Generalized Synchroextracting-Based Stepwise Demodulation Transform and Its Application to Fault Diagnosis of Rotating Machinery

The nonstationary characteristics of time-varying signals can be characterized by time–frequency analysis (TFA) accurately, which has been widely used in fault diagnosis of rotating machinery. However, some practical signals contain complex multicomponent modes and noise interference, which will pose challenges to traditional TFA methods. In this article, a novel technique called generalized synchroextracting-based stepwise demodulation (GSET-SD) transform is proposed. GSET-SD introduces a strategy that combines synchroextracting transform (SET) with a stepwise demodulation procedure, thereby solving the problem of detecting and retrieving the amplitude- and frequency-modulated (AM-FM) components of a multicomponent signal from the time–frequency representation (TFR), while allowing the signal to be reconstructed from the TFR. Furthermore, to increase the estimation accuracy of the initial instantaneous frequency (IF) in processing the strong modulation signals, SET is extended to the second-order or higher order domain, and the IF is accurately estimated by the higher order polynomial method, which can obtain higher resolution TFR. The proposed approach has been applied to numerical simulations and application research. The experimental results verify the effectiveness and superiority of GSET-SD in processing strong modulation signals and demonstrate its promise in the field of fault diagnosis of rotating machinery under time-varying speeds.