Fault pattern recognition of bearing based on principal components analysis and Support Vector Machine

2009 2nd International Conference on Intelligent Computing Technology and Automation, ICICTA 2009

Volumn 2, Issue , 2009, Pages 533-536

  Shuang, Lu ^a   Fujin, Yu ^a  

^a ZHEJIANG NORMAL UNIVERSITY   (China)

Author keywords

Fault diagnosis; Pattern recognition; Principal components analysis; Rolling bearing; Support vector machine

Indexed keywords

EIGENVECTORS; FAULT DIAGNOSIS; FAULT PATTERNS; FEATURE ANALYSIS; FEATURE EXTRACTING; INTELLIGENT FAULT DIAGNOSIS; LOW DIMENSIONAL; MULTIPLE FAULTS; NEW APPROACHES; NON-LINEAR REGRESSION; PRINCIPAL COMPONENTS ANALYSIS; ROLLING BEARINGS; SINGULARITY VALUE DECOMPOSITION; STATE MONITORING; STATISTICAL LEARNING THEORY;

BEARINGS (MACHINE PARTS); BEARINGS (STRUCTURAL); COMPUTER SCIENCE; EIGENVALUES AND EIGENFUNCTIONS; FAILURE ANALYSIS; FEATURE EXTRACTION; IMAGE RETRIEVAL; INTELLIGENT COMPUTING; QUALITY ASSURANCE; RECURSIVE FUNCTIONS; ROBOTICS; SUPPORT VECTOR MACHINES; VECTORS;

PRINCIPAL COMPONENT ANALYSIS;

EID: 71949116350     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICICTA.2009.363     Document Type: Conference Paper

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