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Wavelet coefficient partial discharge signal noise elimination method based on related space domain correction threshold values

A technology of wavelet coefficients and discharge signals, which is applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., to achieve the effects of improving convergence speed, improving noise elimination speed and accuracy, and reducing influence

Inactive Publication Date: 2014-08-20
HARBIN ENG UNIV +2
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But so far, no one has applied this algorithm to the optimization aspect of threshold selection denoising

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  • Wavelet coefficient partial discharge signal noise elimination method based on related space domain correction threshold values
  • Wavelet coefficient partial discharge signal noise elimination method based on related space domain correction threshold values
  • Wavelet coefficient partial discharge signal noise elimination method based on related space domain correction threshold values

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Embodiment Construction

[0029] The present invention will be further described below in conjunction with the accompanying drawings.

[0030] 1. Selection method of wavelet threshold

[0031] The wavelet threshold selection algorithm data acquisition has a premise assumption: the sampling data records the noise signal when the applied voltage is lower than the initial voltage; as the applied voltage gradually increases, when it is higher than the initial voltage, the partial discharge with noise is recorded Signal.

[0032] In the threshold selection algorithm (Threshold Elimination Method, abbreviated as TEM), the basic wavelet and the number of decomposition layers must be selected first, and the wavelet transform is performed on the signal containing only noise, and the wavelet coefficients of the detail part of each layer and the approximate part of the last layer are selected. The maximum value is recorded, and this maximum value represents the largest noise characteristic. When estimating the ...

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Abstract

The invention belongs to the field of industrial signal processing, and particularly relates to a wavelet coefficient partial discharge signal noise elimination method based on related space domain correction threshold values. The method includes the steps that wavelet transformation is carried out on partial discharge signals containing white noise; an initial value and an estimated value of a wavelet coefficient are extracted; size correlation coefficients are solved; correlation values are obtained after normalization; discrete wavelet transform is recorded and signals after noise elimination are obtained. A wavelet threshold value selection method is improved, a space domain related optimizing partial reestablishment weight matrix is introduced, and therefore, influences of noise points on sample data are reduced, the algorithm convergence rate is improved, and the noise elimination speed and precision of the partial discharge signals are improved.

Description

technical field [0001] The invention belongs to the field of industrial signal processing, and in particular relates to a partial discharge signal denoising method based on a variable wavelet coefficient correction threshold value in a space domain. Background technique [0002] With the wide application of various organic insulating materials in power equipment, the effective extraction of partial discharge signals (PD for short) in power equipment has become more and more prominent. The partial discharge signal can be used to diagnose insulation faults, determine the degree and type of discharge, and judge the insulation degradation of equipment, etc., all of which play a vital role in the safe and stable operation of power equipment. However, there is electromagnetic interference in the actual operating environment of power equipment, which causes partial discharge signals to be submerged in noise, which in turn affects the accuracy of using partial discharge signals to d...

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Application Information

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IPC IPC(8): G06F19/00
Inventor 李金王妍玮王磊梁洪于虹马仪丛望栾宽王颖才忠喜
Owner HARBIN ENG UNIV
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