Rotor fault analysis of classification accuracy optimition base on kernel principal component analysis and SVM

Procedia Engineering

Volumn 15, Issue , 2011, Pages 5279-5283

  Jin, Xiangyang ^a   Lin, Lin ^a   Zhong, Shisheng ^a   Ding, Gang ^a  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

Author keywords

Fault classification; Feature extraction; KPCA; Muti SVM; Test cell

Indexed keywords

AERO-ENGINE; CLASSIFICATION ACCURACY; FAULT CLASSIFICATION; FAULT MODES; FAULT SAMPLE; FAULT TYPES; FEATURE SPACE; HIGH DIMENSIONAL FEATURE; HIGH-DIMENSIONAL FEATURE SPACE; HIGH-SPEED ROTORS; INNER PRODUCT; KERNEL FUNCTION; KERNEL FUNCTION PARAMETERS; KERNEL PRINCIPAL COMPONENT ANALYSIS; KPCA; LOW DIMENSIONAL; MULTI-CLASS SUPPORT VECTOR MACHINES; MULTICLASS SVM; MUTI-SVM; NONLINEAR FEATURE EXTRACTION; NONLINEAR MAP; OPTIMIZATION ALGORITHMS; OVERFITTING; PENALTY PARAMETERS; PRINCIPAL COMPONENTS; ROTOR FAULT; ROTOR SYSTEMS; ROTOR VIBRATIONS; STATE RECOGNITION; TEST CELL; TEST SETS; TRAINING SETS;

ALGORITHMS; FAULT DETECTION; FEATURE EXTRACTION; INFORMATION SCIENCE; MACHINERY; NONLINEAR ANALYSIS; OPTIMIZATION; SUPPORT VECTOR MACHINES; VIBRATION ANALYSIS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 84055218772     PISSN: 18777058     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1016/j.proeng.2011.08.978     Document Type: Conference Paper

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