FAULT DIAGNOSIS OF BALL BEARING BASED ON ELCD PERMUTATION ENTROPY AND RVM
Aiming at the no stationary characteristic of a gear fault vibration signal, it proposes a recognition method based on ELCD（Ensemble local Characteristic-scale decomposition） permutation entropy and RVM. First, the vibration signal was decomposed by ELCD, then a series of intrinsic scale components...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Strength
2019-01-01
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| Series: | Jixie qiangdu |
| Subjects: | |
| Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.02.006 |
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| _version_ | 1841535605560836096 |
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| author | WANG Xia GE MingTao |
| author_facet | WANG Xia GE MingTao |
| author_sort | WANG Xia |
| collection | DOAJ |
| description | Aiming at the no stationary characteristic of a gear fault vibration signal, it proposes a recognition method based on ELCD（Ensemble local Characteristic-scale decomposition） permutation entropy and RVM. First, the vibration signal was decomposed by ELCD, then a series of intrinsic scale components were obtained; Secondly, according to the kurtosis of ISCs, principal ISCs were selected, then, calculate the permutation entropy of principal ISCs and combined into a feature vector; Finally, the feature vector were input RVM classifier to train and test to identify the type of rolling bearing faults. Experimental results show that this method can effectively diagnosis four kinds of working condition, and the effect is better than local Characteristic-scale decomposition method. |
| format | Article |
| id | doaj-art-1de12583e87e4721a1f3cd7c39ff0314 |
| institution | Kabale University |
| issn | 1001-9669 |
| language | zho |
| publishDate | 2019-01-01 |
| publisher | Editorial Office of Journal of Mechanical Strength |
| record_format | Article |
| series | Jixie qiangdu |
| spelling | doaj-art-1de12583e87e4721a1f3cd7c39ff03142025-01-15T02:30:09ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692019-01-014129029530604174FAULT DIAGNOSIS OF BALL BEARING BASED ON ELCD PERMUTATION ENTROPY AND RVMWANG XiaGE MingTaoAiming at the no stationary characteristic of a gear fault vibration signal, it proposes a recognition method based on ELCD（Ensemble local Characteristic-scale decomposition） permutation entropy and RVM. First, the vibration signal was decomposed by ELCD, then a series of intrinsic scale components were obtained; Secondly, according to the kurtosis of ISCs, principal ISCs were selected, then, calculate the permutation entropy of principal ISCs and combined into a feature vector; Finally, the feature vector were input RVM classifier to train and test to identify the type of rolling bearing faults. Experimental results show that this method can effectively diagnosis four kinds of working condition, and the effect is better than local Characteristic-scale decomposition method.http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.02.006Rolling element bearingFault diagnosisELCDRVM |
| spellingShingle | WANG Xia GE MingTao FAULT DIAGNOSIS OF BALL BEARING BASED ON ELCD PERMUTATION ENTROPY AND RVM Jixie qiangdu Rolling element bearing Fault diagnosis ELCD RVM |
| title | FAULT DIAGNOSIS OF BALL BEARING BASED ON ELCD PERMUTATION ENTROPY AND RVM |
| title_full | FAULT DIAGNOSIS OF BALL BEARING BASED ON ELCD PERMUTATION ENTROPY AND RVM |
| title_fullStr | FAULT DIAGNOSIS OF BALL BEARING BASED ON ELCD PERMUTATION ENTROPY AND RVM |
| title_full_unstemmed | FAULT DIAGNOSIS OF BALL BEARING BASED ON ELCD PERMUTATION ENTROPY AND RVM |
| title_short | FAULT DIAGNOSIS OF BALL BEARING BASED ON ELCD PERMUTATION ENTROPY AND RVM |
| title_sort | fault diagnosis of ball bearing based on elcd permutation entropy and rvm |
| topic | Rolling element bearing Fault diagnosis ELCD RVM |
| url | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2019.02.006 |
| work_keys_str_mv | AT wangxia faultdiagnosisofballbearingbasedonelcdpermutationentropyandrvm AT gemingtao faultdiagnosisofballbearingbasedonelcdpermutationentropyandrvm |