中南大学学报（自然科学版）2025，Vol.56Issue(7)：2731-2740,10.DOI:10.11817/j.issn.1672-7207.2025.07.010
履带起重机桁架臂最大静力响应预测
Maximum static response prediction of crawler crane's lattice boom
摘要
Abstract
In order to predict the maximum static response of the crawler crane's lattice boom structure in various working cases quickly and accurately,an ICOOT-BP neural network prediction model based on the BP neural network and improved COOT(ICOOT)algorithm was proposed.Firstly,a parametric model of the lattice boom's maximum static response was created by using the Ansys parametric design language(APDL)to obtain static response training samples under various working conditions,with different bar geometric parameters and loads.Secondly,the original COOT algorithm was enhanced by utilizing the Tent chaotic mapping and adaptive mutation method to improve its optimization ability,resulting in the improved COOT algorithm,namely ICOOT.Finally,the topological structure of the BP neural network model was determined,and the weights and thresholds in the BP neural network were optimized by using the ICOOT algorithm,thereby a surrogate model was established between input parameters and output responses for the static analysis of the lattice boom.The results show that the ICOOT-BP model of a special crawler crane's lattice boom can quickly predict the maximum static response of the lattice boom under various working conditions.The prediction results are highly consistent with the finite element analysis results,and the absolute values of the relative errors of stress and displacement are all less than 4%.Moreover,it is significantly superior to other prediction models compared in this paper in terms of prediction accuracy and training efficiency.The proposed ICOOT-BP model significantly enhances the efficiency of the maximum static response analysis for the crawler crane's lattice boom,providing an accurate structural analysis surrogate model for mechanical analysis and structural optimization design of the lattice boom.关键词
履带起重机/桁架臂/静力响应预测/BP神经网络/改进的COOT算法Key words
crawler crane/lattice boom/static response prediction/back propagation neural network/improved COOT optimization algorithm分类
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李金平,张宇,田一,顾海荣,叶敏,张大庆,徐信芯..履带起重机桁架臂最大静力响应预测[J].中南大学学报（自然科学版）,2025,56(7):2731-2740,10.基金项目
国家重点研发计划项目(2021YFC3002003) （2021YFC3002003）
陕西省重点研发计划项目(2023-YBSF-104) （2023-YBSF-104）
陕西省创新能力支撑计划项目(2022PT-30) （2022PT-30）
河南杰出外籍科学家项目(2022004)(Project(2021YFC3002003)supported by the National key Research and Development Plan （2022004）
Project(2023-YBSF-104)supported by the Shaanxi Province Key Research and Development Program （2023-YBSF-104）
Project(2022PT-30)supported by the Shaanxi Province Innovation Capacity Support Plan （2022PT-30）
Project(2022004)supported by the Henan Outstanding Foreign Scientist Workshop) （2022004）
