基于油中溶解气体谱图的变压器故障识别方法

Fault diagnosis method for power transformers based on patterns of dissolved gases in the oil

根据油中溶解气体含量对电力变压器进行故障诊断,一个关键环节是如何从故障气体数据中提取有效反映故障特性的特征量。论文提出了基于特征气体谱图形状参数识别变压器故障的方法,以5种油中溶解气体:乙炔、氢气、乙烷、甲烷和乙烯的相对含量构建了故障的特征气体谱图,并将图形偏斜性、突出性等形状参数作为特征量应用于变压器的故障诊断。应用的结果表明,这种方法有效区分变压器的放电性故障、过热性故障以及"氢主导型"故障,且识别效果达到90%以上,明显优于实践中常用的三比值方法。

In fault diagnosis of power transformers based on dissolved gas analysis (DGA), a key problem is extracting the characteristic features of the transformer faults from the DGA data. A transformer fault diagnostic method was developed based on characteristic gas patterns constructed from the relative concentrations of five kinds of dissolved gases in the oil, acetylene, hydrogen, ethane, methane, and ethylene. The parameters describing these patterns were applied to diagnose transformer faults. The method effectively recognizes transformer faults such as discharge faults, thermal faults, and hydrogen dominated faults with a recognition accuracy above 90%, which is superior to the threeratio method recommend by the International Electrotechnical Commission (IEC).