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Correlated and weakly correlated fault detection based on variable division and ICA

文献类型：期刊论文

作者Shi HB(史海波); Pan FC(潘福成); Zhou XF(周晓锋); Li S(李帅); Wang ZW(王中伟); Li KT(李开拓)
刊名Computers and Industrial Engineering
出版日期2017
卷号112页码:320-335
关键词Fault detection Monitoring Variable division Correlated and weakly correlated variables Independent component analysis
ISSN号0360-8352
产权排序1
通讯作者Li S(李帅)
中文摘要In many industrial processes, the correlations of multiple variables are complicated. Some variables are correlated and some are weakly correlated with others, which should be considered in process modelling and fault detection. This paper proposes a correlated and weakly correlated fault detection approach, which is mainly based on variable division and independent component analysis (ICA). A few variables are weakly correlated with others and fault detection should be implemented separately for correlated and weakly correlated subspaces. Firstly, variable division based on weighted proximity measure is presented to obtain correlated and weakly correlated variables. Then, ICA is used for fault detection in correlated subspace and weakly correlated subspace, which needs not kernel mapping or kernel parameter setting. Finally, comprehensive statistics are built based on different subspaces. The proposed method considers the correlated and weakly correlated characteristics of variables and the advantages of ICA in handling weakly correlated variables. The monitoring results of the numerical system and Tennessee Eastman (TE) process have been used to demonstrate effectiveness and superiority of the proposed approach.
WOS标题词Science & Technology ; Technology
类目[WOS]Computer Science, Interdisciplinary Applications ; Engineering, Industrial
研究领域[WOS]Computer Science ; Engineering
关键词[WOS]INDEPENDENT COMPONENT ANALYSIS ; MAXIMAL INFORMATION COEFFICIENT ; MONITORING BATCH PROCESSES ; NONLINEAR PROCESSES ; CONTROL CHART ; DISTANCE CORRELATION ; STATISTICAL-ANALYSIS ; MULTIMODE PROCESSES ; BAYESIAN-INFERENCE ; PROCESS DISPERSION
收录类别SCI ; EI
语种英语
WOS记录号WOS:000413126700026
源URL[http://ir.sia.cn/handle/173321/20964]  
专题沈阳自动化研究所_数字工厂研究室
作者单位1.Key Laboratory of Network Control System, Chinese Academy of Sciences, Shenyang 110016, China
2.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
3.University of Chinese Academy of Sciences, Beijing 100049, China
推荐引用方式
GB/T 7714		 Shi HB,Pan FC,Zhou XF,et al. Correlated and weakly correlated fault detection based on variable division and ICA[J]. Computers and Industrial Engineering,2017,112:320-335.
APA Shi HB,Pan FC,Zhou XF,Li S,Wang ZW,&Li KT.(2017).Correlated and weakly correlated fault detection based on variable division and ICA.Computers and Industrial Engineering,112,320-335.
MLA Shi HB,et al."Correlated and weakly correlated fault detection based on variable division and ICA".Computers and Industrial Engineering 112(2017):320-335.

入库方式： OAI收割

来源：沈阳自动化研究所

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