Research on fault diagnosis method combining CEEMD with generalized morphology difference filter
HUANG Gangjing， FAN Yugang， HUANG Guoyong
1.Faculty of Information Engineering & Automation， Kunming University of Science and Technology， Kunming 650500；2.Engineering Research Center for Mineral Pipeline Transportation， Kunming 650500
Abstract：In order to extract the early fault feature of rolling bearing， a method based on the combination of Complementary Ensemble Empirical Mode Decomposition (CEEMD) and generalized morphological difference filter for fault diagnosis is proposed in this paper. Firstly， the vibration signals are decomposed by the CEEMD into different scales of IMF component signals， and the IMF component signals with rich fault information are reconstructed by the correlation coefficient and kurtosis criterion. Then the reconstructed signals are filtered by the generalized morphological difference filter to filter the noise. Finally， characteristics of signals are extracted from the vibration signal which filtered signals using Teager-Kaiser Energy Operator (TKEO). The experiment results have shown that the proposed method applied in the rolling bearings fault detection is effective.
2017, Vol. 51 
