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基于专家知识库属性重要度的故障诊断方法研究
引用本文:黄大荣,胡必锦. 基于专家知识库属性重要度的故障诊断方法研究[J]. 计算机仿真, 2007, 24(4): 155-157,210
作者姓名:黄大荣  胡必锦
作者单位:重庆交通大学理学院,重庆,400074;重庆大学自动化学院,重庆,400044;重庆交通大学理学院,重庆,400074
摘    要:利用粗糙集理论中重要性度量的概念和专家知识库集成技术,研究了复杂系统故障诊断的一类新方法.在给出多领域专家知识库集成系统定义和复杂系统状态赋值规则的基础上,利用粗糙集理论中的属性重要度的概念建立了专家知识库属性重要度模型,构造了一种能对实时动态环境进行监控和故障诊断的多领域专家知识库集成故障诊断系统的网络化模型,并提出了相应的算法.此方法已成功应用于复杂系统的故障诊断,取得了良好的应用效果,并具有良好的更新能力和应用前景.

关 键 词:故障诊断  粗糙集理论  专家系统  属性重要度  故障预测
文章编号:1006-9348(2007)04-0155-03
修稿时间:2006-03-27

A New Method of Fault Diagnosis Based on Attribute Significance of Multi-field Experts Database
HUANG Da-rong,HU Bi-jin. A New Method of Fault Diagnosis Based on Attribute Significance of Multi-field Experts Database[J]. Computer Simulation, 2007, 24(4): 155-157,210
Authors:HUANG Da-rong  HU Bi-jin
Affiliation:1 College of Mathematics and Information, Chongqing Jiaotong University, Chongqing 400074, China; 2. College of Automation,Chongqing University, Chongqing, 400044, China
Abstract:Based on attribute significance of rough set and integrated technology of experts database, a new method of fault diagnosis for complex systems is researched. First of all, the attribute significance model of experts database is presented by combining integrated system of multi - field experts and assignment rule of fault state with attribute significance concept in rough set theory. Secondly, a network model based on multi - field experts database is constructed, which can be used to monitor the dynamic systems in real - time and diagnose fault. The presented method has been used in the fault diagnosis of complex systems and good results have been achieved.
Keywords:Fault diagnosis    Rough set theory    Expert system    Attribute significance   Fault prediction
本文献已被 CNKI 维普 万方数据 等数据库收录!
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