DWT and BPNN based fault detection, classification and estimation of location of HVAC transmission line

Binoy Saha, Bikash Patel, P. Bera
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引用次数: 8

Abstract

The paper presents a technique for detection classification and diagnosis of fault location on overhead transmission lines for different types of fault. Discrete wavelet transform (DWT) has been used for extraction of features of signals of current under faulted condition and back propagation neural network (BPNN) have been used for training the features of current signal for different fault location. It has been found that the coefficients of discrete wavelet transform of fault signal and BPNN satisfactorily detect, classify and locate the fault location.
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基于DWT和BPNN的暖通输电线路故障检测、分类和位置估计
提出了一种针对架空输电线路不同类型故障的检测、分类和故障定位诊断技术。采用离散小波变换(DWT)提取故障状态下的电流信号特征,采用反向传播神经网络(BPNN)训练不同故障定位的电流信号特征。研究发现,故障信号的离散小波变换系数和BPNN能较好地检测、分类和定位故障位置。
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