A novel wavelet assisted neural network for transmission line fault analysis

P. Bhowmik, P. Purkait, K. Bhattacharya
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引用次数: 17

Abstract

In this modern era, electric power has become the basic need for the business world. The quality and reliability of power needs to be maintained for obtaining optimum performance. Now-a-days power has also become a business commodity. Hence, faultless and lossless transmission and distribution of power is necessary. Power faults must be identified quickly from various sources (eg. information from relays etc.) and corrected as soon as possible. Advanced signal processing tools such as discrete wavelet transform (DWT) can be used very effectively for parameterization and characterization of the fault signals. On the other hand, properly configured neural network (NN) can be utilized for classification of the faults based on the DWT signal. Presently Electromagnetic Transient Program (EMTP) is used for simulation of a model transmission system and DWT and NN is performed using MATLAB. Faults of various types at different locations along the transmission line have been simulated and attempts have been made to correctly identify and locate the fault.
基于小波辅助神经网络的输电线路故障分析
在这个现代时代,电力已经成为商业世界的基本需求。为了获得最佳性能,需要保持电源的质量和可靠性。如今,电力也已成为一种商业商品。因此,无故障和无损传输和分配电力是必要的。电源故障必须从各种来源迅速识别(例如:来自继电器等的信息)并尽快纠正。先进的信号处理工具,如离散小波变换(DWT)可以非常有效地用于参数化和表征故障信号。另一方面,利用适当配置的神经网络(NN)对小波变换信号进行故障分类。目前采用电磁瞬变程序(EMTP)对某模型传动系统进行仿真,并利用MATLAB进行了DWT和神经网络仿真。对输电线路沿线不同位置的各种类型的故障进行了模拟,并尝试正确识别和定位故障。
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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