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基于神经网络的粉末冶金材料激光焊接工艺优化

唐霞辉, 秦应雄, 钟如涛, 周金鑫, 李正佳

唐霞辉, 秦应雄, 钟如涛, 周金鑫, 李正佳. 基于神经网络的粉末冶金材料激光焊接工艺优化[J]. 激光技术, 2006, 30(5): 471-475.
引用本文: 唐霞辉, 秦应雄, 钟如涛, 周金鑫, 李正佳. 基于神经网络的粉末冶金材料激光焊接工艺优化[J]. 激光技术, 2006, 30(5): 471-475.
TANG Xia-hui, QIN Ying-xiong, ZHONG Ru-tao, ZHOU Jin-xin, LI Zheng-jia. Optimizing laser welding parameters of powder metallurgical material based on artificial neural network[J]. LASER TECHNOLOGY, 2006, 30(5): 471-475.
Citation: TANG Xia-hui, QIN Ying-xiong, ZHONG Ru-tao, ZHOU Jin-xin, LI Zheng-jia. Optimizing laser welding parameters of powder metallurgical material based on artificial neural network[J]. LASER TECHNOLOGY, 2006, 30(5): 471-475.

基于神经网络的粉末冶金材料激光焊接工艺优化

基金项目: 

国家“十五”科技攻关资助项目(2002BA217C)

详细信息
    作者简介:

    唐霞辉(1963- ),男,博士,副教授,主要从事高功率CO2激光技术及应用方面的研究.E-mail:txh1116@hust.edu.cn

  • 中图分类号: TG465.7

Optimizing laser welding parameters of powder metallurgical material based on artificial neural network

  • 摘要: 针对薄壁金刚石钻头的激光焊接应用,采用德国LSM240全自动激光焊接系统进行单面焊接试验,建立了粉末冶金材料激光焊接工艺优化的误差反向传播人工神经网络模型,应用该模型研究了激光焊接工艺参数对气孔率和焊缝强度等焊接质量因素的影响,并对薄壁金刚石钻头激光焊接进行了工艺参数优化处理,获得了无气孔缺陷的优质焊接接头。结果表明,气孔率同激光功率、焊接速度之间具有幂函数关系;焊缝强度同激光功率、焊接速度之间具有高斯函数关系。
    Abstract: The model for optimizing laser welding parameters of powder metallurgical material on back propagation(BP) artificial neural network was presented for laser welding application of thin-wall diamond core driller.The effects of laser welding parameters on porosity and welding strength were investigated with the model on the basis of one-side laser welding experiment by LSM240 auto-welding system.Laser welding parameters of thin-wall diamond core driller were optimized with the model,high quality laser welding seam with porosity defect are obtained.The results showed that the mathematic relation of the porosity with laser power and welding speed was power function and the mathematic relation of the welding strength with laser power and welding speed was Gaussian function.
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出版历程
  • 收稿日期:  2006-01-04
  • 修回日期:  2006-02-19
  • 发布日期:  2006-09-24

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