摘要
数控机床切削加工过程中能量源多、工况复杂多变,使其能耗难以预测。基于数控机床切削原理,分析切削参数对切削加工过程能耗的影响;采用高斯过程回归方法,建立一种以数据为驱动的数控机床能耗预测模型;引入差分进化算法对其进行优化。通过数控机床加工数据仿真,验证了所建模型的有效性和可行性。
In the cutting process of CNC machine tools,there are many energy sources and the working conditions are complex and changeable,making it difficult to predict energy consumption.Based on the cutting principle of CNC machine tools,the influence of cutting parameters on energy consumption of cutting process was analyzed.A Gaussian process regression method was used to establish a data-driven prediction model of energy consumption for CNC machine tools.The differential evolution algorithm was used to optimize it.The data simulation of CNC machine tools validates the feasibility and effectiveness of the model.
作者
宋李俊
潘安大
Jing Shi
陈猛
SONG Lijun;PAN Anda;Jing Shi;CHEN Meng(College of Mechanical Engineering, Chongqing University of Technology,Chongqing 400054, China;College of Mechanical and Material Science,University of Cincinnati, Cincinnati 45242, America)
出处
《重庆理工大学学报（自然科学）》
CAS
北大核心
2018年第11期52-57,共6页
Journal of Chongqing University of Technology：Natural Science
基金
教育部人文社会科学研究项目(15YJCZH049)
重庆市基础科学与前沿技术研究项目(cstc2016jcyjA0385)
重庆市教委科学技术研究项目(15SKG133)
关键词
数控机床
能耗预测
高斯过程回归
差分进化
CNC machine tool
energy consumption prediction
Gaussian process regression
differential evolution
