3D打印机送丝机构和喷嘴协同优化研究

周石林, 张秀芬

机床与液压 ›› 2023, Vol. 51 ›› Issue (13) : 27-33.

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PDF(16757 KB)
机床与液压 ›› 2023, Vol. 51 ›› Issue (13) : 27-33. DOI: 10.3969/j.issn.1001-3881.2023.13.005
试验与研究

3D打印机送丝机构和喷嘴协同优化研究

  • 周石林1,2, 张秀芬1,2
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Collaborative Optimization of Wire Feeding Mechanism and Nozzle for 3D Printer

  • ZHOU Shilin1,2, ZHANG Xiufen1,2
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摘要

为提高3D打印机出丝的连续性与稳定性,提出送丝机构和喷嘴协同优化方法,克服了已有的打印机喷嘴和送丝机构单独优化而忽略两者之间耦合效应的不足。以喷嘴加热段长度、散热段长度、出口长度、送丝速度为优化参数,以喷嘴截面平均速度和平均温度为优化目标,设计正交试验,进行流体仿真。为快速得到最优方案,基于神经网络与NSGA-Ⅱ算法进行优化分析,结果表明:加热段长度为6 mm、散热段长度为4 mm、出口长度为0.7 mm、送丝速度为4.5 mm/s时,最大喷嘴截面平均速度为78 mm/s,最大平均温度为208.39 ℃,最大平均速度提高2.6%,最大平均温度提高1.22%。以最佳工艺参数组合进行流体仿真验证,结果表明:喷嘴截面平均速度与温度确实明显提高。

Abstract

In order to improve the continuity and stability of 3D printer wire,a collaborative optimization method of wire feeding mechanism and nozzle was proposed,which overcome the deficiency that the nozzle and wire feeding mechanism of printer are optimized separately while the coupling effect between them is ignored.Taking the heating section length,the cooling section length,the outlet length and the wire feeding speed as the optimization parameters,and taking the average velocity and average temperature of the nozzle section as the optimization objectives,the orthogonal test was designed and the fluid simulation was carried out.In order to quickly obtain the optimal scheme,neural network and NSGA-Ⅱ algorithm were used to optimize the analysis. The results show that when the heating section length is 6 mm,the cooling section length is 4 mm,the outlet length is 0.7 mm,and the wire feeding speed is 4.5 mm/s,the maximum average velocity of the nozzle section is 78 mm/s,and the maximum average temperature is 208.39 ℃.The maximum average speed and maximum average temperature are increased by 2.6% and 1.22% respectively.Finally,fluid simulation was carried out by using the optimized combination of process parameters. The results show that the average velocity and temperature of nozzle section are obviously improved.

关键词

3D打印 / 协同优化 / 正交试验设计 / 流体仿真 / 神经网络 / 遗传算法

Key words

3D Printing / Collaborative optimization / Orthogonal experimental design / Fluid simulation / Neural network / Genetic algorithm

引用本文

导出引用
周石林, 张秀芬. 3D打印机送丝机构和喷嘴协同优化研究[J]. 机床与液压, 2023, 51(13): 27-33 https://doi.org/10.3969/j.issn.1001-3881.2023.13.005
ZHOU Shilin, ZHANG Xiufen. Collaborative Optimization of Wire Feeding Mechanism and Nozzle for 3D Printer[J]. Machine Tool & Hydraulics, 2023, 51(13): 27-33 https://doi.org/10.3969/j.issn.1001-3881.2023.13.005

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基金

国家自然科学基金(51965049)
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