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作 者:焦培俊 姜晨[1] 姜臻禹 周勇宇 JIAO Peijun;JIANG Chen;JIANG Zhenyu;ZHOU Yongyu(School of Mechanical Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)
出 处:《轻工机械》2024年第3期37-45,53,共10页Light Industry Machinery
基 金:国家自然科学基金项目(51475310)。
摘 要:为了提高机器人的加工质量,针对末端执行装置动刚度不足的问题,课题组开展了机器人气囊抛光工具结构动力学优化研究。分别进行了有限元模态分析和实验模态分析,对比验证仿真结果的准确性,找出抛光工具易发生振动的薄弱结构;基于模态分析对薄弱结构进行谐波激励得到工况下的振动响应加速度;建立动力学近似模型,以提高基频、降低质量及加速度响应为目标,分别采用非支配排序遗传算法NSGA-Ⅲ(non-dominated sorting genetic algorithm-Ⅲ)和多目标粒子群算法(multi-objective particle swarm optimization, MOPSO)对薄弱结构进行多目标优化,获得最优动力响应的参数组合。结果表明:NSGA-Ⅲ具有更好的优化效果,基频提高了21.62%;4个薄弱部位的最大加速度响应分别下降了73.78%,69.06%,56.15%和28.28%;质量减少了3.32%。该方法有效提高了抛光工具的动态特性。In order to improve the machining quality of the robot,aiming at the problem of the insufficient dynamic stiffness of the end-effector,the optimization of the structure dynamics of the robot airbag polishing tool was carried out.The finite element simulation modal analysis and experimental modal analysis were conducted independently to validate the simulation results,finding out the vulnerable structure of the polishing tool prone to vibration.Using modal analysis,the vibration response acceleration of the vulnerable structure was determined through harmonic excitation.A dynamic approximate model was established,and with the objectives of improving fundamental frequency,reducing mass and acceleration response,multi-objective optimization of vulnerable structure was carried out using NSGA-Ⅲ(non-dominated sorting genetic algorithm-Ⅲ)and MOPSO(multi-objective particle swarm optimization)respectively,to obtain the optimal dynamic response parameter combinations.The results show that NSGA-Ⅲhas a better optimization effect,the fundamental frequency is increased by 21.62%,the maximum acceleration response of the four vulnerable structures is reduced by 73.78%,69.06%,56.15%and 28.28%,respectively,and the mass is reduced by 3.32%,which effectively improves the dynamic characteristics of polishing tool.
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