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Prediction model and experimental validation for the thermal deformation of motorized spindle

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Abstract

The thermal deformation of motorized spindle has a great influence on the precision of numerical control (NC) machine tools. Thus, it is crucial to predict the thermal deformation in the design and operation control phase by numerical simulation and improve the precision of NC machine tools. In order to achieve this, an accurate thermal deformation prediction model for motorized spindle is required. In this paper, a model for predicting the thermal error of motorized spindle based on finite element method and parameter optimization is proposed. Levenberg-Marquardt (LM) method is applied to optimize the heat transfer coefficient of motorized spindle by using surface temperature data measured. The optimized heat transfer coefficient is then taken as one of the boundary condition of the finite element model. The boundary conditions about heat of the finite element model are obtained by energy loss experiment. The proposed model is validated by experimental results, and the results have shown well correlation.

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Acknowledgements

The authors gratefully wish to acknowledge the supports of the National Science Foundation (51375317), the National Science Foundation (51675353), Liaoning Province Science Foundation (2015020122), and National (local) Joint Engineering Laboratory for open funds (sjsc-2015-6).

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Authors and Affiliations

  1. Test and Analysis Center, Shenyang Jianzhu University, Shenyang, China

    Lixiu Zhang

  2. School of Mechanical Engineering, Shenyang Jianzhu University, Shenyang, China

    Jinpeng Li, Yuhou Wu & Ke Zhang

  3. Vibro-Acoustics and Sound Quality Research Laboratory, Department of Mechanical and Materials Engineering, University of Cincinnati, Cincinnati, OH, USA

    Yawen Wang

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  1. Lixiu Zhang
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  2. Jinpeng Li
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  3. Yuhou Wu
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  4. Ke Zhang
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Correspondence to Lixiu Zhang.

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Zhang, L., Li, J., Wu, Y. et al. Prediction model and experimental validation for the thermal deformation of motorized spindle. Heat Mass Transfer 54, 2691–2704 (2018). https://doi.org/10.1007/s00231-018-2317-3

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  • DOI: https://doi.org/10.1007/s00231-018-2317-3

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