模糊粗糙集理论在变压器故障诊断中的应用  

Application of Fuzzy Rough Set Theory to Power Transformer Faults Diagnosis

作　　者：熊浩[1] 李卫国[2] 畅广辉[3] 郭惠敏[3] 

机构地区：[1]武汉大学电气工程学院,湖北省武汉市430072 [2]电力系统保护与动态安全监控教育部重点实验室(华北电力大学),北京市昌平区102206 [3]河南省电力公司,河南省郑州市450052

出　　处：《中国电机工程学报》2008年第7期141-147,共7页Proceedings of the CSEE

摘　　要：提出一种改进的三比值变压器故障诊断方法。以模糊粗糙集为数学基础建立信息决策系统,采用数据挖掘技术解决这一建立过程中的若干问题。考虑到信息源的连续取值对模糊粗糙推理的影响,利用模糊集方法处理连续取值型属性。利用数据库知识发现技术挖掘数据库中隐含的聚类信息,设置属性的模糊取值并确定隶属函数。并在此基础上基于包含度对模糊规则进行约简和剔除。设计了适用于模糊粗糙规则提取的数据挖掘算法,从数据库中提取规则,按属性集建立多表决策库的拓扑结构。诊断结果表明,该决策库故障正判率较高,模糊判断规则适应现场条件。This paper is meant to present a new diagnosis measure with gas ratios method for transformer incipient fault. Based on fuzzy rough set （FRS） theory, an information decision system is built, in which some problems in the process of system building are coped with by data mining technology. Firstly, since strict thresholds setting is said to be undergoing the diagnosis effectiveness, continuous attributes are transformed and described based on fuzzy set theory, where the knowledge discovery in database （KDD） technology is used to extract the implied information on fuzzy clustering so as to determine the fuzzy values of attributes and thus the parameters of membership function. Secondly, according to inclusion degree defined in FRS, the formed fuzzy rules are reduced and pruned, where a data-mining algorithm is developed to extract fuzzy rough rules and thus determine the topology of multi-table decision base according to attributes set. Finally, results of testing the proposed diagnosis system on actual dissolved gas records are addressed, which confirms that extracted rules allow diagnosis results to be satisfied with a satisfactory accuracy for diagnosis ratio.

关 键 词：数据库知识发现 溶解气体分析 模糊粗糙集 数 据挖掘 

分 类 号：TM411[电气工程—电器]