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A signal decomposition method based on improved empirical wavelet decomposition

A technology of signal decomposition and empirical wavelet, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as ineffective decomposition, achieve the effects of suppressing excessive decomposition, enriching theoretical methods, and eliminating interference

Pending Publication Date: 2019-06-28
NORTH CHINA UNIVERSITY OF SCIENCE AND TECHNOLOGY
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Problems solved by technology

[0006] Aiming at the problem that EWT cannot effectively decompose modes containing rich fault characteristic information in the background of interference, the present invention provides a signal decomposition method based on Improved Empirical Wavelet Transform (IEWT). Broad, the decomposition effect is more obvious

Method used

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  • A signal decomposition method based on improved empirical wavelet decomposition
  • A signal decomposition method based on improved empirical wavelet decomposition
  • A signal decomposition method based on improved empirical wavelet decomposition

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Embodiment Construction

[0025] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0026] In this embodiment, the fault of slipper wear is taken as an example for illustration.

[0027] see Image 6 , a signal decomposition method based on Improved Empirical Wavelet Transform (IEWT), the specific steps are as follows:

[0028] Step (1), obtain the power density spectrum

[0029] Calculate the power density spectrum of the collected discrete-state fault signal f(n), and its spectrum value distribution sequence is denoted as P.

[0030] Step (2), threshold removal based on power density spectrum

[0031] Use L thresholds of different sizes coefficient×mean(P) to remove the spectral values ​​in P that are smaller than the threshold, and obtain L new spectral value distribution sequences P coefficient , where coefficient=1, 2,..., an integer of L, and mean(P) is the average spectral value. Since the value of the interference spectrum...

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Abstract

The invention relates to a signal decomposition method based on improved empirical wavelet decomposition. The method comprises the following steps: carrying out Fourier power spectrum density spectralline solving on a fault signal; selecting a plurality of different threshold values to remove the interference component spectrum values, decomposing the fault signals based on the new spectral line,and screening an optimal threshold value, an optimal decomposition result and a modal component containing rich fault characteristic information by using the fault characteristic energy ratio information. Under the interference background, modal components containing rich fault feature information can still be effectively and optimally decomposed, interference is eliminated, modal aliasing and excessive decomposition phenomena are restrained, an ideal decomposition result is obtained, the defects of EWT are overcome, and the theoretical method of modal decomposition is enriched.

Description

technical field [0001] The invention relates to a fault signal processing method of a rotating machine, in particular to a signal decomposition method based on improved empirical wavelet decomposition. Background technique [0002] Rotating machinery such as hydraulic pumps, hydraulic motors, motors, bearings, gears and rotors are widely used in various important industrial fields. The deterioration of the health status of rotating machinery is of great significance to the intelligent fault diagnosis of rotating machinery. The vibration form and transmission path of rotating machinery faults are very complex, and the fault signal has the characteristics of nonlinearity and non-stationarity, and is easily introduced by equipment such as noise, background noise and electromagnetic interference. Therefore, how to effectively extract the modal components with rich fault feature information and suppress interference has become a key issue. [0003] The disadvantage of wavelet t...

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Application Information

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IPC IPC(8): G06F17/50G06K9/00
Inventor 郑直
Owner NORTH CHINA UNIVERSITY OF SCIENCE AND TECHNOLOGY
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