Fault classification on transmission line of 10kV rural power grid

被引：0

作者：

Lv, Chunyu ^{[1
]}

Zhang, Shuguang ^{[1
]}

机构：

[1] Agr Univ Hebei, Coll Mech & Elect Engn, Baoding, Peoples R China

来源：

PROCEEDINGS OF THE 2015 4TH INTERNATIONAL CONFERENCE ON SENSORS, MEASUREMENT AND INTELLIGENT MATERIALS | 2016年 / 43卷

关键词：

Discrete Wavelet Transform; Neural Network; Transmission Line; Fault Classification; PSCAD;

D O I：

暂无

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

This paper proposes a technique using Discrete Wavelet Transform (DWT) and Back-Propagation Neural Network (BPNN) to identify the fault types on transmission line of 10kv rural power grid. The PSCAD is used to simulate fault signals. The mother wavelet daubechies4 (db4) is employed to decompose high frequency component from these signals. The variations of first scale high frequency component that detect fault are used as an input for the training pattern. The result has shown that the proposed technique gives satisfactory results

引用

页码：384 / 387

页数：4

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