Skip to main content
SpringerLink
Log in

Research on the machine tool’s temperature spectrum and its application in a gear form grinding machine

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

The machine tool’s temperature spectrum can be defined as the relationship curves between the thermal parameters and the temperature rise of a machine. In this paper, the relationships between the thermal deformation and the temperature rise as well as the heat flux and the temperature rise are studied using the theoretical method, the finite element method, and the experimental method. The results show that there is a linear relationship between the thermal deformation and the temperature rise at the point of golden section. And this linear relationship still holds between the heat flux and the temperature rise. What’s more, the linear relationship does not change when the thermal contact resistance changes. To realize the real-time monitoring of the thermal deformation and the temperature rise of a machine tool, a correction model is established using the measured temperature to real-timely correct the heat flux, an online monitoring application is designed based on the correction model to realize the real-time prediction of the thermal deformation and the temperature rise of a machine tool. To verify the monitoring accuracy of the online monitoring application, an experiment is carried out in a gear form grinding machine. The experimental results show that the prediction accuracy of the online monitoring application is greater than 90%. It is useful for the thermal deformation control, optimization, and compensation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Chen JS, Yuan JX, Ni J et al (1993) Real-time compensation for time-variant volumetric errors on a machining center [J]. Transactions of the ASME Journal of Engineering for Industry 115(4):472–479

    Article  Google Scholar 

  2. Tseng PC (1997) A real-time thermal inaccuracy compensation method on a machining center [J]. Int J Adv Manuf Technol 13(3):182–190

    Article  MathSciNet  Google Scholar 

  3. Lu Y, Islam MN (2012) A new approach to thermally induced volumetric error compensation [J]. Int J Adv Manuf Technol 62(9–12):1071–1085

    Article  Google Scholar 

  4. Zhang Y, Yang J, Xiang S et al (2013) Volumetric error modeling and compensation considering thermal effect on five-axis machine tools [J]. Proc Inst Mech Eng C J Mech Eng Sci 227(5):1102–1115

    Article  Google Scholar 

  5. Chen JS (1996) Neural network-based modeling and error compensation of thermally-induced spindle errors [J]. Int J Adv Manuf Technol 12(4):303–308

    Article  Google Scholar 

  6. Yang S, Yuan J, Ni J (1996) The improvement of thermal error modeling and compensation on machine tools by CMAC neural network [J]. Int J Mach Tools Manuf 36(4):527–537

    Article  Google Scholar 

  7. Mize CD, Ziegert JC (2000) Neural network thermal error compensation of a machining center [J]. Precis Eng 24(4):338–346

    Article  Google Scholar 

  8. Li X (2001) Real-time prediction of workpiece errors for a CNC turning center,part 2: modeling and estimation of thermally induced errors [J]. Int J Adv Manuf Technol 17(9):654–658

    Article  MathSciNet  Google Scholar 

  9. Guo Q, Yang J, Wu H (2010) Application of ACO-BPN to thermal error modeling of NC machine tool [J]. Int J Adv Manuf Technol 50(5):667–675

    Article  Google Scholar 

  10. Lu Y, Yang J, Gelvis T et al (2008) Optimization of measuring points for machine tool thermal error based on grey system theory [J]. Int J Adv Manuf Technol 35(7–8):745–750

    Google Scholar 

  11. Yan J, Yang J (2009) Application of synthetic grey correlation theory on thermal point optimization for machine tool thermal error compensation [J]. Int J Adv Manuf Technol 43(11–12):1124–1132

    Article  Google Scholar 

  12. Han J, Wang L, Cheng N et al (2012) Thermal error modeling of machine tool based on fuzzy c-means cluster analysis and minimal-resource allocating networks [J]. Int J Adv Manuf Technol 60(5–8):463–472

    Article  Google Scholar 

  13. Wang H, Wang L, Li T et al (2013) Thermal sensor selection for the thermal error modeling of machine tool based on the fuzzy clustering method [J]. Int J Adv Manuf Technol 69(1–4):121–126

    Article  Google Scholar 

  14. Yang JG, Yuan JX, Ni J (1999) Thermal error mode analysis and robust modeling for error compensation on a CNC turning center. International Journal of Machine Tools & Manufacture 39:1367–1381

    Article  Google Scholar 

  15. Fan KG, Yang JG, Yao XD, Wang W, Jiang H (2011) Error compensation for shaft parts in batch manufacture based on Newton interpolation. Chinese Journal of Mechanical Engineering 47:112–116

    Article  Google Scholar 

  16. Zheng FQ, Yang JG, Li BZ, Yan RZ, Xu Y (2008) Research on micro-feeding system applied to grinder. Manufacturing Technology & Machine Tool 8:12–15

    Google Scholar 

  17. Fan KG, Yang JG, Yang LY (2014) Unified error model based spatial error compensation for four types of CNC machining center: part II—unified model based spatial error compensation. Mech Syst Signal Process 49(1–2):63–76

    Article  Google Scholar 

  18. Kim SK, Cho AW (1997) Real-time estimation of temperature distribution in a ball screw system. International Journal of Machine Tools & Manufacture 37:451–464

    Article  Google Scholar 

  19. Zhao HT, Yang JG, Shen JH (2007) Simulation of thermal behavior of a CNC machine tool spindle. International Journal of Machine Tools & Manufacture 47:1003–1010

    Article  Google Scholar 

  20. Horejs O (2007) Thermo-mechanical model of ball screw with non-steady heat sources [C]. International Conference on Thermal Issues in Emerging Technologies-Theory and Applications 2007:126–130

    Google Scholar 

  21. Xu M, Jiang S (2011) A thermal model of a ball screw feed drive system for a machine tool [J]. Proceedings of the Institution of Mechanical Engineers,Part C:Journal of Mechanical Engineering Science 225(C1):186–193

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China

    Kaiguo Fan

Authors
  1. Kaiguo Fan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kaiguo Fan.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fan, K. Research on the machine tool’s temperature spectrum and its application in a gear form grinding machine. Int J Adv Manuf Technol 90, 3841–3850 (2017). https://doi.org/10.1007/s00170-016-9722-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-016-9722-x

Keywords

Search

Navigation