Second-order synchroextracting wavelet transform for nonstationary signal analysis of rotating machinery

Characterizing nonstationary signals with widely changing instantaneous frequency features is a challenging issue for time-frequency analysis (TFA) method. A novel TFA method termed second-order synchroextracting wavelet transform (SSEWT) is proposed for this purpose. The method extends the existing synchroextracting transform to the context of wavelet transform, and introduces the second-order instantaneous frequency estimate to improve its capability of processing nonstationary signals. The proposed method provides concentrated time-frequency representation with multiple resolutions, and retains good invertibility. The theories concerned and discrete implementation of the SSEWT are presented. Numerical simulations and experimental data collected from rotating machinery are employed to verify the competitive advantages of the SSEWT in revealing the local time-frequency features of nonstationary signals. (C) 2021 Elsevier B.V. All rights reserved.

Automated summary

A novel TFA method called second-order synchroextracting wavelet transform (SSEWT) is proposed for characterizing nonstationary signals with widely changing instantaneous frequency features. This method extends the existing synchroextracting transform to the context of wavelet transform and introduces the second-order instantaneous frequency estimate to enhance its processing capability for nonstationary signals. The SSEWT provides concentrated time-frequency representation with multiple resolutions and maintains good invertibility.