An Approach on Fault Detection in Diesel Engine by Using Symmetrical Polar Coordinates and Image Recognition
Vibration technique provides useful information in fault detection of diesel engine, bringing significant cost benefits to diesel engine condition monitoring. Usually, time-frequency calculation on vibration signal is so complex that it is difficult to achieve online fault detection. In this paper,...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2014-07-01
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| Series: | Advances in Mechanical Engineering |
| Online Access: | https://doi.org/10.1155/2014/273929 |
| _version_ | 1818969883513192448 |
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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 | Vibration technique provides useful information in fault detection of diesel engine, bringing significant cost benefits to diesel engine condition monitoring. Usually, time-frequency calculation on vibration signal is so complex that it is difficult to achieve online fault detection. In this paper, a method of fault detection in diesel engine is developed based on symmetrical polar coordinates and image recognition. In this method, time-domain waveform of vibration signal is transformed into snowflake-shaped in mirror symmetry pattern without time-frequency analysis. By the comparison of the geometric features of the snowflake images from different wear conditions of crankshaft bearing in diesel engines, we use centroid position and direction angle of the petal in snowflake image as features to detect the fault. Then, fuzzy c-means (FCM) are used to detect the conditions of the engine according to these features. In order to validate the methods, some experiments have been performed, the experimental results show that the centroid position and direction angle of the petal in snowflake image can reflect the information of different wear conditions in crankshaft bearing, and the fault of crankshaft bearing can be detected accurately. Hence, the method can work as fault detection in diesel engine, which is simple and effective, compared with time-frequency calculation method. |
| first_indexed | 2024-12-20T14:27:40Z |
| format | Article |
| id | doaj.art-99fe38f1a53d4b02b4b29a5564328e81 |
| institution | Directory Open Access Journal |
| issn | 1687-8132 |
| language | English |
| last_indexed | 2024-12-20T14:27:40Z |
| publishDate | 2014-07-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Advances in Mechanical Engineering |
| spelling | doaj.art-99fe38f1a53d4b02b4b29a5564328e812022-12-21T19:37:43ZengSAGE PublishingAdvances in Mechanical Engineering1687-81322014-07-01610.1155/2014/27392910.1155_2014/273929An Approach on Fault Detection in Diesel Engine by Using Symmetrical Polar Coordinates and Image RecognitionRuili ZengLingling ZhangYunkui XiaoJianmin MeiBin ZhouHuimin ZhaoJide JiaVibration technique provides useful information in fault detection of diesel engine, bringing significant cost benefits to diesel engine condition monitoring. Usually, time-frequency calculation on vibration signal is so complex that it is difficult to achieve online fault detection. In this paper, a method of fault detection in diesel engine is developed based on symmetrical polar coordinates and image recognition. In this method, time-domain waveform of vibration signal is transformed into snowflake-shaped in mirror symmetry pattern without time-frequency analysis. By the comparison of the geometric features of the snowflake images from different wear conditions of crankshaft bearing in diesel engines, we use centroid position and direction angle of the petal in snowflake image as features to detect the fault. Then, fuzzy c-means (FCM) are used to detect the conditions of the engine according to these features. In order to validate the methods, some experiments have been performed, the experimental results show that the centroid position and direction angle of the petal in snowflake image can reflect the information of different wear conditions in crankshaft bearing, and the fault of crankshaft bearing can be detected accurately. Hence, the method can work as fault detection in diesel engine, which is simple and effective, compared with time-frequency calculation method.https://doi.org/10.1155/2014/273929 |
| spellingShingle | Ruili Zeng Lingling Zhang Yunkui Xiao Jianmin Mei Bin Zhou Huimin Zhao Jide Jia An Approach on Fault Detection in Diesel Engine by Using Symmetrical Polar Coordinates and Image Recognition Advances in Mechanical Engineering |
| title | An Approach on Fault Detection in Diesel Engine by Using Symmetrical Polar Coordinates and Image Recognition |
| title_full | An Approach on Fault Detection in Diesel Engine by Using Symmetrical Polar Coordinates and Image Recognition |
| title_fullStr | An Approach on Fault Detection in Diesel Engine by Using Symmetrical Polar Coordinates and Image Recognition |
| title_full_unstemmed | An Approach on Fault Detection in Diesel Engine by Using Symmetrical Polar Coordinates and Image Recognition |
| title_short | An Approach on Fault Detection in Diesel Engine by Using Symmetrical Polar Coordinates and Image Recognition |
| title_sort | approach on fault detection in diesel engine by using symmetrical polar coordinates and image recognition |
| url | https://doi.org/10.1155/2014/273929 |
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