基于小波变换和人工神经网络的浪涌电流检测

2018 Second International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2018-02-01 DOI:10.1109/ICCMC.2018.8487832

Prachi R. Gondane, Rukhsar M. Sheikh, Kajol A. Chawre, Vivian V. Wasnik, A. Badar, M. Hasan

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引用次数: 7

摘要

本文采用小波变换和人工神经网络(ANN)对电流波形进行处理，区分涌流、故障和正常情况。小波变换用于分析和检测信号中存在的各种频率分量。人工神经网络是一种基于特定属性对数据进行分类的工具。仿真中使用了不同类型的电力系统组合。故障检测是电力系统安全运行的重要组成部分。对于信号的合成和当前状态的分类，将小波变换和人工神经网络共同用于。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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INRUSH CURRENT DETECTION USING WAVELET TRANSFORM AND ARTIFICIAL NEURAL NETWORK

In this paper, wavelet transform and artificial neural network (ANN) is used for processing current waveforms and distinguish between inrush current, fault and normal situation. Wavelet transform is used to analyze and detect various frequency components present in the signal. ANN is a tool which is utilized for classification of data based on specific properties. Different types of power system combinations are used in simulation. Fault detection is an important part for safety of electric power system. For the synthesis of signals and the classification of current conditions, WT and ANN are used in collectively.

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2018 Second International Conference on Computing Methodologies and Communication (ICCMC)

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