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Fault detection and classification approaches in transmission lines using artificial neural networks

机译:人工神经网络的输电线路故障检测与分类方法

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摘要

This paper studies a new approach based on the artificial neural networks (ANN) for the fault detection and classification, in real time, in transmission lines to extra high voltage (EHV) which can be used in the production system digital protection. This approach is based on the treatment of each phase current and voltage. The outputs of the ANN indicate the fault presence and it type. The ANN detector and classifier are tested in various fault types, various locations, different fault resistances and various inception angle. All the test results show that the fault suggested detector and classifier can be used to support a new system generations of protection relay at high speed.
机译:本文研究了一种基于人工神经网络(ANN)的新方法,用于传输线至超高压(EHV)的故障实时检测和分类,可用于生产系统数字保护。该方法基于对每相电流和电压的处理。 ANN的输出指示故障的存在及其类型。 ANN检测器和分类器在各种故障类型,不同位置,不同故障电阻和不同起始角度下进行了测试。所有测试结果表明,建议的故障检测器和分类器可用于支持新一代高速保护继电器系统。

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