Adaptive denoising for pipe leak vibroacoustic in multiple conditions using correlation coefficient matrix and multi-objective optimization

Abstract

To achieve adaptive denoising of pipe leak vibroacoustic under low signal to noise ratio (SNR), a novel method based on correlation coefficient matrix was proposed for selecting the effective mode components obtained using variational mode decomposition (VMD). For the leak signals detected under different conditions, new indicators were designed to evaluate the denoising performance without using the prior knowledge of pure signals, and they were introduced as the objective function of multi-objective grey wolf optimizer (MOGWO). Subsequently, the best mode number K and penalty factor η of VMD were determined according to Pareto front, thus achieving adaptive denoising under multi-condition. To verify the proposed method, an experimental rig was built to simulate gas pipe leaks under multiple conditions with a SNR range from – 8 dB to 4 dB. The results showed that the proposed VMD-based denoising method achieved using the improved MOGWO can effectively suppress noise.