Xiao Qingbiao, Luo Yinquan, Zhao Zhenhua, She Kai, Sun Jing, Jiang Wenqiang
{"title":"Finite Element Model Modification Method of Transmission Tower Based on Static Test Results","authors":"Xiao Qingbiao, Luo Yinquan, Zhao Zhenhua, She Kai, Sun Jing, Jiang Wenqiang","doi":"10.1109/REPE55559.2022.9949091","DOIUrl":null,"url":null,"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.","PeriodicalId":115453,"journal":{"name":"2022 5th International Conference on Renewable Energy and Power Engineering (REPE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 5th International Conference on Renewable Energy and Power Engineering (REPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/REPE55559.2022.9949091","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.