应用模糊多属性理论的电力变压器故障融合诊断

Power transformer fault fusion diagnosis using FMADM theory

大型油浸电力变压器的故障诊断一般通过预防性试验数据进行,预防性试验数据必须经停电检修才能获取,且实际现场数据的采集精度及数量也都很有限。变压器的征兆现象是大量经验的总结,在一定程度上可以反映变压器的故障。提出了在变压器故障诊断中将征兆现象和试验数据融合的思想,实现各种信息的优势互补。通过模糊多属性决策理论,实现对征兆现象的诊断;通过变压器绝缘故障诊断的模糊概率模型,实现对预防性试验的诊断;最后用D-S证据理论对预防性试验数据和征兆现象的诊断结果融合。建立了一种新的故障诊断模型,实例证明了此方法的有效性。

Large oil-immersed power transformer fault diagnosis is always directed at preventive test data,the preventive test data can not be got immediately,otherwise,it must be waited until power off and maintenance time. On the other hand,the accuracy and quantity for the field data collection is always limited. However,the symptoms phenomenon is a summary of a great deal experiences,to some extent,it can reflect the failure of transformer. Therefore,an idea that integrates both of the preventive test data and the symptom phenomenon in the transformer fault diagnosis is proposed. Through this method,all kinds of information can complement each other. First,the diagnosis to symptoms phenomenon is realized by introducing fuzzy multi-attribute decision making （FMADM） theory. Then,by adopting the fuzzy probability model,the failure probability of the preventive tests data is calculated. Finally,through D-S evidence theory,the results of the preventive test data and the symptom phenomenon can be integrated. The paper gives a novel diagnosis model which can be used as a kind of effective means through the given example.