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Digital Twin-Based Energy Modeling of Industrial Robots

  • Ke YanEmail author
  • Wenjun Xu
  • Bitao Yao
  • Zude Zhou
  • Duc Truong Pham
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 946)

Abstract

The rapid development of robotic technologies in recent years has made industrial robots (IRs) increasingly used in various manufacturing process, and the energy problem of IRs has been paid great attention because of their massive adoption and intensive energy consumption. Energy saving of IRs therefore is in great demand for environment protection and enterprise cost reduction, and the energy modeling of IRs is the basis to achieve such goal. In this paper, a novel energy modeling method of IRs based on digital twin is proposed and the system framework is established, which mainly includes the physics-based energy model of the physical IRs, the 3D virtual robot model used to visualize and simulate on the energy consumption of IRs, the digital twin data and the ontology-based unified digitized description model for mapping the virtual model to the corresponding physical energy model. Furthermore, the mapping relation between the physical data and ontology attributes is established to enable the interaction between the physical space and the cyber space of the whole system. Finally, the feasibility and effectiveness of the proposed method is validated by a case study, and the results show that the digital twin-based energy modeling method can be efficiently used for the simulation and prediction of the energy consumption of IRs.

Keywords

Energy modeling Industrial robots Digital twin Unified digitized description 

Notes

Acknowledgment

This research is supported by National Natural Science Foundation of China (Grant No. 51775399), the Fundamental Research Funds for the Central Universities (Grant No. 2018III034GX), and the Engineering and Physical Sciences Research Council (EPSRC), UK (Grant No. EP/N018524/1).

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Ke Yan
    • 1
    • 3
    Email author
  • Wenjun Xu
    • 1
    • 3
  • Bitao Yao
    • 2
    • 3
  • Zude Zhou
    • 1
  • Duc Truong Pham
    • 4
  1. 1.School of Information EngineeringWuhan University of TechnologyWuhanChina
  2. 2.School of Mechanical and Electronic EngineeringWuhan University of TechnologyWuhanChina
  3. 3.Hubei Key Laboratory of Broadband Wireless Communication and Sensor NetworksWuhan University of TechnologyWuhanChina
  4. 4.Department of Mechanical EngineeringUniversity of BirminghamBirminghamUK

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