A Method Combining Order Tracking and Fuzzy C-Means for Diesel Engine Fault Detection and Isolation
Diesel engine works under variable speed conditions; fault symptoms are clearer in the angular/order domains than in the common time/frequency ones. In this paper, firstly, the acceleration signal of diesel engine is resampled by order tracking, in which the rotating speed is computed in every worki...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2015/547238 |
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| _version_ | 1849307440244326400 |
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| author | Ruili Zeng Lingling Zhang Yunkui Xiao Jianmin Mei Bin Zhou Huimin Zhao Jide Jia |
| author_facet | Ruili Zeng Lingling Zhang Yunkui Xiao Jianmin Mei Bin Zhou Huimin Zhao Jide Jia |
| author_sort | Ruili Zeng |
| collection | DOAJ |
| description | Diesel engine works under variable speed conditions; fault symptoms are clearer in the angular/order domains than in the common time/frequency ones. In this paper, firstly, the acceleration signal of diesel engine is resampled by order tracking, in which the rotating speed is computed in every working cycle, and the order tracking spectrum is created in each interval’s speed; then different order band accumulated energy is computed as feature vector. After standardizing these features, the fuzzy c-means (FCM) is introduced to use them as input vector; the optimized classified matrix and clustering centers can be obtained using FCM iteration method; then the fault can be detected by calculating the approach degree between the unknown samples and the known ones. To validate the method, some experiments have been performed; the results show that the signal can be reconstructed, and the features of order band accumulated energy can reflect the information of different wear conditions in crank-shaft bearing; then the fault can be detected accurately. The method of nonentire work cycle is also introduced as a comparison with our method; the result shows our method has more accuracy classification. |
| format | Article |
| id | doaj-art-21079e4b40784e0c88360e9cc802671d |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-21079e4b40784e0c88360e9cc802671d2025-08-20T03:54:47ZengWileyShock and Vibration1070-96221875-92032015-01-01201510.1155/2015/547238547238A Method Combining Order Tracking and Fuzzy C-Means for Diesel Engine Fault Detection and IsolationRuili Zeng0Lingling Zhang1Yunkui Xiao2Jianmin Mei3Bin Zhou4Huimin Zhao5Jide Jia6Department of Automobile Engineering, Military Transportation University, Tianjin 300161, ChinaDepartment of Automobile Engineering, Military Transportation University, Tianjin 300161, ChinaDepartment of Automobile Engineering, Military Transportation University, Tianjin 300161, ChinaDepartment of Automobile Engineering, Military Transportation University, Tianjin 300161, ChinaDepartment of Automobile Engineering, Military Transportation University, Tianjin 300161, ChinaDepartment of Automobile Engineering, Military Transportation University, Tianjin 300161, ChinaDepartment of Automobile Engineering, Military Transportation University, Tianjin 300161, ChinaDiesel engine works under variable speed conditions; fault symptoms are clearer in the angular/order domains than in the common time/frequency ones. In this paper, firstly, the acceleration signal of diesel engine is resampled by order tracking, in which the rotating speed is computed in every working cycle, and the order tracking spectrum is created in each interval’s speed; then different order band accumulated energy is computed as feature vector. After standardizing these features, the fuzzy c-means (FCM) is introduced to use them as input vector; the optimized classified matrix and clustering centers can be obtained using FCM iteration method; then the fault can be detected by calculating the approach degree between the unknown samples and the known ones. To validate the method, some experiments have been performed; the results show that the signal can be reconstructed, and the features of order band accumulated energy can reflect the information of different wear conditions in crank-shaft bearing; then the fault can be detected accurately. The method of nonentire work cycle is also introduced as a comparison with our method; the result shows our method has more accuracy classification.http://dx.doi.org/10.1155/2015/547238 |
| spellingShingle | Ruili Zeng Lingling Zhang Yunkui Xiao Jianmin Mei Bin Zhou Huimin Zhao Jide Jia A Method Combining Order Tracking and Fuzzy C-Means for Diesel Engine Fault Detection and Isolation Shock and Vibration |
| title | A Method Combining Order Tracking and Fuzzy C-Means for Diesel Engine Fault Detection and Isolation |
| title_full | A Method Combining Order Tracking and Fuzzy C-Means for Diesel Engine Fault Detection and Isolation |
| title_fullStr | A Method Combining Order Tracking and Fuzzy C-Means for Diesel Engine Fault Detection and Isolation |
| title_full_unstemmed | A Method Combining Order Tracking and Fuzzy C-Means for Diesel Engine Fault Detection and Isolation |
| title_short | A Method Combining Order Tracking and Fuzzy C-Means for Diesel Engine Fault Detection and Isolation |
| title_sort | method combining order tracking and fuzzy c means for diesel engine fault detection and isolation |
| url | http://dx.doi.org/10.1155/2015/547238 |
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