Time-varying demodulation analysis for rolling bearing fault diagnosis under variable speed conditions

Abstract

Rolling bearings often work under variable speed conditions, resulting in nonstationary vibrations. How to effectively extract the time-varying fault frequency from nonstationary vibration signals is a key issue in rolling bearing fault diagnosis. To address this issue, a quality time–frequency analysis of excellent time–frequency readability and robust to noise is necessary. To this end, the concentration of frequency and time (ConceFT) method is exploited. Based on this time–frequency analysis method, and considering the modulation feature of rolling bearing vibrations, we propose joint time-varying amplitude and frequency demodulated spectra to reveal the time-varying fault characteristic frequency. Firstly, the optimal frequency band sensitive to rolling bearing fault is selected by spectral kurtosis. Then, both the amplitude envelope and instantaneous frequency of the sensitive signal component within the selected optimal frequency band are calculated. Next, the ConceFT method is applied to the amplitude envelope and instantaneous frequency to generate the time-varying amplitude and frequency demodulated spectra. Finally, rolling bearing fault can be diagnosed by analysis of the time-varying frequency revealed by the time-varying demodulated spectra. This method is free from complex time-varying sidebands, and is robust to noise interference. It is illustrated by numerical simulated signal analysis, and is further validated via lab experimental rolling bearing vibration signal analyses. The localized defects on both inner and outer race are successfully diagnosed.