基于模糊推理的SDG故障诊断新方法  

New SDG fault diagnosis method based on fuzzy reasoning

作　　者：刘玥[1] 张贝克[1] 吴重光[1] 

机构地区：[1]北京化工大学信息科学与技术学院,北京100029

出　　处：《计算机应用》2005年第11期2661-2664,共4页journal of Computer Applications

基　　金：国家863计划项目(2003AA412310);北京市教委资助项目(XK100100435)

摘　　要：针对纯定性的SDG推理方法忽略了SDG图中节点之间的影响程度不同导致诊断分辨率不高这一问题,提出了在纯定性SDG推理的基础上用模糊矩阵的形式加入节点间相互影响关系的定量信息的推理新方法,可对多潜在故障源划分优先级,从而提高SDG故障诊断的分辨率。相对于其他模糊SDG故障诊断方法,本方法勿需使用隶属函数,取而代之的是模糊矩阵,后者的获取易于前者,且采用矩阵的表示方法方便了计算机编程的实现。The fault diagnosis method based on qualitative SDG deep knowledge model has better completeness, but lower resolution. Because it ignores the fact that the effect is different between different nodes in a SDG graph. To solve this problem, a new method which added the qualitative information of the effect between nodes into the qualitative SDG reasoning by fuzzy matrix was proposed, according to which the priority could be given to the multi-potential fault origin and the resolution could be improved. Different from other fuzzy SDG fault diagnosis methods, this method used the fuzzy matrix instead of membership function, because fuzzy matrix can be got easier than membership function and it can make the computer programming easier.

关 键 词：SDG 模糊推理 故障诊断 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]