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Numerical analysis onto thermal balance behaviors of motorized spindle unit

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Abstract

Generally, the accuracy stability of a precision motorized spindle unit is influenced by its structural thermal balance behaviors (power matching degree of spindle structural heat generation–dissipations). For the accurate analysis of this spindle heat transfer behaviors based on temperature detections, this paper describes a method constructed with the numerical simulation technology and a proposed genetic algorithm-extreme learning machine (GA-ELM) algorithm. Firstly, the heat–fluid–solid coupling FE transient model is established to simulate spindle thermal behaviors, determinations of its thermal loads/boundary conditions are initially based on empirical calculations. Secondly, according to spindle temperature detections, these initial values are applied to thermal simulations and corrected by GA to make simulated spindle temperatures gradually approach detections. Specially, ELM is adopted to estimate the functional relationships from the parent population to the child population generated by genetic operators with increasing fitness values, and the trained ELM model is utilized to ensure the GA faster convergence. Eventually, based on the corrected thermal load/boundary condition values and simulation results, the time-varying power matching conditions of spindle structural heat generation–dissipation are analyzed. This study provides a theoretical basis for the optimization and promotion of spindle structural design and coolant control strategy.

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Acknowledgements

The authors acknowledge the Fundamental Research Funds for the Central Universities (no. 3122019116).

Funding

The research was supported by the Fundamental Research Funds for the Central Universities (no. 3122019116).

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Authors and Affiliations

  1. School of Computer Science and Technology, Civil Aviation University of China, Tianjin, 300300, China

    Yifan Zhang

  2. School of Mechanical Engineering, Hebei University of Technology, Tianjin, 300130, China

    Teng Liu & Jianjun Zhang

  3. Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin, 300355, China

    Teng Liu, Weiguo Gao & Dawei Zhang

Authors
  1. Yifan Zhang
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  2. Teng Liu
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  3. Weiguo Gao
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  4. Jianjun Zhang
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  5. Dawei Zhang
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Contributions

Yifan Zhang is the main contributor to this paper. She finished the thermal simulation modeling of the motorized spindle unit. Then she designed the procedure of the genetic algorithm to correct its thermal loads by optimization method and then adopted the ELM algorithm to estimate nonlinear functional relationships from parent population to child population generated by genetic operators with increasing fitness values. Teng Liu assisted Yifan Zhang in the thermal simulation of the motorized spindle unit and then improved the handwriting of the manuscript as a whole. Weiguo Gao finished the construction of the experimental platform and then performed the contrasting experiments for this study. Jianjun Zhang finished the data analyses about experimental and simulation results. Dawei Zhang designed the logical structure of the whole manuscript and then gave crucial comments on this work for improving its technical route.

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Correspondence to Teng Liu.

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Zhang, Y., Liu, T., Gao, W. et al. Numerical analysis onto thermal balance behaviors of motorized spindle unit. Int J Adv Manuf Technol 123, 4465–4478 (2022). https://doi.org/10.1007/s00170-022-10399-6

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  • DOI: https://doi.org/10.1007/s00170-022-10399-6

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