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

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一種基于小波變換和全變差的局部放電信號組合去噪法

來源:電工電氣發(fā)布時間:2020-11-19 15:19 瀏覽次數(shù):622
一種基于小波變換和全變差的局部放電信號組合去噪法
 
戴宇1,2,王錄亮1,3,楊旭4,5,張靜4,周思遠5,潘子君5,姚雨杭5
(1 海南電網有限責任公司電力科學研究院,海南 ???570311;2 東北電力大學 建筑工程學院,吉林 吉林 132012;
3 海南省電網理化分析重點實驗室,海南 ???570311;4 國網電力科學研究院武漢南瑞有限責任公司,湖北 武漢 430074;
5 武漢大學 電氣與自動化學院,湖北 武漢 430072)
 
    摘 要:現(xiàn)場測量所得到的局部放電(Partial Discharge,PD)信號會被白噪聲污染,有必要對其進行去噪處理?;谛〔ㄗ儞Q閾值去噪和全變差去噪方法,提出一種小波閾值和全變差組合去噪算法。該算法將兩種方法進行融合,吸收了它們各自優(yōu)點,有效減小PD信號由于小波閾值去噪而造成的波動誤差,并避免了全變差去噪引入的階梯誤差。通過對實驗數(shù)據(jù)進行計算驗證,將所提算法與已有方法進行了對比,結果證明了所提方法的優(yōu)越性。
    關鍵詞:局部放電;去噪;小波變換;閾值去噪;全變差
    中圖分類號:TM866     文獻標識碼:A     文章編號: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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