Fault feature extraction for a planet gear’s bearing inner race based on self-reference adaptive de-noising
HE Dong-tai GUO Yu WU Xing LIU Zhiqi ZHAO Lei
Yunnan Provincial Higher Education Institutes’ Key Lab of Vibration & Noise, College of Mechanical and Electrical Engineering, Kunming University of Science and Technology, Kunming 650500, China
Aiming at problems of planet gear bearing’s vibration signals having time-varying transmission path and these signals being obliterated by gears meshing vibration signals,a diagnosis method for a planet gear bearing’s inner race faults based on self-reference adaptive de-noising (SRAD) was proposed here. Firstly,the disturbances of gears meshing vibration signals were weakened with the technique of SRAD and the pre-whiten technique of AR model. Then,the resonance band’s parameters were solved adaptively based on the spectral kurtosis approach. Furthermore,the square envelope signal was extracted using Hilbert transformation. Finally,the spectral analysis was conducted for the envelope signal. Test results showed that the proposed method can effectively reveal the fault feature information of planet gear bearing’s inner race.
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