APPLIED LASER, Volume. 42, Issue 6, 13(2022)

The Prediction of Welding Bead Geometry and Symetry of Laser-Arc Hybrid Welding

Hong Yanwu1,2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    References(9)

    [1] [1] YANG L J, CHANDEL R S, BIBBY M J. The effects of processvariables on the bead height of submerged-arc weld deposits[J]. Canadian Metallurgical Quarterly, 1992, 31(4): 289-297.

    [2] [2] YANG Z H, LI X Q, WANG Z M, et al. The bead geometry predicting model based on partial least squares regression[J]. Welding Technology, 2010, 39(3): 6-9.

    [3] [3] XU M, LIU S Y, LI Y Q, et al. Optimization of SPCC and 65Mn dissimilar metal laser welding process parameters based on response surface methodology[J]. Applied Laser, 2017, 37(3): 362-366.

    [6] [6] RIDINGS G E, THOMSON R, THEWLIS G. Prediction of multiwire submerged arc weld bead shape using neural network modelling[J]. Science and Technology of Welding and Joining, 2002, 7: 265- 279.

    [7] [7] DONG Z B, WEI Y H, ZHAN X H, et al. Optimization of mechanical properties prediction models of welded joints combined neural network with genetic algorithm[J]. Transactions of the China Welding Institution, 2007, 28(12): 69-72.

    [8] [8] LIU S Y, ZHANG H, SHI Y, et al. Effects of process parameters on droplet transfer and bead shape in CO2-MAG hybrid welding[J]. Chinese Journal of Lasers, 2010, 37(12): 3172-3179.

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    Hong Yanwu. The Prediction of Welding Bead Geometry and Symetry of Laser-Arc Hybrid Welding[J]. APPLIED LASER, 2022, 42(6): 13

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    Paper Information

    Received: Jul. 6, 2021

    Accepted: --

    Published Online: Feb. 4, 2023

    The Author Email:

    DOI:10.14128/j.cnki.al.20224206.013

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