期刊
ISA TRANSACTIONS
卷 64, 期 -, 页码 184-192出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.isatra.2016.06.002
关键词
KPCA; RKPCA; MW-RKPCA; Nonlinear dynamic process; Fault detection
This paper proposes an improved Reduced Kernel Principal Component Analysis (RKPCA) for handling nonlinear dynamic systems. The proposed method is entitled Moving Window Reduced Kernel Principal Component Analysis (MW-RKPCA). It consists firstly in approximating the principal components (PCs) of the KPCA model by a reduced data set that approaches properly the system behavior in the order to elaborate an RKPCA model. Secondly, the proposed MW-RKPCA consists on updating the RKPCA model using a moving window. The relevance of the proposed MW-RKPCA technique is illustrated on a Tennessee Eastman process. (C) 2016 ISA. Published by Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据