紧致融合模糊集和故障树的变压器故障诊断  

Transformer Fault Diagnosis Method Based on Compact Fusion of Fuzzy Set and Fault Tree

作　　者：谷凯凯[1,2] 郭江[1,2] 

机构地区：[1]水力机械过渡过程教育部重点实验室,武汉430072 [2]武汉大学动力与机械学院,武汉430072

出　　处：《高电压技术》2014年第5期1507-1513,共7页High Voltage Engineering

基　　金：国家自然科学基金(51077102)~~

摘　　要：为弥补传统单一诊断在变压器故障诊断应用中的不足,在全面分析模糊集和故障树各自优势的基础上提出了紧致融合模糊集和故障树的变压器故障诊断方法,旨在有机融合模糊集和故障树的优点,提高变压器故障诊断的准确性和效率。以故障树理论分析为基础,构建了紧致融合模糊集和故障树的诊断模型,重点阐述了其构建方法和诊断逻辑。案例分析表明:相比与传统的故障树诊断技术,紧致融合模糊集和故障树的变压器故障诊断技术的容错能力更强;诊断结果记录了诊断的一些中间过程,并在信息不完备的情况下,返回相关的信息为研究人员进行下一步分析提供参考。To make up for the deficiency existing in simplex diagnostic techniques for transformer fault diagnosis, we put forward a transformer diagnose method based on the compact fusion of fuzzy set and fault tree after deeply analyzing the two concepts. Combining the advantages of fuzzy set and fault tree, the proposed method could improve transformer fault diagnose in both accuracy and efficiency. According to the fault tree diagnose theory, we built a diagnose model based on compact fusion of fuzzy set and fault diagnose, and illustrated the model＇s construction method and diagnose logic in detail. Case analysis shows that, compared with traditional fault tree diagnose methods, the proposed method is advanced in fault-tolerance ability. Plus, it records some intermediate processes in the diagnosis to return to users, which is useful for analysis with incomplete diagnosis information.

关 键 词：变压器 模糊集 故障树 紧致融合 容错能力 故障诊断 

分 类 号：TM407[电气工程—电器]