This study aimed to create an artificial neural network (ANN) architecture capable of estimating the fatigue behavior of aluminum overhead conductors, considering specific weight (W) and bending stiffness (EI) as parameters of influence. ANN training and testing is conducted by using a dataset obtained from fatigue tests carried out in a 50 m resonant bench at the University of Brasilia (UnB). ANNs are used to construct constant life diagrams for this family of conductors, and to compare the results obtained experimentally. Our findings show that for the architectures analyzed, it is possible to accurately estimate the fatigue behavior of this family of aluminum conductors.

中文翻译：

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使用人工神经网络估算一系列铝架空导体的疲劳行为

这项研究旨在创建一种人工神经网络（ANN）体系结构，该结构能够将铝架空导体的疲劳行为估计为影响因素，并将比重（W）和弯曲刚度（EI）作为影响参数。通过使用在巴西利亚大学（UnB）的50 m共振台上进行的疲劳测试获得的数据集来进行ANN训练和测试。人工神经网络用于构造该导体系列的恒定寿命图，并比较实验获得的结果。我们的发现表明，对于所分析的体系结构，可以准确估计该系列铝导体的疲劳行为。