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用于机械故障诊断Bayes网络的MLE学习方法
引用本文:费致根,徐小洁,董喜燕.用于机械故障诊断Bayes网络的MLE学习方法[J].河南科学,2007,25(1):98-100.
作者姓名:费致根  徐小洁  董喜燕
作者单位:郑州轻工业学院,机电学院,郑州,450002
摘    要:组建完成了一个用于机械故障诊断的具有两层节点结构的Bayes网络模型,利用Bayes网络的强大学习功能,探讨了当学习样本集完整时,采用MLE(最大似然估计)法则来合理地调整网络模型的CPT表值,使之更加符合特定机组的运行情况,从而为网络模型的判断推理做好了准备。

关 键 词:故障诊断  Bayes网络  网络学习
文章编号:1004-3918(2007)01-0098-03
修稿时间:2006-09-21

The MLE Algorithm on the Bayes Network for Machine Fault Diagnosis
FEI Zhi-gen,XU Xiao-jie,DONG Xi-yan.The MLE Algorithm on the Bayes Network for Machine Fault Diagnosis[J].Henan Science,2007,25(1):98-100.
Authors:FEI Zhi-gen  XU Xiao-jie  DONG Xi-yan
Institution:College of Mechanical and Electrical Engineering, Zhengzhou University of Light Industry 450002, China
Abstract:On the base of Bayes network, the model of fault diagnosis for machine contains two-layer nodes is constructed in the paper. With the help of the strong learning capability of the model, when the learning data samples are complete, MLE algorithm is used to adjust the value of the conditional probability table of the model to the special machine. Consequently the model is ready to reason and calculate.
Keywords:faults diagnosis  Bayes network  learning of the network
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