基于自适应S变换与截断紧致奇异值分解的局部放电源复杂染噪特征提取方法

doi:10.19595/j.cnki.1000-6753.tces.210987

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Abstract To solve the problem that the features of the partial discharge (PD) source are difficult to extract because the PD source signal is polluted by the complex noise, a PD source complex noise feature extraction method is proposed based on the adaptive S-transform and the truncated compact singular value decomposition (TCSVD). First, the S-transform is optimized and improved, and then applied for the PD source to obtain the time-frequency domain matrix. The narrow-band interference signal is filtered adaptively, and the useful time-frequency signal of partial discharge is extracted. Second, compact singular value decomposition is utilized to decompose the extracted time-frequency matrix. Then, the fitting derivative method is proposed to find the singular value threshold parameters and truncate the singular value, the white noise signal in PD source is filtered. Finally, the proposed PD source feature extraction method is verified and analyzed by theoretical simulation and field test. The results indicate that the feature extraction method has well feature extraction ability for the PD signal with complex noise, and can be utilized to effectively extract useful information of PD signal.

Key words： Partial discharge S-transform adaptive S-transform truncated compact singular value decomposition grid search feature extraction

Received: 04 July 2021

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TM835

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	Articles by authors
	Ning Shuguang
	He Yigang
	Cheng Tongtong
	Sui Yongbo
	Huang Yuan

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Ning Shuguang,He Yigang,Cheng Tongtong等. Feature Extraction of Partial Discharge Source with Complex Noise Based on Adaptive S-Transform and Truncated Compact Singular Value Decomposition[J]. Transactions of China Electrotechnical Society, 2022, 37(15): 3951-3962.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.210987 OR https://dgjsxb.ces-transaction.com/EN/Y2022/V37/I15/3951

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