Research on Transient Thermal-Structural Coupling Characteristics and Thermal Error Prediction of Ball Screw Feed System
- 21 April 2022
- journal article
- research article
- Published by SAE International in SAE International Journal of Materials and Manufacturing
- Vol. 15 (4), 313-325
- https://doi.org/10.4271/05-15-04-0020
Abstract
The thermal error of ball screw is the main factor affecting the accuracy of machine tool. Establishing an accurate thermal error model of ball screw is the key to compensate the error of machine tool. The ultimate goal of the research work in this article is to develop a comprehensive modeling method that can predict the temperature rise and thermal error of ball screw. In view of the problem that the reciprocating motion of ball screw nut was ignored in the traditional thermal error model, a transient thermal-structural coupling model considering the actual working conditions was proposed. ANSYS parametric design language (APDL) was used to set the ball screw nut as the moving heat source load, and the displacement-time relationship between the ball screw nut and the ball screw was defined. The temperature and thermal deformation distribution of the ball screw under the action of the bearing and the heat source of the ball screw nut were simulated. Then, the accuracy of the finite element model was verified by experiments. On this basis, the influence of different working conditions (feed speed, cutting load, and ball screw preload) on the temperature rise of ball screw center position was analyzed. In addition, a reliable model was proposed. Particle swarm optimization (PSO) algorithm was employed to optimize the gray neural network (GNN). The prediction was performed with its temperature rise data as input and thermal error data as output. The results show that the modeling method used in this article can well predict the thermal positioning error of the feed system. This work lays a foundation for thermal error compensation of ball screw.Keywords
This publication has 21 references indexed in Scilit:
- Thermal error modelling for a high-precision feed system in varying conditions based on an improved Elman networkThe International Journal of Advanced Manufacturing Technology, 2019
- Thermal error modeling of machine tool spindle based on the improved algorithm optimized BP neural networkThe International Journal of Advanced Manufacturing Technology, 2019
- Thermo-mechanical modelling of ball screw preload force variation in different working conditionsThe International Journal of Advanced Manufacturing Technology, 2018
- Numerical and experimental modeling of thermal errors in a five-axis CNC machining centerThe International Journal of Advanced Manufacturing Technology, 2018
- Adaptive real-time model on thermal error of ball screw feed drive systems of CNC machine toolsThe International Journal of Advanced Manufacturing Technology, 2017
- Comprehensive thermal compensation of the servo axes of CNC machine toolsThe International Journal of Advanced Manufacturing Technology, 2015
- Thermal characteristics analysis and experimental study on the high-speed spindle systemThe International Journal of Advanced Manufacturing Technology, 2015
- Time-varying positioning error modeling and compensation for ball screw systems based on simulation and experimental analysisThe International Journal of Advanced Manufacturing Technology, 2014
- Thermal error compensation method for machine centerThe International Journal of Advanced Manufacturing Technology, 2011
- Machine tool thermal error modeling and prediction by grey neural networkThe International Journal of Advanced Manufacturing Technology, 2011