Fault detection in an engine by fusing information from multivibration sensors
Fault detection based on the vibration signal of an engine is an effective non-disassembly method for engine diagnosis because a vibration signal includes a lot of information about the condition of the engine. To obtain multi-information for this article, three vibration sensors were placed at diff...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2017-07-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/1550147717719057 |
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| _version_ | 1832547772134326272 |
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| author | Ruili Zeng Lingling Zhang Jianmin Mei Hong Shen Huimin Zhao |
| author_facet | Ruili Zeng Lingling Zhang Jianmin Mei Hong Shen Huimin Zhao |
| author_sort | Ruili Zeng |
| collection | DOAJ |
| description | Fault detection based on the vibration signal of an engine is an effective non-disassembly method for engine diagnosis because a vibration signal includes a lot of information about the condition of the engine. To obtain multi-information for this article, three vibration sensors were placed at different test points to collect vibration information about the engine operating process. A method combining support vector data description and Dempster–Shafer evidence theory was developed for engine fault detection, where support vector data description is used to recognize the data from a single sensor and Dempster–Shafer evidence theory is used to classify the information from the three vibration sensors in detail. The experimental results show that the fault detection accuracy using three sensors is higher than using a single sensor. The multi-complementary sensor information can be adopted in the proposed method, which will increase the reliability of fault detection and reduce uncertainty in the recognition of a fault. |
| format | Article |
| id | doaj-art-41fee95e170f4e6395a16a3214435467 |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2017-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-41fee95e170f4e6395a16a32144354672025-02-03T06:43:16ZengWileyInternational Journal of Distributed Sensor Networks1550-14772017-07-011310.1177/1550147717719057Fault detection in an engine by fusing information from multivibration sensorsRuili ZengLingling ZhangJianmin MeiHong ShenHuimin ZhaoFault detection based on the vibration signal of an engine is an effective non-disassembly method for engine diagnosis because a vibration signal includes a lot of information about the condition of the engine. To obtain multi-information for this article, three vibration sensors were placed at different test points to collect vibration information about the engine operating process. A method combining support vector data description and Dempster–Shafer evidence theory was developed for engine fault detection, where support vector data description is used to recognize the data from a single sensor and Dempster–Shafer evidence theory is used to classify the information from the three vibration sensors in detail. The experimental results show that the fault detection accuracy using three sensors is higher than using a single sensor. The multi-complementary sensor information can be adopted in the proposed method, which will increase the reliability of fault detection and reduce uncertainty in the recognition of a fault.https://doi.org/10.1177/1550147717719057 |
| spellingShingle | Ruili Zeng Lingling Zhang Jianmin Mei Hong Shen Huimin Zhao Fault detection in an engine by fusing information from multivibration sensors International Journal of Distributed Sensor Networks |
| title | Fault detection in an engine by fusing information from multivibration sensors |
| title_full | Fault detection in an engine by fusing information from multivibration sensors |
| title_fullStr | Fault detection in an engine by fusing information from multivibration sensors |
| title_full_unstemmed | Fault detection in an engine by fusing information from multivibration sensors |
| title_short | Fault detection in an engine by fusing information from multivibration sensors |
| title_sort | fault detection in an engine by fusing information from multivibration sensors |
| url | https://doi.org/10.1177/1550147717719057 |
| work_keys_str_mv | AT ruilizeng faultdetectioninanenginebyfusinginformationfrommultivibrationsensors AT linglingzhang faultdetectioninanenginebyfusinginformationfrommultivibrationsensors AT jianminmei faultdetectioninanenginebyfusinginformationfrommultivibrationsensors AT hongshen faultdetectioninanenginebyfusinginformationfrommultivibrationsensors AT huiminzhao faultdetectioninanenginebyfusinginformationfrommultivibrationsensors |