基于包含遗传算法的粒子群算法的换轨车结构优化研究  

Structure optimization of rail car based on particle swarm optimization including genetic algorithm

作　　者：吴元科[1] 刘放[1] 刘超群[1] 吴灿龙[1] 

机构地区：[1]西南交通大学机械工程学院,四川成都610031

出　　处：《机械设计》2016年第6期25-29,共5页Journal of Machine Design

基　　金：国家自然科学基金资助项目(51175442)

摘　　要：总结了换轨车换轨状态的6种线路特征。利用ANSYS计算了换轨车换轨工作载荷;建立了伸缩式换轨车换轨伸缩臂的理论模型,对伸缩臂截面惯性矩进行了分析。将粒子群算法和遗传算法结合在一起,利用MATLAB软件进行编码。以伸缩臂的质量为目标函数,对伸缩臂六边形截面的5个主要参数进行优化。优化结果表明:伸缩臂质量降低了27.7%,伸缩臂质心位置下降,同时伸缩臂配重也会减小,整机质心下降,提高了整机的稳定性。Six rail line features of rail changing car state were summarized. The rail changing working load of rail car was calculated using ANSYS. The theoretical model of telescopic arm of track replacement car was established. The inertia section moment of telescopic arm was analyzed. The particle swarm optimization and genetic algorithm were combined together to coding using MATLAB software. The quality of telescopic arm was set as the objective function. The 5 main parameters of hexagonsection in the telescopic arm were optimized. The optimization results showed that, the telescopic arm quality had reduced by27.7%. The centroid position of telescopic arm had fall down and counterweight of telescopic arm would be reduced. The whole machine centroid declined and the stability of the machine improved.

关 键 词：线路特征 理论模型 粒子群算法 遗传算法 参数优化 

分 类 号：TH213.6[机械工程—机械制造及自动化]