Rotating machinery fault diagnosis based on EMD-approximate entropy and LS-SVM

Communications in Computer and Information Science

Volumn 93 CCIS, Issue , 2010, Pages 485-492

  Dai, Guiping ^a  

^a SUZHOU VOCATIONAL UNIVERSITY   (China)

Author keywords

Approximate entropy; Empirical mode decomposition; Fault diagnosis; LS SVM (least square support vector machine)

Indexed keywords

APPROXIMATE ENTROPY; BP (BACK-PROPAGATION) NETWORK; EIGENVECTORS; EMPIRICAL MODE DECOMPOSITION; FAULT DIAGNOSIS; FAULT DIAGNOSIS METHOD; FAULT FEATURE; FAULT TYPE RECOGNITION; FAULT TYPES; INTRINSIC MODE FUNCTIONS; KEYPOINTS; LEAST SQUARE SUPPORT VECTOR MACHINES; MACHINERY FAULTS; RECOGNITION RATES; SIMULATION RESULT; SVM CLASSIFIERS; TRAINING TIME; VIBRATION SIGNAL;

BACKPROPAGATION; COMPUTATION THEORY; COMPUTER SIMULATION; EIGENVALUES AND EIGENFUNCTIONS; ENTROPY; FEATURE EXTRACTION; INTELLIGENT COMPUTING; MACHINERY; POWER QUALITY;

SUPPORT VECTOR MACHINES;

EID: 77956999300     PISSN: 18650929     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-14831-6_63     Document Type: Conference Paper

References (8)

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