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		Aimin MIAO,Zhihuan SONG,Zhiqiang GE,Le ZHOU,Qiaojun WEN.[en_title][J].Control Theory and Technology,2013,11(4):615~622.[Copy]

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AiminMIAO,ZhihuanSONG,ZhiqiangGE,LeZHOU,QiaojunWEN
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(State Key Laboratory of Industrial Control Technology, Zhejiang University)

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Received:May 09, 2012Revised:September 14, 2012

基金项目:This work was supported in part by the National Basic Research Program of China (973 Program) (No. 2012CB720505) and the National Natural Science Foundation of China (No. 61273167).

Nonlinear fault detection based on locally linear embedding

Aimin MIAO,Zhihuan SONG,Zhiqiang GE,Le ZHOU,Qiaojun WEN

(State Key Laboratory of Industrial Control Technology, Zhejiang University)

Abstract:

In this paper, a new nonlinear fault detection technique based on locally linear embedding (LLE) is developed. LLE can efficiently compute the low-dimensional embedding of the data with the local neighborhood structure information preserved. In this method, a data-dependent kernel matrix which can reflect the nonlinear data structure is defined. Based on the kernel matrix, the Nystr¨om formula makes the mapping extended to the testing data possible. With the kernel view of the LLE, two monitoring statistics are constructed. Together with the out of sample extensions, LLE is used for nonlinear fault detection. Simulation cases were studied to demonstrate the performance of the proposed method.

Key words: Locally linear embedding Fault detection Nonlinear dimension reduction