摘要
综合运用模糊聚类和灰色关联度理论对机床温度监测传感器进行了优选。同时针对现行常用的多元回归模型,采用自回归分布滞后模型(ADL模型)对数控机床热误差进行了建模。在获得较高精度基础上,对ADL模型进行扩展,提出了高次多阶ADL建模技术,并对其建模方法及精度进行了分析比对,实例证明,提出的高次多阶ADL模型在数控机床热误差补偿技术中具有较高的建模精度。
Based on the synthesis of the fuzzy clustering and gray relational theory, the temperature sensors for monitoring CNC machine tools were optimized. According to the commonly used multiple regression model,this paper used ADL model to model the thermal error of CNC machine tools. On the basis of better accuracy, we expanded the ADL model and proposed a new high order and multi-level ADL modeling technique, also, analysed its modeling method and accuracy. It shows that the high order and multi-level ADL model has better accuracy in the thermal error compensation of CNC machine tools by the examples presented herein.
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2013年第15期2088-2093,共6页
China Mechanical Engineering
基金
国家自然科学基金资助项目(51175142)
国家科技重大专项(2009ZX04014-023-02)
国家重点实验室开放课题(2010006)
关键词
热误差
多元回归模型
自回归分布滞后模型
高次多阶自回归分布滞后模型
thermal error
multiple regression model
autoregressive distributed lag（ADL） model
high order and multi--level autoregressive distributed lag model
