高速电主轴轴承温度预测与温升影响因素分析  

Temperature Prediction and Analysis of Temperature Influence Factors for the Bearing of High Speed Motorized-Spindle

作　　者：廖敏[1] 王新新 

机构地区：[1]西华大学机械工程与自动化学院,四川成都610039 [2]渭南技师学院,陕西渭南714000

出　　处：《西华大学学报（自然科学版）》2013年第1期88-92,共5页Journal of Xihua University:Natural Science Edition

基　　金：四川省教育厅重点资助项目(10ZA101);四川省重点实验室开放研究基金资助项目(SZJJ2009-025)

摘　　要：高速电主轴轴承在运转过程中产生大量的摩擦热,而轴承温度是影响主轴系统刚度和精度的主要因素。通过高速电主轴空载运转实验,测试了在不同转速下主轴轴承的温度,获得了151组温度值;基于BP神经网络,对每个测试点温度,利用前100个温度数据进行网络构建和训练,求解了后51个数据的误差绝对值累积和,网络训练结果表明所建立的BP神经网络泛化能力强;进行了5种工况的温度预测,其预测结果表明温度预测值与实验值绝对误差小,精度高。此外,文章还分析了轴承的预紧力、主轴转速及润滑油的黏度对轴承温升的影响,其分析结果表明主轴转速是影响轴承温升的主要因素。Bearings generate a la/ge amount of frictional heat when a high speed motorized-spindle runs, and the temperature of the bearings is a main factor affecting stiffness and accuracy of the spindle. When the high speed motorized-spindle without load runs in different speeds, 151 sets of temperature are tested. Based on the principle of BP neural network, as far as each tested temperature is concerned, the former 100 temperature data are used to establish and train the network. Then the network is used to solve absolute val- ue of accumulated error of the latter 51 data. The network training results show that the BP neural network has higher generalization a- bility. Accordingly, the network is used to predict the temperature in 5 different operating conditions. The results show that there is a small absolute error between the predicted values and the experimental values. In addition, bearing preload, spindle speed and the viscosity of the iubrica＇nt are investigated so as to analyze the effect on the increase of bearing temperature. The results show that the spin- dle sneed is the main factor affecting the bearing temperature increase.

关 键 词：高速电主轴 BP神经网络 温度预测 角接触球轴承 

分 类 号：TH161.4[机械工程—机械制造及自动化]