Adjustment of uncertain model parameters to improve the prediction of the thermal behavior of machine tools
| Autor: | Arvid Hellmich, Steffen Schroeder, Lars Penter, Bernd Kauschinger, Steffen Ihlenfeldt |
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| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
business.product_category Computer science Mechanical Engineering Model parameters Control engineering 02 engineering and technology Industrial and Manufacturing Engineering Machine tool Identification (information) 020303 mechanical engineering & transports 020901 industrial engineering & automation 0203 mechanical engineering Thermal business |
| Zdroj: | CIRP Annals. 69:329-332 |
| ISSN: | 0007-8506 |
| Popis: | Computer models, which simulate the thermo-elastic behavior of machine tools, are used for optimizing machine designs and more recently for controller-integrated online corrections. Sufficiently accurate corrections of errors caused by the thermal machine behavior require quick and precise identification of uncertain and irregularly distributed parameters based on measurements. The paper presents a systematic approach to conduct parameter identification during machine commissioning. In particular, the acquisition of required data for parameter adjustment and model optimization is addressed. Finally, the procedure is demonstrated on the example of a machine tool's feed axis. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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