Local maximum synchrosqueezing reassigning chirplet transform and its application to gearbox fault diagnosis

Abstract Aiming at the problems of poor time–frequency (TF) aggregation and severe noise interference when traditional TF analysis (TFA) methods deal with complex multi-component signals, this paper proposes a new TFA method—local maximum synchrosqueezing reassigning chirplet transform (LMSRCT). The core idea of the method is to introduce the principle of general linear chirplet transform (CT) into synchro-reassigning transform, followed by reassigning the results of local maximum synchrosqueezing CT, and then introducing the innovative synchro-reassigning operator. This results to a novel three-step method for extracting instantaneous frequency (IF), which ultimately yields the final TF representation. This method ensures the integrity of each IF, solves the problem of energy divergence problems, and improves aggregation. Simulation and experimental results show that the LMSRCT can provide better characterisation results compared to other methods and can effectively solve the different situations that occur between the IFs of complex signals. The proposed method can effectively estimate transmission speed, which achieves fault diagnosis under tacholess conditions, and the order analysis results are more accurate and reliable.