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作 者:罗帆 罗利敏 励晨 马剑强[1] LUO Fan;LUO Limin;LI Chen;MA Jianqiang(Faculty of Mechanical Engineering&Mechanics,Ningbo University,Ningbo Zhejiang 315211,China;Ningbo Zhongda Leader Intelligent Transmission Co.,Ltd.,Ningbo Zhejiang 315301,China)
机构地区:[1]宁波大学机械工程与力学学院,浙江宁波315211 [2]宁波中大力德智能传动股份有限公司,浙江宁波315301
出 处:《机械设计与研究》2024年第6期78-83,共6页Machine Design And Research
基 金:宁波市重大科技攻关项目(2021Z068);浙江省基础公益研究计划(LGG22E050002);浙江省省属高校基本科研业务费专项基金资助项目(SJLY2020002)
摘 要:作为工业机器人核心部件的RV减速器,面临着超负荷、高速运行等实际工况,容易出现承载能力不足的问题。在分析RV减速器传动原理和摆线针轮副受力的基础上,面向提高承载能力,选取结构参数偏心距和针齿半径为优化变量,建立了RV减速器多目标优化数学模型。采用非支配排序遗传算法对模型进行求解,优化得到帕累托最优解,利用模糊集合理论选出最优方案。以某公司生产的150BX型RV减速器为例,优化求解,加工出优化后的RV减速器样机,并进行了承载能力及传动效率测试。试验结果表明:经过优化后的RV减速器在额定负载下承载能力显著提升,且重载情况表现更加出色。验证了该多目标优化数学模型具有可行性,能有效提升承载能力,为RV减速器实际工程优化设计提供了有益参考。As the core component of industrial robots,the RV reducer is faced with practical working conditions such as overload and high-speed operation,and it is easy to encounter the problem of insufficient load capacity.Based on the analysis of the transmission principle of RV reducers and the stress of the cycloidal pin-wheel pair,a multi-objective optimization mathematical model of RV reducers is established by selecting structural parameters eccentricity and pin tooth radius as optimization variables to improve the load capacity.NSGA-Ⅱalgorithm is used to solve the model,and the Pareto optimal solution is obtained by optimization,and the optimal scheme is selected by fuzzy set theory.Taking the 150BX RV reducer as an example,the optimized RV reducer prototype is manufactured,and the load capacity and transmission efficiency are tested.The test results show that the optimized RV reducer has significantly improved the bearing capacity under rated load,and the performance under heavy load is even better.It is verified that the multi-objective optimization mathematical model is feasible and can effectively improve the load capacity,which provides a useful reference for the practical engineering optimization design of RV reducers.
关 键 词:RV减速器 摆线针轮副 承载能力 多目标优化 NSGA-Ⅱ算法
分 类 号:TH132.46[机械工程—机械制造及自动化]
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