FAULT DIAGNOSIS METHOD OF ROLLING BEARINGS BASED ON ELMD AND KERNEL DENSITY ESTIMATION
Aiming at the no stationary characteristic of a gear fault vibration signal,a method based on Ensemble local mean decomposition and Kernel density estimation is proposed in this paper. First,the vibration signal is decomposed to be a series PF component by ELMD,calculating RMS、kurtosis、skewness coef...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Strength
2017-01-01
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| Series: | Jixie qiangdu |
| Subjects: | |
| Online Access: | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2017.02.004 |
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| _version_ | 1841535174953664512 |
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| author | WU HaiYan HAI Jie YUAN Hao |
| author_facet | WU HaiYan HAI Jie YUAN Hao |
| author_sort | WU HaiYan |
| collection | DOAJ |
| description | Aiming at the no stationary characteristic of a gear fault vibration signal,a method based on Ensemble local mean decomposition and Kernel density estimation is proposed in this paper. First,the vibration signal is decomposed to be a series PF component by ELMD,calculating RMS、kurtosis、skewness coefficient of PF components,which contains main fault information,then they are combined into a feature vector,the Classification based on kernel density estimation is proposed,multiple sets of vibration signal feature vectors are used to train and test,identify their fault condition. The results showed that this method can effectively identify the fault of rolling bearing,and it is better than the LMD method |
| format | Article |
| id | doaj-art-4c07d1606ea8474f9392d974cdc01ef2 |
| institution | Kabale University |
| issn | 1001-9669 |
| language | zho |
| publishDate | 2017-01-01 |
| publisher | Editorial Office of Journal of Mechanical Strength |
| record_format | Article |
| series | Jixie qiangdu |
| spelling | doaj-art-4c07d1606ea8474f9392d974cdc01ef22025-01-15T02:34:35ZzhoEditorial Office of Journal of Mechanical StrengthJixie qiangdu1001-96692017-01-013926126630597904FAULT DIAGNOSIS METHOD OF ROLLING BEARINGS BASED ON ELMD AND KERNEL DENSITY ESTIMATIONWU HaiYanHAI JieYUAN HaoAiming at the no stationary characteristic of a gear fault vibration signal,a method based on Ensemble local mean decomposition and Kernel density estimation is proposed in this paper. First,the vibration signal is decomposed to be a series PF component by ELMD,calculating RMS、kurtosis、skewness coefficient of PF components,which contains main fault information,then they are combined into a feature vector,the Classification based on kernel density estimation is proposed,multiple sets of vibration signal feature vectors are used to train and test,identify their fault condition. The results showed that this method can effectively identify the fault of rolling bearing,and it is better than the LMD methodhttp://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2017.02.004Rolling bearingELMDKernel density estimationFault diagnosis |
| spellingShingle | WU HaiYan HAI Jie YUAN Hao FAULT DIAGNOSIS METHOD OF ROLLING BEARINGS BASED ON ELMD AND KERNEL DENSITY ESTIMATION Jixie qiangdu Rolling bearing ELMD Kernel density estimation Fault diagnosis |
| title | FAULT DIAGNOSIS METHOD OF ROLLING BEARINGS BASED ON ELMD AND KERNEL DENSITY ESTIMATION |
| title_full | FAULT DIAGNOSIS METHOD OF ROLLING BEARINGS BASED ON ELMD AND KERNEL DENSITY ESTIMATION |
| title_fullStr | FAULT DIAGNOSIS METHOD OF ROLLING BEARINGS BASED ON ELMD AND KERNEL DENSITY ESTIMATION |
| title_full_unstemmed | FAULT DIAGNOSIS METHOD OF ROLLING BEARINGS BASED ON ELMD AND KERNEL DENSITY ESTIMATION |
| title_short | FAULT DIAGNOSIS METHOD OF ROLLING BEARINGS BASED ON ELMD AND KERNEL DENSITY ESTIMATION |
| title_sort | fault diagnosis method of rolling bearings based on elmd and kernel density estimation |
| topic | Rolling bearing ELMD Kernel density estimation Fault diagnosis |
| url | http://www.jxqd.net.cn/thesisDetails#10.16579/j.issn.1001.9669.2017.02.004 |
| work_keys_str_mv | AT wuhaiyan faultdiagnosismethodofrollingbearingsbasedonelmdandkerneldensityestimation AT haijie faultdiagnosismethodofrollingbearingsbasedonelmdandkerneldensityestimation AT yuanhao faultdiagnosismethodofrollingbearingsbasedonelmdandkerneldensityestimation |