A novel bearing fault diagnosis model integrated permutation entropy, ensemble empirical mode decomposition and optimized SVM

Measurement: Journal of the International Measurement Confederation

Volumn 69, Issue , 2015, Pages 164-179

  Zhang, Xiaoyuan ^a   Liang, Yitao ^a   Zhou, Jianzhong ^b   Zang, Yi ^a  

^a HENAN UNIVERSITY OF TECHNOLOGY   (China)

^b HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Ensemble empirical mode decomposition; Fault diagnosis; Inter cluster distance; Motor bearing; Permutation entropy; Support vector machine

Indexed keywords

ENTROPY; FAILURE ANALYSIS; SIGNAL DETECTION; SIGNAL PROCESSING; SUPPORT VECTOR MACHINES; VECTOR SPACES;

ENSEMBLE EMPIRICAL MODE DECOMPOSITION; ENSEMBLE EMPIRICAL MODE DECOMPOSITIONS (EEMD); FAULT DETECTION AND CLASSIFICATION; INTER CLUSTERS; INTRINSIC CHARACTERISTICS; INTRINSIC MODE FUNCTIONS; MOTOR BEARINGS; PERMUTATION ENTROPY;

FAULT DETECTION;

EID: 84926352537     PISSN: 02632241     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.measurement.2015.03.017     Document Type: Article

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