Bayes网络在机械故障概率估计中的应用  

Application of bayes network on estimation of machine fault probability

作　　者：费致根[1] 黄士涛[1] 杜云天[1] 姬中华[1] 

机构地区：[1]郑州大学机械工程学院,河南郑州450002

出　　处：《河南科学》2004年第3期317-320,共4页Henan Science

摘　　要：提出了将bayes网络应用于机械故障诊断。主要是为了解决如何从机组运行状态数据中来推断出机组发生某种故障的可能性,从而为进一步的诊断维护提供依据。Bayes网络是一个具有一系列条件概率的有向无循环图。本文采用两层结构的网络模型,上层为旋转机械的故障样本集,下层为症状属性样本集。根据给出的各故障发生先验概率以及各症状节点的条件概率和泄漏概率,利用网络的推理计算,求出机组发生各种故障的后验概率大小。从而达到预测发生某种故障可能性的目的。实例验证了该方法的可行性和正确性。On the base of bayes network, a method of fault diagnosis for machine is presented in the paper. The purpose of using the network is to deduce the probability of a given fault from the condition data of a running machine as well to offer the evidences for further diagnosis. Bayes network is a directed acyclic graph with a series of conditional probabilities. A two-layered network model is constructed in the paper, and the upper layer represents a fault set and the lower layer represents a symptom set. First, the prior probabilities of faults and the conditional probabilities and leak probabilities are given. Second, the posterior probabilities are calculated by the process of reasoning and computation on the bayes network. By comparing all of posterior probabilities a maximum posterior probability is obtained and the trend of the machine faults is completed. The validity and accurateness of the method is checked by an example.

关 键 词：故障诊断 BAYES网络 旋转机械 

分 类 号：TH17[机械工程—机械制造及自动化]