Optimization of Characteristic Diagram Based Thermal Error Compensation via Load Case Dependent Model Updates
Philipp Klimant
7,4
| 1 | Automation and Monitoring, Fraunhofer IWU Chemnitz, Germany |
| 2 | Machine tool technology, Fraunhofer IWU Chemnitz, Germany |
| 3 | Process technology, Fraunhofer IWU Chemnitz, Germany |
| 4 | Institute for Machine Tools and Production Processes, Chemnitz University of Technology, Germany |
| 5 | Production Systems and Factory Automation, Fraunhofer IWU Chemnitz, Germany |
| 6 | Machine Tool Development and Adaptive Controls, Technical University Dresden, Germany |
| 7 | Process Digitalization and Production Automation, Fraunhofer IWU Chemnitz, Germany |
CORRESPONDING AUTHOR
Christian Naumann
Automation and Monitoring, Fraunhofer IWU Chemnitz, Reichenhainer Str. 88, 09126, Chemnitz, Germany
Automation and Monitoring, Fraunhofer IWU Chemnitz, Reichenhainer Str. 88, 09126, Chemnitz, Germany
Submission date: 2022-02-22
Final revision date: 2022-04-04
Acceptance date: 2022-04-08
Online publication date: 2022-04-19
Publication date: 2022-06-28
Journal of Machine Engineering 2022;22(2):43–56
KEYWORDS
TOPICS
ABSTRACT
The compensation of thermal errors in machine tools is one of the major challenges in ensuring positioning accuracy during cutting operations. There are numerous methods for both the model-based estimation of the thermal tool center point (TCP) deflection and for controlling the thermal or thermo-elastic behavior of the machine tool. One branch of thermal error estimation uses regression models to map temperature sensors directly onto the TCP-displacement. This can, e.g., be accomplished using linear models, artificial neural networks or characteristic diagrams. One of the main limitations of these models is the poor extrapolation behavior with regard to untrained load cases. This paper presents a new method for updating characteristic diagram based compensation models by combining existing models with new measurements. This allows the optimization of the compensation for serial production load cases without the effort of computing a new model. The new method was validated on a 5-axis machining center.
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