Table of Contents
Advances in Artificial Neural Systems
Volume 2014 (2014), Article ID 347062, 10 pages
http://dx.doi.org/10.1155/2014/347062
Research Article

Virtual Sensor for Calibration of Thermal Models of Machine Tools

1Institute of Applied Computer Science, Dresden University of Technology, 01062 Dresden, Germany
2Institute of Machine Tools and Control Engineering, Dresden University of Technology, 01062 Dresden, Germany

Received 22 July 2014; Revised 20 October 2014; Accepted 4 November 2014; Published 27 November 2014

Academic Editor: Wilson Wang

Copyright © 2014 Alexander Dementjev et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Machine tools are important parts of high-complex industrial manufacturing. Thus, the end product quality strictly depends on the accuracy of these machines, but they are prone to deformation caused by their own heat. The deformation needs to be compensated in order to assure accurate production. So an adequate model of the high-dimensional thermal deformation process must be created and parameters of this model must be evaluated. Unfortunately, such parameters are often unknown and cannot be calculated a priori. Parameter identification during real experiments is not an option for these models because of its high engineering and machine time effort. The installation of additional sensors to measure these parameters directly is uneconomical. Instead, an effective calibration of thermal models can be reached by combining real and virtual measurements on a machine tool during its real operation, without additional sensors installation. In this paper, a new approach for thermal model calibration is presented. The expected results are very promising and can be recommended as an effective solution for this class of problems.