Fault Diagnosis Method of Rolling Bearing based on Fourier Decomposition Method and 1.5-dimensional Teager Energy Spectrum

Abstract

Based on the characteristic that is the weak fault feature extraction of rolling bearing is very hard under strong background noise,a new method of rolling bearing fault diagnosis based on Fourier decomposition method（ FDM） and 1. 5- dimensional Teager energy spectrum is proposed. The first,the fault signal is decomposed into a number of intrinsic band functions（ FIBFs） which instantaneous frequency has physical significance. Then,the fault signal is reconstituted by using the method of correlation coefficient to screening intrinsic band functions. The last,the fault feature frequency is obtained by using 1. 5- dimensional Teager energy spectrum to the reconstituted signal and the result can be seen. Simulation results show that compared with the traditional envelope spectrum,this method has more obvious fault features and the effect is better. Finally this method is successfully applied to the actual rolling bearing fault diagnosis,further verify the effectiveness of the proposed method.