Study on Noise Reduction Processing of Nondestructive Testing Signals Based on Wavelet Analysis - Zhang Jian; Zhang Ji; Zha Bo; Deng Jiahui; Shao Zhiwei (E3S Web of Conferences)
During the execution of nondestructive testing (NDT) tasks, various noise signals interfere with the collected data, leading to signal distortion. As a result, directly evaluating the damage of mebers based on noisy signals becomes exceedingly challenging. To mitigate the adverse effects of noise, this study employs wavelet analysis theory to analyze denoising parameters for ultrasonic testing signals contaminated by noise. The findings reveal that when the wavelet basis is set to coif5 and the decomposition level is 2, the denoised signal achieves the highest signal-to-noise ratio (SNR), effectively suppressing noise. These results provide a parameter template for future ultrasonic testing signal denoising tasks.