Rolling Bearing Fault Diagnosis Based on ELCD Permutation Entropy and RVM
Joint Authors
Xingmeng, Jiang
Li, Wu
Liwu, Pan
Mingtao, Ge
Daidi, Hu
Source
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-09-07
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Aiming at the nonstationary characteristic of a gear fault vibration signal, a recognition method based on permutation entropy of ensemble local characteristic-scale decomposition (ELCD) and relevance vector machine (RVM) is proposed.
First, the vibration signal was decomposed by ELCD; then a series of intrinsic scale components (ISCs) were obtained.
Second, according to the kurtosis of ISCs, principal ISCs were selected and then the permutation entropy of principal ISCs was calculated and they were combined into a feature vector.
Finally, the feature vectors were input in RVM classifier to train and test and identify the type of rolling bearing faults.
Experimental results show that this method can effectively diagnose four kinds of working condition, and the effect is better than local characteristic-scale decomposition (LCD) method.
American Psychological Association (APA)
Xingmeng, Jiang& Li, Wu& Liwu, Pan& Mingtao, Ge& Daidi, Hu. 2016. Rolling Bearing Fault Diagnosis Based on ELCD Permutation Entropy and RVM. Journal of Engineering،Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1108345
Modern Language Association (MLA)
Xingmeng, Jiang…[et al.]. Rolling Bearing Fault Diagnosis Based on ELCD Permutation Entropy and RVM. Journal of Engineering No. 2016 (2016), pp.1-7.
https://search.emarefa.net/detail/BIM-1108345
American Medical Association (AMA)
Xingmeng, Jiang& Li, Wu& Liwu, Pan& Mingtao, Ge& Daidi, Hu. Rolling Bearing Fault Diagnosis Based on ELCD Permutation Entropy and RVM. Journal of Engineering. 2016. Vol. 2016, no. 2016, pp.1-7.
https://search.emarefa.net/detail/BIM-1108345
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1108345