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作 者:高研 石广丰 孟巳崴[1] 邹春阳 姚栋 Gao Yan;Shi Guangfeng;Meng Siwei;Zou Chunyang;Yao Dong(School of Electro Mechanic Engineering,Changchun University of Science and Technology,Changchun 130000,China;不详)
机构地区:[1]长春理工大学重庆研究院,长春市130000 [2]长春理工大学机电工程学院
出 处:《工具技术》2024年第12期105-109,共5页Tool Engineering
基 金:国家自然科学基金面上项目(52375405);吉林省科技厅自然科学基金面上项目(20240101078JC);吉林省教育厅科学技术研究项目(JJKH20230809KJ,JJKH20240913KJ)。
摘 要:在激光加热过程中,被加热材料的温度变化会对加工精度产生重大影响。为准确了解激光辐照材料引起的物理效应,根据激光加热的实际情况,建立材料表面升温的三维热传导模型。通过COMSOL Multiphysics有限元计算软件建立材料温度场的数值模型,得到在激光辐照下的温升与热变形规律,改变实验参数获得不同加工条件下的工件温度分布模型,并在此基础上建立基于GA-BP神经网络算法的温度分布预测模型。结果表明,基于GA-BP神经网络算法的温度分布预测模型可以迅速计算改变加工参数时的工件温度并预测温度分布情况,预测的平均绝对误差为27.22K,相关系数为0.97。In the process of laser-assisted machining,the temperature change of the material processed have a significant impact on the machining accuracy.In order to accurately understand the physical effects caused by laser irradiation on materials,a three-dimensional heat conduction model of heat transfer between material surface and tool is established according to the actual situation of laser-assisted machining.Through finite element calculation software COMSOL Multiphysics,the numerical simulation of the temperature field of the processed material is established,the law of temperature rise and thermal deformation under laser irradiation is obtained.By changing the experimental parameters,the two-dimensional temperature distribution model of the workpiece under different processing conditions is obtained.On this basis,a temperature distribution prediction model based on GA-BP neural network algorithm is established.The results show that the temperature distribution prediction model based on GA-BP neural network algorithm can quickly calculate the radial temperature distribution of workpiece when the processing parameters are changed and predict the temperature distribution.The average absolute error of the prediction value is 27.22K,and the correlation coefficient is 0.97.
分 类 号:TG506[金属学及工艺—金属切削加工及机床] TH16[机械工程—机械制造及自动化]
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