基于贝叶斯网络和油中溶解气体分析的变压器故障诊断方法

电力变压器属电力系统中的重要设备,目前油中溶解气体分析(DGA)的三比值法是对变压器进行故障诊断的最方便、有效的方法之一.本文结合改良的三比值法,将贝叶斯网络方法引入大型变压器的故障诊断,提出了基于贝叶斯网络(BN)理论和变压器油中溶解气体分析方法的变压器智能故障诊断方法,并据此建立了变压器故障诊断模型.通过实例判断验证了本文方法的有效性.

Fault Diagnosis for Power Transformer Based on BN and DGA

Power transformer is very important in power system. Now, dissolved gas analysis (DGA) is the most effective and convenient method in transformer fault diagnosis. This paper advances a new transformer fault diagnosis method based on both Bayesian network (BN) and dissolved gas analysis technique. This method introduces BN method into transformer fault diagnosis and presents a new idea of finding out transformer faults rapid1y and exactly. Then, the transformer fault diagnosis model based on Bayesian network and DGA is constructded. Finally, the application examples in the fault diagnosis of transformer are given which show that this method is effective.