基于粗糙集和图论的电力系统故障诊断方法  

Method of fault diagnosis in power system based on rough set theory and graph theory

作　　者：卢鹏[1] 王锡淮[1] 肖健梅[1] 

机构地区：[1]上海海事大学物流工程学院,上海200135

出　　处：《控制与决策》2013年第4期511-516,524,共7页Control and Decision

基　　金：上海市教委科研创新重点项目(12ZZ158);上海市教委重点学科建设项目(J50602)

摘　　要：将粗糙集与图论相结合处理电力系统故障诊断,提出了故障决策表图的新概念,得到一种基于粗糙集和图论的电力系统故障诊断方法,并进一步提出了故障信息覆盖度和故障诊断规则分级的概念.利用故障决策表图及其邻接矩阵,得到了快速识别决策表核属性和属性约简的方法,并将规则分级应用于故障规则提取.利用所提出的方法对具体实例进行处理,仿真结果表明,该方法能有效地减少时间和空间复杂度,可根据设定的阈值提取诊断规则.The new concept of the fault decision table graph is proposed based on the idea of processing for fault diagnosis in power system which combines rough set with graph theory. Furthermore, the concepts of fault information coverage and fault diagnosis rule classification are presented by using the fault decision table graph and its adjacency matrix, and the method of fast recognition of core attributes of a decision table and the method of attribute reduction are obtained, and the concept of fault diagnosis rule classification is applied to fault rules extraction. An example is processed by using the proposed method, and the simulation results show that, the method can effectively reduce the complexity of time and space, and extract diagnosis rules according to the set threshold value.

关 键 词：故障决策表图 邻接矩阵 属性约简 故障信息覆盖度 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]