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An application of genetic algorithm for edge detection of molten pool in fixed pipe welding

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Abstract

This paper presents a study on an application of genetic algorithm (GA) for edge detection of molten pool in fixed pipe welding. As circumferential butt-welded pipes are frequently used in power stations, offshore structures, and process industries, it is important to investigate the characteristic of the welding process. In pipe welding using constant arc current and welding speed, the bead width becomes wider as the circumferential welding of small-diameter pipes progresses. In order to avoid the errors and to maintain the uniform weld bead over the entire circumference of the pipe, the welding conditions should be controlled as the welding proceeds. This research studies the intelligent welding process of aluminum alloy pipe 6063S-T5 in fixed position using the AC welding machine. The monitoring system used an omnidirectional camera to monitor backside image of molten pool. A method of optimization for image processing algorithm using GA was proposed and has been implemented into a process to recognize the edge of molten pool. The result of detection, which is back bead width, was delivered into a fuzzy inference system to control welding speed. The experimental results show the effectiveness of the control system that is confirmed by a sound weld of the experimental results.

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References

  1. Saedi HR, Unkel W (1988) Arc and weld pool behavior for pulsed current GTAW. Weld J 67(11):247–255

    Google Scholar 

  2. Vilkas EP (1966) Automation of the gas tungsten arc welding. Weld J 45(5):410–416

    Google Scholar 

  3. Andersen K, Cook GE (1990) Artificial neural networks applied to arc welding process modeling and control. IEEE Trans Ind Appl 26(9):824–830

    Article  Google Scholar 

  4. Lim TG, Cho HS (1993) Estimation of weld pool sizes in GMA welding process using neural networks. J Syst Control Eng 207(1):15–26

    Google Scholar 

  5. Muramatsu M, Suga Y, Mori K (2003) Autonomous mobile robot system for monitoring and control of penetration during fixed pipes welding. JSME Int J Ser A 46(3):391–397

    Article  Google Scholar 

  6. Baskoro AS, Kabutomori M, Suga Y (2008) Monitoring of backside image of molten pool during aluminum pipe welding using vision sensor. Mater Sci Forum 580–582:379–382

    Article  Google Scholar 

  7. Baskoro AS, Kabutomori M, Suga Y (2008) Automatic welding system of aluminum pipe by monitoring backside image of molten pool using vision sensor. J Solid Mech Mater Eng JSME 2(5):582–592

    Article  Google Scholar 

  8. Bingul Z, Cook GE, Strauss AM (2000) Application of fuzzy logic to spatial thermal control in fusion welding. IEEE Trans Ind Appl 36(6):1523–1530

    Article  Google Scholar 

  9. Bae KY, Lee TH, Ahn KC (2003) An optical sensing system for seam tracking and weld pool control in gas metal arc welding of steel pipe. J Mater Process Technol 120(1–3):458–465

    Google Scholar 

  10. Baskoro AS, Kabutomori M, Suga Y (2009) Welding penetration control of fixed pipe in TIG welding using fuzzy inference system. J Solid Mech Mater Eng JSME 3(1):38–48

    Article  Google Scholar 

  11. Brzakovic D, Khani DT (1991) Weld pool edge detection for automated control of welding. IEEE Trans Robot Autom 7(3):397–403

    Article  Google Scholar 

  12. Lee CW, Na SJ (1996) A Study on the influence of reflected arc light on vision sensors for welding automation. Weld J 75(12):379–387

    Google Scholar 

  13. Richardson RW, Gutow DA (1984) Coaxial arc weld pool viewing for process monitoring and control. Weld J 63(3):43–50

    Google Scholar 

  14. Masuda R, Kabutomori M, Baskoro AS, Suga Y (2008) The welding penetration control of aluminum pipe using omnidirectional camera. In: Proc Mech Eng Congress 2008 JSME, pp 399–400

  15. Haupt RL, Haupt SE (1998) Practical genetic algorithms. A Wiley-Interscience publication. Wiley-Interscience, New York

    Google Scholar 

  16. Kim J, Muramatsu M, Murata Y, Suga Y (2007) Omnidirectional vision-based ego-pose estimation for an autonomous in-pipe mobile robot. Adv Robot 21(3–4):441–460

    Article  Google Scholar 

  17. Ahn CW (2006) Advances in evolutionary algorithms: theory, design and practice. Springer, New York

    MATH  Google Scholar 

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Authors and Affiliations

  1. Graduate School of Science and Technology, Keio University, Yokohama, Japan

    Ario Sunar Baskoro, Rui Masuda & Masashi Kabutomori

  2. Faculty of Science and Technology, Keio University, Hiyoshi 3-14-1, Kohoku-ku, Yokohama, 223-8522, Japan

    Yasuo Suga

Authors
  1. Ario Sunar Baskoro
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  2. Rui Masuda
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  3. Masashi Kabutomori
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  4. Yasuo Suga
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Correspondence to Ario Sunar Baskoro.

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Baskoro, A.S., Masuda, R., Kabutomori, M. et al. An application of genetic algorithm for edge detection of molten pool in fixed pipe welding. Int J Adv Manuf Technol 45, 1104 (2009). https://doi.org/10.1007/s00170-009-2048-1

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  • DOI: https://doi.org/10.1007/s00170-009-2048-1

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