An iterative envelope analysis method for wt, spectral kurtosis and smoothing of rolling bearings

Abstract

The invention discloses a WT, spectral kurtosis and smooth iteration envelope analysis method for a rolling bearing. The method comprises the steps that firstly, an original signal is decomposed through a wavelet decomposition method; secondly, noise components and trend terms in a decomposition result are excluded through a data rearrangement and replacement operation; thirdly, a signal obtained after first-time filtering is analyzed through a spectral kurtosis method to obtain the optimal center frequency and bandwidth of a filter; fourthly, the signal obtained after first-time filtering is filtered for the second time through the filter; fifthly, envelope analysis is conduced on the signal obtained after second-time filtering through a smooth iteration envelope analysis method; lastly, the fault type of the rolling bearing is determined according to an envelope spectrum. The method is suitable for processing a complex rolling bearing signal, the fault type of the rolling bearing can be accurately judged, the good noise immunity and robustness are achieved, and engineering application is convenient.

Description

technical field [0001] The invention relates to the field of state monitoring and fault diagnosis of rotating machinery, in particular to a WT, spectrum kurtosis and smooth iterative envelope analysis method of a rolling bearing. Background technique [0002] Envelope analysis technique is widely used in fault diagnosis of gears and rolling bearings. The existing envelope analysis technology has the following three defects: ① The existing envelope analysis technology either directly analyzes the original signal, or only analyzes the original signal after simple filtering, so the existing method It is easily disturbed by noise, trend and other components, resulting in low analysis accuracy of the existing technology; ②The existing envelope analysis technology is based on the Hilbert transform, and the Hilbert transform requires that the signal to be analyzed must be a single component Narrowband signals, otherwise the frequency modulation part of the signal will pollute the ...

AI Technical Summary

Problems solved by technology

The existing envelope analysis technology has the following three defects: ① The existing envelope analysis technology either directly analyzes the original signal, or only analyzes the original signal after simple filtering, so the existing method It is easily disturbed by noise, trend and other components, resulting in low analysis accuracy of the existing technology; ②The existing envelope analysis technology is based on the Hilbert transform, and the Hilbert transform requires that the signal to be analyzed must be a single component Narrowband signals, otherwise the frequency modulation part of the signal will pollute the amplitude envelope analysis results of the signal, but the current signals to be analyzed do not strictly meet the conditions of single component and narrowband, which will lead to the existing technology is easy to The problem of misjudgment occurs; ③The envelope spectrum obtained by traditional methods has endpoint effects

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