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Fault diagnosis model of power transformer based on improved grey relation method with combined weight

机译:基于改进的灰色关联关联权法的电力变压器故障诊断模型

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Dissolved gas analysis is worldwide accepted as an effective method for identifying incipient fault of power transformer. In order to enhance its accuracy and reliability, fault diagnosis model has been developed based on improved grey relation method with combined weight in this paper. Experts determined weight of dissolved gases for fault diagnosis with analytic hierarchical process and improved grey relation method is used to obviate non-uniform weight distribution caused by expert's subjective factors. Besides, Objective weight is calculated with entropy method. The minimum relative information entropy principle is applied to obtain the combined weight of indices. Then, the combined weights are applied to the proposed method for transformer fault diagnosis. The proposed model has been applied to real database and the results presented in this paper clearly indicate relative high degree accuracy over conventional methods of transformer fault diagnosis using DGA.
机译:溶解气体分析是一种识别电力变压器初期故障的有效方法,在世界范围内被广泛接受。为了提高其准确性和可靠性,本文建立了一种基于改进的灰色关联法结合权重的故障诊断模型。专家采用层次分析法确定了溶解气体的重量,以进行故障诊断,并采用改进的灰色关联法来消除专家主观因素引起的重量分布不均。此外,目标权重是用熵法计算的。应用最小相对信息熵原理获得指标的权重。然后,将组合权重应用于提出的变压器故障诊断方法。所提出的模型已经应用于实际数据库,并且本文给出的结果清楚地表明,与传统的使用DGA进行变压器故障诊断的方法相比,该方法具有较高的准确度。

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