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基于时变特性的数控机床综合误差建模方法
引用本文:李杰,刘辛军,谢福贵,李卫东,朱绍维.基于时变特性的数控机床综合误差建模方法[J].科技导报(北京),2016,34(2):65-70.
作者姓名:李杰  刘辛军  谢福贵  李卫东  朱绍维
作者单位:1. 清华大学机械工程系, 北京 100084;
2. 清华大学精密超精密制造装备及控制北京市重点实验室, 北京 100084;
3. 成都飞机工业(集团)有限责任公司, 成都 610092
基金项目:国家科技重大专项(2013ZX04001-021)
摘    要: 以立式B-A 摆头五轴数控机床为例,根据机床误差元素的时变特性,研究一种能够反映静、动态综合误差的数控机床误差建模方法。将动态误差表达为与运动单元速度、加速度相关的傅里叶级数形式,并与静态误差结合,将运动副误差元素表达为静态误差矩阵与动态误差矩阵的复合形式,利用多体系统理论构建了静、动态误差与刀具轨迹误差的映射关系模型。理论分析表明,基于时变特性的综合误差建模方法考虑了运动学、动力学两方面的影响因素,可以更准确地反映机床高速、高精加工过程产生的实际误差,从而为数控机床的误差补偿及控制参数整定奠定一定的理论基础。

关 键 词:数控机床  误差建模  动态误差  误差补偿  控制参数整定  
收稿时间:2015-08-21

A comprehensive error modeling method for numerical control machine tools based on time-varying characteristics
LI Jie,LIU Xinjun,XIE Fugui,LI Weidong,ZHU Shaowei.A comprehensive error modeling method for numerical control machine tools based on time-varying characteristics[J].Science & Technology Review,2016,34(2):65-70.
Authors:LI Jie  LIU Xinjun  XIE Fugui  LI Weidong  ZHU Shaowei
Institution:1. Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China;
2. Beijing Key Lab of Precision/Ultra-precision Manufacturing Equipments and Control, Tsinghua University, Beijing 100084, China;
3. Chengdu Aircraft Industrial (Group) Co., Ltd., Chengdu 610092, China
Abstract:Based on the time-varying characteristics of the error components, a comprehensive error modeling method for a B-A swiveling head 5-axis machine tool is proposed. First, the dynamic error components are expressed as the Fourier series that are associated with the speed and the acceleration of the moving platform. Then, joint error transformation matrixes are modeled as the synthesis of the static and dynamic error transformation matrixes. Subsequently, the error mapping between the trajectory errors of the cutting tool and the joint error sources are constructed based on the MBS method. Finally, a theoretical analysis is made and the results show that both the kinematic and dynamic accuracy impacting factors are considered in this method, which can reflect the machining errors of the machine tools more accurately and also provide a solid foundation for the error compensation and the control parameter modulation.
Keywords:numerical control machine tool  error modeling  dynamic error  error compensation  control parameter modulation  
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