一种双工位旋转式上甑机器人设计
Design of dual-station rotary steamer-filling robot
徐进友 1邢恩宏 1张磊 1李彬 1董磊 1岳之斌1
作者信息
- 1. 天津理工大学天津市先进机电系统设计与智能控制重点实验室,天津 300384;天津理工大学机电工程国家级实验教学示范中心,天津 300384
- 折叠
摘要
上甑是白酒酿造的关键工序,为解决传统白酒酿造上甑过程中劳动强度大、酒质及产酒率不稳定等问题,依据上甑过程的工艺要求及标准,设计了一种双工位旋转式上甑机器人.该机器人采用3个旋转关节和撒料器实现上甑铺料的平面定位,平移关节实现撒料高度的控制.对机器人的正、逆运动学进行了解析求解和验证,采用Monte-Carlo法模拟了上甑机器人的工作空间;基于有限元方法对关键部件进行了强度及模态分析.通过物理试验样机的现场测试,表明样机上甑相比于人工上甑的出酒率提高了 10％左右,尾酒度数降低了 5°～7°,有效提高了上甑的效率,验证了设计的可行性.模拟仿真与样机测试结果表明:文中上甑机器人的结构及功能满足设计要求,可为上甑机器人的设计及后续性能优化提供参考.
Abstract
Steamer-filling is a key process in Chinese liquor brewing.In this article,in order to solve the problems of high labor intensity,unstable liquor quality,and low liquor yield in the process of traditional Chinese liquor brewing,a dual-station ro-tary steamer-filling robot is designed according to the technological requirements and standards of the steamer-filling process.This robot is equipped with three rotary joints and a spreader,so as to position the plane of spreading materials,while the translation joint controls the height of spreading materials.Efforts are made to explore and verify the steamer-filling robot's forward and re-verse kinematics,and its workspace is simulated by means of the Monte-Carlo method.The finite-element method is used to ana-lyze the strength and mode of key components.The physical prototype is subject to the field test;it is found that the yield rate of the prototype is about 10％higher than that of manual steamer-filling,and the alcohol content of the tail wine reduces by 5 to 7 degrees,thus effectively improving the efficiency in steamer-filling and verifying the feasibility of the design.The results obtained from both the simulation and the prototype test show that the robot's structure and function meet the design requirements.This study provides reference for the design and subsequent optimization of the steamer-filling robot.
关键词
上甑机器人/结构设计/运动学分析/工作空间模拟/有限元分析Key words
steamer-filling robot/structural design/kinematics analysis/workspace simulation/finite-element analysis引用本文复制引用
出版年
2024
NETL
NSTL
万方数据