首页|激光熔化沉积Al-Mg-Sc-Zr合金单熔道成形质量预测

激光熔化沉积Al-Mg-Sc-Zr合金单熔道成形质量预测

扫码查看
原文链接
  • NETL
  • NSTL
  • 万方数据
  • 维普
本研究探讨了激光熔化沉积(LMD)工艺参数对Al-Mg-Sc-Zr合金单熔道成形质量的影响,并采用BP神经网络模型和改进的PSO-BP神经网络模型预测了不同工艺参数下的成形孔隙率.结果表明:Al-Mg-Sc-Zr合金的LMD单熔道成形孔隙率,随着激光线能量密度的增加呈现先上升后下降再上升的趋势,在175 J/mm2时孔隙率达到最小值,仅为1.38%.在相同的送粉工艺参数下,LMD成形熔道宽度和熔道深度均与激光功率呈现出正相关性,而熔道高度和熔道深度均与扫描速率呈现出负相关性.相较于BP神经网络模型,改进的PSO-BP神经网络模型的平均绝对误差降低了29.69%,平均相对误差降低了19.42%,均方误差降低了19.02%,相关系数提升了63.44%.
Prediction of single-track forming quality in laser melting deposition of Al-Mg-Sc-Zr alloy
The influence of laser melting deposition(LMD)process parameters on the forming quality of a single-track Al-Mg-Sc-Zr alloy was investigated.A BP neural network model and an improved PSO-BP neural network model were employed to predict the porosity rate of the formed track under different LMD parameters.The results demonstrate that the porosity rate firstly increases,then decreases,and finally increases with laser line energy density increasing.When the laser line energy density was 175 J/mm2,the porosity rate displays a minimum value,which is 1.38%.Under the same powder feeding rate,the width and depth of the track show a positive correlation with laser power,while the height and depth of the track illustrate a negative correlation with scanning speed.In contrast to the BP neural network model,the average absolute error of the improved PSO-BP neural network model is reduced by 29.69%,the average relative error of the improved PSO-BP neural network model is reduced by 19.42%,the mean square error of the improved PSO-BP neural network model is reduced by 19.02%and the correlation coefficient of the improved PSO-BP neural network model is improved by 63.44%.

laser melting depositionAl-Mg-Sc-Zr alloymelting track qualityporosity rateneural network

肖罡、李伟奇、谢莉、路超、刘筱、朱必武、杨钦文

展开 >

湖南科技大学 机电工程学院,湘潭 411201

江西铜业技术研究院有限公司,南昌 330096

湖南大学 机械与运载工程学院,长沙 410082

广东海洋大学 材料科学与工程学院,阳江 529559

展开 >

激光熔化沉积 Al-Mg-Sc-Zr合金 熔池质量 孔隙率 神经网络

国家自然科学基金国家自然科学基金江西省高层次高技能领军人才培养工程项目江西省杰出青年基金湖南省自然科学基金湖南省自然科学基金湖南省自然科学基金湖南省教育厅科研项目

520751595207113920224ACB2180022023JJ302522023JJ302622022JJ3001921B0471

2024

10.11817/j.ysxb.1004.0609.2023-44626

中国有色金属学报
中国有色金属学会

中国有色金属学报

CSTPCD北大核心
影响因子：1.108
ISSN：1004-0609
年,卷(期)：2024.34(4)
  • 33