Partial discharge signal denoising method based on wavelet adaptive threshold

Abstract

The invention discloses a partial discharge signal denoising method based on a wavelet adaptive threshold. The partial discharge signal denoising method based on the wavelet adaptive threshold comprises the following steps of (1) inputting a partial discharge signal to be denoised, (2) carrying out wavelet multi-scale decomposition on the partial discharge signal to obtain high-frequency coefficients of decomposition scales and a low-frequency coefficient of a maximum decomposition scale, (3) using a non-negative garrote threshold function and a adaptive threshold selection method based on particle swarm optimization to carry out quantitative processing on high-frequency coefficient components obtained in the step (2) so as to remove noise components, storing the result to serve as new high-frequency coefficient components, (4) carrying out signal reconstruction through the new high-frequency coefficient components and a low-frequency coefficient component, obtained in the step (2), of the maximum decomposition scale to obtain a partial discharge signal without noise, and (5) outputting the partial discharge signal without the noise. The partial discharge signal denoising method based on the wavelet adaptive threshold achieves wavelet coefficient threshold self-adaptation selection on the premise that any priori knowledge does not exist, and is applicable to various actual partial discharge conditions and good in effect of removing white noise, and the denoised partial discharge signal with higher quality can be obtained.

Description

technical field [0001] The invention relates to a partial discharge signal detection technology of electrical equipment, in particular to a partial discharge signal denoising method based on wavelet self-adaptive threshold. Background technique [0002] On-line detection of partial discharge has become an effective method to evaluate the insulation state of electrical equipment. In the online detection, the electrical equipment is in the live operation state, and the on-site interference is serious; the partial discharge signal generated by the insulation defect is usually very weak, and it is easy to be submerged in the serious background noise. Therefore, the suppression of interference is the key issue of partial discharge on-line detection. Generally speaking, the interference in partial discharge on-line detection can be divided into three categories: periodic narrow-band interference, white noise and random pulse interference. Before suppressing random pulse interfer...

AI Technical Summary

Problems solved by technology

This method can efficiently remove white noise and reduce the distortion of the original signal, thus more effectively solving the problem of partial discharge signal of electrical equipment containing noise

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