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A Practical Energy Modeling Method for Industrial Robots in Manufacturing

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Challenges and Opportunity with Big Data (Monterey Workshop 2016)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10228))

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Abstract

Industrial robots (IRs) are widely used in modern manufacturing systems, and energy problem of IRs is paid more attention to meet requirements of environment protection. Therefore, it is necessary to investigate the approaches to optimize the energy consumption of IRs, and the energy consumption model is the basis for enabling such approaches. Usually, energy consumption modeling for IRs is based on dynamic parameters identification. Meanwhile, the physical parameters, e.g. angle, velocity, acceleration, torque, etc. are all the necessary data of parameter identification. However, since the parts of IRs are not easy to be disassembled and the sensor modules can not be installed easily inside IRs, it is difficult to obtain all such physical parameters through sensing method, in particular the torque data. In this context, a practical energy modeling method by measuring total power for IRs is proposed. This method avoids the problem of directly measuring relevant parameters inside IRs, and the parameter identification process is gradually carried out by several excitation experiments. The experimental results show that the proposed energy modeling method can be used to predict the energy consumption of the process used in robot movement in manufacturing processes, and it can also efficiently support the analysis of the energy consumption characteristics of IRs.

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Acknowledgements

This research is supported by National Natural Science Foundation of China (Grant No. 51305319), the International Science & and Technology Cooperation Program of China (Grant No. 2015DFA70340), and Engineering and Physical Sciences Research Council (EPSRC), UK (Grant No. EP/N018524/1).

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Authors and Affiliations

  1. School of Information Engineering, Wuhan University of Technology, Wuhan, 430070, China

    Wenjun Xu, Huan Liu, Jiayi Liu & Zude Zhou

  2. Key Laboratory of Fiber Optic Sensing Technology and Information Processing, Ministry of Education, Wuhan, 430070, China

    Wenjun Xu, Huan Liu, Jiayi Liu & Zude Zhou

  3. Department of Mechanical Engineering, School of Engineering, University of Birmingham, Birmingham, B15 2TT, UK

    Duc Truong Pham

Authors
  1. Wenjun Xu
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  2. Huan Liu
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  3. Jiayi Liu
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  4. Zude Zhou
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  5. Duc Truong Pham
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Corresponding author

Correspondence to Wenjun Xu .

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Editors and Affiliations

  1. Beihang University, Beijing, China

    Lin Zhang

  2. Beihang University, Beijing, China

    Lei Ren

  3. Université Pierre and Marie Curie, Paris, France

    Fabrice Kordon

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Xu, W., Liu, H., Liu, J., Zhou, Z., Pham, D.T. (2017). A Practical Energy Modeling Method for Industrial Robots in Manufacturing. In: Zhang, L., Ren, L., Kordon, F. (eds) Challenges and Opportunity with Big Data. Monterey Workshop 2016. Lecture Notes in Computer Science(), vol 10228. Springer, Cham. https://doi.org/10.1007/978-3-319-61994-1_3

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  • DOI: https://doi.org/10.1007/978-3-319-61994-1_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61993-4

  • Online ISBN: 978-3-319-61994-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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