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Spatio-temporal fault localization for nonlinear spatially distributed processes: A spatial mapping filter-based framework

delete2021-07-06
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PRE
AI
冯
冯运 (Yun Feng)
王耀南 封面图
王耀南 (Yaonan Wang) *
王俊伟 封面图
王俊伟 (Jun‐Wei Wang)
H
Han‐Xiong Li
S
Steven X. Ding
DOI:10.1002/rnc.5650delete
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摘要

摘要

En 中文
Compared to the fault detection problem, fault localization for spatially distributed processes is physically intuitive but was seldom studied. The main challenge lies in the contradiction between the spatially distributed nature of the processes and a limited number of sensors that can be placed in the space for applications. In this article, we make the first attempt to systematically study the fault localization problem for a class of nonlinear spatially distributed processes without knowing any prior information of the spatial distribution function of the spatio-temporal fault. The main contribution is that a spatial mapping filter is first designed to generate a distributed residual signal which contains spatial information while using limited sensor measurements. The residual evaluation procedure is also conducted in a distributed manner. With these two parts, a systematic methodology framework is constructed and analyzed rigorously. Finally, the performance of the proposed method is evaluated on a faulty catalytic rod, which widely exists in chemical engineering.
Keyword:
distributed parameter systems
fault detection
fault localization
spatially distributed processes
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期刊

International Journal of Robust and Nonlinear Control 封面图
International Journal of Robust and Nonlinear Control
IF:
3.2
论文数:
7.0K
被引数:
1.4W

机构

C
City University of Hong Kong
学者数:
2.3W
论文数: 3.0W
被引数: 6.1W
U
University of Duisburg Essen
学者数:
2.2W
论文数: 1.7W
被引数: 22
H
hunan university
学者数:
4.5W
论文数: 3.3W
被引数: 70
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