Return
Generalized wavelet-based synchrosqueezing transform: Algorithm and applications
DOI:10.1177/1475921720906112.png)
Abstract
En 中文
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.
Keywords:
Fault diagnosis
instantaneous frequency
nonstationary signal
rotor system
synchrosqueezing transform
time-frequency analysis
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
S
IF:
5.7
Papers:
2.3K
Citations:
1.1W

