基于NSGA-Ⅱ的面曝光3D打印工艺参数多目标优化
Multi-Objective Optimization of Mask Projection Stereolithography Process Parameters Based on NSGA-Ⅱ
宗学文 1韦毅博 2刘亮晶2
作者信息
- 1. 西安科技大学,机械工程学院,陕西,西安 710054
- 2. 比亚迪汽车有限公司,陕西,西安 710119
- 折叠
摘要
为改善面曝光3D打印制件的打印质量差、效率低等问题,采用非支配排序遗传算法(NSGA-Ⅱ)对工艺参数进行优化.选择温度、分层厚度、曝光时间、回合等待时间为优化变量,成型试样的变形率、表面硬度、时间为优化目标,通过单因素实验确定优化变量约束范围.根据Box-Behnken实验方案,建立各优化 目标的预测模型,使用NSGA-Ⅱ算法进行多 目标优化,规定优先精度、优先硬度、优先速度原则,按照不同优化原则分析帕累托前沿得到对应的最优工艺参数,并进行打印验证.结果表明,优先精度原则下,变形率最小值为0.508％,与优化前相比,降低了9.290％;优先硬度原则下,表面硬度最高达到95.3 HD,与优化前相比,提高了0.316％;在优先速度原则下,打印时间与优化前相比缩短了17.220％,优化效果显著.
Abstract
The non-dominant sorting genetic algorithm was proposed to optimize the process parameters in order to solve the problems of poor curing performance and low efficiency of parts made by Mask Projection Stereolithography.The temperature,layer thickness,exposure time,and round waiting time were selected as optimization variables,and the deformation rate,surface hardness,and time were taken as optimization targets,and the restrain range of optimization variables was determined through singl e factor experiment.based on Box-Behnken design experiments,the prediction model of each optimization target was established,and the NSGA-Ⅱ algorithm was used for multi-objective optimization,the principles of priority accuracy,priority hardness and priority speed were formulated,and the pareto front was analyzed according to their respective optimization principles to obtain the corresponding optimal process parameters,and experimental verification was carried out.The results showed that under the principle of priority accuracy,the minimum value of the deformation rate was 0.508％,which was reduced by 9.290％compared with before optimization;under the principle of priority hardness,the surface hardness reached 95.3 HD,which was increased by 0.316％compared with before optimization;under the principle of priority speed,the printing time was shortened by 17.220％compared with before optimization,and the optimization effect was obvious.
关键词
面曝光3D打印/工艺参数/非支配排序遗传算法/多/目标优化/优化原则Key words
mask projection stereolithography/process parameters/NSGA-Ⅱ algorithm/multi-objective optimization/optimization principle引用本文复制引用
基金项目
国家自然科学基金(51875452)
叶轮增材制造产业化应用"科学家+工程师"队伍项目(2022KXJ-012)
出版年
2024
NETL
NSTL
万方数据