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Decision about criticality of power transformers using whitenization weight functions on DGA caution levels

机译:在DGA警告级别上使用白化权重函数确定电力变压器的关键性

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Power transformers are the most significant as well as the major asset of any power system network. The condition monitoring and assessment is the main concern in transformer management activities. As a first information source, dissolved gases-in-oil analysis (DGA) is universally accepted. The assessment of dissolved gases is characteristically observed analogous to grey system analysis. Grey system theory is supportive to the cases, when less information about the system is available. The cluster of grey incidences and whitenization weight functions classifies the factors of same type, in order to simplify a complex system. Three caution levels of key gases specified in IEEE standards are utilized in this study, to whiten the weight functions. The whitenization weight function with lower measure is selected for caution level-1. However, whitenization weight functions with middle measure are preferred for level-2 and level-3. Several key gas samples of the equal rating transformers are collected from gas analyzer section and utilized in condition assessment computations. The test samples are verified with variable and equal weight clustering criteria. The criticality judgment of transformer with variable weight clustering successfully identifies the crucial elements amongst samples.
机译:电力变压器是任何电力系统网络中最重要也是最重要的资产。状态监视和评估是变压器管理活动中的主要关注点。作为第一个信息来源,油中溶解气体分析(DGA)被普遍接受。典型地观察到溶解气体的评估,类似于灰色系统分析。当有关该系统的信息较少时,灰色系统理论可为这些情况提供支持。灰色关联和白化权重函数类将相同类型的因素分类,以简化复杂的系统。这项研究采用了IEEE标准中规定的三种关键气体警告等级,以使重量函数变白。选择较低级别的增白权重功能可将其作为警告级别1。但是,级别2和级别3最好使用带有中间度量的美白权重函数。从气体分析仪部分收集了等额定变压器的几个关键气体样本,并将其用于状态评估计算中。用可变和相等重量的聚类标准验证测试样品。具有可变权重聚类的变压器的关键性判断成功地确定了样本中的关键要素。

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