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首页> 外文期刊>Electric power systems research >Design of an artificial neural network for the estimation of the flashover voltage on insulators
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Design of an artificial neural network for the estimation of the flashover voltage on insulators

机译:用于估计绝缘子闪络电压的人工神经网络设计

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摘要

This work attempts to apply an artificial neural network in order to estimate the critical flashover voltage on polluted insulators. The artificial neural network uses as input variables the following characteristics of the insulator: diameter, height, creepage distance, form factor and equivalent salt deposit density, and estimates the critical flashover voltage. The data used to train the network and test its performance is derived from experimental measurements and a mathematical model. Various cases have been studied and their results presented separately. Training and testing sets have been modified for each case.
机译:这项工作试图应用人工神经网络,以估计污染绝缘体上的临界闪络电压。人工神经网络将绝缘子的以下特征用作输入变量:直径,高度,爬电距离,形状因数和等效盐沉积密度,并估算临界闪络电压。用于训练网络并测试其性能的数据来自实验测量结果和数学模型。研究了各种情况,并分别给出了结果。每种情况下的培训和测试集均已修改。

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