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浙江大学学报(工学版)  2024, Vol. 58 Issue (7): 1479-1487    DOI: 10.3785/j.issn.1008-973X.2024.07.017
机械工程、能源工程     
抗阻式颈部康复机器人系统设计
黄松林1,2(),郑秀娟1,2,谭笑月1,2,胡兴3,涂海燕1,2,*(),李康4
1. 四川大学 电气工程学院,四川 成都 610065
2. 四川大学 信息与自动化技术四川省高校重点实验室,四川 成都 610065
3. 四川大学 机械工程学院,四川 成都 610065
4. 四川大学 华西医院生物医学大数据中心,四川 成都 610041
Design of resistance neck rehabilitation robot system
Songlin HUANG1,2(),Xiujuan ZHENG1,2,Xiaoyue TAN1,2,Xing HU3,Haiyan TU1,2,*(),Kang LI4
1. College of Electrical Engineering, Sichuan University, Chengdu 610065, China
2. Key Laboratory of Information and Automation Technology of Sichuan Province, Sichuan University, Chengdu 610065, China
3. School of Mechanical Engineering, Sichuan University, Chengdu 610065, China
4. West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu 610041, China
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摘要:

已有颈部康复设备负载精度差且负载调节时间长,为此基于抗阻康复训练治疗理论设计新的颈部康复机器人系统. 设计机械结构,使电机输出的拉力转换成颈部的抗阻负载. 将控制系统分为控制模块与算法模块,提高系统的流畅性和稳定性. 利用磁场定向控制算法实现电机力矩的精准控制,为颈部康复训练提供稳定可控的拉力. 设置拉力传感器和姿态陀螺仪传感器,防止使用者头颈部姿态错误或未知事故. 统计10名受试者使用所设计系统进行颈部康复训练的评估参数,并对统计结果进行分析. 仿真测试显示,磁场定向控制算法能够提高负载精度并缩短调节时间;负载测试与仿真测试结果的一致性验证了控制方案的可行性. 系统性能测试表明,所设计的颈部康复机器人的拉力控制误差不超过0.59 N,响应速度为0.53 s,达到临床使用标准.

关键词: 永磁同步电机磁场定向控制抗阻训练传感器康复机器人    
Abstract:

A new neck rehabilitation robot system was designed based on the theory of resistance rehabilitation training, as the existing rehabilitation devices with poor load accuracy and long load adjustment time. The newly designed mechanical structure converted the motor output tension into a neck resistance load, and the control system was divided into a control module and an algorithmic module to improve the system’s fluidity and stability. The magnetic field-oriented control algorithm was used to achieve precise control of the motor torque, providing a stable and controllable tension for neck rehabilitation training. Force sensors and posture gyroscopes were set up to prevent users form incorrect head and neck postures or unforeseen accidents. Assessment parameters of 10 subjects using the system for rehabilitation training were counted and the statistical results were analyzed. Simulation tests show that the magnetic field-oriented control algorithm improves the load accuracy and reduces the adjustment time. The consistency between the load testing results and the simulation results confirms the feasibility of the control scheme. The system performance tests indicated that the neck rehabilitation robot had a tension control error within 0.59 N and a response speed of 0.53 s, which meeting the standard for clinical use.

Key words: permanent magnet synchronous motor    field oriented control    resistance training    sensor    rehabilitation robot
收稿日期: 2023-10-31 出版日期: 2024-07-01
CLC:  TP 242  
基金资助: 国家自然科学基金重大研究计划集成项目(92248304).
通讯作者: 涂海燕     E-mail: hslhuangsonglin@126.com;haiyantu@163.com
作者简介: 黄松林(1998—),男,硕士生,从事康复机器人研究. orcid.org/0009-0009-4089-1702. E-mail:hslhuangsonglin@126.com
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引用本文:

黄松林,郑秀娟,谭笑月,胡兴,涂海燕,李康. 抗阻式颈部康复机器人系统设计[J]. 浙江大学学报(工学版), 2024, 58(7): 1479-1487.

Songlin HUANG,Xiujuan ZHENG,Xiaoyue TAN,Xing HU,Haiyan TU,Kang LI. Design of resistance neck rehabilitation robot system. Journal of ZheJiang University (Engineering Science), 2024, 58(7): 1479-1487.

链接本文:

https://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2024.07.017        https://www.zjujournals.com/eng/CN/Y2024/V58/I7/1479

图 1  颈椎关节运动示意图
图 2  颈部康复机器人系统的机械结构图
图 3  控制系统总体框架
图 4  双环磁场定向控制算法的框架
图 5  控制系统的流程图
图 6  电流环仿真的原理图
图 7  颈部康复机器人系统原型
图 8  转矩电流的仿真曲线
图 9  转矩电流的实测曲线
图 10  理论拉力与实测拉力关系
设备$ {e}_{{\mathrm{ss}}} $/NTu/s负载调节方式
文献[21]0.605.50电机转动调节
文献[25]0.505.00电机转动调节
文献[15]1.003.80电机转动调节
本研究0.590.53PI电流调节
表 1  不同颈部康复设备的性能和参数对比结果
图 11  2种拉力下侧屈运动的角曲线
ID性别侧屈旋转屈伸
$ {F}_{\mathrm{e}\mathrm{v}\mathrm{a}} $/N$ {\theta }_{\mathrm{m}\mathrm{a}\mathrm{x}} $/(°)$ {\theta }_{\mathrm{a}\mathrm{v}\mathrm{r}} $/(°)$ {\theta }_{\mathrm{s}\mathrm{t}\mathrm{d}} $/(°)$ {F}_{\mathrm{e}\mathrm{v}\mathrm{a}} $/N$ {\theta }_{\mathrm{m}\mathrm{a}\mathrm{x}} $/(°)$ {\theta }_{\mathrm{a}\mathrm{v}\mathrm{r}} $/(°)$ {\theta }_{\mathrm{s}\mathrm{t}\mathrm{d}} $/(°)$ {F}_{\mathrm{e}\mathrm{v}\mathrm{a}} $/N$ {\theta }_{\mathrm{m}\mathrm{a}\mathrm{x}} $/(°)$ {\theta }_{\mathrm{a}\mathrm{v}\mathrm{r}} $/(°)$ {\theta }_{\mathrm{s}\mathrm{t}\mathrm{d}} $/(°)
12636.0431.0023.0923373.9967.8082.2322225.0222.2321.749
22340.7833.5434.5032768.5365.7220.9573141.7638.4512.512
33528.6123.9143.0654262.5759.8452.6743337.5434.5252.879
41833.4230.6951.9091872.5370.5331.3412333.3532.4840.748
53026.3022.9621.4143766.5464.2571.8963243.5439.5884.547
62331.2028.5431.6272056.5452.3642.5492739.5437.0241.243
71536.0933.5182.3301878.8973.5962.0351540.2538.5141.245
82825.8222.7374.4002563.1560.8751.1842536.4734.1240.974
92229.5220.9685.1163074.5170.9742.8492034.8432.1451.545
101532.5330.5501.2172068.5461.6894.9481837.9834.5223.074
表 2  10位测试者在3种训练下的数据统计
图 12  测试者1在3种训练下的角度曲线
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