A VMD and CNN Combined Fault Diagnosis Method for Rolling Bearings
Aiming at the difficulty of extracting fault features of rolling bearings under the influence of strong background noise, a rolling bearing fault diagnosis method based on the fusion of variational mode decomposition (VMD) and convolutional neural network (CNN) is proposed. After decomposing the ori...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
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Editorial Office of Journal of Mechanical Transmission
2022-11-01
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| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2022.11.021 |
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| _version_ | 1841547057602494464 |
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| author | Li Kui Sui Xin Liu Chunyang Li Jishun Xu Yanwei Yang Fang |
| author_facet | Li Kui Sui Xin Liu Chunyang Li Jishun Xu Yanwei Yang Fang |
| author_sort | Li Kui |
| collection | DOAJ |
| description | Aiming at the difficulty of extracting fault features of rolling bearings under the influence of strong background noise, a rolling bearing fault diagnosis method based on the fusion of variational mode decomposition (VMD) and convolutional neural network (CNN) is proposed. After decomposing the original variation signal into multiple components, the proposed method employs the Pearson correlation coefficient as the automatic decomposition termination threshold and the optimal modal component selection index; a convolutional neural network is constructed according to bearing fault features and the optimal modal component is used as the input to extract and classify the fault types. The experiments validate that the proposed method can accurately diagnose the rolling bearing faults, which is validated as a new method for rolling bearing fault diagnosis regarding strong background noise. |
| format | Article |
| id | doaj-art-c2f2414acc14499da1b244ec8340fb94 |
| institution | Kabale University |
| issn | 1004-2539 |
| language | zho |
| publishDate | 2022-11-01 |
| publisher | Editorial Office of Journal of Mechanical Transmission |
| record_format | Article |
| series | Jixie chuandong |
| spelling | doaj-art-c2f2414acc14499da1b244ec8340fb942025-01-10T14:56:33ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392022-11-014613414032292598A VMD and CNN Combined Fault Diagnosis Method for Rolling BearingsLi KuiSui XinLiu ChunyangLi JishunXu YanweiYang FangAiming at the difficulty of extracting fault features of rolling bearings under the influence of strong background noise, a rolling bearing fault diagnosis method based on the fusion of variational mode decomposition (VMD) and convolutional neural network (CNN) is proposed. After decomposing the original variation signal into multiple components, the proposed method employs the Pearson correlation coefficient as the automatic decomposition termination threshold and the optimal modal component selection index; a convolutional neural network is constructed according to bearing fault features and the optimal modal component is used as the input to extract and classify the fault types. The experiments validate that the proposed method can accurately diagnose the rolling bearing faults, which is validated as a new method for rolling bearing fault diagnosis regarding strong background noise.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2022.11.021Rolling bearingFault diagnosisStrong background noiseVariational mode decompositionConvolutional neural network |
| spellingShingle | Li Kui Sui Xin Liu Chunyang Li Jishun Xu Yanwei Yang Fang A VMD and CNN Combined Fault Diagnosis Method for Rolling Bearings Jixie chuandong Rolling bearing Fault diagnosis Strong background noise Variational mode decomposition Convolutional neural network |
| title | A VMD and CNN Combined Fault Diagnosis Method for Rolling Bearings |
| title_full | A VMD and CNN Combined Fault Diagnosis Method for Rolling Bearings |
| title_fullStr | A VMD and CNN Combined Fault Diagnosis Method for Rolling Bearings |
| title_full_unstemmed | A VMD and CNN Combined Fault Diagnosis Method for Rolling Bearings |
| title_short | A VMD and CNN Combined Fault Diagnosis Method for Rolling Bearings |
| title_sort | vmd and cnn combined fault diagnosis method for rolling bearings |
| topic | Rolling bearing Fault diagnosis Strong background noise Variational mode decomposition Convolutional neural network |
| url | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2022.11.021 |
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