车床主轴温度测量及基于神经网络的热误差预测

Temperature Measurement of Lathe Spindle and Thermal Error Prediction Based on Neural Network

在精密加工中,热误差对加工精度的影响不容忽视。为了精准预测热误差对车床主轴的影响,文章基于Arduino设计了温度测量系统,并配合千分表测量了主轴径向圆跳动随温度的变化情况。根据测量数据采用BP神经网络建立了车床主轴径向跳动热误差模型,通过该预测模型的结果可以采用BP神经网络来对车床主轴径向跳动热误差来进行分析预测。

In precision machining,the influence of thermal error on machining accuracy cannot be ignored.In order to accurately predict the influence of thermal error on the lathe spindle,a temperature measurement system is designed based on Arduino,and the variation of the radial runout of the main shaft with temperature change is measured using a dial indicator.Based on the measured data,a thermal error model of lathe spindle radial runout is established using BP neural network.The results of the prediction model can be used to analyze and predict the thermal error of lathe spindle radial runout using BP neural network.