A robust clustering method for detection of abnormal situations in a process with multiple steady-state operation modes

Computers and Chemical Engineering

Volumn 34, Issue 2, 2010, Pages 223-231

  Maestri, Mauricio ^a   Farall, Andrés ^b   Groisman, Pablo ^b   Cassanello, Miryan ^a   Horowitz, Gabriel ^a,c  

^a UNIVERSIDAD DE BUENOS AIRES   (Argentina)

^b INSTITUTO DE CÁLCULO   (Argentina)

^c YPF S A   (Argentina)

Author keywords

Fault detection; Multiple operating modes; Multivariate statistical process monitoring

Indexed keywords

ALARM RATE; CLUSTERING TECHNIQUES; FALSE ALARMS; INDUSTRIAL INSTALLATIONS; INDUSTRIAL PROCESSS; METHANOL PLANTS; MULTIPLE OPERATIONS; MULTIVARIATE STATISTICAL PROCESS MONITORING; NOMINAL OPERATIONS; OPERATING MODES; REALISTIC SIMULATION; ROBUST CLUSTERING; STEADY-STATE OPERATION; TENNESSEE EASTMAN PROCESS;

CHEMICAL DETECTION; CLUSTER ANALYSIS; COVARIANCE MATRIX; INSPECTION EQUIPMENT; METHANOL; MULTIVARIANT ANALYSIS; NORMAL DISTRIBUTION; PROCESS MONITORING; STATISTICAL PROCESS CONTROL;

FAULT DETECTION;

EID: 73749084616     PISSN: 00981354     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compchemeng.2009.05.012     Document Type: Article

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