Fault diagnosis for motor rotor based on KPCA-SVM

Applied Mechanics and Materials

Volumn 143-144, Issue , 2012, Pages 680-684

  Li, Ping ^a   Li, Xuejun ^a   Jiang, Lingli ^a   Yang, Dalian ^a  

^a HUNAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Fault diagnosis; KPCA; Motor rotor; SVM

Indexed keywords

FAULT CLASSIFICATION; FAULT CLASSIFIER; FAULT DIAGNOSIS METHOD; FEATURE VECTORS; HIGH DIMENSIONAL SPACES; HIGHER-DIMENSIONAL; KERNEL FUNCTION; KERNEL PRINCIPAL COMPONENT ANALYSIS; KPCA; MOTOR ROTOR; MOTOR ROTORS; NONLINEAR FEATURES; NONLINEAR PROPERTIES; PCA METHOD; ROTOR FAULT; SVM; TRAINING SAMPLE; VIBRATION SIGNAL;

DATA MINING; ELECTRIC PROPERTIES; FAILURE ANALYSIS; FAULT DETECTION; PRINCIPAL COMPONENT ANALYSIS; VECTOR SPACES; VIBRATION ANALYSIS;

SUPPORT VECTOR MACHINES;

EID: 84555196829     PISSN: 16609336     EISSN: 16627482     Source Type: Book Series    
DOI: 10.4028/www.scientific.net/AMM.143-144.680     Document Type: Conference Paper

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