Research on mechanical fault diagnosis method based on synchro-extractinggeneralized S-transform
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 R ényi 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.
NETL
NSTL
万方数据
维普
