Research on mechanical fault diagnosis method based on synchro extractinggeneralized S transform

DOI:	10.11809/bqzbgcxb2024.02.033
Keywords:	Synchroextracting Transform; generalized S transform; time frequency analysis; mechanical fault diagnosis; aero engine
Abstract:	The existing Synchroextracting Transform (SET) window function lacks flexibility, which makes it difficult to obtain transient frequencies with high time frequency accuracy and high anti interference performance when performing fault diagnosis. The SEGST method is characterized by using the Rényi entropy as a measure of time frequency aggregation, introducing two scale adjustment factors in the Gaussian window function to select the optimal values of the parameters, and constructing a synchronous extraction operator for the two dimensional time frequency spectrum of the obtained generalized S transform. A simultaneous extraction operator is constructed to extract the time frequency coefficients at the time frequency ridges, which can retain the TF information most relevant to the time varying characteristics of the signal and eliminate the redundant fuzzy time frequency energy, thus obtaining time frequency energy features with high time frequency resolution. The simulation results show that the proposed method outperforms the conventional time frequency analysis methods in terms of both time frequency resolution and noise robustness, and maintains good reconfigurability. Finally, the proposed method is applied to the fault diagnosis of high speed rolling bearings in aero engines, and the results show that the method can accurately identify the characteristic frequencies in the fault signals.
Published:	2024-02-28
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