首页> 外文会议>International Conference on Artificial Neural Networks(ICANN 2006) pt.2; 20060910-14; Athens(GR) >New Phenemenon on Power Transformers and Fault Identification Using Artificial Neural Networks
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New Phenemenon on Power Transformers and Fault Identification Using Artificial Neural Networks

机译:电力变压器和人工神经网络故障识别的新现象

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In this paper voltage recovery after voltage dip that cause magnetizing inrush current which is a new phenomenon in power transformers are discussed and a new technique is proposed to distinquish internal fault conditions from no-fault conditions that is also containing these new phenomenons. The proposed differential algorithm is based on Artificial Neural Network (ANN). The training and testing data sets are obtained using SIMPOW-STRI power system simulation program and laboratory transformer. A novel neural network is designed and trained using back-propagation algorithm. It is seen that the proposed network is well trained and able to discriminate no-fault examples from fault examples with high accuracy.
机译:本文讨论了电压骤降后引起励磁涌流的电压恢复问题,这是电力变压器中的一种新现象,并提出了一种新技术来区分内部故障条件与无故障条件,无故障条件也包含这些新现象。所提出的差分算法基于人工神经网络(ANN)。培训和测试数据集是使用SIMPOW-STRI电力系统仿真程序和实验室变压器获得的。使用反向传播算法设计和训练了一种新颖的神经网络。可以看出,所提出的网络训练有素,并且能够高精度地将无故障示例与故障示例区分开。

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