Bearing fault diagnosis based on statistical locally linear embedding

Sensors (Switzerland)

Volumn 15, Issue 7, 2015, Pages 16225-16247

  Wang, Xiang ^a,b   Zheng, Yuan ^a   Zhao, Zhenzhou ^a   Wang, Jinping ^a  

^a HOHAI UNIVERSITY   (China)

^b NANJING INSTITUTE OF TECHNOLOGY   (China)

Author keywords

Dimensionality reduction; Fault diagnosis; Feature extraction; High dimensional data; Manifold learning; Statistical locally linear embedding

Indexed keywords

BEARINGS (MACHINE PARTS); CLUSTERING ALGORITHMS; COMPUTER AIDED DIAGNOSIS; DATA MINING; DOMAIN DECOMPOSITION METHODS; EXTRACTION; FAILURE ANALYSIS; FEATURE EXTRACTION; FREQUENCY DOMAIN ANALYSIS; LEARNING ALGORITHMS; MACHINERY; PATTERN RECOGNITION; ROLLER BEARINGS; SIGNAL PROCESSING; TIME DOMAIN ANALYSIS; VECTOR SPACES;

CLASSIFICATION PERFORMANCE; DIMENSIONALITY REDUCTION; EMPIRICAL MODE DECOMPOSITION; HIGH DIMENSIONAL DATA; LOCALLY LINEAR EMBEDDING; MACHINERY FAULT DIAGNOSIS; MANIFOLD LEARNING; MANIFOLD LEARNING ALGORITHM;

FAULT DETECTION;

EID: 84940174438     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s150716225     Document Type: Article

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