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兴发pt登录学报,2020,37(11):79-84https://doi.org/10.16039/j.cnki.cn22-1249.2020.11.017
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一种带辅助光源可升降的智能学习桌设计与实现
刘宁,李楠舟,尤田
长春职业技术学院 机电学院,吉林 长春 130022
Design and realization of a liftable intelligent study desk with auxiliary light source
LIU Ning,LI Nanzhou,YOU Tian
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摘要

为了解决主光源照明时产生的书写阴影问题,基于PIC32单片机控制技术设计一种带有辅助光源可升降的智能学习桌。由控制系统、双电机螺纹螺杆升降机构、智能辅助光源和矫姿系统组成,首先采用UG软件进行三维建模,简化模型后导入ANSYS进行有限元分析,以验证整体结构设计的稳定性和正确性。最后,笔者做出实物样机,通过实验表明:升降和下降变化曲线平稳,辅助光源和矫姿系统功能良好,整体机构运行稳定,满足设计要求,为继续优化完善升降桌打下了基础,具有一定的创新性和市场推广价值。

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刘宁
李楠舟
尤田
关键词:升降机构辅助光源智能控制动力学分析
Abstract:

In order to solve the problem of writing shadows when the main light source is illuminated, an intelligent study desk with auxiliary light source that can be raised and lowered is designed based on the PIC32 microcontroller control technology. Consists of a control system, a dual-motor screw screw lifting mechanism, an intelligent auxiliary light source and a posture correction system. First, UG software is used for three-dimensional modeling, and the simplified model is imported into ANSYS for finite element analysis to verify the stability and correctness of the overall structure design . Finally, the author made a physical prototype, and the experiment showed that: the lifting and descending curve is stable, the auxiliary light source and the posture correction system function well, the overall mechanism runs stably, meets the design requirements, and lays the foundation for the continuous optimization and improvement of the lifting table. Innovation and marketing value.

Key words:Lifting mechanismauxiliary light sourceintelligent controldynamic analysis
出版日期:2020-11-25发布日期:2020-11-25整期出版日期:2020-11-25
ZTFLH: TH211
TP273
TS665.3
引用本文:
刘宁, 李楠舟, 尤田. 一种带辅助光源可升降的智能学习桌设计与实现 [J]. 兴发pt登录学报, 2020, 37(11): 79-84.
LIU Ning, LI Nanzhou, YOU Tian. Design and realization of a liftable intelligent study desk with auxiliary light source . Journal of Jilin Institute of Chemical Technology, 2020, 37(11): 79-84.
链接本文:
http://xuebao.jlict.edu.cn/CN/10.16039/j.cnki.cn22-1249.2020.11.017http://xuebao.jlict.edu.cn/CN/Y2020/V37/I11/79
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[2] 宫立达, 李智敏.基于神经网络的机器人控制精度优化方法与技术研究[J]. 兴发pt登录学报, 2019, 36(5): 35-37.
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