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Multidisciplinary co-design optimization of structural and control parameters for bucket wheel reclaimer

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Abstract

Bucket wheel reclaimer (BWR) is an extremely complex engineering machine that involves multiple disciplines, such as structure, dynamics, and electromechanics. The conventional design strategy, namely, sequential strategy, is structural design followed by control optimization. However, the global optimal solution is difficult to achieve because of the discoordination of structural and control parameters. The co-design strategy is explored to address the aforementioned problem by combining the structural and control system design based on simultaneous dynamic optimization approach. The radial basis function model is applied for the planning of the rotation speed considering the relationships of subsystems to minimize the energy consumption per volume. Co-design strategy is implemented to resolve the optimization problem, and numerical results are compared with those of sequential strategy. The dynamic response of the BWR is also analyzed with different optimization strategies to evaluate the advantages of the strategies. Results indicate that co-design strategy not only can reduce the energy consumption of the BWR but also can achieve a smaller vibration amplitude than the sequential strategy.

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References

  1. Bošnjak S M, Arsić M A, Zrnić N D, et al. Bucket wheel excavator: Integrity assessment of the bucket wheel boom tie-rod welded joint. Engineering Failure Analysis, 2011, 18(1): 212–222

    Article  Google Scholar 

  2. Chatterjee A, Das D. A review of bucket wheel reclaimer failure through mechanical test and metallographic analysis. Journal of Failure Analysis and Prevention, 2014, 14(6): 715–721

    Article  Google Scholar 

  3. Bosnjak S, Pantelić M, Zrnic N, et al. Failure analysis and reconstruction design of the slewing platform mantle of the bucket wheel excavator O&K SchRs 630. Engineering Failure Analysis, 2011, 18(2): 658–669

    Article  Google Scholar 

  4. Lu T F. Preparation for turning a bucket wheel reclaimer into a robotic arm. In: Proceedings of the International Conference on Robotics and Biomimetics. Bangkok: IEEE, 2008, 1710–1715

    Google Scholar 

  5. Lu T F. Bucket wheel reclaimer modeling as a robotic arm. In: Proceedings of the International Conference on Robotics and Biomimetics. Guilin: IEEE, 2009, 263–268

    Google Scholar 

  6. Zhao S, Lu T F, Koch B, et al. A simulation study of sensor data fusion using UKF for bucket wheel reclaimer localization. In: Proceedings of the IEEE International Conference on Automation Science and Engineering (CASE). Seoul: IEEE, 2012, 1192–1197

    Google Scholar 

  7. Yang L, Qi J, Li S, et al. Collaborative optimization for train scheduling and train stop planning on high-speed railways. Omega, 2016, 64: 57–76

    Article  Google Scholar 

  8. Yuan Y L, Song X G, Sun W, et al. Multidisciplinary design optimization of the belt drive system considering both structure and vibration characteristics based on improved genetic algorithm. AIP Advances, 2018, 8(5): 055115

    Article  Google Scholar 

  9. Li W, Wang P, Li D, et al. Multiphysical field collaborative optimization of premium induction motor based on GA. IEEE Transactions on Industrial Electronics, 2018, 65(2): 1704–1710

    Article  MathSciNet  Google Scholar 

  10. Zhao T, Liu D, Chen Q. A collaborative optimization method for heat transfer systems based on the heat current method and entransy dissipation extremum principle. Applied Thermal Engineering, 2019, 146: 635–647

    Article  Google Scholar 

  11. Sun W, Wang X B, Wang L T, et al. Multidisciplinary design optimization of tunnel boring machine considering both structure and control parameters under complex geological conditions. Structural and Multidisciplinary Optimization, 2016, 54(4): 1073–1092

    Article  Google Scholar 

  12. Sun W, Wang X B, Shi M L, et al. Multidisciplinary design optimization of hard rock tunnel boring machine using collaborative optimization. Advances in Mechanical Engineering, 2018, 10(1): 1687814018754726

    Article  Google Scholar 

  13. Huang Z L, Zhou Y S, Jiang C, et al. Reliability-based multi-disciplinary design optimization using incremental shifting vector strategy and its application in electronic product design. Acta Mechanica Sinica, 2018, 34(2): 285–302

    Article  MATH  MathSciNet  Google Scholar 

  14. Bidoki M, Mortazavi M, Sabzehparvar M. A new approach in system and tactic design optimization of an autonomous underwater vehicle by using multidisciplinary design optimization. Ocean Engineering, 2018, 147: 517–530

    Article  Google Scholar 

  15. Garg D, Patterson M A, Francolin C, et al. Direct trajectory optimization and costate estimation of finite-horizon and infinite-horizon optimal control problems using a Radau pseudospectral method. Computational Optimization and Applications, 2011, 49(2): 335–358

    Article  MATH  MathSciNet  Google Scholar 

  16. Janson L, Schmerling E, Pavone M. Monte Carlo motion planning for robot trajectory optimization under uncertainty. In: Bicchi A, Burgard W, eds. Robotics Research. Cham: Springer, 2018, 343–361

    Chapter  Google Scholar 

  17. Wang X B, Sun W, Li E Y, et al. Energy-minimum optimization of the intelligent excavating process for large cable shovel through trajectory planning. Structural and Multidisciplinary Optimization, 2018, 58(5): 2219–2237

    Article  Google Scholar 

  18. Tian L, Collins C. An effective robot trajectory planning method using a genetic algorithm. Mechatronics, 2004, 14(5): 455–470

    Article  Google Scholar 

  19. Franke R. Scattered data interpolation: Tests of some methods. Mathematics of Computation, 1982, 38(157): 181–200

    MATH  MathSciNet  Google Scholar 

  20. Rippa S. An algorithm for selecting a good value for the parameter c in radial basis function interpolation. Advances in Computational Mathematics, 1999, 11(2–3): 193–210

    Article  MATH  MathSciNet  Google Scholar 

  21. Wu Z, Schaback R. Local error estimates for radial basis function interpolation of scattered data. IMA Journal of Numerical Analysis, 1993, 13(1): 13–27

    Article  MATH  MathSciNet  Google Scholar 

  22. He E J. Cantilever wheel arm gyral machine for heaping and taking the material 1/cosφ speed control system. The World of Inverters, 2006, 10(5): 106–107 (in Chinese)

    Google Scholar 

  23. Chudnovskii V Y. Vertical oscillations of the working unit of a bucket-wheel excavator in a pit face and their suppression. Journal of Machinery Manufacture and Reliability, 2008, 37(3): 221–227

    Article  Google Scholar 

  24. Wolpert D H, Macready W G. No free lunch theorems for optimization. IEEE Transactions on Evolutionary Computation, 1997, 1(1): 67–82

    Article  Google Scholar 

  25. Yuan Y L, Lv L Y, Wang X B, et al. Optimization of a frame structure using the Coulomb force search strategy-based dragonfly algorithm. Engineering Optimization, 2019 (in press)

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Acknowledgements

The research was supported by the National Key R&D Program of China (Grant Nos. 2018YFB1700704 and 2018YFB1702502).

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Authors and Affiliations

  1. School of Mechanical Engineering, Dalian University of Technology, Dalian, 116024, China

    Yongliang Yuan, Liye Lv, Shuo Wang & Xueguan Song

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  1. Yongliang Yuan
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  2. Liye Lv
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  3. Shuo Wang
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  4. Xueguan Song
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Correspondence to Xueguan Song.

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Yuan, Y., Lv, L., Wang, S. et al. Multidisciplinary co-design optimization of structural and control parameters for bucket wheel reclaimer. Front. Mech. Eng. 15, 406–416 (2020). https://doi.org/10.1007/s11465-019-0578-2

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  • DOI: https://doi.org/10.1007/s11465-019-0578-2

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