Early Fault Extraction of Rolling Bearing based on LMD and MCKD
When the roller bearings are in the early stage of failure,the characteristic signal is weak and it is affected by the interference noise,which makes the fault feature difficult to extract. In order to solve this problem,a fault diagnosis method based on the combination of local mean decomposition（...
| Main Authors: | , , |
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Transmission
2018-01-01
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| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2018.03.025 |
| _version_ | 1797819209615409152 |
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| author | Wang Jianguo Zhang Jiawei Yang Bin |
| author_facet | Wang Jianguo Zhang Jiawei Yang Bin |
| author_sort | Wang Jianguo |
| collection | DOAJ |
| description | When the roller bearings are in the early stage of failure,the characteristic signal is weak and it is affected by the interference noise,which makes the fault feature difficult to extract. In order to solve this problem,a fault diagnosis method based on the combination of local mean decomposition（ LMD） and maximum correlated kurtosis deconvolution（ MCKD） is proposed. Under the strong noise environment,LMD is difficult to extract the characteristic of weak fault signal,therefore,a set of PF components that are decomposed by LMD which use the correlation coefficient and kurtosis value select sensitive component for signal reconstruction. Then MCKD is used to filter and it is used to highlight the pulse of fault signal. Finally,according to the signal envelope power spectrum,the fault characteristic frequency is extracted,the effectiveness of the method is proved by some simulation and application examples. |
| first_indexed | 2024-03-13T09:19:36Z |
| format | Article |
| id | doaj.art-cf37e7a7766d4b829e7d92e3d73e7aa6 |
| institution | Directory Open Access Journal |
| issn | 1004-2539 |
| language | zho |
| last_indexed | 2024-03-13T09:19:36Z |
| publishDate | 2018-01-01 |
| publisher | Editorial Office of Journal of Mechanical Transmission |
| record_format | Article |
| series | Jixie chuandong |
| spelling | doaj.art-cf37e7a7766d4b829e7d92e3d73e7aa62023-05-26T09:47:41ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392018-01-014211712129935514Early Fault Extraction of Rolling Bearing based on LMD and MCKDWang JianguoZhang JiaweiYang BinWhen the roller bearings are in the early stage of failure,the characteristic signal is weak and it is affected by the interference noise,which makes the fault feature difficult to extract. In order to solve this problem,a fault diagnosis method based on the combination of local mean decomposition（ LMD） and maximum correlated kurtosis deconvolution（ MCKD） is proposed. Under the strong noise environment,LMD is difficult to extract the characteristic of weak fault signal,therefore,a set of PF components that are decomposed by LMD which use the correlation coefficient and kurtosis value select sensitive component for signal reconstruction. Then MCKD is used to filter and it is used to highlight the pulse of fault signal. Finally,according to the signal envelope power spectrum,the fault characteristic frequency is extracted,the effectiveness of the method is proved by some simulation and application examples.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2018.03.025Rolling bearing;Fault diagnosis;Local mean decomposition;Maximum correlation kurtosis deconvolution |
| spellingShingle | Wang Jianguo Zhang Jiawei Yang Bin Early Fault Extraction of Rolling Bearing based on LMD and MCKD Jixie chuandong Rolling bearing;Fault diagnosis;Local mean decomposition;Maximum correlation kurtosis deconvolution |
| title | Early Fault Extraction of Rolling Bearing based on LMD and MCKD |
| title_full | Early Fault Extraction of Rolling Bearing based on LMD and MCKD |
| title_fullStr | Early Fault Extraction of Rolling Bearing based on LMD and MCKD |
| title_full_unstemmed | Early Fault Extraction of Rolling Bearing based on LMD and MCKD |
| title_short | Early Fault Extraction of Rolling Bearing based on LMD and MCKD |
| title_sort | early fault extraction of rolling bearing based on lmd and mckd |
| topic | Rolling bearing;Fault diagnosis;Local mean decomposition;Maximum correlation kurtosis deconvolution |
| url | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2018.03.025 |
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