数控机床热误差动态灰色优化建模研究  

Research on Dynamic Grey Optimization Modeling for Thermal Error in Numerical Control Machine

作　　者：李一民[1] 

机构地区：[1]南京信息职业技术学院机电学院,江苏南京210046

出　　处：《机床与液压》2011年第11期54-57,60,共5页Machine Tool & Hydraulics

基　　金：江苏省自然科学基金资助项目(BK200606060)

摘　　要：为降低热误差对加工精度的影响,以减少补偿成本、简化数据采集、提高补偿精度为目标,提出采用灰色GM(0,N)模型进行数控机床热误差建模预测;以优化数据配置、改善补偿系统动态品质、提高鲁棒性为目的,建立了GM(0,N)优化模型。采用智能温度传感器和位移传感器采集了MCH63精密卧式加工中心温度数据和主轴3个方向热位移量,并根据采集数据构建热误差模型。试验结果表明:GM(0,N)建模方法简单,数据量少,运算时间短,预测精度较高;优化模型可根据在线输入的新数据不断修正模型本身,其精度高、鲁棒性强、通用性好,适合于在线建模。To reduce thermal error＇s influence on machining accuracy,a grey GM（0,N）model was presented for predicting CNC machine＇s thermal error with the aim of lowering compensation cost,simplifying data collection process and improving compensation accuracy.The GM（0,N）optimized model was established,which could optimize data allocation,improve system dynamic character and enhance robustness.Intelligent temperature sensors and displacement sensors were used to collect temperature data and spindle＇s thermal displacement information in the three directions of precise horizontal machining centre MCH63.Thermal error model was built up with the collected data.The experimental results show that the GM（0,N）modeling method is simple with less data,short operation time and higher predication accuracy,and the optimal model can modify itself due to input new data on line with high accuracy,good robustness and general usage,which is fit for modelling on line.

关 键 词：数控机床 热误差 建模 优化 

分 类 号：TG659[金属学及工艺—金属切削加工及机床]