模具技术Issue(6)：51-58,8.
基于机器学习的Inconel718孔增材制造工艺多目标优化
Multi objective optimization of Inconel 718 hole additive manufacturing process based on machine learning
张晶晶 1卢慧 1李艳利 1翟媛媛1
作者信息
- 1. 陕西服装工程学院,陕西 咸阳 712046
- 折叠
摘要
Abstract
This article studies the multi-objective optimization of additive manufacturing processes based on machine learning,and proposes a multi-objective optimization model for drilling machining parameters based on improved genetic algorithm.The optimal drilling parameters are solved to improve the quality and efficiency of drilling machining,thereby achieving the improvement of dimensional accuracy and machining quality of additive parts and achieving the use standards of the parts.Firstly,a multi-objective optimization model for drilling machining parameters is constructed,and then an improved genetic algorithm is used to solve it.Finally,the solution results are experimentally tested.The test results show that the optimal machining parameter combination obtained by the improved genetic algorithm in actual experiments has an average error of only 3.3％in hole size and 7.1％in hole surface roughness compared to the actual test results.This can achieve the goal of improving the dimensional accuracy and machining quality of additive parts,making them meet the usage standards,and promoting the application and promotion of additive manufacturing technology in the industrial field.关键词
机器学习/增材制造工艺/钻孔加工/遗传算法Key words
machine learning/additive manufacturing process/drilling processing/genetic algorithm分类
信息技术与安全科学引用本文复制引用
张晶晶,卢慧,李艳利,翟媛媛..基于机器学习的Inconel718孔增材制造工艺多目标优化[J].模具技术,2024,(6):51-58,8.
