Yunfeng Zhang, Xiangshun Li, Chuyue Lou, Jin Jiang
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Principal Component Analysis Methods for Fault Detection Evaluated on a Nuclear Power Plant Simulation Platform
In this paper, fault detection methods based on principal component analysis (PCA) have been investigated. The methods have been evaluated using the data acquired from a practical nuclear power plant simulation platform. PCA, dynamic principal component analysis (DPCA), kernel principal component analysis (KPCA), two-step principal component analysis (TS-PCA) have been considered. The performance of these methods in fault detection has been compared.
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