Resonance-Based Nonlinear Demodulation Analysis Method of Rolling Bearing Fault

Abstract

Numerous mechanical nonstationary fault signals are a mixture of sustained oscillations and nonoscillatory transients, which are difficult to efficiently analyze using linear methods. We propose a nonlinear demodulation analysis method based on resonance and apply it to the fault diagnosis of rolling bearings. Unlike conventional demodulation methods that use frequency-based analysis and filtering techniques, our nonlinear demodulation analysis method is a decomposition demodulation of the signals according to different resonance based on Q-factors. When a local rolling bearing fault such as pitting is present, the fault vibration signals consist of the regular vibration signals and noise (a high resonance component containing multiple simultaneous sustained oscillations) and a transient impulse signal (a low resonance component being a signal containing nonoscillatory transients of faults). The regular vibration signal is a narrowband signal that has a high Q-factor, and the transient impulse signal is a wideband signal that has a low Q-factor. Using our resonance-based nonlinear demodulation analysis method, we decompose the signal into high resonance, low resonance, and residual components. Then, we perform a demodulation analysis on the low resonance component that includes the fault information. We have verified the feasibility and validity of the algorithm by analyzing the results of experimental and engineering signals.