Multivariate Statistical Process Monitoring of an Industrial Polypropylene Catalyzer Reactor with Component Analysis and Kernel Density Estimation1 1 Supported by the National Natural Science Foundation of China (No.60574047) and the Doctorate Foundation of the State Education Ministry of China (No.20050335018).

Chinese Journal of Chemical Engineering

Volumn 15, Issue 4, 2007, Pages 524-532

  XIONG, Li ^a   LIANG, Jun ^a   QIAN, Jixin ^a  

^a STATE KEY LABORATORY OF INDUSTRIAL CONTROL TECHNOLOGY   (China)

Author keywords

catalyzer reactor; data driven tools; fault detection; independent component analysis; kernel density estimation; multivariate statistical process monitoring; polypropylene; principal component analysis

Indexed keywords

CONSTRAINT THEORY; FAULT DETECTION; GAUSSIAN DISTRIBUTION; POLYPROPYLENES; PRINCIPAL COMPONENT ANALYSIS; PROCESS MONITORING;

KERNEL DENSITY ESTIMATION; LABORATORY EMULATOR; PRACTICAL INDUSTRIAL;

CHEMICAL REACTORS;

CHEMICAL REACTORS; CONSTRAINT THEORY; FAULT DETECTION; GAUSSIAN DISTRIBUTION; POLYPROPYLENES; PRINCIPAL COMPONENT ANALYSIS; PROCESS MONITORING;

EID: 34548425643     PISSN: 10049541     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1004-9541(07)60119-0     Document Type: Article

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