An improved tracking method for bearing characteristic frequencies in the time-frequency representation of vibration signal

Rolling bearing is one of the most critical components for support and energy conversion in machines. The fault characteristic frequency (FCF) of time-frequency representation has received increasing attention in bearing diagnosis under variable speed conditions. However, FCF-extracted methods have poor adaptability to amplitude attenuation and noise interference due to local distortions or even transitions in the estimated instantaneous frequency ridges. Consequently, this paper proposes an improved FCF tracking method for variable speed bearing diagnosis. A strategy for locating distortion intervals is first developed using exponential smoothing and residual distribution. Subsequently, an advanced fast path optimization method, including peak map renewal and curve search optimization, is proposed to extract the ridges of interest. Finally, the probability density function of curve-to-curve ratios is designed to accurately identifying bearing faults. Simulation and experimental results demonstrate the effectiveness of the proposed method.