Fault diagnosis of rolling bearings based on variational mode decomposition and calculus enhanced energy operator

Aiming at the characteristics of rolling bearing fault vibration signals and considering the merits of variational mode decomposition in mono-component separation and calculus enhanced energy operator in transient impulse detection, this article introduces a new method termed fault diagnosis of rolling bearings based on variational mode decomposition and calculus enhanced energy opera-tor. Firstly, the vibration signal is decomposed into several intrinsic mode functions by variational mode decomposition to reduce the noise interferences and to satisfy the mono-component requirement by energy operator. Then, the sensitive intrinsic mode function containing the main fault information about the bearing is selected by the proposed criterion. Finally, the impulses are strengthened using calculus enhanced energy operator, and the bearing fault is diagnosed by the time domain waveform and Fourier spectrum of the sensitive mono-component instantaneous energy. The analysis results show that the proposed method can effectively diagnose the rolling bearing faults.