Methodological study demonstrates improved signal denoising and waveform preservation in aluminum plates, indicating enhanced defect detection under industrial interference.
In ultrasonic Lamb wave non-destructive testing of aluminum plates, Lamb wave signals are susceptible to industrial interference, which may obscure useful information. To address this issue, this paper developed a signal denoising method combining Improved Crown Porcupine Optimization (ICPO) and Variational Mode Decomposition (VMD) with an improved wavelet threshold. The ICPO algorithm optimizes VMD parameters using fuzzy entropy as the fitness function. The decomposed modes are categorized into signal-dominant, mixed, and noise-dominant modes by the correlation coefficient method. The mixed modes are denoised using wavelet thresholding, and the final signal is reconstructed from the signal-dominant modes and the denoised mixed modes. Compared with VMD, direct wavelet thresholding, and ICPO-VMD combined with soft or hard thresholding, the proposed method outperforms the compared methods in both quantitative metrics and waveform preservation. These results confirm the effectiveness of the proposed method for aluminum plate Lamb wave denoising under the tested conditions.
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Chen et al. (2026) studied this question.
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