摘要
针对电力变压器故障诊断中的复杂非线性关系,提出一种基于RIMER(基于证据推理算法的置信规则库推理方法)专家系统和油中溶解气体分析(DGA)技术的变压器故障诊断方法。该方法考虑了变压器故障特征量和征兆的概率不确定性和模糊不确定性,在IEC三比值法和变压器油中溶解气体故障数据样本训练的基础上获得置信规则库的主要参数,结合证据推理算法建立一个新型的变压器DGA故障诊断模型。通过RIMER和DGA变压器故障诊断模型进行故障诊断,克服了IEC三比值法故障编码缺失的问题,故障诊断准确率获得提高,其分布式置信度的输出方式对描述混合故障类型更加有效。仿真实验表明该方法推理计算简单有效,具有较强实用价值。
A transformer fault diagnosis method based on RIMER （belief rule-base inference methodology using the evidential reasoning approach） expert system and data of dissolved gasses analysis （DGA） is proposed to deal with the complex nonlinear relation in transformer fault diagnosis. Considering the probability uncertainty and fuzzy uncertainty of the transformer fault characters, a new DGA fault diagnosis model is established based on the evidence consequence and the parameters of belief rule base from both IEC three-ratio method and training of fault samples of dissolved gasses. The RIMER-DGA transformer fault diagnosis model solves the problem of fault code missing in IEC three-ratio method, thus improves the fault diagnosis accuracy and obtains better description of mixed-type fault. Simulation shows that the proposed method is simple and feasible.
出处
《高压电器》
CAS
CSCD
北大核心
2013年第11期76-81,共6页
High Voltage Apparatus
基金
中央高校基本科研业务费专项资金资助项目(SWJTU11BR034)~~
