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Neural network approach to fault classification for high speed protective relaying

机译:高速继电保护的神经网络故障分类方法

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摘要

This paper presents a new approach to fault classification for high speed protective relaying and show its effectiveness in computer simulations on parallel transmission lines. The scheme is based on the use of neural network architecture and implementation of digital signal processing concepts. We begin by classifying several fault types like 1-phase-to-ground, 2-phase-to-ground and 3-phase-to-ground faults. We proceed with classification of arcing and nonarcing faults in order to obtain a successful automatic reclosing. Encouraging results are shown and indicate that this approach can be used for supporting a new generation of very high speed protective relaying systems.
机译:本文提出了一种用于高速保护继电器的故障分类新方法,并在并行传输线上的计算机仿真中显示了其有效性。该方案基于神经网络架构的使用和数字信号处理概念的实现。我们首先对几种故障类型进行分类,例如1相接地,2相接地和3相接地故障。为了进行成功的自动重合闸,我们对电弧和非电弧故障进行了分类。显示了令人鼓舞的结果,表明该方法可用于支持新一代超高速保护继电器系统。

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