Fault detection and diagnosis in chemical processes using sensitive principal component analysis

Industrial and Engineering Chemistry Research

Volumn 52, Issue 4, 2013, Pages 1635-1644

  Jiang, Qingchao ^a   Yan, Xuefeng ^a   Zhao, Weixiang ^b  

^a School of Information Science and Engineering   (China)

^b NATIONAL GRID   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CHEMICAL PROCESS; CHEMICAL PROCESS MONITORING; FAULT DETECTION AND DIAGNOSIS; INFORMATION LOSS; MONITORING PERFORMANCE; NON-DETECTION; ONLINE MONITORING; PCA METHOD; PCA MODEL; PRINCIPAL COMPONENTS; TENNESSEE EASTMAN PROCESS;

FAULT DETECTION; PROCESS MONITORING;

PRINCIPAL COMPONENT ANALYSIS;

EID: 84873855648     PISSN: 08885885     EISSN: 15205045     Source Type: Journal    
DOI: 10.1021/ie3017016     Document Type: Article

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