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基于多因素权重法的高压GMAW焊缝成形分析

郑朋朋,薛龙,黄继强,黄军芬

郑朋朋,薛龙,黄继强,黄军芬. 基于多因素权重法的高压GMAW焊缝成形分析[J]. 焊接学报, 2018, 39(10): 75-80. DOI: 10.12073/j.hjxb.2018390252
引用本文: 郑朋朋,薛龙,黄继强,黄军芬. 基于多因素权重法的高压GMAW焊缝成形分析[J]. 焊接学报, 2018, 39(10): 75-80. DOI: 10.12073/j.hjxb.2018390252
ZHENG Pengpeng, XUE Long, HUANG Jiqiang, HUANG Junfen. Analysis on weld bead geometry of hyperbaric GMAW based on multi-factor weighting method[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2018, 39(10): 75-80. DOI: 10.12073/j.hjxb.2018390252
Citation: ZHENG Pengpeng, XUE Long, HUANG Jiqiang, HUANG Junfen. Analysis on weld bead geometry of hyperbaric GMAW based on multi-factor weighting method[J]. TRANSACTIONS OF THE CHINA WELDING INSTITUTION, 2018, 39(10): 75-80. DOI: 10.12073/j.hjxb.2018390252

基于多因素权重法的高压GMAW焊缝成形分析

Analysis on weld bead geometry of hyperbaric GMAW based on multi-factor weighting method

  • 摘要: 水下高压干式GMAW焊缝成形难以控制,影响焊接质量,通过多因素权重法对影响高压GMAW焊缝成形的参数进行分析,以确定焊接过程中主要参数与焊缝成形之间的关系. 以高压GMAW焊接正交试验结果作为训练样本,利用BP神经网络建立了焊缝成形预测模型. 将模型预测结果与实际焊接试验结果进行对比,验证了模型的精确度. 以预测模型中的权值为基础,通过Garson算法得出各参数变量对于焊缝成形参数的权重系数,并通过高压干式GMAW试验进行验证. 结果表明,不同焊接参数变化引起的焊缝成形参数变化幅度与相应焊接参数对焊缝成形的影响权重基本对应,所得权重系数对于高压GMAW焊接工程应用具有指导作用.
    Abstract: A multi-factor weighting method was used to analyze the parameters influencing weld bead geometry of hyperbaric GMAW. The orthogonal test results of hyperbaric GMAW were taken as training samples and the prediction model for weld bead geometry was established via BP neural network. Accuracy of the model was verified by comparing the prediction results with the actual welding test results. Based on the weights and thresholds in the prediction model, the weighting coefficient of each factor to the parameters of weld bead geometry was obtained by the Garson algorithm, which was verified by experiments. The results show that the weighting coefficients obtained by the multi-factor weighting method were consistent with the variation tendencies of the parameters of weld bead geometry with various factors and the weighting coefficients had a guiding role for the engineering application of hyperbaric GMAW.
  • [1] 唐德渝, 牛虎理, 薛 龙, 等. 水下高压干法GMAW焊接方法[J]. 电焊机, 2012, 42(12): 1 ? 3
    Tang Deyu, Niu Huli, Xue Long, et al. Study on underwater hyperbaric dry GMAW[J]. Electric Welding Machine, 2012, 42(12): 1 ? 3
    [2] Xue L, Wu J M, Huang J F, et al. Welding polarity effects on weld spatters and bead geometry of hyperbaric dry GMAW[J]. Chinese Journal of Mechanical Engineering, 2016, 29(2): 351 ? 356.
    [3] Hu J, Tsai H L. Metal transfer and arc plasma in gas metal arc welding[J]. Journal of Heat Transfer, 2007, 129(8): 1025 ? 1035.
    [4] Huang J Q, Xue L, Huang J F, et al. Arc behavior and joints performance of CMT welding process in hyperbaric atmosphere[J]. Acta Metallurgica Sinica, 2016, 52(1): 93 ? 99.
    [5] 黄继强, 薛 龙, 吕 涛, 等. 水下高压环境下GMAW电弧特性试验[J]. 焊接学报, 2010, 31(12): 18 ? 20
    Huang Jiqiang, Xue Long, Lü Tao, et al. Experiment on characteristics of GMAW arc in underwater hyperbaric condition[J]. Transactions of the China Welding Institution, 2010, 31(12): 18 ? 20
    [6] 刘 宏, 薛 龙, 黄继强, 等. 环境压力对熔化极气体保护焊焊缝强度及韧性的影响[J]. 上海交通大学学报, 2016, 50(10): 1613 ? 1617
    Liu Hong, Xue Long, Huang Jiqiang, et al. Influence of environmental pressure on strength and toughness of weld by Gas Metal Arc Welding[J]. Journal of Shanghai Jiao Tong University, 2016, 50(10): 1613 ? 1617
    [7] 冯 静, 薛 龙, 黄军芬, 等. 高压环境下湿度对低碳钢熔化极气体保护焊焊接质量的影响[J]. 上海交通大学学报, 2016, 50(10): 1631 ? 1634
    Feng Jing, Xue Long, Huang Junfen, et al. Influence of humidity on welding quality of gas metal arc welding in hyperbaric environment[J]. Journal of Shanghai Jiao Tong University, 2016, 50(10): 1631 ? 1634
    [8] Xie Z H, Zhang Y, Jin C. Prediction of coal spontaneous combustion in goaf based on the BP neural network[J]. Procedia Engineering, 2012, 43(7): 88 ? 92.
    [9] 唐万梅. BP神经网络结构优化问题的研究[J]. 系统工程理论与实践, 2005, 25(10): 95 ? 100
    Tang Wanmei. The study of the optimal structure of BP nueral network[J]. Systems Engineering-Theory & Practice, 2005, 25(10): 95 ? 100
    [10] Wong T C, Law K M Y, Yau H K, et al. Analyzing supply chain operation models with the PC-algorithm and the neural network[J]. Expert Systems with Applications, 2011, 38(6): 7526 ? 7534.
    [11] 韩力群.人工神经网络理论、设计及应用[M]. 北京: 化学工业出版社,2007.
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  • 收稿日期:  2017-04-07

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