基于灰关联熵的充油变压器故障诊断方法

油中溶解气体分析是目前发现变压器潜伏性故障的重要方法,鉴于用IEC推荐的三比值法中编码缺陷(编码超出码表)及变压器故障诊断的复杂性,文中详细阐述了如何将灰关联熵应用于变压器故障诊断。首先通过统计方法,选择典型油中气体作为参考列,并经反复调整,挖掘出油中气体所含故障信息,然后利用灰关联熵方法进行变压器故障类型诊断。该方法基于融合互补的思想,将灰关联分析方法与信息熵理论有机结合起来,克服了单一灰关联分析中易造成局部关联及信息损失等缺陷,尽可能多地包含变压器本体所含信息。实例分析结果表明,该方法具有较好的分类效果。

Fault Diagnosis for Power Transformer Based on Grey Relation Entropy

Dissolved gas-in-oil analysis (DGA) is an important method to find the hidden or incipient insulation faults of oil-immersed power transformer. However, code deficiency exists in the gas ratio methods specified by the IEC/IEEE standard (such as ratio code nonentity) and complexity of fault diagnosis for power transformer. Hence a new fault diagnosis method is presented based on grey relation entropy in this paper. After fault information is mined via taking collected fault samples of oil-immersed transformers as reference list by the statistic analysis and adjusting data reiteratively, fault diagnosis for transformer is accomplished according to the grey relation entropy. Based on complementary strategy, the proposed method integrates grey relation analysis and information entropy. By doing so the result can contain as more information of transformer as required, which overcomes shortcomings of original grey relation analysis, such as partial relation and information losing. The effectiveness of this model has been verified through the application of examples.