Rolling bearing fault diagnosis based on minimum entropy deconvolution and 1.5-dimensional Teager energy spectrum

Abstract

Based on the characteristics that it is difficult to extract weak fault signals of rolling bearings against the strong noise background, this paper proposes a new method of rolling bearing fault diagnosis based on minimum entropy deconvolution and 1.5-dimensional Teager energy spectrum. Firstly, minimum entropy deconvolution (MED) is used to reduce noise of rolling bearings against the strong noise background, then Teager energy operator demodulation is conducted, and finally 1.5-dimensional spectrum analysis of demodulated signals is conducted. The effectiveness and accuracy of the proposed method have been validated through analysis of simulation signals of inner and outer ring faults and processing of experimental data, and comparison and contrast with envelope spectrum.