| 基于可拓学的故障诊断及预防方法研究 |
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| 引用本文： | 张家宾,张金春,李日华,李超亚.基于可拓学的故障诊断及预防方法研究[J].广东工业大学学报,2015,32(1):11-15. |
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| 作者姓名： | 张家宾 张金春 李日华 李超亚 |
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| 作者单位： | 海军航空工程学院 1.研究生大队; 2.基础部，山东 烟台 264001 |
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| 摘 要： | 将可拓数据挖掘方法和模式识别技术相结合，用于解决基于大量数据的故障模式识别问题.利用粗糙集理论进行属性约减和权值确定，保证了获得权值的客观性和稳定性.然后用汽车发动机故障诊断的实例验证了模型的可靠性.最后根据基于变换的可拓集分类思想，探讨了故障预防的一种方法.
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| 关 键 词： | 可拓学 数据挖掘 故障诊断 粗糙集 |
| 收稿时间： | 2014-10-21 |
Research on Fault Diagnosis and Prevention Based on Extension |
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| Zhang Jia-bin,Zhang Jin-chun,Li Ri-hua,Li Chao-ya.Research on Fault Diagnosis and Prevention Based on Extension[J].Journal of Guangdong University of Technology,2015,32(1):11-15. |
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| Authors: | Zhang Jia-bin Zhang Jin-chun Li Ri-hua Li Chao-ya |
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| Affiliation: | 1. Graduate Administrative Group; 2. Department of Basic, Naval Aeronautical and Astronautical University, Yantai 264001, China |
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| Abstract: | The extension data mining methods and pattern recognition technology are combined to solve the problem of fault diagnosis involved with large amounts of data. By taking advantage of the theory of rough set to make attribute reduction and weight value determination, it ensures the objectivity and stability of weights. Then it verifies the reliability of the model with the example of fault diagnosis of automobile engine. Finally, according to the classification method of extension set based on the transform, this paper presents a method for fault prevention. |
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| Keywords: | Extenics data mining fault diagnosis rough set |
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