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时间最优链斗式连续卸船机寻舱轨迹规划研究

Time Optimal Trajectory Planning of Searching Hatch for Chain-Bucket Continuous Ship Unloader
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摘要 为提高链斗式连续卸船机卸船效率,实现智能化取料作业,提出了一种基于麻雀搜索算法(SSA)优化取料装置寻舱轨迹时间最优的方法。采用3-3-5-3-3分段多项式插值,以连续卸船机各关节速度及加速度作为约束条件,采用麻雀搜索算法对各段轨迹进行优化。将麻雀搜索算法的优化结果与粒子群算法进行对比,结果表明麻雀算法优化结果比粒子群算法优化结果时间更少,大大提高连续卸船机的整体卸船效率;同时,麻雀算法具有较好的搜索能力,收敛能力强,在进行时间最优轨迹规划上效果较好。 In order to improve the unloading efficiency of the chain-bucket continuous ship unloader and realize the intelligent operation of the ship unloader,a method based on Sparrow Search Algorithm(SSA)is proposed to optimize the track time of searching hatch of the chain bucket continuous ship unloader.The 3-3-5-3-3 piecewise polynomial interpolation is adopted,and the trajectory of each segment is optimized by sparrow algorithm with the velocity and acceleration of each joint of the ship un⁃loader as the constraint conditions.The comparison between the sparrow algorithm and the particle swarm optimization algorithm shows that the sparrow algorithm takes less time than the particle swarm optimization algorithm,which greatly improves the un⁃loading efficiency of the continuous ship unloader.At the same time,the sparrow algorithm has better global search and local search ability,strong convergence ability,and good effect in time optimal trajectory planning.
作者 刘雪莲 王欣 姜鑫 吴庆贺 LIU Xue-lian;WANG Xin;JIANG Xin;WU Qing-he(School of Mechanical Engineering,Dalian University of Technology,Liaoning Dalian 116023,China;Dalian Huarui Heavy Industry Croup Co.,Ltd.,Liaoning Dalian 116013,China)
出处 《机械设计与制造》 北大核心 2024年第9期16-21,共6页 Machinery Design & Manufacture
基金 大连市科技重大专项(2019ZD15GX006)。
关键词 连续卸船机 麻雀搜索算法 粒子群算法 轨迹规划 仿真 Continuous Ship Unloader Sparrow Search Algorithm Particle Swarm Optimization Trajectory Planning Simulation
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