A Novel Fault Diagnosis Method for Diesel Engine Based on MVMD and Band Energy
Vibration signal, as an important means for diesel engine condition detection and fault diagnosis, has attracted attention for many years. In traditional vibration signal analysis, most processing methods are for single-channel data. However, single-channel vibration signal cannot reflect the operat...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2020/8247194 |
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| _version_ | 1832566370777169920 |
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| author | Cheng Gu Xinyong Qiao Ying Jin Yanbin Liu |
| author_facet | Cheng Gu Xinyong Qiao Ying Jin Yanbin Liu |
| author_sort | Cheng Gu |
| collection | DOAJ |
| description | Vibration signal, as an important means for diesel engine condition detection and fault diagnosis, has attracted attention for many years. In traditional vibration signal analysis, most processing methods are for single-channel data. However, single-channel vibration signal cannot reflect the operating information of the diesel engine comprehensively because diesel engine vibration is coupled by multiple source signals. This paper proposes the MVMD band energy method for fault diagnosis by four channels of vibration signals. First, the original multivariate signals are decomposed adaptively by MVMD, which obtains a series of components with modal alignment. Then, the band energy values of each measuring point are calculated as the fault characteristics. Finally, SVM is used to realize the diagnosis and identification of diesel engine misfire. The working conditions have a great influence on the vibration signal of the cylinder. In order to obtain the best diagnostic working conditions, six working conditions are set for testing. The result shows that the fault identification rate is highest under the 1500 rpm and 50% load working condition. The fault recognition rate of this method reaches more than 99%, which is superior to the other four common methods. |
| format | Article |
| id | doaj-art-d5196034ec15489daab12dec66aefe2e |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-d5196034ec15489daab12dec66aefe2e2025-02-03T01:04:22ZengWileyShock and Vibration1070-96221875-92032020-01-01202010.1155/2020/82471948247194A Novel Fault Diagnosis Method for Diesel Engine Based on MVMD and Band EnergyCheng Gu0Xinyong Qiao1Ying Jin2Yanbin Liu3Department of Vehicle Engineering, Academy of Army Armored Force, Beijing, ChinaDepartment of Vehicle Engineering, Academy of Army Armored Force, Beijing, ChinaDepartment of Vehicle Engineering, Academy of Army Armored Force, Beijing, ChinaDepartment of Vehicle Engineering, Academy of Army Armored Force, Beijing, ChinaVibration signal, as an important means for diesel engine condition detection and fault diagnosis, has attracted attention for many years. In traditional vibration signal analysis, most processing methods are for single-channel data. However, single-channel vibration signal cannot reflect the operating information of the diesel engine comprehensively because diesel engine vibration is coupled by multiple source signals. This paper proposes the MVMD band energy method for fault diagnosis by four channels of vibration signals. First, the original multivariate signals are decomposed adaptively by MVMD, which obtains a series of components with modal alignment. Then, the band energy values of each measuring point are calculated as the fault characteristics. Finally, SVM is used to realize the diagnosis and identification of diesel engine misfire. The working conditions have a great influence on the vibration signal of the cylinder. In order to obtain the best diagnostic working conditions, six working conditions are set for testing. The result shows that the fault identification rate is highest under the 1500 rpm and 50% load working condition. The fault recognition rate of this method reaches more than 99%, which is superior to the other four common methods.http://dx.doi.org/10.1155/2020/8247194 |
| spellingShingle | Cheng Gu Xinyong Qiao Ying Jin Yanbin Liu A Novel Fault Diagnosis Method for Diesel Engine Based on MVMD and Band Energy Shock and Vibration |
| title | A Novel Fault Diagnosis Method for Diesel Engine Based on MVMD and Band Energy |
| title_full | A Novel Fault Diagnosis Method for Diesel Engine Based on MVMD and Band Energy |
| title_fullStr | A Novel Fault Diagnosis Method for Diesel Engine Based on MVMD and Band Energy |
| title_full_unstemmed | A Novel Fault Diagnosis Method for Diesel Engine Based on MVMD and Band Energy |
| title_short | A Novel Fault Diagnosis Method for Diesel Engine Based on MVMD and Band Energy |
| title_sort | novel fault diagnosis method for diesel engine based on mvmd and band energy |
| url | http://dx.doi.org/10.1155/2020/8247194 |
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