A wavelet threshold denoising method for fault data based on CEEMD and permutation entropy

Considering the non-stationarity of rotating machinery fault data,a wavelet threshold denoising method based on CEEMD and permutation entropy( PE) was proposed to overcome the shortages of the CEEMD denoising method and the wavelet threshold denoising method. CEEMD was used to decompose signals into a series of IMF components,the permutation entropy was used to determine the amount of noise contained in each IMF component,and the wavelet threshold method was adopted to denoise the IMF components containing more noise and retain the useful information of these components. The simulation and test results showed that the wavelet threshold denoising method based on CEEMD and PE is better than the pure CEEMD denoising method and the wavelet threshold denoising method.