| 引用本文： |
-
刘欢,高学山,吕鹏飞,石永杰,吕佳乐,郝亮超,牛军道,赵鹏,车红娟.基于NSGA-Ⅱ算法的康复机器人减重单元的优化设计[J].广西科学院学报,2021,37(4):354-360,371. [点击复制]
- LIU Huan,GAO Xueshan,LÜPengfei,SHI Yongjie,LÜJiale,HAO Liangchao,NIU Jundao,ZHAO Peng,CHE Hongjuan.Optimal Design of Weight Reduction Unit for Rehabilitation Robot Based on NSGA-Ⅱ Algorithm[J].Journal of Guangxi Academy of Sciences,2021,37(4):354-360,371. [点击复制]
|
|
| |
|
|
| 本文已被：浏览 230次 下载 300次 |
码上扫一扫！ |
| 基于NSGA-Ⅱ算法的康复机器人减重单元的优化设计 |
|
刘欢1, 高学山1,2, 吕鹏飞1, 石永杰3, 吕佳乐3, 郝亮超1, 牛军道1, 赵鹏3, 车红娟3
|
|
|
| (1.广西科技大学机械与交通工程学院, 广西柳州 545616;2.北京理工大学机电学院, 北京 100081;3.广西科技大学电气与信息工程学院, 广西柳州 545006) |
|
| 摘要: |
| 下肢运动障碍患者康复训练治疗手段之一是减重步行训练，移动式下肢康复训练机器人既可以跟随保护患者，又可以对其进行减重步态训练。针对机器人核心部件之一的减重单元，本研究提出一种启发式设计算法，可以避免机构本身复杂因素所带来的结构优化困难，获得多目标的优化解集。通过带精英策略的非支配排序遗传算法（NSGA-Ⅱ）在多目标优化问题中确定减重单元的设计参数。实验验证表明，减重单元体积减小明显，使结构更加紧凑。 |
| 关键词: 多目标优化 机械结构 优化设计 医工结合 NSGA-Ⅱ |
| DOI：10.13657/j.cnki.gxkxyxb.20211216.007 |
| 投稿时间：2020-06-20 |
| 基金项目:国家重点研发计划“主动健康和老龄化科技应对”专项和“中国老年失能预防与干预管理网络及技术研究”项目（2020YFC2008503）资助。 |
|
| Optimal Design of Weight Reduction Unit for Rehabilitation Robot Based on NSGA-Ⅱ Algorithm |
|
LIU Huan1, GAO Xueshan1,2, LÜPengfei1, SHI Yongjie3, LÜJiale3, HAO Liangchao1, NIU Jundao1, ZHAO Peng3, CHE Hongjuan3
|
| (1.School of Mechanical and Transportation Engineering, Guangxi University of Science and Technology, Liuzhou, Guangxi, 545616, China;2.School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, 100081, China;3.School of Electrical and Information Engineering, Guangxi University of Science and Technology, Liuzhou, Guangxi, 545006, China) |
| Abstract: |
| One of the rehabilitation training treatments for patients with lower limb movement disorders is weight reduction walking training.A mobile lower limb rehabilitation training robot can not only follow and protect patients,but also realize weight reduction gait training for them.For the weight reduction unit,one of the core components of the robot,a heuristic design algorithm is proposed in this study,which can avoid the structural optimization difficulties caused by the complex factors of the mechanism itself and obtain the multi-objective optimization solution set.The design parameters of the weight reduction unit mechanism are determined in the multi-objective optimization problem by the non-dominated ranking genetic algorithm with elite strategy (NSGA-Ⅱ).The experimental verification shows that the volume of the weight reduction unit is reduced significantly,resulting in a more compact structure. |
| Key words: multi-objective optimization mechanical structure optimal design medical-industrial integration NSGA-Ⅱ |
|
|
|
|
|
