Abstract
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.
Highlights
Feed systems are used to position the machine tool components carrying the cutting tool and workpiece to the desired location [1]
This paper argues that the multi-domain coupling characteristics of the feed system should be taken into account when establishing an analytical model
The wereimported importedinto into the multi-domain hybrid model ofsystem, feed system, system, the tracking tracking error could be be were thethe multi-domain hybrid model of feed the tracking error could be predicted imported into multi-domain hybrid model of feed the error could predicted by the model and the comparison between the measured results and the simulation results by the model and the comparison between the measured results and the simulation results could predicted by the model and the comparison between the measured results and the simulation results could be performed
Summary
Feed systems are used to position the machine tool components carrying the cutting tool and workpiece to the desired location [1]. Research on multi-domain integrated modeling of ball screw feed systems has been rare so far. The feed system model is usually derived from expert domain knowledge (e.g., basic physical principles) This modeling approach is called analytical modeling, known as knowledge-driven, physics-based, or mechanism modeling. Considered at system level, this paper develops a hybrid multi-domain analytical and data-driven model for the ball screw feed system to predict the tracking error. According to the law of conservation of energy, based on energy flow and symmetry transformation, a complete multi-domain system analytical model of the ball screw feed system is established.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
