华南理工大学学报(自然科学版) ›› 2020, Vol. 48 ›› Issue (2): 9-15.doi: 10.12141/j.issn.1000-565X.190328

• 能源、动力与电气工程 • 上一篇    下一篇

基于S 变换与奇异值分解的局部放电信号去噪方法

牛海清1 宋廷汉1 罗新2 庄小亮2   

  1. 1. 华南理工大学电力学院,广东广州510640; 2. 中国南方电网超高压输电公司广州局,广东广州510663
  • 收稿日期:2019-06-10 修回日期:2019-08-28 出版日期:2020-02-25 发布日期:2020-02-01
  • 通信作者: 牛海清(1969-) ,女,博士,副教授,主要从事高压输电线路及高压电气设备研究。 E-mail:niuhq@scut.edu.cn
  • 作者简介:牛海清(1969-) ,女,博士,副教授,主要从事高压输电线路及高压电气设备研究。
  • 基金资助:
    国家“863”计划项目( 2015AA050201)

Partial Discharge Signal Denoising Method Based on S-Transform and Singular Value Decomposition#br#

NIU Haiqing1 SONG Tinghan1 LUO Xin2 ZHUANG Xiaoliang2   

  1. 1. School of Electric Power,South China University of Technology,Guangzhou 510640,Guangdong,China; 2. Guangzhou Bureau of CSG EHV Power Transmission Company,Guangzhou 510663,Guangdong,China
  • Received:2019-06-10 Revised:2019-08-28 Online:2020-02-25 Published:2020-02-01
  • Contact: 牛海清(1969-) ,女,博士,副教授,主要从事高压输电线路及高压电气设备研究。 E-mail:niuhq@scut.edu.cn
  • About author:牛海清(1969-) ,女,博士,副教授,主要从事高压输电线路及高压电气设备研究。
  • Supported by:
    Supported by the High-Tech R& D Program of China ( 2015AA050201)

摘要: 根据白噪声在S 变换域服从2 分布且平均功率谱与频率成正比的特点,提出了基于S 变换与奇异值分解( SVD) 的局部放电( PD) 信号去噪方法。首先对带噪PD信号进行S 变换,得到时频矩阵; 接着利用SVD 与奇异值差分谱理论,确定PD 信号发生的时间与个数,得到白噪声区域; 然后通过构造与频率成正比的线性方程,采用硬阈值法对时频矩阵进行处理,完成PD 信号的第一次去噪; 最后利用SVD 对PD 信号进行第二次去噪。仿真和实测信号的分析结果表明,文中方法的去噪效果优于小波阈值法,且该方法更简便快捷。

关键词: 局部放电, S 变换, 奇异值分解, 噪声抑制

Abstract: According to the characteristics that white noise follows 2 distribution in the S-transform domain and its average power spectrum is linearly correlated with the frequency,a partial discharge signal denoising method based on S-transform and singular value decomposition was proposed. Firstly,the time-frequency matrix of noisy partial discharge signals was obtained by S-transform. Secondly,the time and number of PD signal were determined by singular value decomposition and singular value difference spectrum theory,and the white noise area was obtained.Then the first denoising of PD signal was carried out by constructing the linear equation in proportion to frequency and dealing with the time-frequency matrix with hard threshold method. Finally,the second denoising of PD signal was done with singular value decomposition theory. Both the simulation and the measured signals show that the denoising effect of the proposed method is better than that of the wavelet threshold method,and the method is simpler and faster.

Key words: partial discharge, S-transform, singular value decomposition, noise suppression

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