Generalized wavelet-based synchrosqueezing transform: Algorithm and applications

Abstract

Time–frequency analysis is recognized as an efficient tool to characterize the time-varying feature from the oscillatory signal by transforming it into an identifiable form. Some traditional time–frequency transforms are subjected to poor time–frequency resolution or do not allow for mode reconstruction. As a postprocessing method, the synchrosqueezing transform has been utilized to tackle these problems. In this framework, a new method termed as generalized wavelet-based synchrosqueezing transform is developed in the current research work to deal with a strong modulated signal. The proposed method is capable to theoretically generate unbiased instantaneous frequency estimation at any order by defining a higher-order Taylor expansion signal model. The signal mapping procedure is also embedded in the algorithm to further improve the anti-noise robustness of the presented method. Numerical investigation of synthetic signal verifies the feasibility of the generalized wavelet-based synchrosqueezing transform as compared to previously developed approaches. Moreover, the practical implementation of the proposed method for the detection of the rotor rub-impact fault demonstrates that the generalized wavelet-based synchrosqueezing transform is qualified for machine fault diagnosis under the variable speed conditions.