南方电网技术2011，Vol.5Issue(z2)：113-117,5.
可拓关联函数与属性约简相结合的变压器故障诊断方法
The Fault Diagnosis of Transformer Using Association Function of Extenics and Attribute Predigesting of Rough Set Theory
摘要
Abstract
Since the general diagnosis methods such as DGA and attributes' reduction of rough set haven't enough precision for transformer's fault diagnosis, Extenics and rough set theory are brought into diagnosing the fault of transformer. Using attribute predigesting method in rough set theory to classify the attribute term which needed by each fault diagnosis. Then building matter element model for transformer's fault diagnosis. Using DGA testing datum to be attribute set and the transformer's standard fault model to be the decision set for transformer's fault diagnosis. Utilize association function from Extenics to count each fault degree. Define the fault accepting rule to get transformer's fault. Use this method to diagnose one fault transformer and the diagnosis result matched case of fact fault. Apply this method to diagnose 76 DGA testing data and the right ratio of diagnostic result is better than IEC method.关键词
变压器/故障诊断/可拓学/物元模型/粗糙集Key words
transformer/fault diagnosis/extenics/matter element model/rough set分类
信息技术与安全科学引用本文复制引用
胡泽江,张海涛..可拓关联函数与属性约简相结合的变压器故障诊断方法[J].南方电网技术,2011,5(z2):113-117,5.
