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基于神经网络和遗传算法的三维打印工艺参数优化

李淑娟 陈文彬 刘永 符柳

李淑娟, 陈文彬, 刘永, 符柳. 基于神经网络和遗传算法的三维打印工艺参数优化[J]. 机械科学与技术, 2014, 33(11): 1688-1693. doi: 10.13433/j.cnki.1003-8728.2014.1116
引用本文: 李淑娟, 陈文彬, 刘永, 符柳. 基于神经网络和遗传算法的三维打印工艺参数优化[J]. 机械科学与技术, 2014, 33(11): 1688-1693. doi: 10.13433/j.cnki.1003-8728.2014.1116
Li Shujuan, Chen Wenbin, Liu Yong, Fu Liu. Optimization of the 3DP Printing Parameters Based on the Neural Networks and Genetic Algorithm[J]. Mechanical Science and Technology for Aerospace Engineering, 2014, 33(11): 1688-1693. doi: 10.13433/j.cnki.1003-8728.2014.1116
Citation: Li Shujuan, Chen Wenbin, Liu Yong, Fu Liu. Optimization of the 3DP Printing Parameters Based on the Neural Networks and Genetic Algorithm[J]. Mechanical Science and Technology for Aerospace Engineering, 2014, 33(11): 1688-1693. doi: 10.13433/j.cnki.1003-8728.2014.1116

基于神经网络和遗传算法的三维打印工艺参数优化

doi: 10.13433/j.cnki.1003-8728.2014.1116
基金项目: 

国家973项目(2009CB724406)

陕西省工业攻关项目(2012K07-25)资助

详细信息
    作者简介:

    李淑娟(1965- ),教授,博士生导师,研究方向为直接数字制造技术,shujuanli2009@gmail.com。

Optimization of the 3DP Printing Parameters Based on the Neural Networks and Genetic Algorithm

  • 摘要: 分析了粉末材料三维打印(three dimensional printing,3DP)过程中影响成型精度的因素,采用试验的方法确定打印过程中的三维制件的收缩率范围.以“H”型工件为标准,建立了基于神经网络(neural network,NN)的制件尺寸精度误差和打印工艺参数之间关系的模型.以制件最小尺寸误差为目标,采用遗传算法(genetic algorithm,GA)对3DP中的工艺参数如饱和度、层厚和X、Y、Z这3个方向的收缩补偿值进行优化,获得了相应的打印工艺参数.采用3DP默认的打印参数、打印参数的最小值、最大值以及NN-GA得到的参数进行对比试验.结果表明:采用NN-GA获得的工艺参数打印的制件的尺寸误差最小,可以预测3DP成型制件相对尺寸误差.
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  • 收稿日期:  2013-04-10

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