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A novel fault location technique based on current signals only for thyristor controlled series compensated transmission lines using wavelet analysis and self organising map neural networks

机译:基于小波分析和自组织映射神经网络的仅基于电流信号的可控硅串联补偿输电线路故障定位新技术

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This paper describes the applications of discrete wavelet transforms (DWT) coupled with conventional artificial neural networks (ANN) to the development of a fault location technique under an improved TCSC transmission system model. The fault location scheme is modular based whereby fault type is verified before identifying the fault location using ANN. This method relies on utilising DWT to decompose the line currents obtained from a single terminal into a series of time-scale representations. A feature model using self-organising maps (SOM) is applied herein to verify the fault location capability of the extracted features. Simulation results indicate that this approach can be used as an effective tool for accurate fault location in TCSC systems.
机译:本文介绍了在改进的TCSC传输系统模型下,结合传统的人工神经网络(ANN)的离散小波变换(DWT)在故障定位技术开发中的应用。故障定位方案是基于模块化的,由此在使用ANN识别故障位置之前验证故障类型。此方法依赖于利用DWT将从单个端子获得的线路电流分解为一系列时标表示。本文中使用了使用自组织映射(SOM)的特征模型来验证提取特征的故障定位能力。仿真结果表明,该方法可作为TCSC系统中准确定位故障的有效工具。

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