Rolling Bearing Fault Diagnosis Method Based on MCMF and SAIMFE
Fault diagnosis of rolling bearing is important for ensuring the safe operation of industrial machinery. In order to improve diagnosis accuracy of bearing fault, a rolling bearing fault diagnosis method based on multiscale combined morphological filter (MCMF) and self-adaption improved multiscale fu...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2022/5859155 |
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| _version_ | 1832549917486219264 |
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| author | Dejun Meng Changyun. Miao Xianguo Li Jia Shi Yi Liu Jie Li |
| author_facet | Dejun Meng Changyun. Miao Xianguo Li Jia Shi Yi Liu Jie Li |
| author_sort | Dejun Meng |
| collection | DOAJ |
| description | Fault diagnosis of rolling bearing is important for ensuring the safe operation of industrial machinery. In order to improve diagnosis accuracy of bearing fault, a rolling bearing fault diagnosis method based on multiscale combined morphological filter (MCMF) and self-adaption improved multiscale fuzzy entropy (SAIMFE) is proposed in this paper. First, the MCMF is designed to eliminate noise and preserve fault information more effectively. Second, SAIMFE is proposed to extract bearing fault features, and the optimized scale factor of SAIMFE is determined based on the absolute skewness. Third, some experiments are completed to demonstrate the effectiveness and superiority of the proposed method. The experimental results show that the proposed method not only has high diagnosis accuracy but also less dependent on the diagnosis model. |
| format | Article |
| id | doaj-art-23d54b2b3ad34353b77d42a85eb23a6d |
| institution | Kabale University |
| issn | 1875-9203 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-23d54b2b3ad34353b77d42a85eb23a6d2025-02-03T06:08:15ZengWileyShock and Vibration1875-92032022-01-01202210.1155/2022/5859155Rolling Bearing Fault Diagnosis Method Based on MCMF and SAIMFEDejun Meng0Changyun. Miao1Xianguo Li2Jia Shi3Yi Liu4Jie Li5Tianjin Key Laboratory of Optoelectronic Detection Technology and SystemTianjin Key Laboratory of Optoelectronic Detection Technology and SystemTianjin Key Laboratory of Optoelectronic Detection Technology and SystemTianjin Key Laboratory of Optoelectronic Detection Technology and SystemTianjin Key Laboratory of Optoelectronic Detection Technology and SystemTianjin Key Laboratory of Optoelectronic Detection Technology and SystemFault diagnosis of rolling bearing is important for ensuring the safe operation of industrial machinery. In order to improve diagnosis accuracy of bearing fault, a rolling bearing fault diagnosis method based on multiscale combined morphological filter (MCMF) and self-adaption improved multiscale fuzzy entropy (SAIMFE) is proposed in this paper. First, the MCMF is designed to eliminate noise and preserve fault information more effectively. Second, SAIMFE is proposed to extract bearing fault features, and the optimized scale factor of SAIMFE is determined based on the absolute skewness. Third, some experiments are completed to demonstrate the effectiveness and superiority of the proposed method. The experimental results show that the proposed method not only has high diagnosis accuracy but also less dependent on the diagnosis model.http://dx.doi.org/10.1155/2022/5859155 |
| spellingShingle | Dejun Meng Changyun. Miao Xianguo Li Jia Shi Yi Liu Jie Li Rolling Bearing Fault Diagnosis Method Based on MCMF and SAIMFE Shock and Vibration |
| title | Rolling Bearing Fault Diagnosis Method Based on MCMF and SAIMFE |
| title_full | Rolling Bearing Fault Diagnosis Method Based on MCMF and SAIMFE |
| title_fullStr | Rolling Bearing Fault Diagnosis Method Based on MCMF and SAIMFE |
| title_full_unstemmed | Rolling Bearing Fault Diagnosis Method Based on MCMF and SAIMFE |
| title_short | Rolling Bearing Fault Diagnosis Method Based on MCMF and SAIMFE |
| title_sort | rolling bearing fault diagnosis method based on mcmf and saimfe |
| url | http://dx.doi.org/10.1155/2022/5859155 |
| work_keys_str_mv | AT dejunmeng rollingbearingfaultdiagnosismethodbasedonmcmfandsaimfe AT changyunmiao rollingbearingfaultdiagnosismethodbasedonmcmfandsaimfe AT xianguoli rollingbearingfaultdiagnosismethodbasedonmcmfandsaimfe AT jiashi rollingbearingfaultdiagnosismethodbasedonmcmfandsaimfe AT yiliu rollingbearingfaultdiagnosismethodbasedonmcmfandsaimfe AT jieli rollingbearingfaultdiagnosismethodbasedonmcmfandsaimfe |