基于混合GSA-GA的起重机主梁优化设计

Optimization Design of Crane Main Beam Based on Hybrid GSA-GA

主梁作为双梁桥式起重机金属结构中的主要构件,它的重量在整个系统中占很大比例,过多的自重会增加企业的制造成本,在满足性能的情况下造成资源浪费。为了减轻主梁的重量,分析了主梁的重量与主梁横截面面积的关系,建立了起重机主梁的数学模型。利用遗传算法中的遗传算子来解决主梁优化中引力搜索算法容易陷入局部最优解,收敛速度慢的问题,提高了引力搜索算法的性能。优化结果表明,混合了引力搜索的遗传算法的收敛速度比标准的引力搜索算法优化率提高约3.93%左右。改进的算法使目标函数的横截面积从初始数据减少了约12.35%,并且优化分析结果符合设计标准。采用混合GSA-GA优化算法对起重机主梁在实际工程设计中具有重要的指导意义。

The main beam is the main component in the metal structure of the double girder bridge crane.Its weight accounts for a large proportion of the whole system.Excessive self-weight will increase the manufacturing cost of the enterprise and cause waste of resources in the case of satisfying performance.In order to reduce the weight of the main beam,the relationship between the weight of the main beam and the cross-sectional area of the main beam is analyzed,and the mathematical model of the main beam of the crane is established.The genetic operator in genetic algorithm is used to solve the problem that the gravity search algorithm in the main beam optimization is easy to fall into the local optimal solution and the convergence speed is slow,and the performance of the gravity search algorithm is improved.The optimization results show that the convergence rate of the genetic algorithm mixed with gravity search is about 3.93%higher than that of the standard gravity search algorithm.The improved algorithm reduces the cross-sectional area of the objective function by approximately 12.35%from the initial data and optimizes the analytical results to meet design criteria.The hybrid GSA-GA optimization algorithm has important guiding significance for the actual engineering design of the crane main beam.