人工神经网络技术在架空输电线路故障检测与定位中的应用

P. S. Pouabe Eboule, J. Pretorius, N. Mbuli
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引用次数: 6

摘要

本文研究了人工智能技术在超高压输电线路故障检测、分类和定位中的应用。本文比较了多层感知器(MLP)技术和并行神经模糊技术对735 kV、600 km线路电压和400 kV、120 km线路电压的超高压输电线路进行故障检测、分类和定位的结果。所使用的这些技术的优点是,它们可以提高电力线的可靠性,减少在故障发生时查找故障所浪费的时间,并且有利于服务的连续性,这是经济繁荣的标志。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Neural Network Techniques apply for Fault detecting and Locating in Overhead Power Transmission Line
The study carried out here in this paper presents the application of artificial intelligence techniques to detect, classify and locate faults on power transmission line very high voltage. This paper compares the results of the techniques call Multi- Layers Perceptron (MLP) and Concurrent Neuro-Fuzzy used to detect, classify and locate the faults on two different very high voltage electrical lines of 735 kV line voltage, 600 km long for the first line and a second line of 400 kV, 120 km long. The advantages of these techniques used are that they permit to increase the level of reliability of a power line, to limit the lost time in the search for the defects when they occur and then to favorize a continuity of service so much sought by companies sign of economic prosperity.
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