Fault detection and isolation in nonlinear systems with partial Reduced Kernel Principal Component Analysis method
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL(2018)
摘要
In this article, we suggest an extension of our proposed method in fault detection called Reduced Kernel Principal Component Analysis (RKPCA) (Taouali et al., 2015) to fault isolation. To this end, a set of structured residues is generated by using a partial RKPCA model. Furthermore, each partial RKPCA model was performed on a subset of variables to generate structured residues according to a properly designed incidence matrix. The relevance of the proposed algorithm is revealed on Continuous Stirred Tank Reactor.
更多查看译文
关键词
KPCA,RKPCA,fault detection isolation,partial KPCA
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络