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数据驱动的焊接机器人数字孪生系统研究

Research on the Digital Twin System of Welding Robots Driven by Data.

作者信息

Wang Saishuang, Jiao Yufeng, Wang Lijun, Wang Wenjie, Ma Xiao, Xu Qiang, Lu Zhongyu

机构信息

College of Electrical Engineeringy, North China University of Water Resources and Electric Power, Zhengzhou 450045, China.

Management Center of Xiaolangdi Water Conservancy Hub of Ministry of Water Resources, Jiyuan 459000, China.

出版信息

Sensors (Basel). 2025 Jun 22;25(13):3889. doi: 10.3390/s25133889.

Abstract

With the rise of digital twin technology, the application of digital twin technology to industrial automation provides a new direction for the digital transformation of the global smart manufacturing industry. In order to further improve production efficiency, as well as realize enterprise digital empowerment, this paper takes a welding robot arm as the research object and constructs a welding robot arm digital twin system. Using three-dimensional modeling technology and model rendering, the welding robot arm digital twin simulation environment was built. Parent-child hierarchy and particle effects were used to truly restore the movement characteristics of the robot arm and the welding effect, with the help of TCP communication and Bluetooth communication to realize data transmission between the virtual segment and the physical end. A variety of UI components were used to design the human-machine interaction interface of the digital twin system, ultimately realizing the data-driven digital twin system. Finally, according to the digital twin maturity model constructed by Prof. Tao Fei's team, the system was scored using five dimensions and 19 evaluation factors. After testing the system, we found that the combination of digital twin technology and automation is feasible and achieves the expected results.

摘要

随着数字孪生技术的兴起,数字孪生技术在工业自动化中的应用为全球智能制造产业的数字化转型提供了新方向。为进一步提高生产效率并实现企业数字化赋能,本文以焊接机器人手臂为研究对象,构建了焊接机器人手臂数字孪生系统。利用三维建模技术和模型渲染,搭建了焊接机器人手臂数字孪生仿真环境。采用父子层级结构和粒子效果真实还原机器人手臂的运动特性及焊接效果,借助TCP通信和蓝牙通信实现虚拟端与物理端之间的数据传输。运用多种UI组件设计数字孪生系统的人机交互界面,最终实现数据驱动的数字孪生系统。最后,依据陶飞教授团队构建的数字孪生成熟度模型,从五个维度、19个评估因素对系统进行评分。经过系统测试,发现数字孪生技术与自动化的结合是可行的,且达到了预期效果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58c0/12251800/ad8dffb44f39/sensors-25-03889-g001.jpg

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