Suppressing White Noise in Partial Discharge Based on the Wavelet Entropy of Lifting Wavelet Decomposition

WU Juzhuo; NIU Haiqing

doi:10.13296/j.1001-1609.hva.2014.12.023

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Suppressing White Noise in Partial Discharge Based on the Wavelet Entropy of Lifting Wavelet Decomposition

更新时间：2025-04-26

- Suppressing White Noise in Partial Discharge Based on the Wavelet Entropy of Lifting Wavelet Decomposition
- High VoltageApparatus Vol. 50, Issue 12, Pages: 126-132(2014)
- 作者机构：
  
  华南理工大学电力学院
- 作者简介：
- 基金信息：
- DOI：10.13296/j.1001-1609.hva.2014.12.023
  CLC： TN911.4
- Published：2014
- 稿件说明：
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[1]吴炬卓,牛海清.基于提升小波分解的小波熵在抑制局部放电白噪声干扰中的应用[J].高压电器,2014,50(12):126-132.

WU Juzhuo, NIU Haiqing. Suppressing White Noise in Partial Discharge Based on the Wavelet Entropy of Lifting Wavelet Decomposition[J]. High voltageapparatus, 2014, 50(12): 126-132.
[1]吴炬卓,牛海清.基于提升小波分解的小波熵在抑制局部放电白噪声干扰中的应用[J].高压电器,2014,50(12):126-132. DOI： 10.13296/j.1001-1609.hva.2014.12.023.

WU Juzhuo, NIU Haiqing. Suppressing White Noise in Partial Discharge Based on the Wavelet Entropy of Lifting Wavelet Decomposition[J]. High voltageapparatus, 2014, 50(12): 126-132. DOI： 10.13296/j.1001-1609.hva.2014.12.023.

摘要

抑制白噪声干扰是局部放电在线检测中的关键技术。文中提出了一种基于小波熵的局部放电信号去除白噪声方法:先将信号进行提升小波分解;再对最高一层的低频系数和不同分解尺度上的高频系数进行阈值及量化处理;利用经过阈值处理过的最高一层的低频系数和各分解尺度的高频系数重构信号

去掉白噪声干扰。计算机仿真分析和现场数据处理表明

文中提出的提升小波熵分层软阈值去噪法可以有效地滤除局部放电信号中的白噪声

在抑制白噪声的性能和稳定性方面优于提升小波软阈值法。

Abstract

The suppression of white noise interference is one of the key techniques of on-line monitoring of partial discharge.This paper puts forward a method of denoising white noise based on wavelet entropy.Firstly

the signal is disposed of by lifting wavelet decomposition.Secondly

the low-frequency coefficients of the highest decomposition scale and the high-frequency lifting wavelet decomposition coefficients of different scale are processed with wavelet entropy thresholds and quantification.Then reconstruct the signal and the white noise is removed.Simulation and denoising of signals detected online show that the proposed method can effectively remove the white noise in PD signal and has better performance and stability compared to the denoising method of lifting wavelet soft threshold.

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