摘要
为解决救灾工作中颠簸路况对救灾人员体力消耗的问题,设计一款3DOF颠簸训练模拟器,由于本设计用于车载救灾颠簸模拟器,存在限高的问题,所以平台的安装高度极其有限。文章基于Stewart运动平台和空间运动机构的相关理论,设计了一种带防扭臂的重载荷3自由度并联平台(3-UPU/RRU),其中UPU为驱动支链,两条RRU为恰约束从动支链,运用螺旋理论分析其约束情况,表明该机构的运动合理性。利用加速遗传算法和工程实际安装空间,得到平台的尺寸的最优解。利用ADAMS软件建立虚拟机,通过驱动件与动平台末端运动曲线,得到驱动件的逆解,最终得到平台运动情况。并且将此成果用于某款抗颠簸训练模拟器中,运行良好。此研究成果可以在安装空间较为狭窄的情况下,作为工程师设计并联平台的参考。
In order to solve the problem of physical exertion of disaster relief personnel on bumpy road conditions in disaster relief work,a 3DOF bumpy training simulator is designed,and the mounting height of the platform is extremely limited due to the problem of height limitation as this design is used for the vehicle-mounted disaster relief bumpy simulator.Based on the theory of Stewart motion platform and space motion mechanism,the article designs a heavy load 3-degree-of-freedom parallel platform(3-UPU/RRU)with anti-torsion arm,in which UPU is the driving pivot chain and the two RRUs are the cha-constrained follower pivot chains,and analyzes the constraints by using the helix theory,which demonstrates the reasonableness of the motion of the mechanism.Using the accelerated genetic algorithm and the actual installation space of the project,the optimal solution of the size of the platform is obtained.ADAMS software is utilized to establish a virtual machine,and the inverse solution of the driving parts is obtained through the motion curve of the driving parts and the end of the moving platform,and the platform motion is finally obtained.And this result is used in a certain anti-bump training simulator,which runs well.This research result can be used as a reference for engineers to design the parallel platform in the case of narrower installation space.
作者
王成刚
张喻阳
杨旺
高泽宇
WANG Chenggang;ZHANG Yuyang;YANG wang;GAO Zeyu(Power Engineering,Wuhan Institute of Technology,Wuhan 430205,China)
出处
《自动化与仪器仪表》
2024年第3期251-254,259,共5页
Automation & Instrumentation
关键词
三自由度
模拟平台
机构设计
螺旋算法
ADAMS仿真
遗传算法
优化设计
机械制造
three degrees of freedom
simulation platform
mechanism design
helix algorithm
adams simulation
genetic algorithm
optimization design
mechanical engineering