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Study on thermal deformation and cooling suppression of five-axis direct drive swing head

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Abstract

Suppressing thermal deformation is an effective measure to reduce the thermal error of CNC (computer numerical control), and the machining accuracy of CNC directly determines the quality and accuracy of parts. A cooling pipe is designed for the non-heat source parts with large swing head deformation to restrain its thermal deformation. At present, there is a lack of research results in this field. Through the finite element simulation analysis of 5AS01 five-axis direct drive swing head, the thermal deformation of swing head and motorized spindle is compared. It has been determined that the thermal deformation of the shell in the Z- and X-axes has a significant impact on the precision of the swing head’s machining; thus, steps must be taken to limit its deformation. The cooling position was determined by simulating the normal working condition of the shell and gray correlation analysis. Capillary copper tube was connected with water-cooling system for cooling, and the heat transfer performance between the shell and copper tube was improved by using heat conductive silica gel sheet. Comparing the shell cooling simulation with the shell cooling experiment, it is found that both of them have the same trend in restraining the thermal deformation of the shell, reducing the thermal deformation in X direction by more than 50% and in Z direction by more than 24%. It verifies the accuracy of the cooling simulation model and the effectiveness of this cooling method, which can effectively reduce the thermal deformation of the shell and improve the machining accuracy of the machine tool.

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References

  1. Li R (2019) A/B double pendulum angle milling head characteristics analysis and thermal deformation experimental study. Dissertation, Jilin University

  2. Wen MF, Zhong JL, Peng BY, Wang PJ, Wang ZX (2023) Thermal-structural coupling and material selection analysis of high-speed motorized spindle. Machine Tool and Hydraulic 51:158–163

    Google Scholar 

  3. Li Y, Chen GH, Xia M, Li B (2023) Design and simulation optimization of cooling system for motorized spindle. J Eng Des 30:39–47

    Google Scholar 

  4. Zhang C, Liu BG, Feng W (2019) Thermal characteristics analysis of ultra-high-speed grinding motorized spindle. Modular Machine Tool and Automatic Machining Technol 542:41–44. https://doi.org/10.13462/J.CNKI.MMT.2019.04.010

    Article  Google Scholar 

  5. Liu Z, Chen W, Li DS, Zhang WJ (2017) Theoretical analysis and experimental study on thermal stability of high-speed motorized spindle. Ind Lubr Tribol 69:1049–1065

    Article  Google Scholar 

  6. Xiang ST, Yao XD, Du ZC, Yang JG (2018) Dynamic linearization modeling approach for spindle thermal errors of machine tools. Mechatronics 53:215–228. https://doi.org/10.1016/j.mechatronics.2018.06.018

    Article  Google Scholar 

  7. Tan F, Yin M, Wang L, Yin GF (2018) Spindle thermal error robust modeling using LASSO and LS-SVM. Int J Adv Manuf Technol 94:2861–2874. https://doi.org/10.1007/s00170-017-1096-1

    Article  Google Scholar 

  8. Fu G, Gong H, Gao H, Gu T, Cao Z (2019) Integrated thermal error modeling of machine tool spindle using a chicken swarm optimization algorithm-based radial basic function neural network. Int J Adv Manuf Technol 105:2039–2055. https://doi.org/10.1007/s00170-019-04388-5

    Article  Google Scholar 

  9. Yin Q, Tan F, Chen H, Yin G (2019) Spindle thermal error modeling based on selective ensemble BP neural networks. Int J Adv Manuf Technol 101:1699–1713. https://doi.org/10.1007/s00170-018-2994-6

    Article  Google Scholar 

  10. Wang KC, Shen HC, Yang CH, Chen HY (2019) Temperature sensing and two-stage integrated modeling of the thermal error for a computer-numerical control Swiss-type turning center. Sens Mater 31:1007–1020

    Google Scholar 

  11. Guo Q, Fan S, Xu RC, Cheng X, Zhao GY, Yang JG (2017) Spindle thermal error optimization modeling of a five-axis machine tool. Chin J Mech Eng 30:746–753. https://doi.org/10.1007/s10033-017-0098-0

    Article  Google Scholar 

  12. Zhang Y, Wang LF, Zhang YD, Zhang YD (2021) Design and thermal characteristic analysis of motorized spindle cooling system. Adv Mech Eng 13(5). https://doi.org/10.1177/16878140211020878

  13. Liu JB, Yuan FT, Zhou B, Yang SW, Lv K, Tang B (2022) Structure parameters optimization of the rain cover and ventilation duct of dry air core reactor under the forced air cooling condition. IEEJ Trans Electr Electron Eng 17:792–800. https://doi.org/10.1002/tee.23568

    Article  Google Scholar 

  14. Ma YL, Xu ZQ, Wu MQ, Chen JS, Wang XH (2019) Study on alternating air-cooled heat dissipation structure of battery pack. Power Supply Technol 43:1810–1812

    Google Scholar 

  15. Li BQ, Liu XB, Feng XG (2017) Simulation-based forced air cooling structure design of high-power power amplifier module. Warship Electronic Countermeasure 40:99–103

    Google Scholar 

  16. He L (2020) Study on thermal management of battery based on thermal conductive silica gel/phase change material composite components. Dissertation, Guangdong University of Technology. https://doi.org/10.27029/d.cnki.ggdgu.2020.001945

  17. Li XN, Zhou DQ, Zhang GQ, Cong W, Lin RH, Zhong ZD (2019) Experimental investigation of the thermal performance of silicon cold plate for battery thermal management system. Appl Therm Eng 155:331–340

    Article  CAS  Google Scholar 

  18. Zheng Y, Shi Y, Huang Y (2019) Optimization with adiabatic interlayers for liquid-dominated cooling system on fast charging battery packs. Appl Therm Eng 147:636–646

    Article  ADS  Google Scholar 

  19. Yuan JY, Li XG, Wang WC, Fu CK (2022) Simulation of serpentine cooling structure of battery pack considering mass flow. Energy Storage Sci Technol 11:2274–2281. https://doi.org/10.19799/J.CNKI.2095-4239.2009.1000000000026

    Article  Google Scholar 

  20. Wang PT, Jin WF, Ren HF, Li X (2023) Thermal error prediction of grinder spindle based on heat conduction and convolutional neural network. Opt Precision Eng 31:129–140

    Article  Google Scholar 

  21. Chen K, Zhou JZ, Jing LP (2022) Thermal performance analysis and calculation of high-speed motorized spindle. World Manuf Technol Equipment Market 5:64–67

    Google Scholar 

  22. Mao XB, Shi JM, Lei S, Mao KM (2022) Parametric modeling method of convective heat transfer coefficient of machine tool structure. Manuf Technol Machine Tool 10:177–182. https://doi.org/10.19287/j.mtmt.1005-2402.2022

    Article  Google Scholar 

  23. Glenda M, Jenith B (2023) Risk management in humanitarian supply chain based on FMEA and grey relational analysis. Socio-Econ Plan Sci 87. https://doi.org/10.1016/j.seps.2023.101551

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Funding

Supported by Opening Project of the Key Laboratory of Advanced Processing Technology and Intelligent Manufacturing (Heilongjiang Province), Harbin University of Science and Technology (KFKT202205), and National Natural Science Foundation of China (grant number: 52075134).

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All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Z. L., Q. W., W. Z., B. W., J. D., B. S., and Y. B. The first draft of the manuscript was written by Z. L., and all authors commented on the previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Zhaolong Li.

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Li, Z., Wang, Q., Zhu, W. et al. Study on thermal deformation and cooling suppression of five-axis direct drive swing head. Int J Adv Manuf Technol 131, 515–527 (2024). https://doi.org/10.1007/s00170-024-13157-y

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  • DOI: https://doi.org/10.1007/s00170-024-13157-y

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