基于频域介电响应特征指纹的油纸绝缘受潮及老化状态区间识别

doi:10.19595/j.cnki.1000-6753.tces.170197

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Abstract Frequency domain spectroscopy (FDS) technology has received widespread attention and become the research hot spot in recent years as a kind of nondestructive test and insulation diagnosis method, especially the assessment of the moisture status of transformer solid insulation has made significant progress. As the two important factors influencing the transformer insulation performance,moisture and aging status present similar effect on the frequency domain dielectric response of oil-paper insulation. In the present study, it is unable to separate the moisture and aging status or effective assess the aging status of transformer with FDS method. The oil-paper insulation state was divided to several state patterns according to different moisture and aging status and a fuzzy pattern recognition method was proposed in this paper, the inputs of the classifier were the dielectric response characteristic fingerprint, and the standard state pattern corresponding to the pattern recognition results was regarded as the assessment moisture and aging status of oil-paper insulation. Thirty standard state patterns were divided according to the degree polarization and moisture content of laboratory oil-paper insulation samples in this paper, the serial integrals of dielectric loss spectroscopy in three frequency bands were selected as the dielectric response characteristic fingerprints and the state pattern was classified based on close-degree. The analysis of laboratory oilpaper samples and field transformer FDS results preliminarily proves the validity of the proposed method in this paper.

Key words： Frequency domain spectroscopy oil-paper insulation moisture and aging status fuzzy pattern recognition

Received: 27 February 2017 Published: 08 May 2018

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TM855

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	Yang Lijun
	Peng Pan
	Gao Jun
	Liu Xiao

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Yang Lijun,Peng Pan,Gao Jun等. The Range Recognition of Moisture and Aging Status of Oil-Paper Insulation Based on Frequency Domain Dielectric Response Characteristic Fingerprint[J]. Transactions of China Electrotechnical Society, 2018, 33(9): 2105-2114.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.170197 OR https://dgjsxb.ces-transaction.com/EN/Y2018/V33/I9/2105

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