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Design and Control of a Crawler-Type Wall-Climbing Robot System for Measuring Paint Film Thickness of Offshore Wind Turbine Tower

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Abstract

In the process of detecting the paint film thickness of offshore wind turbine towers, there are problems such as the risk of high-altitude and the changeable working environments, which pose a great threat to the safety of operators. In response to the above problems, a crawler-type climbing-robot system for measuring paint film thickness of offshore wind turbine towers is developed. Firstly, the robot structure is designed by adopting modular design idea. Secondly, the kinematics analysis of the robot's facade steering is carried out, and the kinematics model of the robot's instantaneous steering is established. On this basis, considering the influence of hydrodynamic force and track deformation, a dynamic model of multi-track coordinated motion is established. Then, the kinematics and dynamics of the robot are simulated and calculated by Matlab. The robot control system is designed according to the requirements of multi-module cooperative operation. Finally, a robot prototype is developed based on the theory and simulation, and the robot is verified through the experimental platform and the offshore wind power field experiment.

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Code or Data Availability

The theoretical curve data involved in the thesis are all calculated by formulas. The experimental curves and charts involved are directly derived from the motor encoder and inertial navigation in the designed robot.

References

  1. Yang, X., Bai, K.: Development and prospects of offshore wind power. In: World Non-grid-connected Wind Power & Energy Conference. IEEE. (2010)

  2. Ren, Z., Verma, A.S., Li, Y., et al.: Offshore wind turbine operations and maintenance: a state-of-the-art review. Renew. Sustain. Energy Rev. 144, 110886 (2021)

    Article  Google Scholar 

  3. Mitchell, D., Blanche, J., Zaki, O., et al.: Symbiotic system of systems design for safe and resilient autonomous robotics in offshore wind farms. IEEE Access. 9, 141421–141452 (2021)

    Article  Google Scholar 

  4. Petersen, K.R., Madsen, E.S., Bilberg, A.: Offshore wind power at rough sea: the need for new maintenance models. In: 20th EurOMA Conference. (2013)

  5. Zhang, L., Ke, W., Ye, Q., et al.: A novel laser vision sensor for weld line detection on wall-climbing robot. Opt. Laser Technol. 60, 69–79 (2014)

    Article  Google Scholar 

  6. Dethe, R.D., Jaju, S.B.: Developments in wall climbing robots: a review. Int. J. Eng. Res. General Sci. 2(3), 33–42 (2014)

    Google Scholar 

  7. Nansai, S., Mohan, R.E.: A survey of wall climbing robots: recent advances and challenges. Robotics 5(3), 14 (2016)

    Article  Google Scholar 

  8. Huang, H., Li, D., Xue, Z., et al.: Design and performance analysis of a tracked wall-climbing robot for ship inspection in shipbuilding. Ocean Eng. 131, 224–230 (2017)

    Article  Google Scholar 

  9. Liu, Y., Hajj, M., Bao, Y.: Review of robot-based damage assessment for offshore wind turbines. Renew. Sustain. Energy Rev. 158, 112187 (2022)

    Article  Google Scholar 

  10. Jie, S., Li, X., Zong, C., et al.: A wall-climbing robot with gecko features. In: International Conference on Mechatronics & Automation. IEEE. (2012)

  11. Gao, X., Shao, J., Dai, F., et al.: Strong magnetic units for a wind power tower inspection and maintenance robot. Int. J. Adv. Robot. Syst. 9(5), 1 (2012)

    Article  Google Scholar 

  12. Gao, X.S., Shao, J., Dai, F.Q., et al.: A gecko-inspired robot for wind power tower inspection. Appl. Mech. Mater. Trans Tech Publications Ltd. 461, 831–837 (2014)

  13. Liang, W.: Wind turbine tower cleaning robot. AIP Conf. Proc. AIP Publishing LLC. 2036(1), 030057 (2018)

  14. Wang, B., Luo, H., Jin, Y., et al.: Path planning for detection robot climbing on rotor blade surfaces of wind turbine based on neural network. Adv. Mech. Eng. 5, 760126 (2013)

    Article  Google Scholar 

  15. Li, Z., Tokhi, M.O., Zhao, Z., et al.: A compact laser shearography system integrated with robotic climber for on-site inspection of wind turbine blades. In: CLAWAR 2020: 23rd International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines. CLAWAR Association (2020)

  16. BladeBUG: Advanced robotics for turbine maintenance. https://bladebug.co.uk (2021)

  17. Mondal C S.: A robot design for wind generator support structure inspection. In: CLAWAR 2020: 23rd International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines. CLAWAR Association (2020)

  18. Mondal, S.C., Marquez, P.L.C., Tokhi, M.O.: Analysis of mechanical adhesion climbing robot design for wind tower inspection. J. Artif. Intell. Technol. 1(4), 219–227 (2021)

    Google Scholar 

  19. Hatoum, K., Alkhatib, R., Jaber, N., et al.: Windmill climbing robot. In: 2018 International Conference on Computer and Applications (ICCA), pp. 394–398. IEEE (2018)

  20. Liu, J.H., Padrigalan, K.: Design and development of a climbing robot for wind turbine maintenance. Appl. Sci. 11(5), 2328 (2021)

    Article  Google Scholar 

  21. Elkmann, N., Felsch, T., Förster, T.: Robot for rotor blade inspection. In: 2010 1st International Conference on Applied Robotics for the Power Industry, pp. 1–5. IEEE (2010)

  22. Schleupen, J., Engemann, H., Bagheri, M., et al.: Developing a climbing maintenance robot for tower and rotor blade service of wind turbines. In: International Conference on Robotics in Alpe-Adria Danube Region, pp. 310–319. Springer, Cham (2016)

  23. Sattar, T.P., Rodriguez, H.L., Bridge, B.: Climbing ring robot for inspection of offshore wind turbines. Ind. Robot. 36(4), 326–330 (2009)

    Article  Google Scholar 

  24. Sattar, T.P., Marques, V., Anvo, R., et al.: Climbing robot to perform radiography of wind blades. In: Climbing and Walking Robots Conference, pp. 165–176. Springer, Cham (2021)

  25. Franko, J., Du, S., Kallweit, S., et al.: Design of a multi-robot system for wind turbine maintenance. Energies 13(10), 2552 (2020)

    Article  Google Scholar 

  26. Lee, D.G., Oh, S., Son, H.I.: Maintenance robot for 5-MW offshore wind turbines and its control. IEEE/ASME Trans. Mechatron. 21(5), 2272–2283 (2016)

    Article  Google Scholar 

  27. Kallweit, S., Dahmann, P., Schleupen, J., et al.: Developing a climbing maintenance robot for tower and rotor blade service of wind turbines. In: Advances in Robot Design and Intelligent Control: Proceedings of the 25th Conference on Robotics in Alpe-Adria-Danube Region (RAAD16). pp. 540–310. Springer (2016)

  28. Liu, Y., Kim, H.G., Seo, T.W.: AnyClimb: a new wall-climbing robotic platform for various curvatures. IEEE/ASME Trans. Mechatron. 21(4), 1812–1821 (2016)

    Article  Google Scholar 

  29. Wang, Y., Zhang, X., Zhang, M., et al.: Self-compliant track-type wall-climbing robot for variable curvature facade. IEEE Access. (2021)

  30. Hu, J., Han, X., Tao, Y., et al.: A magnetic crawler wall-climbing robot with capacity of high payload on the convex surface. Robot. Auton. Syst. 148, 103907 (2022)

    Article  Google Scholar 

  31. Huang, Z.: Analysis on the principle and performance index of tower climbing robot. IOP Conf. Ser.: Earth Environ. Sci. IOP Publishing. 440(3), 032097 (2020)

  32. Tovarnov, M.S., Bykov, N.V.: A mathematical model of the locomotion mechanism of a mobile track robot with the magnetic-tape principle of wall climbing. J. Mach. Manuf. Reliab. 48(3), 250–258 (2019)

    Article  Google Scholar 

  33. Martínez, J.L., Morales, J., Mandow, A., et al.: Inertia-based ICR kinematic model for tracked skid-steer robots. 2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR), pp. 166–171. IEEE (2017)

  34. Wong, J.Y., Chiang, C.F.: A general theory for skid steering of tracked vehicles on firm ground. Proc. Inst. Mech. Eng. D: J. Automob. Eng. 215(3), 343–355 (2001)

    Article  Google Scholar 

  35. Maclaurin, B.: A skid steering model using the magic formula. J. Terrramech. 48(4), 247–263 (2011)

    Article  Google Scholar 

  36. Moniri, M.M., Bamdad, M., Sayyadan, M.Z. A novel design of wall climbing robot for inspection of storage steel tanks. 2015 3rd RSI International Conference on Robotics and Mechatronics (ICROM), pp. 557–562. IEEE (2015)

  37. Yi, Z., Gong, Y., Wang, Z., et al.: Dynamic modeling and analysis on a new type wall-climbing robot for ship wall rust removal. Jixie Gongcheng Xuebao (Chinese Journal of Mechanical Engineering) 46(15), 23–30 (2010)

    Article  Google Scholar 

  38. Jiwei, Q., Yong, C., Bingbing, Y., et al.: Dynamics modeling and analysis of a rolling sealed wall-climbing robot. China mechanical engineering. 30(24), 2978 (2019)

    Google Scholar 

  39. Choi, J.S., Yoo, J.: Design of a Halbach magnet array based on optimization techniques. IEEE Trans. Magn. 44(10), 2361–2366 (2008)

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank the anonymous reviewers for their comments. This research was supported by the National Key Research and Development Project of China (Grant No. 2018YFB1309401).

Funding

This research was supported by the National Key Research and Development Project of China (Grant No. 2018YFB1309401).

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Authors and Affiliations

  1. College of Mechanical Engineering, Hebei University of Technology, Tianjin, 300130, China

    Pei Yang, Minglu Zhang, Lingyu Sun & Xinbao Li

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  1. Pei Yang
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  2. Minglu Zhang
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  3. Lingyu Sun
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  4. Xinbao Li
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Contributions

All authors contributed to the study conception and design. Pei Yang and Lingyu Sun conceived the original ideas, and designed all the experiments. Minglu Zhang provided supervision to the project, formal analysis, and resources. Pei Yang, Lingyu Sun and Xinbao Li conducted all the experiments and provided human resources. Pei Yang drafted the manuscript of the paper. Lingyu Sun reviewed the writing. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Lingyu Sun.

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Yang, P., Zhang, M., Sun, L. et al. Design and Control of a Crawler-Type Wall-Climbing Robot System for Measuring Paint Film Thickness of Offshore Wind Turbine Tower. J Intell Robot Syst 106, 50 (2022). https://doi.org/10.1007/s10846-022-01750-w

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