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Analysis of Weld Pool Characteristics in Narrow Gap GTAW Welding Based on Passive Vision

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6GN for Future Wireless Networks (6GN 2023)

Abstract

In the process of narrow gap pipeline welding, the welding quality can be controlled and judged by the characteristic information of the weld pool. The traditional active vision laser is limited by the geometric characteristics of the narrow gap groove, which cannot be projected into the workpiece groove, and the weld seam is easily blocked by the welding wire, which cannot obtain the weld seam characteristics, so the welding quality cannot be judged online. In this paper, the molten pool image is obtained directly by passive vision, and the complete contour of narrow gap welding molten pool is restored by means of median filtering noise reduction, Canny edge detection, area filtering screening and circle fitting. Two key characteristic parameters, curvature radius and advancing angle of molten pool contour, which can be used to characterize the welding quality, are extracted. The results of pipeline welding experiments show that the greater the welding current, the greater the radius of curvature and the forward angle of the molten pool profile. The variation range of characteristic parameters under different penetration states is analyzed, which provides a basis for subsequent parameter adjustment and matching.

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References

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Correspondence to Zehao Li .

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© 2024 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Li, Z., Zhao, S., Zhang, W., Fan, L., Zhou, J. (2024). Analysis of Weld Pool Characteristics in Narrow Gap GTAW Welding Based on Passive Vision. In: Li, J., Zhang, B., Ying, Y. (eds) 6GN for Future Wireless Networks. 6GN 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 554. Springer, Cham. https://doi.org/10.1007/978-3-031-53404-1_25

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  • DOI: https://doi.org/10.1007/978-3-031-53404-1_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-53403-4

  • Online ISBN: 978-3-031-53404-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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