Feature Extraction of Weak Fault for Rolling Bearing based on CYCBD and Envelope Spectrum

Abstract

To solve the problem that it is difficult to extract the weak fault features of rolling bearing effectively under the interference of strong background noise，a method of extracting the weak fault features based on the combination of maximum second-order cyclostationary blind deconvolution （CYCBD） and envelope spectrum is proposed.Firstly，a reasonable cycle frequency set is set by the fault characteristic frequency，and CYCBD is used to reduce the noise of weak fault impulse signal with strong noise，so as to enhance the periodic impulse component in the signal.Then，the noise reduction signal is analyzed by Hilbert envelope spectrum to identify the fault characteristic frequency.The simulation and experimental results show that the method can effectively extract the weak fault features submerged by strong noise.

Keywords

• Rolling bearing;Maximum second-order cyclostationarity blind deconvolution;Weak fault;Feature extraction