Advertisement

Measurement of Spindle Tilt Error Based on Interference Fringe

  • Pengqiang FuEmail author
  • Yinhong Jiang
  • Lijie Zhou
  • Yiwen Wang
  • Qinghui Cao
  • Qiang Zhang
  • Feihu Zhang
Regular Paper
  • 23 Downloads

Abstract

The spindle rotation error is one of the important factors that affect the precision of the machined parts. The study of spindle rotation error is of great significance for finding the source of error, predicting the surface shape error of machining parts and improving the machining accuracy of ultra-precision machine tools. The structural of the aerostatic spindle this article focuses on is motorized spindle and the spindle tilt error has the maximum effect on the machining precision. A new method for measuring the rotation error of ultra-precision aerostatic spindle based on interference fringes is proposed in this paper. By using the principle of phase shifting interferometry, the mathematical model between the shape of interference fringes and the motion law of the spindle rotor is established by theoretical modeling. The interference fringes are processed with gray, smooth filtering, expansion corrosion, and edge detection and so on. The distance and direction of the interference fringes are calculated in the coordinate system, so as to get the spindle tilt error. Finally, the measurement system for the spindle rotation error of the aerostatic spindle is developed. The accuracy and effectiveness of this method are shown based on the experimental results.

Keywords

Spindle tilt error Interferometry Distance and direction of interference fringe Image processing 

Notes

Acknowledgements

Thanks to the National Natural Science Foundation Project (51405114) and the National Science and Technology Major Project (2017ZX04022001-204) supports the research of this subject.

References

  1. 1.
    Guan, J. L., Wang, W. C., Zhu, S. G., & Chen, Z. D. (2012). The status of development in ultra-precision machining of KDP crystal with single point diamond turning. Modern Manufacturing Engineering, 8, 129–132.Google Scholar
  2. 2.
    Sun, X. W., Zhang, F. H., & Dong, S. (2006). Research on SPDT milling KDP crystals experiment. Aviation Precision Manufacturing Technology, 42(4), 18–20.Google Scholar
  3. 3.
    Wang, S. F., Fu, P. Q., Zhang, F. H., An, C. H., & Zhang, Y. (2014). Investigation of surface micro waviness in single point diamond fly cutting. Journal of Harbin Institute of Technology, 21(5), 119–123.Google Scholar
  4. 4.
    Deng, L. M., Yang, H., Zeng, X. Y., Wu, B. Y., Liu, P., Wang, X. Z., et al. (2015). Study on mechanics and key technologies of laser nondestructive mirror-separation for KDP crystal. International Journal of Machine Tools and Manufacture, 94, 26–36.CrossRefGoogle Scholar
  5. 5.
    Li, M. Q. (2013). Study on influence of KDP crystal ultra-precision fly-cutting micronano-topography on its laser induced damage threshold. Harbin: Harbin Institute of Technology.Google Scholar
  6. 6.
    Abele, E., Altintas, Y., & Brecher, C. (2010). Machine tool spindle units. CIRP Annals—Manufacturing Technology, 59(2), 781–802.CrossRefGoogle Scholar
  7. 7.
    Gou, W. D. (2012). Technical discussion on rotation accuracy of high—Speed spindle. Manufacturing Technology and Machine Tool, 36(8), 83–86.Google Scholar
  8. 8.
    Jin, L., Yan, Z. Y., Xie, L. M., Gou, W. D., & Shi, D. X. (2012). Dynamic measurement and analysis of rotation error of high-speed spindle. Manufacturing Technology and Machine Tools, 4, 93–95.Google Scholar
  9. 9.
    Xie, L. M., Yan, Z. Y., Jin, L., Pei, D. W., & He, C. Y. (2012). Research on high speed spindle gyration error testing device. Mechanical Manufacture, 50(569), 38–40.Google Scholar
  10. 10.
    Wang, M. J. (2016). Research on high speed precision spindle test platform based on electromagnetic loading technology. Leshan: Southwest Jiao Tong University.Google Scholar
  11. 11.
    Huang, C. Z., & Sheng, Y. (2002). Dynamic measurement of spindle error motion of ultraprecision lathe. Aviation Precision Manufacturing Technology, 38(4), 1–3.Google Scholar
  12. 12.
    Liu, C. H., Jywe, W. Y., & Lee, H. W. (2004). Development of a simple test device for spindle error measurement using a position sensitive detector. Measurement Science & Technology, 15(9), 1733–1741.CrossRefGoogle Scholar
  13. 13.
    Marsh, E. R. (2010). Precision spindle metrology. Lancaster: DEStech Publications, Inc.Google Scholar
  14. 14.
    Fu, P. Q. (2013). Study on the influence of the characteristics of the spindle on the surface waviness and dynamic testing system. Harbin: Harbin Institute of Technology.Google Scholar
  15. 15.
    Anandan, K. P., & Ozdoganlar, O. B. (2016). A multi-orientation error separation technique for spindle metrology of miniature ultra-high-speed spindles. Precision Engineering, 43, 119–131.CrossRefGoogle Scholar
  16. 16.
    Wu, L. S., Yang, Y., & Zhou, D. S. (2008). Dynamic measurement technology of the spindle motion error of high speed spindle. Aviation Precision Manufacturing Technology, 44(4), 26–29.Google Scholar
  17. 17.
    Denis Ashok, S., & Samuel, G. L. (2012). Modeling, measurement, and evaluation of spindle radial errors in a miniaturized machine tool. The International Journal of Advanced Manufacturing Technology, 59(5–8), 445–461.CrossRefGoogle Scholar
  18. 18.
    Anandan, K. P., Tulsian, A. S., Donmez, A., & Ozdoganlar, O. B. (2011). A Technique for measuring radial error motions of ultra-high-speed miniature spindles used for micro-machining. Precision Engineering, 36(1), 104–120.CrossRefGoogle Scholar
  19. 19.
    Rosen, J., & Takeda, M. (2000). Longitudinal spatial coherence applied for surface profilometry. Applied Optics, 39(23), 4107–4111.CrossRefGoogle Scholar
  20. 20.
    Fan, Z. G., Li, R. S., & Cui, Z. H. (2000). Research on the processing of interference fringe patterns. Optical Technology, 26(3), 258–259,262.Google Scholar
  21. 21.
    Yang, C. J. (2016). Research on image denoising and its effect evaluation. Changchun: Jilin University.Google Scholar
  22. 22.
    Liu, G. H., Zhao, L., Sun, J. G., & Wang, X. (2016). A Otsu image threshold segmentation method for improved particle swarm optimization. Computer Science, 43(3), 309–312.Google Scholar

Copyright information

© Korean Society for Precision Engineering 2019

Authors and Affiliations

  1. 1.Harbin University of Science and TechnologyHarbinChina
  2. 2.Johnson Electric (Guangdong) Co., Ltd.ShenzhenChina
  3. 3.Harbin Institute of TechnologyHarbinChina

Personalised recommendations