Research on rolling bearing fault diagnosis based on Ensemble Empirical Mode Decomposition and Hilbert envelope spectrum analysis.

Rolling bearings are important components of rotating machinery and equipment, and their fault diagnosis is of great significance. A fault diagnosis method that combines EEMD (ensemble empirical mode decomposition) and Hilbert envelope spectrum analysis is proposed. First, the EEMD method is used to decompose the original fault signal to obtain the IMF (intrinsic mode function) component containing bearing fault characteristic information, and then through Hilbert the envelope spectrum analysis method analyzes the IMF component and finally obtains the fault characteristic frequency. The fault characteristic frequency obtained by analysis is compared with the bearing rolling element fault frequency calculated theoretically. The results show that the rolling bearing fault diagnosis method based on EEMD and Hilbert envelope spectrum analysis can effectively identify the rolling element fault of the bearing.