摘要
在研究故障树分析(FTA)和双向联想记忆(BAM)神经网络在故障诊断中应用的基础上,提出了一种融合FTA和BAM的故障诊断方法.故障树存贮了系统关于顶事件发生的全部知识,利用FTA得到系统所有的故障模式,进而归纳出BAM的学习样本,即故障树中故障现象(监测点状态组合)和底事件发生与否之间的对应.BAM通过联想记忆矩阵并行联想,得到诊断结果,扩展综合故障诊断能力.仿真结果表明该方法用于解决此类问题是有效的.
Based On the study about the application of Fault Tree Analysis and Bidirectiongal Associative Memory network in fault diagnosis,a method of fault diagnosis based on the fuse of FTA and BAM is proposed.In a system,all the knowledge on the happening of top events is stored in Fault tree,so all of the fault modes are obtained by using FTA,and then the learning sample of BAM are summarized which are the corresponding relations between the fault phenomena（the states of the assembled monitoring points）and the happening or not of the bottom events in fault tree.The results of diagnosis are associated parallel by the associative memory matrix,thus expanding the general ability of fault diagnosis.A simulation results showed that the approach is valid to the fault diagnosis of systems.
出处
《微电子学与计算机》
CSCD
北大核心
2010年第6期60-63,共4页
Microelectronics & Computer
基金
国家自然科学基金项目(60475021)
河南科技大学博士基金项目(09001396)
关键词
故障树分析
BAM神经网络
故障诊断
fault tree analysis
bidirectional associative memory network
fault diagnosis
作者简介
苗伟 女，（1982-），硕士研究生．研究方向为故障诊断、智能检测、变频器技术．
范波 男，（1975-），博士，硕士生导师．研究方向为无线传感器网络、信息融合、多智能体系统等．
