Hankel-SVD-CEEMDAN Improved Threshold Partial Discharge Feature Extraction Method

被引：0
|
作者：
Jiang Y. [1 ]
Zhu Y. [1 ]
Yang X. [1 ]
Jiang X. [2 ]
机构：
[1] College of Electronics and Information Engineering, Shanghai University of Electric Power, Pudong New District, Shanghai
[2] Anqing Power Supply Company, State Grid Anhui Electric Power Co., Ltd., Anhui Province, Anqing
来源：
Dianwang Jishu/Power System Technology | 2022年 / 46卷 / 11期
基金：
上海市自然科学基金;
关键词：
complete empirical mode decomposition with adaptive noise; correlation coefficient; partial discharge; sample entropy; singular value decomposition; threshold function;
D O I：
10.13335/j.1000-3673.pst.2021.1208
中图分类号：
学科分类号：
摘要：
Aiming at the partial discharge of the power equipment immersed in the periodic narrow-band and the white noise interferences in the on-line monitoring, this paper proposes a partial discharge feature extraction based on the combination of the singular value decomposition (SVD) and the improved threshold adaptive noise complete empirical mode decomposition (CEEMDAN). First, we construct a Hankel matrix to upgrade the original partial discharge (PD) signal to a two-dimensional matrix space for singular value decomposition. The singular value corresponding to the periodic narrow-band interference is discovered according to the changing rule of the singular value slope and the periodic narrow-band interference is reconstructed and is removed from the noise signal. Then, the signal is decomposed by the CEEMDAN, and the correlation coefficient is calculated to determine the boundary between the noise component and the signal component in order that the noise component can be removed to filter out most of the white noise. Finally, with the improved threshold function combined by the merits of the traditional soft and hard threshold functions the residual component is picked up by calculating the sample entropy for the high-frequency components. The residual white noise in the high-frequency components is removed by the improved threshold function, and the high-frequency and the low-frequency components denoised by the improved threshold are reconstructed to obtain the final extracted PD signal. After verification of quantitative indicators and measured signals, this method has significant suppression of the periodic narrowband interference and the white noise, with small waveform distortion and high detail similarity. © 2022 Power System Technology Press. All rights reserved.
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页码：4557 / 4567
页数：10
相关论文
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