Bearing Fault Signal Analysis Based on an Adaptive Multiscale Combined Morphological Filter
Bearing fault signal analysis is an important means of bearing fault diagnosis. To effectively eliminate noise in a fault signal, an adaptive multiscale combined morphological filter is proposed based on the theory of mathematical morphology. Both simulation and experimental results show that the ad...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | International Journal of Rotating Machinery |
| Online Access: | http://dx.doi.org/10.1155/2020/7567439 |
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| _version_ | 1832554112642711552 |
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| author | Chun Lv Peilin Zhang Dinghai Wu Bing Li Yunqiang Zhang |
| author_facet | Chun Lv Peilin Zhang Dinghai Wu Bing Li Yunqiang Zhang |
| author_sort | Chun Lv |
| collection | DOAJ |
| description | Bearing fault signal analysis is an important means of bearing fault diagnosis. To effectively eliminate noise in a fault signal, an adaptive multiscale combined morphological filter is proposed based on the theory of mathematical morphology. Both simulation and experimental results show that the adaptive multiscale combined morphological filter can remove noise more thoroughly and retain details of the fault signal better than the dual-tree complex wavelet filter, traditional morphological filter, adaptive singular value decomposition method (ASVD), and improved switching Kalman filter (ISKF). The adaptive multiscale combined morphological filter considers both positive and negative impulses in the signal; therefore, it has strong adaptability to complex noise in the environment, making it an effective new method for bearing fault diagnosis. |
| format | Article |
| id | doaj-art-bf581822d7bb4e44973c2d37df265648 |
| institution | Kabale University |
| issn | 1023-621X 1542-3034 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Rotating Machinery |
| spelling | doaj-art-bf581822d7bb4e44973c2d37df2656482025-02-03T05:52:29ZengWileyInternational Journal of Rotating Machinery1023-621X1542-30342020-01-01202010.1155/2020/75674397567439Bearing Fault Signal Analysis Based on an Adaptive Multiscale Combined Morphological FilterChun Lv0Peilin Zhang1Dinghai Wu2Bing Li3Yunqiang Zhang4Department of Vehicle and Electrical Engineering, Army Engineering University, Shijiazhuang 050003, ChinaDepartment of Vehicle and Electrical Engineering, Army Engineering University, Shijiazhuang 050003, ChinaDepartment of Vehicle and Electrical Engineering, Army Engineering University, Shijiazhuang 050003, ChinaDepartment of Electronic Information Engineering, Shantou University, Shantou 515063, ChinaDepartment of Vehicle and Electrical Engineering, Army Engineering University, Shijiazhuang 050003, ChinaBearing fault signal analysis is an important means of bearing fault diagnosis. To effectively eliminate noise in a fault signal, an adaptive multiscale combined morphological filter is proposed based on the theory of mathematical morphology. Both simulation and experimental results show that the adaptive multiscale combined morphological filter can remove noise more thoroughly and retain details of the fault signal better than the dual-tree complex wavelet filter, traditional morphological filter, adaptive singular value decomposition method (ASVD), and improved switching Kalman filter (ISKF). The adaptive multiscale combined morphological filter considers both positive and negative impulses in the signal; therefore, it has strong adaptability to complex noise in the environment, making it an effective new method for bearing fault diagnosis.http://dx.doi.org/10.1155/2020/7567439 |
| spellingShingle | Chun Lv Peilin Zhang Dinghai Wu Bing Li Yunqiang Zhang Bearing Fault Signal Analysis Based on an Adaptive Multiscale Combined Morphological Filter International Journal of Rotating Machinery |
| title | Bearing Fault Signal Analysis Based on an Adaptive Multiscale Combined Morphological Filter |
| title_full | Bearing Fault Signal Analysis Based on an Adaptive Multiscale Combined Morphological Filter |
| title_fullStr | Bearing Fault Signal Analysis Based on an Adaptive Multiscale Combined Morphological Filter |
| title_full_unstemmed | Bearing Fault Signal Analysis Based on an Adaptive Multiscale Combined Morphological Filter |
| title_short | Bearing Fault Signal Analysis Based on an Adaptive Multiscale Combined Morphological Filter |
| title_sort | bearing fault signal analysis based on an adaptive multiscale combined morphological filter |
| url | http://dx.doi.org/10.1155/2020/7567439 |
| work_keys_str_mv | AT chunlv bearingfaultsignalanalysisbasedonanadaptivemultiscalecombinedmorphologicalfilter AT peilinzhang bearingfaultsignalanalysisbasedonanadaptivemultiscalecombinedmorphologicalfilter AT dinghaiwu bearingfaultsignalanalysisbasedonanadaptivemultiscalecombinedmorphologicalfilter AT bingli bearingfaultsignalanalysisbasedonanadaptivemultiscalecombinedmorphologicalfilter AT yunqiangzhang bearingfaultsignalanalysisbasedonanadaptivemultiscalecombinedmorphologicalfilter |