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.
王天真, 刘远, 汤天浩, 陈炎. 基于相对主元分析的动态数据窗口故障检测方法[J]. 电工技术学报, 2013, 28(1): 142-148.
Wang Tianzhen, Liu Yuan, Tang Tianhao, Chen Yan. Dynamic Data Window Fault Detection Method Based on Relative Principal Component Analysis. Transactions of China Electrotechnical Society, 2013, 28(1): 142-148.
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