Cover
Vol. 21 No. 1 (2021)

Published: January 31, 2021

Pages: 20-26

Original Article

Flexible Rotor Balancing Without Trial Runs Using Experimentally Tuned FE Based Rotor Model

Abstract

A method based on experimentally calibrated rotor model is proposed in this work for unbalance identification of flexible rotors without trial runs. Influence coefficient balancing method especially when applied to flexible rotors is disadvantaged by its low efficiency and lengthy procedure, whilst the proposed method has the advantage of being efficient, applicable to multi-operating spin speeds and do not need trial runs. An accurate model for the rotor and its supports based on rotordynamics and finite elements analysis combined with experimental modal analysis, is produced to identify the unbalance distribution on the rotor. To create digital model of the rotor, frequency response functions (FRFs) are determined from excitation and response data, and then modal parameters (natural frequencies and mode shapes) are extracted and compared with experimental analogies. Unbalance response is measured traditionally on rotor supports, in this work the response measured from rotating disks instead. The obtained results show that the proposed approach provides an effective alternative in rotor balancing. Increasing the number of balancing disks on balancing quality is investigated as well.

References

  1. F. Ehrich, Handbook of Rotordynamics, McGraw – Hill, 1992.
  2. M. S. Darlow, Balancing of High-Speed Machinery, Springer-Verlag, 1989.
  3. R. Nordmann, E. Knopf and B. Abrate, “Numerical Analysis of Influence Coefficients for on Site Balancing of Flexible Rotors”, Proc. of the 10th Int. Conf. on Rotor Dynamics – IFToMM, Springer, Mechanisms and Machine Science, Vol. 63, pp. 157-172, 2018.
  4. I. Nistor, P. Voinis, M. A. Hassini, R. Lacombe and P. Pennacchi, “Application of a Model Based Method for Balancing a Large Steam Turbo Generator Unit-page”, Proc. of the 9th Int. Conf. on Rotor Dynamics-IFToMM, Springer, Mechanisms and Machine Science, Vol. 21, pp. 735-743, 2015.
  5. J. He and Z. Fu, Modal analysis, Butterworth-Heinemann, Oxford, England, 2001.
  6. M. I. Friswell, J. E. T. Penny, S. D. Garvey and A. W. Lees, Dynamics of Rotating Machines, Cambridge University Press, 2010.
  7. Yahya Muhammed Ameen and Jaafar Khalaf Ali, “Theoretical and experimental modal analysis of circular cross-section shaft”, The Fourth Scientific Conference for Engineering and Postgraduate Research (PEc19), Baghdad, IOP Conference Series: Materials Science and Engineering, Vol. 745, No. 012066, 2019.
  8. J. M. Vance, B. Murphy and F. Zeidan, Machinery vibration and rotordynamics, John Wiley and Sons, 2010.
  9. R. Tiwari, Rotor Systems: Analysis and Identification, CRC Press, Boca Raton, 2017.
  10. Kreuzinger-Janik T., Irretier H., “Experimental Modal Analysis – A Tool for Unbalance Identification of Rotating Machines”, International Journal of Rotating Machinery, Vol. 6, Article ID 304015, 2000.
  11. Jei, Y. G. and Kim, Y. J. Modal testing theory of rotorbearing systems, 1993.
  12. M. H. Sadeghi, Soheil Jafari, Bahman Nasseroleslami, “Modal analysis of a turbo-pump shaft: An innovative suspending method to improve the results”, International Journal of Engineering Science, Vol. 19, No. 5-1, pp. 143149, 2008.
  13. Carvalho V. N., Dourado A. D., Rende B. R., Cavalini Jr A. A., Steffen Jr V., “Experimental validation of a robust model-based balancing approach”, Journal of Vibration and Control, Vol. 25, Issue 2, pp. 423-434, 2019.
  14. Xialun Yun, Xuesong Mei, Gedong Jiang, Zhenbang Hu, and Zunhao Zhang, “Investigation on a No Trial Weight Spray Online Dynamic Balancer”, Shock and Vibration, Vol. 2018, Article ID 7021215, 2018.
  15. Benjamin Siegl, and Richard Markert, “Model-based Non-stationary Unbalance Identification”, 16th International Symposium on Transport Phenomena and Dynamics of Rotating Machinery, Honolulu, United States, Apr 2016.