Vold-Kalman generalized demodulation for multi-faults detection of gear and bearing under variable speeds

Abstract

Vibration signals that carry information of faulty gear and bearing under variable speeds are multi-components and time-varying by nature, presenting a challenge for effective fault feature detection. To address this issue, a Vold-Kalman generalized demodulation based multi-faults detection method has been developed. Specifically, the time-varying instantaneous dominant meshing multiple (IDMM) is firstly extracted from the time-frequency representation (TFR) of the measured raw signal. Next, the phase function (PF) set and frequency points (FP) containing fault indexes of gears and bearing are constructed based on the IDMM function and mechanical parameters. Furthermore, based on the PF set and FPs, the raw signal is successively processed by the Hilbert transform, the generalized demodulation transform (GDT), the Vold-Kalman filtering (VKF), and fast Fourier transform (FFT). Finally, integrated spectra for determining localized faults are obtained, where the spectra are calculated by repeating the above demodulation and filtering processes based on the PFs of the harmonics. The experiment result shows that the proposed method can effectively separate and extract fault features of gearbox and bearing under variable speeds. The method does not need angular resampling and rotational speed measurement as is the case in computed order tracking, and can achieve higher performance than that of band-pass filtering based techniques.