文献类型：期刊文献

英文题名：Fault Detection in Non-Gaussian Processes Based on Mutual Information Weighted Independent Component Analysis

作者：Jiang, Qingchao[1];Wang, Bei[1];Yan, Xuefeng[1]

机构：[1]E China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China

年份：2014

卷号：47

期号：1

起止页码：60

外文期刊名：JOURNAL OF CHEMICAL ENGINEERING OF JAPAN

收录：;EI(收录号：20140517244539);WOS:【SCI-EXPANDED(收录号:WOS:000330340700008)】；

基金：The authors gratefully acknowledge the support of the following foundations: 973 project of China (2013CB733600), National Natural Science Foundation of China (21176073) and the Fundamental Research Funds for the Central Universities.

语种：英文

外文关键词：Mutual Information; Independent Component Analysis; Fault Detection; Non-Gaussian Process Monitoring

摘要：A novel method which integrates mutual information (MI) with weighted independent component analysis (MI-WICA) is proposed to highlight useful information for non-Gaussian process monitoring. Since the traditional independent component analysis (ICA) may not function well for non-Gaussian process monitoring, the MI-WICA uses MI technology to evaluate the importance of each independent component (IC) within a moving window, and then set different weighting values on the selected ICs to highlight the fault information for fault detection. The proposed method is applied to a simple multivariate process and the Tennessee Eastman benchmark process, and process simulation results demonstrate that the method is superior to those of the regular principal component analysis, ICA methods.