基于模糊因果图的故障诊断  

Fault Diagnosis Based on the Fuzzy Causality Diagram

作　　者：王洪春[1,2] 张勤[1] 

机构地区：[1]重庆大学自动化学院 [2]重庆师范大学数学与计算机科学学院,重庆400047

出　　处：《微电子学与计算机》2005年第6期109-112,共4页Microelectronics & Computer

基　　金：国家高等学校博士点专项基金(99061116);重庆市科技攻关项目(5990)

摘　　要：因果图理论是一种基于概率论的不确定推理模型,能够进行在线动态推理和对复杂系统进行故障诊断,但在因果图模型中,要求事件的发生概率为精确值。针对实际情况事件发生概率具有模糊性和不确定性的特点,文章将模糊数引入因果图中,解决了获取事件发生概率精确值的难度,又使因果图能处理带模糊性和不确定性的问题。实例表明,该方法不但比故障树分析(FTA)更有效,而且能进行故障树分析不能进行的诊断推理和辩解推理。Causality diagram theory is an uncertainty reasoning methodology based on probability theory, it can progress dynamic reasoning online and fault diagnosis to complex system, but the probability is precision value in causality diagram. Under the reality conditions, the occurrence probability of event shows fuzzy and random, the fuzzy number is inducted into the causality diagram in this paper, and it can solve the difficulty of obtaining the precision probability value as well as solve the problem of the fuzzy and random of the occurrence probability of event. According to the example, this is an efficient approach over FTA, but also it can handle diagnosis reasoning and exculpation reasoning and that FTA cannot.

关 键 词：因果图 故障诊断 模糊数 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]