数控机床热变形误差超前预测研究  

Research on the Thermal Deformation Errors Prediction of CNC Machine Tools

作　　者：于博 王利涛[1] 陈志红[1] 胡月[2,3] YU Bo;WANG Litao;CHEN Zhihong;HU Yue(School of Mechanical and Electrical Engineering,Changchun Institute of Technology,Changchun Jilin 130012,China;School of Mechanical and Electrical Engineering,Changchun University of Science and Technology,Changchun Jilin 130012;Department of Physics and Electronic Engineering,Hebei Normal University for Nationalities,Chengde Hebei 067000,China)

机构地区：[1]长春工程学院机电工程学院,吉林长春130012 [2]长春理工大学机电工程学院,吉林长春130012 [3]河北民族师范学院物理与电子工程学院,河北承德067000

出　　处：《机床与液压》2023年第4期75-79,共5页Machine Tool & Hydraulics

基　　金：吉林省科技厅自由探索一般项目(YDZJ202201ZYTS391)。

摘　　要：针对当前数控机床热变形误差实施补偿存在的预测值滞后实际补偿值问题,提出基于长短期记忆(LSTM)神经网络算法热误差超前预测解决方案,详细探讨LSTM神经网络算法的解析流程,建立基于LSTM神经网络算法热误差超前预测模型,并进行关键温测点及热变形误差超前预测实验。实验结果表明:热变形误差实际值与预测值的最大残差、平均值和均方差均在可控范围内,超前预测的准确度为86.3%,进一步论证了机床热变形误差超前预测的有效性。Aiming at the problem that the prediction value lags behind the actual compensation value in the CNC machine tool thermal deformation error compensation,a thermal error advance prediction solution based on the long and short-term memory(LSTM)neural network algorithm was proposed,and the analytical process of LSTM neural network algorithm was discussed in detail.The thermal error advance prediction model of the neural network algorithm based on LSTM was established,and the key temperature measurement points and the thermal deformation error advance prediction experiment were carried out.The experimental results show that the maximum residual,the average value and the mean square error of the actual value of the thermal deformation error and the predicted value are all within the controllable range,and the accuracy of the advance prediction is 86.3%,which further demonstrates the effectiveness of the advance prediction of the thermal deformation error of the machine tool.

关 键 词：热变形误差 长短期记忆 神经网络算法 超前预测建模 关键温测点 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]