鉴于常用的三比值法诊断变压器故障时会出现“无编码”情况,提出了利用可拓学与粗糙集理论对变压器故障进行诊断的方法.以粗糙集属性约简方法对各种故障类型所需要的属性条件进行初步约简分类,然后建立变压器故障诊断的物元模型,以DGA测试数据作为变压器故障诊断属性集,以变压器标准故障模式作为变压器故障诊断决策集,利用可拓关联函数计算各种故障程度,定义故障取舍规则以确定变压器故障.以某台故障变压器为实例进行分析,其诊断结果与实际情况相符；收集76条变压器DGA信息,利用该方法进行故障诊断,诊断正确率较IEC法乐观.%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.
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