Nonlinear Lamb Wave Micro-Crack Direction Identification in Plates with Mixed-Frequency Technique

A Comparative Study of Geometric Phase Change- and Sideband Peak Count-Based Techniques for Monitoring Damage Growth and Material Nonlinearity

This work presents numerical modeling-based investigations for detecting and monitoring damage growth and material nonlinearity in plate structures using topological acoustic (TA) and sideband peak count (SPC)-based sensing techniques. The nonlinear ultrasonic SPC-based technique (SPC-index or SPC-I) has shown its effectiveness in monitoring damage growth affecting various engineering materials. However, the new acoustic parameter, "geometric phase change (GPC)" and GPC-index (or GPC-I), derived from the TA sensing technique adopted for monitoring damage growth or material nonlinearity has not been reported yet. The damage growth modeling is carried out by the peri-ultrasound technique to simulate nonlinear interactions between elastic waves and damages (cracks). For damage growth with a purely linear response and for the nonlinearity arising from only the nonlinear stress-strain relationship of the material, the numerical analysis is conducted by the finite element method (FEM) in the Abaqus/CAE 2021 software. In both numerical modeling scenarios, the SPC- and GPC-based techniques are adopted to capture and compare those responses. The computed results show that, from a purely linear scattering response in FEM modeling, the GPC-I can effectively detect the existence of damage but cannot monitor damage growth since the linear scattering differences are small when crack thickness increases. The SPC-I does not show any change when a nonlinear response is not generated. However, the nonlinear response from the damage growth can be efficiently modeled by the nonlocal peri-ultrasound technique. Both the GPC-I and SPC-I techniques can clearly show the damage evolution process if the frequencies are properly chosen. This investigation also shows that the GPC-I indicator has the capability to distinguish nonlinear materials from linear materials while the SPC-I is found to be more effective in distinguishing between different types of nonlinear materials. This work can reveal the mechanism of GPC-I for capturing linear and nonlinear responses, and thus can provide guidance in structural health monitoring (SHM).

A non-destructive technique using digital holographic vibrometry and Lamb waves for quality determination of polymer-metal laminates

We used digital holographic vibrometry (DHV) as a non-destructive method to detect debonding areas in laminates made of aluminum and polymer (polylactide, polyvinylidene fluoride or polycarbonate). At low frequencies (up to 30 kHz) \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$A_0$$\end{document}A0 Lamb waves were excited and the amplitude and the phase patterns of the vibration of the sample were simultaneously registered for metal and polymer side of the laminate. Based on these patterns debonding areas in laminates were localized. The transmission properties at low frequencies were also studied in terms of: the frequency range for which regular Lamb waves have been observed, Lamb wave amplitudes and Lamb wave propagation velocity depending on the frequency. We have shown that these properties also change when a defect occures in the laminate. Even when we could not localize the defect it was still possible to detect if a sample was damaged based on the behaviour of the Lamb waves.

Microcrack localization using nonlinear Lamb waves and cross-shaped sensor clusters

Using the nonlinear interaction effect between ultrasonic Lamb waves and microcracks to detect and locate microcracks has the advantages of fast detection speed and high sensitivity. In this paper, a method for microcrack localization based on cross-shaped sensor clusters in a plate is proposed by combining nonlinear ultrasonic Lamb wave technology and time difference of arrival (TDOA) technology. The antisymmetric (A0) mode at low frequency is chosen as the primary Lamb wave to simplify the complication of the dispersion and multi-mode properties of Lamb waves. The selected mode pair (A0-s0) weakens the influence of the cumulative growth effect of higher harmonics induced by the inherent material nonlinearity on the microcrack characteristic signals. Pulse inversion technique and cross correlation function are used to extract the TDOAs of the nonlinear characteristic signals including microcrack information. The cross-shaped sensor clusters approach proposed for the first time can achieve reliable and fast microcrack localization without being affected by the duration of the excitation signal, and a priori knowledge of group velocities of primary wave modes or generated harmonics. Experimental and numerical results validate the proposed method in isotropic and anisotropic plates. This paper provides a new idea for nonlinear ultrasonic nondestructive evaluation and structural health monitoring of microcracks in plates.

Detection of Micro-Cracks in Metals Using Modulation of PZT-Induced Lamb Waves

The ultrasonic modulation technique, developed by inspecting the nonlinearity from the interactions of crack surfaces, has been considered very effective in detecting fatigue cracks in the early stage of the crack development due to its high sensitivity. The wave modulation is the frequency shift of a wave passing through a crack and does not occur in intact specimens. Various parameters affect the modulation of the wave, but quantitative analysis for each variable has not been comprehensively conducted due to the complicated interaction of irregular crack surfaces. In this study, specimens with a constant crack width are manufactured, and the effects of various excitation parameters on modulated wave generation are analyzed. Based on the analysis, an effective crack detection algorithm is proposed and verified by applying the algorithm to fatigue cracks. For the quantitative analysis, tests are repeatedly conducted by varying parameters. As a result, the excitation intensity shows a strong linear relationship with the amount of modulated waves, and the increase of modulated wave is expected as crack length increases. However, the change in the dynamic characteristics of the specimen with the crack length is more dominant in the results. The excitation frequency is the most dominant variable to generate the modulated waves, but a direct correlation is not observed as it is difficult to measure the interaction of crack surfaces. A numerical analysis technique is developed to accurately simulate the movement and interaction of the crack surface. The crack detection algorithm, improved by using the observations from the quantitative analyses, can distinguish the occurrence of modulated waves from the ambient noises, and the state of the specimens is determined by using two nonlinear indexes.

An Application Study on Road Surface Monitoring Using DTW Based Image Processing and Ultrasonic Sensors

Road surface monitoring is an essential problem in providing smooth road infrastructure to commuters. This paper proposed an efficient road surface monitoring using an ultrasonic sensor and image processing technique. A novel cost-effective system, which includes ultrasonic sensors sensing with GPS for the detection of the road surface conditions, was designed and proposed. Dynamic time warping (DTW) technique was incorporated with ultrasonic sensors to improve the classification and accuracy of road surface detecting conditions. A new algorithm, HANUMAN, was proposed for automatic recognition and calculation of pothole and speed bumps. Manual inspection was performed and comparison was undertaken to validate the results. The proposed system showed better efficiency than the previous systems with a 95.50% detection rate for various road surface irregularities. The novel framework will not only identify the road irregularities, but also help in decreasing the number of accidents by alerting drivers.

A Nonlinear Ultrasonic Modulation Method for Crack Detection in Turbine Blades

In modern gas turbines, efforts are being made to improve efficiency even further. This is achieved primarily by increasing the generated pressure ratio in the compressor and by increasing the turbine inlet temperature. This leads to enormous loads on the components in the hot gas region in the turbine. As a result, non-destructive testing and structural health monitoring (SHM) processes are becoming increasingly important to gas turbine manufacturers. Initial cracks in the turbine blades must be identified before catastrophic events occur. A proven method is the linear ultrasound method. By monitoring the amplitude and phase fluctuations of the input signal, structural integrity of the components can be detected. However, closed cracks or small cracks cannot be easily detected due to a low impedance mismatch with the surrounding materials. By contrast, nonlinear ultrasound methods have shown that damages can be identified at an early stage by monitoring new signal components such as sub- and higher harmonics of the fundamental frequency in the frequency spectrum. These are generated by distortion of the elastic waveform due to damage/nonlinearity of the material. In this paper, new global nonlinear parameters were derived that result from the dual excitation of two different ultrasound frequencies. These nonlinear features were used to assess the presence of cracks as well as their qualitative sizes. The proposed approach was tested on several samples and turbine blades with artificial and real defects. The results were compared to samples without failure. Numerical simulations were conducted to investigate nonlinear elastic interaction of the stress waves with the damage regions. The results show a clear trend of nonlinear parameters changing as a function of the crack size, demonstrating the capability of the proposed approach to detect in-service cracks.