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首页> 外文期刊>Arabian Journal for Science and Engineering. Section A, Sciences >Smart Diagnosis of Incipient Faults Using Dissolved Gas Analysis-Based Fault Interpretation Matrix (FIM)
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Smart Diagnosis of Incipient Faults Using Dissolved Gas Analysis-Based Fault Interpretation Matrix (FIM)

机译：基于溶解气体分析的故障解释矩阵（FIM）智能诊断初期诊断

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摘要

An intelligent transformer fault diagnostic model is the urgent need of reliable power system. To achieve this goal, a diagnostic system using a dissolved gas analysis (DGA)-based fault interpretation matrix (FIM) is proposed. FIM overcomes the issues of contradictory decisions of independent methods and provides low-complexity solution in comparison with the previous literature for transformer fault diagnosis. The developed system has accuracy enhancement and decision-making stages. In the first stage, fuzzy augmentation of three important DGA methods, namely Rogers', IEC and Duval triangle, is carried out followed by the FIM stage and an intermediate normalisation stage. The output of fuzzy models serves as input to the matrix which smartly interprets the fault along with its criticality by exploiting the advantages of individual methods in diagnosing particular fault. This matrix integrates fuzzy augmented methods as per priorities assigned to their outputs. The rules of integration are constructed based on performance assessing factors of individual fuzzy models, and overall decision is made on sensitivity of method for the particular fault type. The performance evaluation of FIM shows its improved diagnostic ability which is intended to improve reliability of DGA-based condition monitoring.
机译：智能变压器故障诊断模型是迫切需要可靠的电力系统。为了实现这一目标，提出了一种使用溶解气体分析（DGA）的故障解释矩阵（FIM）的诊断系统。 FIM克服了独立方法矛盾决策的问题，并提供了与以前的变压器故障诊断文献相比的低复杂性解决方案。开发系统具有准确的增强和决策阶段。在第一阶段，三个重要的DGA方法的模糊增强，即Rogers'，IEC和Duval三角形，然后进行FIM阶段和中间归一化阶段。模糊模型的输出用作矩阵的输入，通过利用单个方法诊断特定故障的优点，巧妙地解释故障。此矩阵根据分配给其输出的优先级集成了模糊增强方法。基于各个模糊模型的性能评估因素构建了整合规则，对特定故障类型的方法的灵敏度进行了整体决策。 FIM的性能评估表明其提高了诊断能力，旨在提高基于DGA的状态监测的可靠性。

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