丝杠驱动进给系统的径向振动特性直接影响机床加工精度和可靠性,其径向振动特性主要受到轴承、螺母和导轨的径向刚度、阻尼的影响。当前,各部件之间的结合面参数辨识方法还不成熟,因此,文中基于Timoshenko梁的传递矩阵法预测进给系统频响函数,并利用改进的粒子群优化算法(Particle Swarm Optimization)最小化理论和实验结果,辨识轴承、螺母和导轨的径向刚度、阻尼。比较结果发现,预测和实验结果一致性较好,表明文中提出的辨识方法能够有效辨识进给系统结合面参数。
The radial vibration performance of the feeding system with nut screw drive can affect directly the accuracy and reliability of machine tools,and the radial vibration performance was primarily influenced by the radial stiffness and damping of bearing,nut and guideway. Currently,there is no a mature algorithm in the identification of the parameters at each interface of parts. Therefore,the transfer matrix method based on Timoshenko beam were used to predict frequency response functions of the feeding system,and improved Particle Swarm Optimization( PSO) algorithm was used to determine the radial stiffness and damping of bearing,nut and guideway by minimizing theory and experimental results. Comparison results show that the predicted and experimental results show a good agreement,which demonstrate the proposed identification method is well valid in the recognition of the interface parameters at the feeding system.