A multi-fault diagnosis method of rolling bearing based on wavelet-PCA and fuzzy K-nearest neighbor

Applied Mechanics and Materials

Volumn 29-32, Issue , 2010, Pages 1602-1607

  Chen, Xiangshun ^a   Zeng, Hubiao ^b   Li, Zhixiong ^c  

^a Hunan Railway Professional Technology College   (China)

^b Zhuzhou Lince Group Co Ltd   (China)

^c WUHAN UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Fuzzy K nearest neighbor; Multi fault diagnosis; PCA; Rolling bearing

Indexed keywords

CLASSIFICATION RATES; DIAGNOSTIC SYSTEMS; FAULT DETECTION AND DIAGNOSIS; FAULT FEATURE; FEATURE SPACE; FEATURE VECTORS; K-NEAREST NEIGHBORS; MULTI-FAULT DIAGNOSIS; OPERATING CONDITION; PCA; PRINCIPLE COMPONENT ANALYSIS; ROLLING BEARING; ROLLING BEARINGS; SUB-BANDS; VIBRATION DATA;

BEARINGS (MACHINE PARTS); BEARINGS (STRUCTURAL); FLIGHT DYNAMICS; MACHINERY; MECHANICS; PATTERN RECOGNITION; PRINCIPAL COMPONENT ANALYSIS; QUALITY ASSURANCE; RELIABILITY; VIBRATION ANALYSIS; WAVELET ANALYSIS;

FAULT DETECTION;

EID: 78650782574     PISSN: 16609336     EISSN: 16627482     Source Type: Book Series    
DOI: 10.4028/www.scientific.net/AMM.29-32.1602     Document Type: Conference Paper

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