Title :
The Research on Thermal Error Modeling and Compensation on Machine Tools
Author :
Bing Ren ; Xiaohong Ren ; Shan Huang ; Guozhi Li
Author_Institution :
Dept. of Autom. & Electron. Inf., Sichuan Univ. of Sci. & Eng. Zigong, Zigong, China
Abstract :
To diminish the thermal error and to enhance the machining precision of CNC machines, thermal error compensation is an effective way. Taking GMC4000H/2 machining center as research object, this paper focuses on the thermal compensation skills of machine tools. Firstly, detection method of thermal deformation error on machine tool was introduced. And then, this paper established compensation models between measured temperature parameters and thermal error parameters using PSO-BP neural network. Finally, a thermal compensation controller that was used to implement error compensation was developed. The thermal compensation controller hardware and simulation result were given. The simulation experimentation showed that the PSOBP neural network can enhance precision from 93μm to 13μm, and also the model had good performance of compensation and fitting.
Keywords :
backpropagation; computerised numerical control; machine tools; neural nets; particle swarm optimisation; production engineering computing; CNC machine; GMC4000H/2 machining center; PSO-BP neural network; machine tool; machining precision; temperature parameter measurement; thermal compensation controller; thermal compensation skill; thermal deformation error detection method; thermal error compensation; thermal error modeling; thermal error parameter measurement; Biological neural networks; Error compensation; Machine tools; Machining; Particle swarm optimization; Temperature measurement; BP neural network; Particle swarm optimization; embedded system; machine tools; thermal compensation;
Conference_Titel :
Control Engineering and Communication Technology (ICCECT), 2012 International Conference on
Conference_Location :
Liaoning
Print_ISBN :
978-1-4673-4499-9
DOI :
10.1109/ICCECT.2012.61