基于粗糙集理论的电力设备故障诊断方法  

FAULT DIAGNOSIS FOR POWER EQUIPMENT BASED ON ROUGH SET METHOD

作　　者：董立新[1] 肖登明[1] 杨荆林[1] 刘奕路[2] 

机构地区：[1]上海交通大学电子信息及电气工程学院,上海200030 [2]美国弗吉尼亚理工大学电气工程系

出　　处：《高压电器》2003年第5期23-25,28,共4页High Voltage Apparatus

基　　金：国家自然科学基金(50128706)

摘　　要：电力设备的故障诊断可以看成一个模式分类问题,每一个电力设备故障对应一组特征集。笔者提出了根据电力设备故障案例的故障状况和故障的相关检测参数,建立故障诊断决策表(即“知识库”),并以决策表为主要工具,采用粗糙集理论方法,直接从故障样本集中导出诊断规则,为电力设备提供有效的故障诊断。采用这一方法,在通过信息网络实现远程诊断等过程中,在用户所获取的故障参数信息数据不完备的情况下,有可能为电力设备故障诊断服务提供一条新途径。The fault diagnosis of power equipment can be looked as pattern classification problem. Each fault of power equipment is corresponding to a set of traits. In this paper, according to fault status and correlated measured parameters of power equipment fault cases, a fault diagnosis decision-making table (i.e. 'knowledge base') is structured. By way of the decision-making table, the diagnosis rules is extract directly from fault patterns using rough set method. The extracted rules can be used to offer the effective fault diagnosis for power equipment. This paper brings forward a new approach to process diagnosis and give the more satisfied diagnosis service for power equipment in remote diagnosis by information network when some diagnosis data information offered by user is not complete.

关 键 词：电力设备 故障诊断 粗糙集理论 决策表 电力系统 可靠性 

分 类 号：TM711[电气工程—电力系统及自动化]