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题名: Improved Locally Linear Embedding based method for nonlinear system fault detection
作者: Zhang W(张伟) ; Liu XY(刘晓源) ; Qi RL(祁若龙) ; Jiang Y(姜勇)
作者部门: 空间自动化技术研究室
关键词: Fault detection ; Nonlinear systems
刊名: International Journal of Advancements in Computing Technology
ISSN号: 2005-8039
出版日期: 2013
卷号: 5, 期号:1, 页码:515-523
收录类别: EI
产权排序: 1
摘要: In order to detect faults of nonlinear systems, an approach based on improved Locally Linear Embedding (LLE) was proposed. Firstly, the raw data was projected to lower dimensional space by LLE. In this step, tangent space distance was introduced to LLE and certain enhancement had also been made to intrinsic dimension estimation to make the approach more efficient and robust. Secondly, the inner class distance of data was calculated as an index of fault detection. To demonstrate the effectiveness of the improved LLE method, it is applied to Tennessee Eastman (TE) process and compared with kernel principle component analysis (KPCA) method. By simulation analysis, the false negative rate of the proposed approach achieves 4.498% in average, which is much better than 77.53% of KPCA, certifying the effectiveness of the approach to nonlinear fault detection.
内容类型: 期刊论文
URI标识: http://ir.sia.cn/handle/173321/10540
Appears in Collections:空间自动化技术研究室_期刊论文

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