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机构地区:[1]西安交通大学机械工程学院,西安710049 [2]西安交通大学机械制造系统工程国家重点实验室,西安710049
出 处:《西安交通大学学报》2013年第11期65-69,96,共6页Journal of Xi'an Jiaotong University
基 金:国家高技术研究发展计划资助项目(2012AA040701)
摘 要:为了提高数控机床的加工精度,降低由摩擦造成的轮廓误差,针对传统摩擦误差补偿方法难以达到最优补偿效果的问题,提出了一种针对数控机床进行摩擦误差自适应补偿的方法。该摩擦误差补偿方法通过摩擦补偿参数学习算法对摩擦误差补偿脉冲幅值进行粗、精学习,并采用广义回归神经网络拟合生成具有高精度的摩擦补偿脉冲幅值函数,实现了对摩擦误差自适应补偿。对XY轴工作台的摩擦误差自适应补偿实验结果表明,不同工况下过象限处的圆轮廓误差峰值及摩擦补偿效果评价值均降低55%以上,与常规矩形摩擦补偿脉冲相比,具有对伺服进给系统冲击小、摩擦补偿特性适应性强和补偿效果好的优点,能够有效地提高机床的加工精度。To improve the machining precision of numerical control machine tool and reduce contour error caused by friction,a novel adaptive compensation of friction error strategy is proposed to solve the problem that conventional method for compensation of friction error can hardly achieve desired performance.Via coarse and fine learning process for amplitude of compensation pulse,the amplitude function of friction compensation pulse is established by precision curve fitting based on generalized regression neural network algorithm,and the friction error can be compensated adaptively.The new compensation strategy is adopted on a X-Y worktable,the peak of circular contour error in quadrant and the evaluation function value of friction compensation are reduced by more than 55% under different working conditions.Compared with the conventional rectangular pulse friction compensation,the proposed approach effectively improves the machining precision of the machine tool due to the robust adaptability,lower impact on the servo feed system and better compensation performance.
分 类 号:TP271.4[自动化与计算机技术—检测技术与自动化装置]
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