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A robot welding approach for the sphere-pipe joints with swing and multi-layer planning

  • Yan Liu
  • Lijuan Ren
  • Xincheng TianEmail author
ORIGINAL ARTICLE
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Abstract

Sphere-pipe joints welding is widely used in industrial applications. This paper presents a robot welding approach for the sphere-pipe joints with swing and multi-layer planning. Firstly, various coordinate systems are used to describe the geometric relationship between weld seam and robot welding torch. The sphere-pipe intersecting curve welding process is basically uphill and downhill welding. Therefore, this paper establishes a description model of the welding torch attitude, which parameterizes the attitude description and automatically adjusts the torch attitude during the welding process according to the change of weld inclination angle. To overcome the negative effects of gravity, such as deepening of the molten pool and reduction of the weld width, this paper integrates the swing welding technology into trajectory planning and gives a solving algorithm for the welding torch swing curve. The swing welding also can reduce the number of weld pass. Therefore, multi-layer single-pass swing welding is an economical and efficient way for thicker weldments. In this paper, a multi-layer single-pass swing welding planning algorithm is proposed, which can automatically determine the height and swing amplitude of each welding layer. Finally, the industrial robot Puma560 is used to carry out experimental simulation, and the simulation results are used to verify the feasibility and accuracy of this approach.

Keywords

Sphere-pipe intersecting curve Swing welding Multi-layer planning Trajectory planning Robot welding 

Notes

Funding information

The authors gratefully thank the research funding by the National Key Research and Development Plan of China under Grant No. 2017YFB13035.

References

  1. 1.
    Xu F (2014) Concise manual for welding process 2rd. Shanghai Science and Technology Press, ShanghaiGoogle Scholar
  2. 2.
    Sharma V, Shahi AS (2014) Effect of groove design on mechanical and metallurgical properties of quenched and tempered low alloy abrasion resistant steel welded joints. Mater Des 53:727–736CrossRefGoogle Scholar
  3. 3.
    Yan L, Ya L, Xincheng T (2019) Trajectory and velocity planning of the robot for sphere-pipe intersection hole cutting with single-Y welding groove. Robot Comput Integr Manuf 56:244–253CrossRefGoogle Scholar
  4. 4.
    Wang QH, Yin GF, Xu L, He SS (2012) Mathematical model and simulation for cutting of pipe tee with root face groove. Trans China Weld Instit 33(3):77–80Google Scholar
  5. 5.
    Kavraki L, Svestka P, Latombe JC, Overmars M (1996) Probabilistic roadmaps for path planning in high-dimensional configuration space. IEEE Trans Robot Autom 12(4):566–580CrossRefGoogle Scholar
  6. 6.
    Barraquand J, Kavraki L, Latombe JC, Li TY, Motwani R, Raghavan P (1997) A random sampling scheme for path planning. Int J Robot Res 16(6):759–774CrossRefGoogle Scholar
  7. 7.
    Zou Q, Guo W, Hamimid FY (2017) A novel robot trajectory planning algorithm based on NURBS velocity adaptive interpolation. International conference on mechanical design 1191–1208Google Scholar
  8. 8.
    Fang HC, Ong SK, Nee AYC (2017) Adaptive pass planning and optimization for robotic welding of complex joints. Adv Manuf 5(2):93–104CrossRefGoogle Scholar
  9. 9.
    Dharmawan A, Sedore B, Soh G, Foong S, Otto K Robot base placement and kinematic evaluation of 6r serial manipulators to achieve collision-free welding of large intersecting cylindrical pipes. International design engineering technical conferences and computers and information in engineering conference, Volume 5C:39th Mechanisms and Robotics ConferenceGoogle Scholar
  10. 10.
    Zhang C, Li H, Jin Z, Gao H (2017) Seam sensing of multi-layer and multi-pass welding based on grid structured laser. Int J Adv Manuf Technol 91(1-4):1103–1110CrossRefGoogle Scholar
  11. 11.
    Shi L, Tian XC (2014) Automation of main pipe-rotating welding scheme for intersecting pipes. Int J Adv Manuf Technol 77(5-8):955–964CrossRefGoogle Scholar
  12. 12.
    Shi L, Tian XC, Zhang CH (2015) Automatic programming for industrial robot to weld intersecting pipes. Int J Adv Manuf Technol 81(9-12):2099–2107CrossRefGoogle Scholar
  13. 13.
    Bahrami-Samani M, Agahi M, Moosavian SA (2007) Design and analysis of a welding robot. IEEE International Conference on Automation Science and Engineering pp 454–459Google Scholar
  14. 14.
    Fang HC, Ong SK, Nee AYC (2017) Robot path planning optimization for welding complex joints. Int J Adv Manuf Technol 90:3829–3839CrossRefGoogle Scholar
  15. 15.
    Liu J, Hu S, Junqi S, Tuo Y, Changliang C (2017) Intersection seam of sphere and tube welding robot trajectory optimization based on spatial offset curve. Trans China Weld Instit 38(11):47–50Google Scholar
  16. 16.
    Zhao J, Hu S, Junqi S, Changliang C, Wei D (2011) Mathematical model based on MATLAB for intersection seam of sphere and tube. Trans China Weld Instit 32(8):89–92Google Scholar
  17. 17.
    Changliang C, Hu S, He D, Junqi S (2013) An approach to the path planning of tube-sphere intersection welds with the robot dedicated to j-groove joints. Robot Comput Integr Manuf 29(4):41–48CrossRefGoogle Scholar
  18. 18.
    Mitsi S, Bouzakis KD, Mansour G, Sagris D, Maliaris G (2005) Off-line programming of an industrial robot for manufacturing. Int J Adv Manuf Technol 26(3):262–267CrossRefGoogle Scholar
  19. 19.
    Kucuk S (2016) Maximal dexterous trajectory generation and cubic spline optimization for fully planar parallel manipulators. Comput Electr Eng 56:634–647CrossRefGoogle Scholar
  20. 20.
    Kucuk S (2017) Optimal trajectory generation algorithm for serial and parallel manipulators. Robot Comput Integr Manuf 48:219–232CrossRefGoogle Scholar
  21. 21.
    Yu JP, Shi P (2015) Approximation-based discrete-time adaptive position tracking control for interior permanent magnet synchronous motors. IEEE Trans Cybern 45(7):1363–1371MathSciNetCrossRefGoogle Scholar
  22. 22.
    Craig JJ (2003) Introduction to Robotics: mechanics and control, 3rd edn. Prentice Hall, LondonGoogle Scholar
  23. 23.
    Siciliano B, Sciavicco L, Villani L, Oriolo G (2008) Robotics: Modelling, planning, and controlGoogle Scholar
  24. 24.
    Hongzhu G, Jinggeng W, Fu R (2007) Space analytic geometry. Beijing Normal University Press, BeijingGoogle Scholar
  25. 25.
    Spong MW, Hutchinson S, Vidyasagar M (2016) Robot modeling and controlGoogle Scholar

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Control Science and EngineeringShandong UniversityJinanChina

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