Intelligent Control of the Linear Motor Direct Drive Feed System for CNC Machine Tools

Author(s):  
Shuhong Xiao ◽  
Guangyuan Zheng ◽  
Shuquan Chen
2014 ◽  
Vol 945-949 ◽  
pp. 1700-1706
Author(s):  
Rong Bo Shi ◽  
Zhi Ping Guo ◽  
Zhi Yong Song

This paper studies control and motion theory of feed system of the five-axis CNC machine tools, propose the method of establish mathematical model, kinematics model of the feed system, in order to provide a method of theoretical research for accuracy identification of five-axis CNC machine tools.


2016 ◽  
Vol 836-837 ◽  
pp. 584-591
Author(s):  
Xiao Jun Yang ◽  
Cheng Fang Ma ◽  
Yan Li ◽  
Dun Lv ◽  
Jun Zhang ◽  
...  

With the development of the high-speed and high-precision CNC machine tools, the interaction between mechanical system and servo drive torque in the feed system becomes more and more serious which affects the surface quality of the workpiece. In this paper, taking a small-sized vertical milling center as the research object, the characteristics of servo torque and mechanical system are analyzed, respectively. Then the influence of electromechanical matching on the tracking fluctuation of the feed system is discussed. Furthermore, aiming at the surface roughness of the workpiece, the influence of the interaction between servo torque and mechanical system on the surface quality of the workpiece is analyzed under different milling ways. Finally, a large number of experiments are carried out to verify the analysis above. At last, the optimization methods of machining precision based on electromechanical matching are put forward. It can be found that in the high-speed machining, the servo torque has lots of harmonics which act on the mechanical system with kinds of modals, leading to the vibration. The surface quality of the workpiece will be deteriorated rapidly when the mode of vibration is consistent with the sensitive direction of machining error. The surface quality of the workpiece can be significantly improved through optimizing the feed velocity and the processing method and realizing the electromechanical matching.


Symmetry ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1156 ◽  
Author(s):  
Zaiwu Mei ◽  
Jianwan Ding ◽  
Liping Chen ◽  
Ting Pi ◽  
Zaidao Mei

Position error-compensation control in the servo system of computerized numerical control (CNC) machine tools relies on accurate prediction of dynamic tracking errors of the machine tool feed system. In this paper, in order to accurately predict dynamic tracking errors, a hybrid modeling method is proposed and a dynamic model of the ball screw feed system is developed. Firstly, according to the law of conservation of energy, a complete multi-domain system analytical model of a ball screw feed system was established based on energy flow. In order to overcome the uncertainties of the analytical model, then the data-driven model based on the back propagation (BP) neural network was established and trained using experimental data. Finally, the data-driven model was coupled with the multi-domain analytical model and the hybrid model was developed. The model was verified by experiment at different velocities and the results show that the prediction accuracy of the hybrid model reaches high levels. The hybrid modeling method combines the advantages of analytical modeling and data-driven modeling methods, and can significantly improve the feed system’s modeling accuracy. The research results of this paper are of great significance to improve the compensation control accuracy of CNC machine tools.


Author(s):  
Michael A. Stephens ◽  
Chris Manzie ◽  
Malcolm C. Good

The high performance demands on commercial computer numerical control (CNC) machine tools have led to the widespread adoption of direct-drive servo axes. In industrial machines, where the workpiece is manipulated by the axis, the plant dynamics seen by the control system may vary widely between different workpieces. These changing plant dynamics have been observed to lead to limit-cycle behavior for a given controller. In such a situation, conventional modeling approximations used by practitioners may fail to predict the onset of instability for these axes. This work demonstrates the failure of conventional modeling approximations to predict the observed instability in an industrial CNC servo axis and investigates the model fidelity required to replicate the observations. This represents an important consideration when designing model-based controllers for direct-drive axes in CNC machines.


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