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On the Key Technologies of Intelligentized Welding Robot

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Robotic Welding, Intelligence and Automation

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 362))

Abstract

This paper addresses on key intelligentized technologies for robotic welding, which contains computer vision technology for recognizing weld seam and starting, locally autonomous guiding and tracking seam, real-time intelligent control of weld penetration, seam forming and welding pool dynamics. A locally autonomous intelligentized welding robot (LAIWR) systems was developed, which could realize detecting and recognizing weld surroundings by visual sensing technology, identifying the initial position of weld seam, autonomously guiding weld torch to the weld starting and tracking the seam, real-time control of pulsed GTAW pool dynamics by vision computing and intelligent strategies

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References

  1. Trailer, Manufacturer Depends on Robotic Welding to Boast Production. Welding Journal. 1995, 74(7): 49–51

    Google Scholar 

  2. U. Dilthey, L. Stein. Robot System for Arc Welding-Current Position and Future Trends. Welding & Cutting. 1992, (8): E150–E152

    Google Scholar 

  3. J. L. Pan, “A survey of welding sciences in 21th century.” Proceeding of 9th Chinese Welding Conference, Tianjun, China, Oct. 1999, (1): D-001–D-017

    Google Scholar 

  4. K. P. Valavanis, G. N., Saridis, Intelligent Robotics System: Theory, Design and Applications. Boston, 1992: 12–18

    Google Scholar 

  5. S. B. Chen, et al., 2004. “Intelligentlized technologies for robotic welding”, Series Lecture Notes in Control and Information Sciences, vol. 299: 123–143

    Google Scholar 

  6. Chen Shanben, et al., 2003, “On intelligentized technologies for modern welding manufacturing,” Chinese Journal of Mechanical Engineering, vol.16, No.4, pp367–370

    Article  Google Scholar 

  7. R.J. Beatlie, S.K. Cheng and P.S. Logue. The Use of Vision Sensors in Multipass Welding Applications. Welding Journal. 1988, Vol. 67(11): pp28–33

    Google Scholar 

  8. Zh.Y. Zhu, T. Lin, Y.J. Piao, S.B. Chen, Recognition of the initial position of the weld based on the image pattern match technology. The International Journal of Advanced Manufacturing Technology, vol.26:784–788, 2005

    Article  Google Scholar 

  9. S.B. Chen, X.Z. Chen, J.Q. Li, T. Lin, 2005, “Acquisition of Welding Seam Space Position Information for Arc Welding Robot Based on Vision,” Journal of Intelligent & Robotic Systems, vol.43, pp77–97.

    Article  Google Scholar 

  10. J.W. Kim and S.J. Na. A Self-Organizing Fuzzy Control Approach to Arc Sensor for Weld Joint Tracking in Gas Metal Arc Welding of Butt Joints. Welding Journal. 1993, Vol. 72(1): pp60s–66s

    Google Scholar 

  11. Y. Suga and M. Naruse. Application of Neural Network to Visual Sensing of Weld Line and Automatic Tracking in Robot Welding. Welding in the World. 1994, 34: pp275–284

    Google Scholar 

  12. S. B Chen, Y. Zhang, T. Qiu, T Lin., 2003, “Robotic Welding Systems with Vision Sensing and Self-learning Neuron Control of Arc Weld Dynamic Process”, Journal of Intelligent and Robotic Systems, vol.36, No.2, pp191–208.

    Article  Google Scholar 

  13. S. B. Chen, Y. J. Lou, L. Wu and D.B. Zhao, Intelligent Methodology for Sensing, Modeling and Control of Pulsed GTAW: PART1—Band-on-Plate Welding, Welding Journal, 2000, 79(6):151s–163s

    Google Scholar 

  14. S.B. Chen, D. B. Zhao, L. Wu and Y. J. Lou, Intelligent Methodology for Sensing, Modeling and Control of Pulsed GTAW: PART2—Butt Joint Welding, Welding Journal, 2000, 79(6):164s–174s

    Google Scholar 

  15. R.W. Richardson and D.A. Gutow. Coaxial Arc Weld Pool Viewing for Process Monitoring and Control. Welding Journal. 1984. 63(3): 43–50

    Google Scholar 

  16. J J Wang, T Lin, Shanben Chen, 2005, “Obtaining of weld pool vision information during aluminum alloy TIG welding,” International Journal of Advanced manufacturing technology, vol.26:219–227, 2005

    Article  Google Scholar 

  17. R. Kovacevic, Y.M. Zhang and L. Li. Monitoring of Weld Joint Penetration Based on Weld Pool Geometrical Appearance. Welding Journal. 1996, Vol. 75(10): pp317s–329s

    Google Scholar 

  18. T.G. Lim and H.S. Cho. Estimation of Weld Pool Sizes in GMA Welding Process Using Neural Networks. Journal of Systems and Control Engineering. 1993, Vol. 207(1): pp15–26

    Google Scholar 

  19. D. B. Zhao, S. B. Chen, L. Wu, and Q. Chen., 2001, “Intelligent Control for the Double-sided Shape of the Weld Pool in Pulsed GTAW with Wire Filler,” Welding Journal, vol.80, No.11, pp253s–260s

    Google Scholar 

  20. W. J. Chen, “Research on Local Autonomous Intelligent Welding Robot System and its Remote Control,” Doctoral Dissertation Shanghai Jiao Tong University, 2004.

    Google Scholar 

  21. Zh.Y. Zhu, “Research on Welding Robot Recognizing and Guiding of the Initial Welding Position with Visual Method,” Doctoral Dissertation Shanghai Jiao Tong University, 2004.

    Google Scholar 

  22. Lv. Zhou, “Vision-based Autonomous Programming methods of welding robotic path,” Doctoral Dissertation Shanghai Jiao Tong University, 2006.

    Google Scholar 

  23. B. Wang, S. B. Chen, J. J. Wang, 2005, “Rough set based knowledge modeling for the aluminium alloy pulsed GTAW process,” International Journal of Advanced Manufacturing Technology, vol. 25(9–10): 902–908.

    Article  Google Scholar 

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© 2007 Springer-Verlag Berlin Heidelberg

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Chen, S.B. (2007). On the Key Technologies of Intelligentized Welding Robot. In: Tarn, TJ., Chen, SB., Zhou, C. (eds) Robotic Welding, Intelligence and Automation. Lecture Notes in Control and Information Sciences, vol 362. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73374-4_12

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  • DOI: https://doi.org/10.1007/978-3-540-73374-4_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73373-7

  • Online ISBN: 978-3-540-73374-4

  • eBook Packages: EngineeringEngineering (R0)

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