Suzhou Electric Appliance Research Institute
期刊号: CN32-1800/TM| ISSN1007-3175

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一种基于小波变换和全变差的局部放电信号组合去噪法

来源:电工电气发布时间:2020-11-19 15:19 浏览次数:552
一种基于小波变换和全变差的局部放电信号组合去噪法
 
戴宇1,2,王录亮1,3,杨旭4,5,张静4,周思远5,潘子君5,姚雨杭5
(1 海南电网有限责任公司电力科学研究院,海南 海口 570311;2 东北电力大学 建筑工程学院,吉林 吉林 132012;
3 海南省电网理化分析重点实验室,海南 海口 570311;4 国网电力科学研究院武汉南瑞有限责任公司,湖北 武汉 430074;
5 武汉大学 电气与自动化学院,湖北 武汉 430072)
 
    摘 要:现场测量所得到的局部放电(Partial Discharge,PD)信号会被白噪声污染,有必要对其进行去噪处理。基于小波变换阈值去噪和全变差去噪方法,提出一种小波阈值和全变差组合去噪算法。该算法将两种方法进行融合,吸收了它们各自优点,有效减小PD信号由于小波阈值去噪而造成的波动误差,并避免了全变差去噪引入的阶梯误差。通过对实验数据进行计算验证,将所提算法与已有方法进行了对比,结果证明了所提方法的优越性。
    关键词:局部放电;去噪;小波变换;阈值去噪;全变差
    中图分类号:TM866     文献标识码:A     文章编号:1007-3175(2020)11-0016-07
 
Combined Partial Discharge Signal Denoising Algorithm Based on Wavelet Transform and Total Variation
 
DAI Yu1,2, WANG Lu-liang1,3, YANG Xu4,5, ZHANG Jing4, ZHOU Si-yuan5, PAN Zi-jun5, YAO Yu-hang5
(1 Electric Power Research Institute of Hainan Power Grid Limited Company, Haikou 570311 , China;
2 School of Civil Engineering and Architecture, Northeast Electric Power University, Jilin 132012,China;
3 Hainan Key Laboratory of Physical and Chemical Analysis of Power Grid, Haikou 570311 ,China;
4 Wuhan NARI Limited Liability Company of State Grid Electric Power Research Institute, Wuhan 430074, China;
5 School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China)
 
    Abstract: On-site measurement partial discharge (Partial Discharge, PD) signal will be polluted by white noise, and it is necessary to denoise it. Based on wavelet transform threshold denoising and total variation denoising method, a combined wavelet threshold and total variation denoising algorithm is proposed. The algorithm merges the two methods, absorbs their respective advantages, effectively reduces the fluctuation error of the PD signal due to wavelet threshold denoising, and avoids the step error introduced by the total variation denoising. By calculating and verifying the experimental data, the proposed algorithm is compared with the existing method, and the result proves the superiority of the proposed method.
    Key words: partial discharge; denoising; wavelet transform; threshold denoising; total variation
 
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