A Crack Size Quantification Method Using High-Resolution Lamb Waves

Abstract

Traditional tone burst excitation cannot attain a high output resolution, due to the time duration. The received signal is much longer than that of excitation during the propagation, which can increase the difficulty of signal processing, and reduce the resolution. Therefore, it is of significant interest to develop a general methodology for crack quantification through the optimal design of the excitation waveform and signal-processing methods. This paper presents a new crack size quantification method based on high-resolution Lamb waves. The linear chirp (L-Chirp) signal and Golay complementary code (GCC) signal are used as Lamb wave excitation signals. After dispersion removal, these excitation waveforms, based on pulse compression, can effectively improve the inspection resolution in plate-like structures. A series of simulations of both healthy plates and plates with different crack sizes are performed by Abaqus CAE, using different excitation waveforms. The first wave package of the S0 mode after pulse compression is chosen to extract the damage features. A multivariate regression model is proposed to correlate the damage features to the crack size. The effectiveness of the proposed crack size quantification method is verified by a comparison with tone burst excitation, and the accuracy of the crack size quantification method is verified by validation experiments.

Quantitative evaluation of crack damage under a variable temperature environment based on a Gaussian mixture model

“…The PZT sensors are placed on each side of the crack, and all wave propagation paths in this study are perpendicular to the crack propagation, as shown in Figure 2. According to the existing research, 26 the damage indexes can be extracted from the forward-transmission Lamb waves, which contain damage information after interacting with the crack. Seven damage indexes with clear physical signification are conducted for crack damage detection under different temperatures.…”

Quantitative characterization of fatigue damage in plate structures based on FSOM

“…To enhance the detection of subtle defect signals, Zhang et al [12] harnessed time reversal theory, effectively addressing the practical limitations associated with damage scattering signals and achieving precise localization of damage in metal plates; Zhang et al [13] proposed a composite damage identification method that combines phased array ultrasonic detection with deep learning techniques, significantly improving the signal-to-noise ratio in composite ultrasonic detection. Additionally, Li et al [14] quantified crack size using highresolution Lamb wave-based approaches. Nonetheless, it is important to acknowledge that these techniques are not only operationally intricate but are also susceptible to the presence of spurious waves during the focusing process, potentially impacting the accuracy of damage detection results.…”

Baseline-free damage detection and sizing under varying temperatures using Lamb waves without temperature compensation

“…1,2 Guided wavebased SHM techniques have gained enormous interest for health management of thin plate-and shell-type structures due to their ability to detect small-sized damages and swiftly examine large regions with a limited number of transducers. [3][4][5][6][7][8][9][10][11][12] Lamb waves are generated in thin-walled structures by actuating the adhesivebonded piezoelectric transducers with electrical voltage. The propagating Lamb wave interacts with the structure and can be recorded at the same transducer (pulse-echo configuration) or a different transducer (pitch-catch configuration).…”