摘要
船用起重机在海上作业时因风浪引起吊重摆动导致作业风险较高,需要对起重机加装相应的防摆装置,而在起重机上加装防摆装置会增加起重机负荷影响工作效率,因此需要对船用起重机防摆装置结构进行轻量化设计。针对船用起重机防摆装置,以装置结构重量最小作为优化目标建立结构优化数学模型。使用粒子群算法(particle swarm optimization,PSO)对船用起重机防摆装置进行结构优化设计并对算法参数进行改进。经过优化后,结构总重量较优化前降低了28.64%。对优化过程和结果的分析表明,与结构优化中常用的遗传算法进行比较,PSO算法相比遗传算法可以快速收敛到全局最优解,求解精度高且算法运行稳定,优化后效果满足工程实际应用的需求。验证了PSO算法在船用起重机防摆装置结构优化设计中具有可行性和有效性。
Ship cranes operating at sea are exposed to high risks,primarily due to payload swing caused by wind and waves.Therefore,the installation of anti-swing devices on the crane is deemed necessary.However,it should be noted that the crane's working efficiency is affected by the increased load resulting from the installation of such devices.Thus,a lightweight design of the anti-swing device structure for ship cranes was required.In order to minimize the weight of the anti-swing device structure for ship cranes a mathematical model for structural optimization was establish.The structure of the anti-swing device for ship cranes was optimized using PSO(particle swarm optimization) algorithm,and improvements were made to the algorithm parameters.After optimization,a reduction of 28.64% in the total weight of the structure was achieved compared to before optimization.The analysis of the optimization process and results demonstrates that the PSO algorithm,in contrast to the commonly used genetic algorithm in structural optimization,exhibits rapid convergence to the global optimal solution,high solution accuracy,and stable algorithm operation.The optimized results meet the requirements of engineering application,affirming the feasibility and effectiveness of the PSO algorithm in the structural optimization design of anti-swing devices for ship cranes.
作者
孙泽文
王生海
安淋
韩广冬
陈海泉
SUN Ze-wen;WANG Sheng-hai;AN Lin;HAN Guang-dong;CHEN Hai-quan(College of Marine Engineering,Dalian Maritime University,Dalian 116026,China)
出处
《科学技术与工程》
北大核心
2024年第26期11441-11448,共8页
Science Technology and Engineering
基金
国家自然科学基金(52101396)
国家重点研发计划(2018YFC0309003)。
关键词
船用起重机
防摆装置
粒子群算法
结构优化
ship crane
anti-swing device
particle swarm optimization
structural optimization
