燕山大学学报2025，Vol.49Issue(3)：207-218,12.DOI:10.3969/j.issn.1007-791X.2025.03.002
基于IDBO-BP算法的覆冰状态输电塔应力与位移预测模型
Stress and displacement prediction model of icing transmission tower based on IDBO-BP algorithm
摘要
Abstract
Transmission towers are highly susceptible to deformation of tower materials,inclination of the tower body,and even tower collapse due to the effects of strong winds and icing.Establishing a state prediction model for transmission towers under extreme weather conditions can predict the changes in stress on key parts of the tower body and the overall inclination.In this paper,an icing transmission tower stress and displacement prediction model based on the IDBO-BP algorithm is proposed.Initially,the dung beetle optimization algorithm is optimized by using the Singer chaotic map and the variable spiral search strategy,which is followed by optimizing the weights and thresholds of the BP neural network using the improved dung beetle optimization algorithm,resulting in a prediction model for the stress and displacement of the icing transmission tower.Secondly,finite element simulation calculations are used to obtain the state response of the transmission tower under different working conditions.Finally,the prediction model and simulation results are combined to obtain the predicted values of stress on key parts and the displacement of the tower head under icing conditions.The results show that the proposed IDBO-BP algorithm reduces the absolute mean error by 62.9%,the mean relative error by 58.1%,and the root mean square error by 60.2%compared to the DBO-BP algorithm,providing a reference for the safety prediction of the tower's self conditions under icing.关键词
输电塔/BP神经网络/覆冰/改进蜣螂算法Key words
transmission towers/BP neural network/icing/improved dung beetle algorithm分类
动力与电气工程引用本文复制引用
王彦海,李恩阳,苗红璞,石习双,李书炀,周冬阳..基于IDBO-BP算法的覆冰状态输电塔应力与位移预测模型[J].燕山大学学报,2025,49(3):207-218,12.基金项目
国家自然科学基金资助项目(U22A20600,52079070) （U22A20600,52079070）
防灾减灾湖北省重点实验室开放资金资助项目(2022KJZ07) （2022KJZ07）
