Nonlinear process monitoring and fault diagnosis based on KPCA and MKL-SVM

Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument

Volumn 31, Issue 11, 2010, Pages 2428-2433

  Xu, Jie ^a,b   Hu, Shousong ^a  

^a NANJING UNIVERSITY OF AERONAUTICS AND ASTRONAUTICS   (China)

^b NANJING NORMAL UNIVERSITY   (China)

Author keywords

Fault diagnosis; Kernel principal component analysis; Multiple kernel learning; Process monitoring; Support vector machine

Indexed keywords

CONTROL LIMITS; FAULT DETECTION AND DIAGNOSIS; FAULT DIAGNOSIS; FEATURE SPACE; KERNEL PRINCIPAL COMPONENT ANALYSIS; MULTIPLE FAULTS; MULTIPLE KERNEL LEARNING; NONLINEAR PROCESS MONITORING; SIMULATION RESULT; SVM CLASSIFICATION; TENNESSEE EASTMAN;

CHEMICAL INDUSTRY; FAULT DETECTION; GEARS; NONLINEAR ANALYSIS; PRINCIPAL COMPONENT ANALYSIS; PROCESS CONTROL; PROCESS MONITORING; VECTORS;

SUPPORT VECTOR MACHINES;

EID: 78650780371     PISSN: 02543087     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

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