基于改进GEP的数控机床切削加工能耗预测研究  

Research on CNC Machine Tool Cutting Energy Consumption Prediction Based on Improved GEP

作　　者：石杨斌 张梦洋 SHI Yang-bin;ZHANG Meng-yang(School of Mechanical and Electrical Engineering,Xi'an Polytechnic University,Xi'an 710048,China)

机构地区：[1]西安工程大学机电工程学院,西安710048

出　　处：《价值工程》2021年第5期239-240,共2页Value Engineering

摘　　要：针对数控机床高能耗问题,提出一种基于传统基因表达式编程算法和共轭梯度法的优化算法。利用传统基因表达式编程算法对数控机床的进给量、切削速度和切削深度进行编码,通过适应度函数获得相应适应度值后应用于父代种群交叉、变异和插串等遗传操作。之后运用共轭梯度法对子代种群进行局部寻优,找出最优种群,从而构建数控机床能耗预测模型。结果表明,该模型对数控机床切削加工期间的能耗具有良好的预测效果,说明了模型的有效性和可行性。Aiming at the problem of high energy consumption of CNC machine tools,an optimization algorithm based on traditional gene expression programming algorithm and conjugate gradient method is proposed.The feed rate,cutting speed and cutting depth of CNC machine tools are coded by traditional gene expression programming algorithm.The corresponding fitness values are obtained by fitness function and applied to genetic operations such as parent population crossover,mutation and string insertion.After that,conjugate gradient method is used to optimize the offspring population locally,and the optimal population is found out,so as to construct the energy consumption prediction model of CNC machine tools.The results show that the model has a good prediction effect on the energy consumption during the cutting process of CNC machine tools,which shows the validity and feasibility of the model.

关 键 词：改进基因表达式编程算法 数控机床 切削加工能耗 能耗预测 

分 类 号：TH17[机械工程—机械制造及自动化]