A new rolling bearing fault diagnosis method based on multiscale permutation entropy and improved support vector machine based binary tree

Measurement: Journal of the International Measurement Confederation

Volumn 77, Issue , 2016, Pages 80-94

  Li, Yongbo ^a   Xu, Minqiang ^a   Wei, Yu ^a   Huang, Wenhu ^a  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

Author keywords

Fault diagnosis; Improved support vector machine based binary tree (ISVM BT); Laplacian score (LS); Local mean decomposition (LMD); Multi scale permutation entropy (MPE)

Indexed keywords

BEARINGS (MACHINE PARTS); BINARY TREES; ENTROPY; EXTRACTION; FAILURE ANALYSIS; FEATURE EXTRACTION; LAPLACE TRANSFORMS; PATTERN RECOGNITION; ROLLER BEARINGS; SUPPORT VECTOR MACHINES; VIBRATION ANALYSIS;

ADAPTIVE TIME-FREQUENCY ANALYSIS; FAULT IDENTIFICATIONS; FEATURE EXTRACTION METHODS; IMPROVED SUPPORT VECTOR MACHINE BASED BINARY TREE (ISVM-BT); LAPLACIANS; LOCAL MEAN DECOMPOSITION (LMD); MULTISCALE PERMUTATION ENTROPIES (MPE); PERMUTATION ENTROPY;

FAULT DETECTION;

EID: 84941884955     PISSN: 02632241     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.measurement.2015.08.034     Document Type: Article

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