Diagnosis of Weak Fault of Rolling Bearing Based on EEMD and Envelope Spectrum Analysis

Abstract

As the vibration features of roller signals of rolling bearing are weak and difficult to be extracted and diagnosed, a new fault diagnosis method based on ensemble empirical mode decomposition (EEMD) and envelope spectrum analysis is used in this paper to solve the problem. The weak fault vibration signals of rolling bearing are decomposed by EEMD firstly. Considering that the kurtosis value is very sensitive to the impact characteristics of the signal, the intrinsic modal functions (IMF) are screened out with kurtosis value and cross-correlation coefficient for signal reconstruction, and the screened IMFs are superposed for signal reconstruction, and then the Hilbert transform is carried out for these reconstructed signals to get the envelope spectrum. Finally, the data obtained from the spectral envelope of results are compared to the rolling bearing fault frequency. After fault diagnosis is carried out for the roller signals, the results show that the envelope spectrum method based on EEMD has great advantages. It can effectively highlight the characteristic frequency of the roller fault of the rolling bearing and is convenient to diagnose the weak fault signal of the rolling bearing.