基于数字孪生的工业机器人建模及监测方法

Modeling and monitoring methods for industrial robots based on digital twin

针对工业机器人数据不透明、监测存在死角等问题,通过对实体工业机器人分析和研究,构建数字孪生机器人监测系统。首先从几何、物理、逻辑3个维度完成虚拟机器人的建模;其次基于开放平台通信联合架构(open platform communications united architecture,OPC UA),实现机器人的数据采集和通信,设计用户显示界面,达到数据实时可视化的效果;最后,通过机器人仿真实验得出机器人末端执行器X、Y、Z坐标的相对位置误差分别为0.48%、0.32%、0.27%,通过数字孪生机器人监测同步实验验证机器人关节角度误差最大值为0.31°。实验结果表明:该方法能够实现数字孪生工业机器人的运动数据监测,减少工业机器人在生产过程中发生意外和故障的风险,为智能工业机器人的发展提供思路和方向。

In view of the issues such as opaque data and monitoring blind spots in industrial robots,study was conducted on physical industrial robots,leading to the development of a digital twin robot monitoring system.Firstly,modeling of virtual robots was accomplished from three dimensions:geometric,physical,and logical.Secondly,based on the open platform communications united architecture(OPC UA),data collection and communication for robots were implemented.User display interfaces were designed to achieve real-time visualization of data.Finally,through robot simulation experiments,the relative position errors of the robot end effector in the X,Y,and Z coordinates were determined to be 0.48%,0.32%,and 0.27%,respectively.The maximum error in joint angles of the robot,verified through synchronized experiments using a digital twin robot monitoring system,was found to be 0.31°.The experimental results demonstrate that the method can achieve motion data monitoring for digital twin industrial robots,reducing the risk of accidents and failures in the production process.It provides insights and directions for the development of intelligent industrial robots.