| 内燃机黑色金属零件磨损状态判别研究 |
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| 引用本文： | 王正军,张培林,任国全,曹建军,刘昆仑.内燃机黑色金属零件磨损状态判别研究[J].车用发动机,2008(1):65-67. |
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| 作者姓名： | 王正军 张培林 任国全 曹建军 刘昆仑 |
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| 作者单位： | 1. 军械工程学院自行火炮教研室,河北,石家庄,050003
2. 龙泉驿区驻一六七厂军代室,四川,成都,610110 |
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| 摘 要： | 以对内燃机运行状态具有重要影响的黑色金属零件磨损为研究对象,对其磨损状态进行判别研究。运用欧氏距离分类法区分黑色金属零件磨损"正常"、"异常"2类状态,对该方法表现出的分类准确率不高的问题,运用支持向量机方法进行了解决,实例表明,支持向量机方法在内燃机运行状态监测中更为准确可靠,分类正确率可达100%。
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| 关 键 词： | 内燃机 黑色金属 磨损 状态判别 故障诊断 |
| 文章编号： | 1001-2222（2008）01-0065-03 |
| 收稿时间： | 2007-07-30 |
| 修稿时间： | 2007-12-03 |
Research on Ferrous Metal Part Wear States Discrimination of IC Engine |
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| WANG Zheng-jun,ZHANG Pei-lin,REN Guo-quan,CAO Jian-jun,LIU Kun-lun.Research on Ferrous Metal Part Wear States Discrimination of IC Engine[J].Vehicle Engine,2008(1):65-67. |
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| Authors: | WANG Zheng-jun ZHANG Pei-lin REN Guo-quan CAO Jian-jun LIU Kun-lun |
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| Abstract: | As the ferrous metal part wear has a great influence to the running status of the IC engine,this paper carried out research to differentiate its wear states.Paper used Euclid distance classification method to differentiate the "normal" and "abnormal" states of the ferrous metal part wear.But the classification accuracy of this method was not high,to solve this problem,the paper introduced SVM method.The example shows that the SVM method is much more accurate and reliable in the monitoring of the IC engine running status,and its classification precision can reach 100%. |
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| Keywords: | ICE ferrous metal wear state discrimination fault diagnosis |
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