Development of Thermal Displacement Prediction Model and Thermal Deformation Measurement Methods

Abstract

In machine tools, it is important to maintain accuracy against heat in the entire machining space. The reduction of thermal displacement is achieved by measuring it accurately and then clarify the relationship between the temperature change and the thermal deformation and then creating the prediction and compensation model or applying the countermeasure to suppress the thermal deformation. To solve this issue, the authors have developed methods to measure thermal deformation in two-dimensional space using a laser tracker and cameras. A laser tracker method achieved higher accuracy and smaller measurement uncertainty. Vision-based methods achieved equivalent measurement accuracy to a laser tracker method at shorter measurement time and lower cost. To compensate thermal displacement, convolutional neural network model was developed. Thermal displacement was predicted from temperature sensors with higher accuracy than conventional models. These methods contribute to the development of higher precision machine tools.