期刊论文

Partial Discharge Detection for GIS Based on Normalized Autocorrelation Function and Similar Wavelet Soft Threshold

中文

高压电器

1001-1609

2018

54

3

17-24

10.13296/j.1001-1609.hva.2018.03.003

收稿日期：2017-09-11； 修回日期：2017 - 11 - 25 基金项目：湖南省科技计划项目(2015GK3018)；湖南省高校创新平台开放基金项目(14K001)。 Project Supported by Scientific and Technological Projects in Hunan Province(2015GK3018)，the Open Fund Project of the Innovation Platform of Hunan Province’s Colleges and Universities(14K001).

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针对目前利用特高频方法检测GIS典型缺陷时,存在白噪声干扰滤除效率低以及原始信号波形畸变率高等问题,构建了GIS特高频局部放电检测试验模型,经人工处理获得4种典型局部放电UHF信号,提出采用EMD分解将4种典型缺陷的特高频信号分解为有限个IMF分量,利用归一化自相关函数找到IMF分量中局部放电信号与白噪声的分界点,对含白噪声的IMF分量使用类小波软阈值进行滤波,随后重构所有IMF分量,得到各缺陷局部放电特高频信号。将文中方法所得信号与小波去噪信号进行信噪比以及波形畸变率对比,结果表明文中所用方法具有更为良好的去噪效果,可用于GIS局部放电监测。

Four typical defects are made in GIS,the UHF partial discharge signals of these defects are acquired,and a denoising method for these UHF PD signals is proposed. The empirical mode decomposition(EMD) is used to decompose the UHF PD signals of the four defects into a finite number of the intrinsic mode function(IMF) components,the cut-off point between the PD signal and the white noise in the IMF component is determined by using the normalized autocorrelation function,and the IMF component with white noise is filtered by using the wavelet soft t...