Abstract： On the basis of fault diagnosis of rolling element bearings which combined signal processing method such as EMD, spectral kurtosis and envelope analysis, an improved methodology based on EEMD ，measure-factor and the fast kurtogram was proposed. Firstly, fault signals were decomposed into a group of intrinsic mode functions (IMFs) by ensemble empirical mode decomposition (EEMD). Secondly, the IMF which could best represent the fault information was selected to reconstruct signals using measure-factor based on distance. Thirdly, an optimal band-pass filter was constructed by the center frequency and bandwidth generated by the fast kurtogram. Finally, the specific fault was determined by comparing the envelope spectrum of filtered signals with the fault characteristic frequency of rolling element bearings. The effectiveness of the proposed methodology was demonstrated by the simulated data and actual signals of inner race, and the improved method had a good prospect in the application of rolling element bearing diagnosis.
彭畅;柏林;谢小亮. 基于EEMD、度量因子和快速峭度图的滚动轴承故障诊断方法[J]. , 2012, 31(20): 143-146.
PENG Chang;BO Lin;XIE Xiao-liang. Fault diagnosis method of rolling element bearings based on EEMD,measure-factor and fast kurtogram. , 2012, 31(20): 143-146.
2012, Vol. 31 
