基于多目标粒子群算法的平衡式变幅臂架系统优化设计

Optimization Design of Balanced Luffing Boom System Based on Multi-Objective Particle Swarm Optimization

平衡式变幅广泛用于港口装卸用门座式起重机的工作性变幅机构,其变幅臂架系统为单自由度系统,设计变量多,受力较复杂,约束条件多。因此,针对其特点,以平衡式臂架系统自重最轻、变幅功率最小作为优化目标,以实际工况的工作性能要求作为约束条件,建立臂架系统及活动系统的优化模型,采用多目标粒子群算法并通过Python语言编程进行优化求解,以获得最优的几何尺寸参数。通过ADAMS软件对优化结果进行仿真验证,有效地缩短了设计周期,提高了设计水平。

Balanced luffing is widely used in the working luffing mechanism of portal cranes for port loading and unloading.Its luffing arm system is a single-degree-of-freedom system,with many design variables,more complicated forces,and more constraints.Therefore,according to its characteristics,with the lightest weight and the smallest amplitude power of the balanced boom system as the optimization objectives,and the performance requirements of the actual working conditions as the constraints,the optimization model of the boom system and the active system is established,and the multi-objective is adopted.The particle swarm algorithm is optimized and solved by programming in Python language to obtain the optimal geometric size parameters.The simulation results of the optimization results are verified by ADAMS software,which effectively shortens the design cycle and improves the design level.