Neural network based fault diagnosis in an HVDC system

H. Etemadi, V. Sood, K. Khorasani, R. Patel
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引用次数: 20

Abstract

This paper presents a neural network (NN) based method for fault classification in a power system. A new method of generating the training data is proposed which has the advantage that the total number of fault simulations needed to generate the training patterns is less than that required by the conventional training method. This is obtained at the cost of a time delay in the NN output response. The performance of the proposed method is investigated using the Matlab simulation model of a simple HVDC system.
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基于神经网络的高压直流系统故障诊断
提出了一种基于神经网络的电力系统故障分类方法。提出了一种新的训练数据生成方法,该方法的优点是生成训练模式所需的故障模拟总数比传统训练方法少。这是以神经网络输出响应的时间延迟为代价获得的。利用简单直流输电系统的Matlab仿真模型对该方法的性能进行了研究。
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