基于相对主元分析的动态数据窗口故障检测方法

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Abstract In traditional principal component analysis(PCA), because of the neglect of the influence of dimension standardization, it was difficult to extract principal components(PCs) effectively. The fault detection method based on relative principal component analysis(RPCA), its control limit is related to the number of PCs and confidence. For these problems, a dynamic data window method based on RPCA is proposed in this paper. The proposed method combined the traditional control limit and dynamic data window by introducing a weight. Finally, it is applied to wind power generation system, can detect failures effectively and reduce the rate of false alarm.

Key words： RPCA T²-statistic,dynamic data window fault detect

Received: 08 October 2011 Published: 27 November 2013

PACS:

TM315

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	Articles by authors
	Wang Tianzhen
	Liu Yuan
	Tang Tianhao
	Chen Yan

Cite this article:

Wang Tianzhen,Liu Yuan,Tang Tianhao等. Dynamic Data Window Fault Detection Method Based on Relative Principal Component Analysis[J]. Transactions of China Electrotechnical Society, 2013, 28(1): 142-148.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2013/V28/I1/142

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