An Envelope Analysis Method Based on Local Mean Decomposition Filtering

Abstract

The present invention discloses a local mean decomposition and filtering-based envelope analysis method. The method includes the following steps that: original signals are decomposed by using a local mean decomposition method; noise components and trend terms in a decomposition result are eliminated by using data rearrangement and replacement; the signals which have been subjected to the primary filtering are analyzed through adopting a spectral kurtosis method, so that the center frequency and bandwidth of an optimal filter are obtained; the filter is utilized to perform secondary filtering on the signals which have been subjected to the primary filtering; a rational spline iterative smoothing envelope analysis method is adopted to carry out envelope analysis on the signals which have been subjected to the secondary filtering; and the fault type of rotating machinery is determined according to an envelope spectrum. The method of the invention is suitable for processing complex rotating machinery fault signals, can accurately determine the fault type of the rotating machinery, has good noise immunity and robustness, and is convenient to apply to engineering application.

Description

technical field [0001] The invention relates to the field of state monitoring and fault diagnosis of rotating machinery, in particular to an envelope analysis method based on local mean value decomposition filtering. 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 amplitude env...

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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