文献类型：期刊文章

作　　者：赵忠盖[1] 刘飞[1]

机构地区：[1]江南大学自动化研究所,江苏无锡214122

出　　处：《化工学报》

基　　金：新世纪优秀人才支持计划项目(NCET-05-0485)~~

年　　份：2007

卷　　号：58

期　　号：4

起止页码：970-974

语　　种：中文

收录情况：AJ、BDHX、BDHX2004、CAS、CSCD、CSCD2011_2012、EI(收录号：20072110613707)、IC、JST、RCCSE、SCOPUS、ZGKJHX、核心刊

摘　　要：Principal component analysis (PCA) has already been widely applied to process monitoring.However,PCA model is only a special case of probabilistic principal component analysis (PPCA) model and the latter itself is a special case of factor analysis (FA)model.Compared with PCA and PPCA models,FA model has less restriction and can do better to reveal essential features of the data.A FA model was built by the expectation maximum (EM)algorithm,and was introduced into industrial process monitoring.Monitoring indices based on FA were proposed to monitor the process factors space and residual space,respectively.A method was presented to select the number of factors by means of the property that the explanation ratio for the process information was convergent with the increasing number of factors.A contrastive study with PCA and PPCA was carried out in the Tennessee Eastman (TE) process,which showed the FA-based method’s superiority either in missed detection rate or in the sensitivity for fault.

关 键 词：因子分析  监控指标  主元分析 TE过程

分 类 号：TP277]