机械科学与技术2017，Vol.36Issue(4)：610-615,6.DOI:10.13433/j.cnki.1003-8728.2017.0419
应用多目标粒子群的驾驶室悬置参数联合仿真优化
Co-simulation of Cab Mounting System Optimization using MOPSO Algorithm
摘要
Abstract
In order to simplify development process and cut down the period of cab mounting system,the cosimulation method is used to solve the multi-objective optimization problem of a loader cab mounting system's vibration isolation performance whose virtual prototype is built in ADAMS,excitation signals come from experimental test and optimization algorithms are coded in MATLAB.The objective includes minimization of vibration total value and maximization decoupling ratio.The multi-objective particle swarm optimization (MOPSO) algorithm shows a better optimization performance than non-dominated sorting genetic (NSGA-Ⅱ) algorithm by covering a better Pareto frontier in this problem.Simulation results also confirm the feasibility and effectiveness of the approach in this study.关键词
驾驶室悬置/联合仿真/隔振/MOPSO/能量解耦Key words
cab mounting system/co-simulation/MATLAB/vibration isolation/particle swarm optimization (PSO)/multi-objective optimization分类
机械制造引用本文复制引用
姚昱儒,毕凤荣,景亚兵,齐彬,田赛龙,田从丰..应用多目标粒子群的驾驶室悬置参数联合仿真优化[J].机械科学与技术,2017,36(4):610-615,6.基金项目
国家科技支撑计划项目(2015BAF07B04)资助 （2015BAF07B04）
