Identification and optimization of CNC dynamics in time-dependent machining processes and its validation to fluid jet polishing
Identification and optimization of CNC dynamics in time-dependent machining processes and its validation to fluid jet polishing
复制标题
瞬态加工过程中 CNC 动力学的识别和优化及其对流体喷射抛光的验证
DOI：
10.1016/j.ijmachtools.2020.103648
复制
发表时间：
2020
影响因子：
14
通讯作者：
Beaucamp Anthony
中科院分区：
文献类型：
--
作者：
Mizoue Yuichi;Sencer Burak;Beaucamp Anthony
在诸如抛光的时间依赖性CNC工艺中，通过创建具有变化进给的G代码并将其输入到机床的控制器中来获得目标材料去除轮廓。输入的G代码首先由CNC滤波器滤波，然后实时生成的信号进入机床的进给驱动系统。通过这些步骤，原始信号失真，并且在某些区域不能实现理想的馈电轮廓。这种变形影响材料去除分布，从而影响最终抛光表面轮廓的精度。虽然已经开发了一些方法来预测抛光表面，他们中的大多数未能考虑控制器动态的影响。本文提出了一种精确预测抛光表面的方法，该方法考虑了控制信号失真的误差贡献，并提出了补偿该误差的策略。首先，阐述了机床控制系统行为辨识的原理，介绍了流体喷射抛光的过程模型。其次，辨识控制系统的传递函数，并根据实验数据对过程模型进行标定。第三，结合控制系统和工艺模型，实现了一个用于预测抛光表面轮廓的模拟器。通过微槽抛光实验验证了该方法的可靠性，并指出了其局限性。最后，提出了一种基于粒子群优化的算法来减少控制器动态特性对微槽抛光的影响。
In time dependent CNC processes such as polishing, a target material removal profile is obtained by creating and inputting G-codes with varying feed into the controller of a machine tool. The input G-codes are firstly filtered by a CNC interpolator, and the real-time generated signal then goes to a feed drive system of the machine. Through these steps, the original signal is distorted and the ideal feed profile cannot be achieved in some areas. This distortion affects the material removal distribution, and thus the accuracy of the final polished surface profile. While a number of methods have been developed for predicting polished surfaces, most of them fail to consider the influence of controller dynamics. In this paper, a method for accurate prediction of polished surfaces is proposed that considers the error contribution from control signal distortion, and a strategy for compensation of this error. Firstly, the principles of identification of control system behavior in a machine tool are explained, and a process model for Fluid Jet Polishing (FJP) is introduced. Secondly, the transfer functions of the control system are identified, and the process model calibrated against experimental data. Thirdly, a simulator for predicting polished surface profiles is implemented that combines the control system and process model. A micro-groove polishing experiment is carried out that validates the reliability of the proposed method, and shows its limitations. Finally, an algorithm based on particle swarm optimization is proposed for reducing the impact of controller dynamics in micro-groove polishing.
用于轮廓仿真的 5 轴机床进给驱动系统识别
DOI：
10.20965/ijat.2011.p0377
发表时间：
2011
期刊：
Int. J. Autom. Technol.
影响因子：
--
作者：
B. Sencer;Y. Altintas
通讯作者：
Y. Altintas
DOI：
10.1016/j.ijmachtools.2015.09.006
发表时间：
2015-12-01
影响因子：
14
作者：
Guillerna, A. Bilbao;Axinte, D.;Billingham, J.
通讯作者：
Billingham, J.