期刊名称：International Journal of Security and Its Applications
印刷版ISSN：1738-9976
出版年度：2014
卷号：8
期号：5
页码：65-74
DOI：10.14257/ijsia.2014.8.5.07
出版社：SERSC
摘要：Extenics and rough set theory are brought into transformer fault diagnosing procedure in this paper to get rid of abundant information data and to obtain more precise diagnosing result. Using the dissolved gas data as fault diagnosing attribution set, attributions which are needed for transformer fault diagnosis are predigested and preliminarily grouped by means of rough set method, and then matter element model for transformer’s fault diagnosing is built. With the transformer’s standard fault modes as the transformer’s fault diagnosing decision set, utilizing extenics association function to calculate each fault degree, acceptance and rejection rule is defined to diagnose transformer’s fault. 76 dissolved gas information data have been collected to verify the method proposed in this paper, the diagnosing results show that the correctness of diagnosing results got by this method is better than frequently used IEC three ratio methods.
关键词：transformer; fault diagnosis; extenics; matter element model; rough set
