Study on PD detection for GIS based on autocorrelation coefficient and similar Wavelet soft threshold

被引:4
作者
Fan, Shaosheng [1 ]
Wang, Xuhong [1 ]
Zhang, Yihuan [2 ]
机构
[1] Changsha Univ Sci & Technol, Coll Elect & Informat Engn, Changsha 410114, Hunan, Peoples R China
[2] State Grid Zhuzhou Power Supply Co, Zhuzhou 412000, Hunan, Peoples R China
来源
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS | 2019年 / 22卷 / Suppl 3期
基金
中国国家自然科学基金;
关键词
Partial discharge; Ultra high frequency; External sensor; Empirical mode decomposition; Autocorrelation coefficient; Similar Wavelet soft threshold; PARTIAL DISCHARGE DIAGNOSIS;
D O I
10.1007/s10586-018-2619-8
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
To address the issue of white noise at partial discharge (PD) ultra high frequency (UHF) signal in gas insulated substation (GIS), this paper develops an external sensor and proposes new empirical mode decomposition (EMD) denoising method based on autocorrelation coefficient and similar wavelet soft threshold. Four types of typical GIS defects at the PD UHF signal were obtained through experiment. The autocorrelation coefficient of intrinsic mode functions (IMF) components at the PD UHF signal was computed, the cut-off point between the noise signal dominant mode and the UHF signal dominant mode was found. The similar wavelet soft threshold denoising was performed on the signal which is dominated by the noise signal, all the UHF signals were finally reconstructed. The signal-to-noise ratio computed by the proposed denoising method was compared with the one computed by the wavelet denoising method, the results shows that the proposed denoising method in this paper is more effective than the wavelet denoising method.
引用
收藏
页码:S6755 / S6766
页数:12
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