Large-size sprocket repairing based on robotic GMAW additive manufacturing

Welding in the World (2021)Cite this article

Abstract

The variable and irregular surface damage of large-size sprockets has led to many challenges in the robotic GMAW-based automatic repair, which is a problem that has not been solved well. In this paper, a highly adaptive method based on robotic GMAW additive manufacturing was developed to repair the large-size sprocket with high quality. Key technologies including 3d rebuilding of damage surface and automatic robot deposition path planning have been researched. The model of damaged sprocket surface was obtained by point cloud registration algorithm including improved Iterative Closest Point (ICP) and Boolean subtraction operations. A highly adaptive slicing and path planning method for repairing sprockets with variable and irregular surface damage was proposed. Deposition parameters were obtained through experiments and a database with neural networks. The robot repairing process was simulated by 3D animation before executing the robot codes. The developed robot GMAW repairing system has integrated 3D scan modeling, slicing, path planning, parameters planning, and 3D animation simulation. The validation experiment results of repairing the damaged sprockets showed that the developed system has strong adaptability and high efficiency, and the repair accuracy met the actual requirements.

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References

  1. 1.

    Liu H, Hu Z, Qin X, Wang Y, Zhang J, Huang S (2017) Parameter optimization and experimental study of the sprocket repairing using laser cladding. Int J Adv Manuf Technol 91:3967–3975

    Article  Google Scholar 

  2. 2.

    Liang WANG (2019) Research on remanufacturing and repairing process of mining sprocket. Lanzhou University of Technology, Master thesis

    Google Scholar 

  3. 3.

    Wang SP, Yang ZJ, Wang XW (2014) Wear of driving sprocket for scraper convoy and mechanical behaviors at meshing progress. J China Coal Soc 39(1):166–171

    Google Scholar 

  4. 4.

    Pan Z, Ding D, Wu B et al (2018) Arc welding processes for additive manufacturing: A review. Trans Intell Weld Manuf:3–24

  5. 5.

    Kumar LJ, Nair CGK (2017) Laser metal deposition repair applications for Inconel 718 alloy. Mater Today Proc. 4:11068–11077

    Article  Google Scholar 

  6. 6.

    Yin S, Cavaliere P, Aldwell B, Jenkins R, Liao H, Li W, Lupoi R (2018) Cold spray additive manufacturing and repair: Fundamentals and applications. Addit Manuf 21:628–650

    CAS  Google Scholar 

  7. 7.

    Jhavar S, Paul CP, Jain NK (2016) Micro-Plasma Transferred Arc Additive Manufacturing for Die and Mold Surface Remanufacturing. JOM 68:1801–1809

    CAS  Article  Google Scholar 

  8. 8.

    Chen WJ, Chen H, Li CC, Wang X, Cai Q (2017) Microstructure and fatigue crack growth of EA4T steel in laser cladding remanufacturing. Eng Fail Anal 79:120–129

    CAS  Article  Google Scholar 

  9. 9.

    Ding D, Pan Z, Cuiuri D, Li H (2015) Wire-feed additive manufacturing of metal components: technologies, developments and future interests. Int J Adv Manuf 81(1-4):465–481

    Article  Google Scholar 

  10. 10.

    Qi H, Azer M, Singh P (2010) Adaptive toolpath deposition method for laser net shape manufacturing and repair of turbine compressor airfoils. Int J Adv Manuf Technol 48:121–131

    Article  Google Scholar 

  11. 11.

    Motta JMST, Llanos CH, Carvalho GC, Alfaro SCA (2010) A prototype of a specialized robotic system for repairing hydraulic turbine blades. In: 2010 1st International Conference on Applied Robotics for the Power Industry, CARPI, p 5624449

    Google Scholar 

  12. 12.

    Hazel B, Boudreault E, Côté J, Godin S (2015) Robotic post-weld heat treatment for in situ repair of stainless steel turbine runners. In: Proceedings of the 3rd International Conference on Applied Robotics for the Power Industry, p 7030051

    Google Scholar 

  13. 13.

    Miao G, Shijie D, Peng J, Wang D (2019) Heat transfer modeling and cooling method for aeroengine blade MPAW repair. Trans China Weld Inst 40(7):24–30

    Google Scholar 

  14. 14.

    Shen H, Huabin C (2016) TOPTIG robot welding technology and welding joint performance research of the aircraft engine blade. J Shanghai Jiaotong Univ 50:114–116

    Google Scholar 

  15. 15.

    Michal C, Jindrich L (2016) 3D robotic welding with a laser profile scanner. In: 2016 International Conference on Control, Automation and Information Sciences, ICCAIS 2016, pp 7–12

    Google Scholar 

  16. 16.

    Yang Z, Xiaoqing L, Xu L, Hongyang J, Yongdian H (2019) A segmentation planning method based on the change rate of cross-sectional area of single V-groove for robotic multi-pass welding in intersecting pipe-pipe joint. Int J Adv Manuf Technol 101(1-4):23–38

    Article  Google Scholar 

  17. 17.

    Zhu S, Liang Y (2006) Path planning for MIG surfacing of robot-based remanufacturing system. China Weld 15(4):59–62

    Google Scholar 

  18. 18.

    Ding D, Pan Z, Cuiuri D, Li H (2014) A tool-path generation strategy for wire and arc additive manufacturing. Int J Adv Manuf Technol 73:173–183

    Article  Google Scholar 

  19. 19.

    Pan Z, Ding D, Cuiuri D, Li H (2015) A practical path planning methodology for wire and arc additive manufacturing of thin-walled structures. Robot Cim-Int Manuf 34:8–19

    Article  Google Scholar 

  20. 20.

    Ding D, Pan Z, Cuiuri D, Li H, Duin SV, Larkin N (2016) Bead modelling and implementation of adaptive MAT path in wire and arc additive manufacturing. Robot Cim-Int Manuf 39:32–42

    Article  Google Scholar 

  21. 21.

    Michel F, Lockett H, Ding J, Martina F, Marinelli G, Williams S (2019) A modular path planning solution for Wire plus Arc Additive Manufacturing. Robot Cim-Int Manuf 60:1–11

    Article  Google Scholar 

  22. 22.

    Besl PJ, McKay NJ (1992) A method for registration of 3-D shapes. IEEE T Pattern Anal 14(2):239–256

    Article  Google Scholar 

  23. 23.

    Li W, Song P (2015) A modified ICP algorithm based on dynamic adjustment factor for registration of point cloud and CAD model. Pattern Recognit Lett 65:88–94

    Article  Google Scholar 

  24. 24.

    Ding D, Z Pan Z, Cuiuri D, Li H. (2015) A multi-bead overlapping model for robotic wire and arc additive manufacturing (WAAM). Robot Cim-Int Manuf 31:101–110

    Article  Google Scholar 

  25. 25.

    Xiong J, Zhang G, Hu J, Wu L (2014) Bead geometry prediction for robotic GMAW-based rapid manufacturing through a neural network and a second-order regression analysis. J Intell Manuf 25(1):157–163

    Article  Google Scholar 

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Funding

This work was supported by Key R&D Project of Guangdong Province, China (2018B090906004) and National Natural Science Foundation of China (Grant No. 52075121).

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Affiliations

  1. State Key Laboratory of Advanced Welding and Joining, Harbin Institute of Technology, No.92, West Da-Zhi Street, Harbin, 150001, Heilongjiang, China

    Xinlei Li, Qinglin Han & Guangjun Zhang

Authors
  1. Xinlei Li
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  2. Qinglin Han
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  3. Guangjun Zhang
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Corresponding author

Correspondence to Guangjun Zhang.

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Recommended for publication by Commission I - Additive Manufacturing, Surfacing, and Thermal Cutting

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Li, X., Han, Q. & Zhang, G. Large-size sprocket repairing based on robotic GMAW additive manufacturing. Weld World (2021). https://doi.org/10.1007/s40194-021-01080-9

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Keywords

  • Sprocket repair
  • Wire and arc additive manufacturing
  • Slicing and path planning
  • Robotic GMAW