Sensor fault detection and isolation of an industrial gas turbine using partial kernel PCA

IFAC-PapersOnLine

Volumn 28, Issue 21, 2015, Pages 1389-1396

  Navi, Mania ^a   Davoodi, Mohammad Reza ^a   Meskin, Nader ^a  

^a Qatar University   (Qatar)

Author keywords

Aeroderivative gas turbine; Fault detection and isolation; Partial kernel principal component analysis (PKPCA)

Indexed keywords

DATA HANDLING; GAS TURBINES; GASES; PLANT MANAGEMENT; PROCESS MONITORING; FAULT DETECTION; PRINCIPAL COMPONENT ANALYSIS;

FAULT DETECTION AND ISOLATION; HEALTH MONITORING; INDUSTRIAL GAS TURBINES; KERNEL PRINCIPAL COMPONENT ANALYSES (KPCA); NONLINEAR PROCESS; RESIDUAL SIGNALS; SENSOR FAULT DETECTION; SIMULATION STUDIES; AERODERIVATIVE GAS TURBINE; AERODERIVATIVES; EFFECTIVE TOOL; MONITORING TASKS; PARTIAL KERNEL PRINCIPAL COMPONENT ANALYSE; PRINCIPAL-COMPONENT ANALYSIS;

FAULT DETECTION; GAS TURBINES;

EID: 84992494181     PISSN: None     EISSN: 24058963     Source Type: Conference Proceeding    
DOI: 10.1016/j.ifacol.2015.09.719     Document Type: Conference Paper

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