摘要
基于多品种小批量零件加工成本高的问题,基于人工鱼群-遗传算法(AFSA-GA)构建了数控机床能耗模型,以实现零件加工能耗下降。首先,将数控机床功率划分为各工序功率模型,基于功率模型与工作时间关系得出机床运转能耗模型,结合产品表面粗糙度模型,对各工序能耗模型及整体粗糙度进行归一化处理,形成整体能耗模型;其次,以能耗及粗糙度为目标函数,建立AFSA-GA算法,通过对各工序能耗求解得出最适当的机床功率及其所对应的能耗和表面粗糙度;最后,针对所获得的最优功率,进行优化结果的验证,为五轴机床的实际加工提供解决方案。
Based on the high cost of multi-variety and small-batch parts processing,a numerical control machine tool energy consumption model was constructed based on artificial fish swarm genetic algorithm(AFSA-GA)to reduce the energy consumption of parts processing.Firstly,the power of CNC machine tool is divided into power model of each process,and the energy consumption model of machine tool is obtained based on the relationship between power model and working time.Combined with the product surface roughness model,the energy consumption model of each process and the overall roughness are normalized to form the overall energy consumption model.Secondly,taking energy consumption and roughness as the objective function,AFSA-GA algorithm is established,and the most appropriate machine power and its corresponding energy consumption and surface roughness are obtained by solving the energy consumption of each process.Finally,according to the optimal power obtained,the optimization results are verified,and a solution is provided for the actual processing of the five-axis machine tool.
作者
张天瑞
乔文澍
ZHANG Tianrui;QIAO Wenshu(School of Mechanical Engineering,Shenyang University,Shenyang 110003,CHN)
出处
《制造技术与机床》
北大核心
2024年第5期152-159,共8页
Manufacturing Technology & Machine Tool
基金
国家自然科学基金面上项目(52075088)
辽宁省研究生教育教学改革研究资助项目(LNYJG2022490)。
关键词
加工工艺优化
多品种小批量
零件加工
人工鱼群-遗传算法
optimization of processing process
muti-varieties and small batch
parts processing
artificial fish swarm-genetic algorithm
