Local Maximum Synchrosqueezing-Based Velocity Synchronous Chirplet Transform for Bearing Multi-Fault Diagnosis

The chirplet transform is widely used to process nonstationary signals and detect mechanical faults. Recently, the velocity synchronous linear chirplet transform (VSLCT), can effectively alleviate the smear effect and characterize nonlinear signals. However, the VSLCT suffers from the limitation of window transform, and is difficult to characterize close-spaced instantaneous frequencies (IFs) in nonstationary signals. For addressing the above issues, an improved time–frequency analysis (TFA) technique, termed local maximum synchrosqueezing-based velocity synchronous chirplet transform (LMSVSCT) is proposed in this paper. In the LMSVSCT, by determining the local maximum of the time–frequency amplitudes, a local maximum synchrosqueezing operator is constructed and employed to reassign time–frequency amplitudes calculated by the VSLCT in the frequency direction. Therefore, the energy concentration of the time–frequency representation (TFR) is further improved. Meanwhile, the developed technique has capable of handling signals with close-spaced IFs. Analysis result of the simulated multi-component signals, whose IFs are close-spaced, verifies the effectiveness of the LMSVSCT. Experimental analysis shows that the proposed algorithm has the ability to process bearing multi-fault characteristics and detect fault types. Compared with the VSLCT, generalized linear chirplet transform (GLCT), scaling-basis chirplet transform (SBCT), and short-time Fourier transform (STFT), the Rényi entropies show that the LMSVSCT exhibits better energy concentration.