| 基于RBF神经网络的内燃机活塞-缸套磨损故障诊断 |
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| 引用本文： | 游张平,李自光.基于RBF神经网络的内燃机活塞-缸套磨损故障诊断[J].机床与液压,2003(6):322-324. |
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| 作者姓名： | 游张平 李自光 |
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| 作者单位： | 长沙交通学院,汽车与机电工程系,湖南长沙,410076 |
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| 摘 要： | 以RBF网络为识别模型，对内燃机活塞-缸套磨损的几种故障进行分类训练，并应用于待识别故障样本的识别仿真，结果表明，基于RBF的故障诊断方法优于基于BP网络故障诊断，在活塞-缸套故障诊断中是行之有效的方法。
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| 关 键 词： | 径向基函数神经网络 故障诊断 内燃机 活塞-缸套磨损 RBF网络 故障识别 |
| 文章编号： | 1001-3881(2003)6-322-3 |
| 修稿时间： | 2002年10月28 |
The Fault Diagnosis of Piston-Liner Wear Condition Dased on RBF Neural Network |
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| YOU Zhang-ping,LI Zi-guang.The Fault Diagnosis of Piston-Liner Wear Condition Dased on RBF Neural Network[J].Machine Tool & Hydraulics,2003(6):322-324. |
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| Authors: | YOU Zhang-ping LI Zi-guang |
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| Abstract: | Based on the Radial Basis Function neural network,with some fault samples of I.C. engine piston-liner wear condition was trained,and also the neural network model was applied to identify the samples for identify. The result indicates that the method of the fault diagnosis based on RBF is more effective than the method based on BP neural network in the fault diagnosis of piston-liner wear condition. |
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