wave. To obtain the scattered waves as well as the incident waves, a scanning laser Doppler vibrometer was adopted for acquiring time-space multidimensional wavefield, followed with frequency-wavenumber processing. The proof-of-concept study was conducted in an aluminum plate with a hairline fatigue crack. A frequency-wavenumber filtering method was used to obtain the incident wave and the scattered wave wavefields for the cross-correlation imaging. After this, the imaging method was applied to evaluate cracks on a stainless-steel plate generated during fatigue loading tests. The presented imaging method showed successful inspection and quantification results of the crack and its growth.

Ultrasonic Touch Sensing System Based on Lamb Waves and Convolutional Neural Network

A tactile position sensing system based on the sensing of acoustic waves and analyzing with artificial intelligence is proposed. The system comprises a thin steel plate with multiple piezoelectric transducers attached to the underside, to excite and detect Lamb waves (or plate waves). A data acquisition and control system synchronizes the wave excitation and detection and records the transducer signals. When the steel plate is touched by a finger, the waveform signals are perturbed by wave absorption and diffraction effects, and the corresponding changes in the output signal waveforms are sent to a convolutional neural network (CNN) model to predict the x- and y-coordinates of the finger contact position on the sensing surface. The CNN model is trained by using the experimental waveform data collected using an artificial finger carried by a three-axis motorized stage. The trained model is then used in a series of tactile sensing experiments performed using a human finger. The experimental results show that the proposed touch sensing system has an accuracy of more than 95%, a spatial resolution of 1 × 1 cm2, and a response time of 60 ms.

Mode-mixing-induced second harmonic A0 mode Lamb wave for local incipient damage inspection

This paper reports the discovery of a special type of second harmonic A0 mode Lamb wave, which is generated through the mixing of primary S0 and A0 mode Lamb waves in a PZT-activated weakly nonlinear plate. Owing to the different propagating velocities of the S0 and A0 waves and the finite duration of their corresponding tone-burst wave packets, wave mixing takes place within a confined area which can be precisely controlled by tuning the wave excitation durations. When local incipient damage falls into the mixing zone, this second harmonic A0 mode wave provides higher damage detectability than the commonly used second harmonic S0 mode wave resulting from the global material nonlinearity. Moreover, through a tactic tuning of the mixing zone size, damage detection can be carried out zone by zone along the transmitter–receiver path to achieve damage localization. Finite element (FE) simulations are first carried out to ascertain the theoretically predicted phenomenon and the underlying generation mechanism of the second harmonic A0 mode Lamb waves. Capitalizing on its mode mixing feature between the primary A0 and S0 mode Lamb waves, a dedicated damage localization strategy alongside the corresponding algorithm is then proposed. Experiments are finally carried out with a dedicatedly designed inspection system with mitigated non-damage-related nonlinear interference. Both FE and experimental results demonstrate the appealing characteristics and the potential of the second harmonic A0 mode Lamb waves for local incipient damage detection and localization.

Phase-Shifted Fiber Bragg Grating Sensing Network and its Ultrasonic Sensing Application

Optical fiber sensors have been utilized as an alternative to piezoelectric sensors in ultrasonic nondestructive testing due to their advantages such as a light weight, small size, and anti-electromagnetic interference. Although phase-shifted fiber Bragg gratings (PSFBGs) have better performance in sensitivity and bandwidth compared to conventional uniform fiber Bragg grating, the problem of PSFBG multiplexing originating from the demodulation technique should be addressed, and their practical applications should be further explored. We designed a novel PSFBG ultrasonic sensing network by integrating a proportional-integral-derivative controller to maintain system stability in this study. The proposed sensing network can have two different layouts, namely, rosette and array. Its sensing performance was demonstrated with ultrasonic detection of Lamb waves propagating on an aluminum plate and a composite laminate. The PSFBG rosette manifested omni-directional sensitivity because the orientation-dependent sensitivity of each PSFBG sensor in the rosette can be mutually compensated. The PSFBG array monitored the mode dispersion and amplitude change along the wave propagation. Since the sensitivity of the PSFBG sensor is comparable to that of a conventional lead–zirconate–titanate sensor, the PSFBG sensor succeeded in detecting Lamb waves in the composite laminate and evaluating the number of matrix cracks generated in a three-point bending test by monitoring the amplitude decrease of the Lamb waves. These experiments demonstrated that the proposed PSFBG network has a good application prospect in ultrasonic nondestructive testing.

Use of delay and sum for sparse reconstruction improvement for structural health monitoring

To perform active structural health monitoring, guided Lamb waves for damage detection have recently gained extensive attention. Many algorithms are used for damage detection with guided waves and among them, the delay-and-sum method is the most commonly used algorithm because of its robustness and simplicity. However, delay-and-sum images tend to have poor accuracy with a large spot size and a high noise floor, especially in the presence of multiple damages. To overcome these problems, another method that is based on sparse reconstruction can be used. Although the images produced by the sparse reconstruction method are superior to the conventional delay-and-sum method, it has the challenges of the time and cost of computations in comparison with the delay-and-sum method. Also, in some cases in multi-damage detection, the sparse reconstruction method totally fails. In this article, using prior support information of the structure achieved by the delay-and-sum method, a hybrid method based on sparse reconstruction method is proposed to improve the computational performance and robustness of sparse reconstruction method in the case of multi-damage presence. The effectiveness of the proposed method in detecting damages is demonstrated experimentally and numerically on a simple aluminum plate. The technique is also shown to accurately identify and localize multi-site damages as well as single damage with low sampled signals.

Multi-feature Fusion and Damage Identification of Large Generator Stator Insulation Based on Lamb Wave Detection and SVM Method.

Due to the merits of Lamb wave to Structural Health Monitoring (SHM) of composite, the Lamb wave-based damage detection and identification technology show a potential solution for the insulation condition evaluation of large generator stator. This was performed in order to overcome the problem that it is difficult to effectively identify the stator insulation damage the using single feature of Lamb wave. In this paper, a damage identification method of stator insulation based on Lamb wave multi-feature fusion is presented. Firstly, the different damage features were extracted from time domain, frequency domain, and fractal dimension of lamb wave signals, respectively. The features of Lamb wave signals were extracted by Hilbert transform (HT), power spectral density (PSD), fast Fourier transform (FFT), and wavelet fractal dimension (WFD). Then, a machine learning method based on support vector machine (SVM) was used to fuse and reconstruct the multi-features of Lamb wave and furtherly identify damage type of stator insulation. Finally, the effect of typical stator insulation damage identification is verified by simulation and experiment.

A reconstruction-based mode separation method of Lamb wave for damage detection in plate structures

This paper presents a new method to separate multi-mode signal of Lamb wave through reconstruction of pure mode basis signals calculated based on phase and group velocity. Individual signal of each mode contained in multi-mode signal can be obtained and analyzed by mode separation. Simultaneously, the hidden damage scattering signal can be extracted after removing the undesired signal. Two simulations are conducted on aluminum plates as examples to demonstrate the procedure of mode separation in detail. The first one models Lamb wave propagating in an aluminum plate without damage to separate each mode step by step. Extraction of damage scattering signal through mode separation is presented with the other simulation conducted on a damaged aluminum plate. Also an experiment is designed to example the applicability of this method. The results of both simulations and experiment verify the validity and accuracy of this method. This mode separation method provides a potential baseline free approach for damage detection using Lamb wave.