Multiple squeezing based on velocity synchronous chirplet transform with application for bearing fault diagnosis

Abstract

Traditional constant basis time–frequency analysis (TFA) methods are limited by the frequency smearing effect when dealing with time-varying synchronous multi-component signals, which makes it difficult to obtain a clear time–frequency representation (TFR) for signals with closely-spaced frequencies. Therefore, it is still a challenge to segregate the synchronous components and to concentrate the energy of frequency components in the TFR. As such, a new nonlinear basis TFA method is proposed in this paper, named multiple squeezing based on velocity synchronous chirplet transform (MSVSCT). In the MSVSCT, the second-order velocity-synchronous chirplet transform is used to generate a nonlinear basis that has a consistent trend complying the instantaneous frequency (IF) variations, so that synchronous components can be separated even in a closely spaced situation. The multi-squeezing technique is adopted to further improve the energy concentration and the accuracy of the TFR. Simulated and experimental signals are employed for validations. The analysis results confirm that MSVSCT has higher accuracy, more robustness to noise, better observability, and higher fidelity of signal reconstruction over other popular TFA methods when processing synchronous multi-component signals.