摘要
针对传统开环、同一化循环控温策略对电主轴单元结构温度场及精度稳定性控制方面的不利影响,基于PID控制与BP神经网络相结合的方式,提出了一种适用于电主轴单元结构的差异化和闭环稳定性温控策略,借助BP神经网络实现了PID控制策略在电主轴单元结构温度闭环控制中关键参数的自适应动态调整.最后,通过对比试验的方式验证了BP-PID差异化、闭环温控策略在电主轴单元结构温度场稳定性控制、热误差抑制方面的有效性,有利于精密机床精度及精度稳定性控制的实现.
In order to solve the negative influence of traditional open-loop and uniform recirculation cooling strategy on the temperature field and accuracy stability control of electric spindle unit,a differentiated and close-loop stability strategy on spindle temperature control was developed,based on the combination of PID control andBP neural network.This strategy realized the self-adaptive dynamic regulation of PID critical parameters with the help of BP neural network.Finally,the comparison experiments verified that the presentedBP-PID differentiated and close-loop temperature control strategy is more advantageous in spindle temperature field stabilization and thermal error decrease.Moreover,this strategy can contribute to the improvements of accuracy and accuracy stability of precision machine tools.
出处
《天津大学学报（自然科学与工程技术版）》
EI
CSCD
北大核心
2017年第8期885-891,共7页
Journal of Tianjin University：Science and Technology
基金
高档数控机床与基础制造装备科技重大专项项目(2012ZX04012-031
2013ZX04005-013
2014ZX04014-011
2015ZX04005001
2016ZX04004-002)
河北省自然科学基金青年基金资助项目(E2017202194)
河北省普通高等学校青年拔尖人才计划项目(BJ2017039)~~
关键词
电主轴
BP-PID
闭环稳定性温控
温度场
热误差
electric spindle
BP-PID
close-loop stability temperature control
temperature field
thermal error
