Dynamic modeling for thermal error in motorized spindles

Abstract

This paper proposes a new modeling methodology to predict thermal error in motorized spindles. The dynamic model predicts thermal errors that are caused by deformation in the motorized spindle structure due to heat flow from internal sources. These thermally induced errors become more serious and dominate the total error when it comes to high speed and high precision. If these thermal errors can be predicted, they can be compensated in real time. In this paper, a new thermal errors model (ARX model) is presented which capitalizes on the notion that the motorized spindle thermoelastic system has very complicated dynamics. Furthermore, the selection principle of temperature key points, which are indispensable for building a robust thermal error model, is provided using the thermal error sensitivity technology. At last, an experiment on the thermal error in a motorized spindle is conducted to verify the effectiveness of the ARX model, the experimental results show that above 80 % of axial thermal errors are predicted for a variety of motorized spindle cycles and the dynamic model has good accuracy and robustness.