计算机集成制造系统 ›› 2024, Vol. 30 ›› Issue (3): 811-824.DOI: 10.13196/j.cims.2023.0240

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基于数字孪生的盾构机换刀机器人监控系统

殷光淼1,朱国力1+,谢哲1,王一新2   

  1. 1.华中科技大学机械科学与工程学院
    2.中铁工程装备集团有限公司
  • 出版日期:2024-03-31 发布日期:2024-04-02
  • 基金资助:
    国家重点研发计划资助项目(2018YFB1306703)。

Monitoring system for shield machine tool changing  robot based on digital twin

YIN Guangmiao1,ZHU Guoli1+,XIE Zhe1,WANG Yixin2   

  1. 1.School of Mechanical Science and Engineering,Huazhong University of Science and Technology
    2.China Railway Engineering Equipment Group Co.,Ltd.
  • Online:2024-03-31 Published:2024-04-02
  • Supported by:
    Project supported by the National Key Research and Development Program,China(No.2018YFB1306703).

摘要: 为解决当前盾构换刀机器人缺乏有效监控方式的问题,设计了基于数字孪生的盾构机换刀机器人监控系统。系统通过Unity3D仿真平台构建孪生模型,利用机器人运动学模型在实时数据驱动下映射物理实体的运动状态,实现换刀机器人可视化监控,并利用虚拟现实技术提高系统沉浸性和可交互性。同时,针对有限元仿真软件获取力学数据的方式耗时较长、难以满足监控系统实时性要求的问题,构建了基于BP神经网络的换刀机器人力学数据监测模型,可快速获取末端执行器的应力和形变数据以保证系统安全性。最后,开发了盾构机换刀机器人数字孪生监控系统原型样机,验证了所提监控系统的有效性和可行性。

关键词: 数字孪生, 盾构换刀机器人, BP神经网络, 机器人监控系统

Abstract: To address the lack of effective monitoring methods for shield tunneling tool changing robots,a digital twin based monitoring system for shield tunneling tool changing robots was designed.The twin model was constructed through Unity3D simulation platform and the movement state of physical entity driven by real-time data with robot kinematics model was mapped to realize visual monitoring of tool changing robot,and the virtual reality technology was used to improve system immersion and interactivity.At the same time,in response to the problem of time-consuming finite element simulation software to obtain mechanical data and difficulty in meeting the real-time requirements of the monitoring system,a mechanical data monitoring model for the tool changing robot was constructed based on BP neural network,which could quickly obtain stress and deformation data of the end-effector to ensure system safety.A prototype of the digital twin monitoring system for the shield tunneling machine tool changing robot was developed to verify the effectiveness and feasibility of the proposed monitoring system.

Key words: digital twin, shield cutter changing robot, BP neural network, robot monitoring system

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