Considering the non-stationary of rolling machinery fault data, the wavelet threshold denoising method based on CEEMD and Permutation Entropy (PE)is proposed to cover the shortage of Complementary Ensemble Empirical Mode Decomposition (CEEMD) denoising method and wavelet threshold denoising method. CEEMD is used to decompose signals into a series of IMF components, the Permutation Entropy is presentedto evaluate noise contained in each IMF component, and wavelet threshold method is adopted for IMF components containingmuch noise for denoising, in order to retain the useful information of these components. The test results ofsimulation data and experimental data show that, the wavelet threshold denoising method based on CEEMD and PE is better than pure CEEMD denoising method and the wavelet threshold denoising method.
引用本文:
周涛涛1,2,朱显明1,2,彭伟才1,2,刘彦1,2. 基于CEEMD和排列熵的故障数据小波阈值降噪方法[J]. 振动与冲击, 2015, 34(23): 207-211.
Taotao Zhou1,2, Xianming Zhu1,2, Weicai Peng1,2, Yan Liu1,2. Awavelet threshold denoising method for fault data based on CEEMD and Permutation Entropy. JOURNAL OF VIBRATION AND SHOCK, 2015, 34(23): 207-211.