基于灰狼算法的桥梁检测车伸缩臂结构的优化设计  

Optimal design of bridge inspection vehicle’s telescopic boom structure based on Gray Wolf Algorithm

作　　者：蔡池兰[1] 周嘉裔 CAI Chilan;ZHOU Jiayi(School of Intelligent Manufacturing and Control Engineering,Shanghai Polytechnic University,Shanghai 201209)

机构地区：[1]上海第二工业大学智能制造与控制工程学院,上海201209

出　　处：《机械设计》2025年第1期78-84,共7页Journal of Machine Design

摘　　要：针对桥梁检测车伸缩臂结构的轻量化问题,文中以最小结构质量为目标,提出一种改进灰狼算法(Ameliorated Grey Wolf Algorithm, AGWO)。根据问题特征建立了伸缩臂结构的数学模型,针对灰狼算法的缺陷,引入混沌策略和反向学习生成灰狼初始种群,提高初始解的质量,同时,将自适应步长加入到灰狼算法的优化过程中,提高算法的收敛速度,并在满足可靠性的前提下,使其达到轻量化的效果。最后,应用有限元分析,检验了改进后算法的可行性,得出优化后的质量减小了18.33%,对实际工程结构的设计有指导意义。Since the bridge inspection vehicle’s telescopic boom structure suffers the lightweight problem,in this article the Ameliorated Grey Wolf Algorithm(AGWO)is proposed to minimize the structural mass.According to the lightweight characteristics,the mathematical model of the telescopic boom structure is set up;in view of the Grey Wolf Algorithm’s defects,both the chaos strategy and the method of reverse learning are introduced to generate the Grey Wolf’s initial population and improve the quality of the initial solution.At the same time,the adaptive step length is added into the optimization process of the Grey Wolf Algorithm,so as to improve its rate of convergence and ensure the effect of lightweight on basis of reliability.Finally,finite-element analysis is used to verified the feasibility of AGWO.After optimization,the structural mass reduces by 18.33%,which provides guidance for structural design in different projects.

关 键 词：桥梁检测车 伸缩臂 灰狼算法 优化设计 

分 类 号：O441[理学—电磁学]