Dynamic modeling for thermal error in motorized spindles
| Autor: | Xuesong Mei, Fei Zhu, Bao-min Wang, Zaixin Wu |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Engineering
business.industry Mechanical Engineering Deformation (meteorology) Industrial and Manufacturing Engineering Total error Computer Science Applications System dynamics Quantitative Biology::Subcellular Processes Thermoelastic damping Control and Systems Engineering Robustness (computer science) Thermal Selection principle Sensitivity (control systems) business Software Simulation |
| Zdroj: | The International Journal of Advanced Manufacturing Technology. 78:1141-1146 |
| ISSN: | 1433-3015 0268-3768 |
| DOI: | 10.1007/s00170-014-6716-4 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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