Thermal Error Robust Modeling and Real Time Compensation Based on the GA-BPN Theory on a Vertical Machine Centre

Abstract

Thermal errors generally account for as much as 70% of the total errors of CNC machine tools, are the most contributor to the workpiece dimensional precision in precision machining process. Thermal error compensation is an effective way to decreasing thermal errors. Precision mode is a key to thermal error compensation. In this paper thermal error modeling method based on the artificial neural networks (ANN) algorithm is applied for a vertical machining center. Four key temperature points of a vertical machining center were obtained based on the temperature field analysis. A novel genetic algorism-Back propagation neural network (GA-BPN) thermal error model was proposed on the basis of four temperature points. The emulations and experiments prove that there was about a 60% increase in machine tool precision.