| 基于支持向量机的故障诊断方法及其应用 |
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| 引用本文： | 王丽,周新立,尉询楷.基于支持向量机的故障诊断方法及其应用[J].火力与指挥控制,2006,31(4):9-11. |
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| 作者姓名： | 王丽 周新立 尉询楷 |
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| 作者单位： | 空军工程大学工程学院,陕西,西安,710038 |
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| 摘 要： | 提出了一种采用模糊手段进行特征提取、支持向量机进行模式分类的内燃机燃油系统故障诊断方法.该方法专门针对小样本集合设计,能够在小样本情况下获得较大的推广能力,首先采用模糊手段对故障信号和原因进行特征提取,接着利用支持向量机进行分类实现特征级诊断,最后将其应用于内燃机燃油系统的故障诊断中,取得了令人满意的结果.
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| 关 键 词： | 支持向量机 模糊手段 特征提取 故障诊断 |
| 文章编号： | 1002-0640(2006)04-0009-03 |
| 修稿时间： | 2004年6月11日 |
Fault Diagnosis Method based on Support Vector Machines and Its Application |
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| WANG Li,ZHOU Xin-li,WEI Xun-kai.Fault Diagnosis Method based on Support Vector Machines and Its Application[J].Fire Control & Command Control,2006,31(4):9-11. |
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| Authors: | WANG Li ZHOU Xin-li WEI Xun-kai |
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| Abstract: | A noverl fault diagnosis method based on support vector machines is presented in this paper.The method is special designed for small sample set,and can obtain commendable generalization ability.First,feature information is extracted via fuzzy mehtods.Then,support vector machines is adopted to realize patter recognition and correlation.Finally,fault diagnoses samples of some kind of gas engine's fuel system is trained and tested,results are satisfactory and proves this method is effective and commendable. |
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| Keywords: | support vector machines fuzzy mehtod feature extraction fault diagnosis |
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