Finite Element Model Modification Method of Transmission Tower Based on Static Test Results

Xiao Qingbiao, Luo Yinquan, Zhao Zhenhua, She Kai, Sun Jing, Jiang Wenqiang
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Abstract

The results of finite element model of transmission tower are inconsistent with those of test. In order to better reflect the actual mechanical properties of transmission towers, it is necessary to modify its finite element model. Compared with the dynamic modification method, the statics modification method has higher accuracy, but it is seldom studied because of the difficulty of obtaining experimental data. Based on static test of tower, this paper considers the influence of bolt connection slip on the axial stiffness of rods of tower, and proposes a static finite element model modification method based on BP neural network. According to the input parameters of the model, three different modified models are constructed. The results show that the model of taking displacement and strain as the input parameter, the difference between the results of the modified finite element model and the experimental measurement values are the smallest, and the correction effect is the best. And then the influence of different loading conditions on the model modification effect is analyzed. After a comprehensive analysis and discussion of the results, the model structure and model input parameters with the best modification effect are given. The modified finite element model can provide important reference for health monitoring and damage identification of transmission tower.
基于静态试验结果的输电塔有限元模型修正方法
输电塔有限元模型计算结果与试验结果不一致。为了更好地反映输电塔的实际力学性能,有必要对其有限元模型进行修正。与动态修正值相比,静态修正值具有更高的精度,但由于实验数据获取困难,研究较少。在塔架静力试验的基础上,考虑螺栓连接滑移对塔架杆轴向刚度的影响,提出了一种基于BP神经网络的静力有限元模型修正方法。根据模型的输入参数,构造了三种不同的修正模型。结果表明,以位移和应变为输入参数的模型,修正有限元模型的结果与实验测量值的差异最小,修正效果最好。然后分析了不同加载条件对模型修正效果的影响。经过对结果的综合分析和讨论,给出了修正效果最好的模型结构和模型输入参数。修正后的有限元模型可为输电塔的健康监测和损伤识别提供重要参考。
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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