Skip to main content

Advertisement

SpringerLink
Log in

Fault Diagnosis Method for Rolling Element Bearings Under Variable Speed Based on TKEO and Fast-SC

  • Tools and Techniques
  • Published:
Journal of Failure Analysis and Prevention Aims and scope Submit manuscript

Abstract

With rotating speed of rotating machinery, it is difficult to maintain stability in practical work which brings many difficulties to the condition monitoring of rotating machinery. When rolling element bearings work under variable speed, the corresponding vibration will contain obvious non-stationary characteristics, along with the presence of strong background noise, which makes it difficult for some traditional spectrum analysis methods to identify the characteristic frequency of bearings fault. In spite of the existence of strong non-stationary characteristics, the bearing fault signal has some hidden periodic components in the angle domain which makes it possible to extract the fault feature of bearings by means of spectral correlation analysis. Therefore, a fault feature extraction method based on Teager–Kaiser energy operator (TKEO) and fast spectral correlation (Fast-SC) in angle domain is proposed in this paper; Fast-SC is a newly proposed spectral correlation calculation method which can effectively improve the efficiency of computing; Teager–Kaiser energy operator can enhance the transient impact which also has a fast computing speed. In this paper, the instantaneous speed of each time is estimated by the time–frequency analysis method based on short-time Fourier transform and then, the original time-domain signal is resampled in angle domain; the TKEO is used to strengthen the fault impact components in signal; finally, the Fast-SC is applied to the strengthened signals, the enhanced envelope spectrum is calculated, and the fault features of rolling bearings are extracted. The effectiveness of the method is verified by measured signals.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  1. L. Hong, Y. Qu, J.S. Dhupia et al., A novel vibration-based fault diagnostic algorithm for gearboxes under speed fluctuations without rotational speed measurement. Mech. Syst. Signal Process. 94, 14–32 (2017)

    Article  Google Scholar 

  2. M. Zhao, X. Jia, J. Lin et al., Instantaneous speed jitter detection via encoder signal and its application for the diagnosis of planetary gearbox. Mech. Syst. Signal Process. 98, 16–31 (2018)

    Article  Google Scholar 

  3. B. Li, X. Zhang, J. Wu, New procedure for gear fault detection and diagnosis using instantaneous angular speed. Mech. Syst. Signal Process. 85, 415–428 (2017)

    Article  Google Scholar 

  4. C. Mishra, A.K. Samantaray, G. Chakraborty, Rolling element bearing defect diagnosis under variable speed operation through angle synchronous averaging of wavelet de-noised estimate. Mech. Syst. Signal Process. 72–73, 206–222 (2016)

    Article  Google Scholar 

  5. T. Yang, Y. Guo, X. Wu et al., Fault feature extraction based on combination of envelope order tracking and cICA for rolling element bearings. Mech. Syst. Signal Process. (2017). https://doi.org/10.1016/j.ymssp.2017.03.050

  6. R. Potter, M. Gribler. Computed Order Tracking Obsoletes Older Methods, in SAE Noise and Vibration Conference and Exposition (1989)

  7. F. Bonnardot, M.E. Badaoui, R.B. Randall et al., Use of the acceleration signal of a gearbox in order to perform angular resampling (with limited speed fluctuation). Mech. Syst. Signal Process. 19(4), 766–785 (2005)

    Article  Google Scholar 

  8. F. Combet, R. Zimroz, A new method for the estimation of the instantaneous speed relative fluctuation in a vibration signal based on the short time scale transform. Mech. Syst. Signal Process. 23(4), 1382–1397 (2009)

    Article  Google Scholar 

  9. J. Antoni, J. Griffaton, H. André et al., Feedback on the Surveillance 8 challenge: vibration-based diagnosis of a Safran aircraft engine. Mech. Syst. Signal Process. 97, 112–144 (2017). https://doi.org/10.1016/j.ymssp.2017.01.037

    Article  Google Scholar 

  10. J. Antoni, Cyclic spectral analysis in practice. Mech. Syst. Signal Process. 21(2), 597–630 (2007)

    Article  Google Scholar 

  11. J. Antoni, N. Ducleaux, G. Nghiem et al., Separation of combustion noise in IC engines under cyclo-non-stationary regime. Mech. Syst. Signal Process. 38(1), 223–236 (2013)

    Article  Google Scholar 

  12. D. Abboud, J. Antoni, S. Sieg-Zieba et al., Envelope analysis of rotating machine vibrations in variable speed conditions: a comprehensive treatment. Mech. Syst. Signal Process. 84, 200–226 (2017)

    Article  Google Scholar 

  13. D. Abboud, S. Baudin, J. Antoni et al., The spectral analysis of cyclo-non-stationary signals. Mech. Syst. Signal Process. 75(5), 280–300 (2016)

    Article  Google Scholar 

  14. D. Abboud, J. Antoni, Order-frequency analysis of machine signals. Mech. Syst. Signal Process. 87, 229–258 (2017)

    Article  Google Scholar 

  15. J. Antoni, G. Xin, N. Hamzaoui, Fast computation of the spectral correlation. Mech. Syst. Signal Process. 92, 248–277 (2017)

    Article  Google Scholar 

  16. R.B. Randall, W.A. Smith. Application of the Teager Kaiser Energy Operator to Machine Diagnostics, in Tenth Dst Group International Conference on Health and Usage Monitoring Systems (2017)

  17. R. Randall, W. Smith. Use of the Teager Kaiser Energy Operator to Estimate Machine Speed, in European Conference of the Phm Society (2016)

Download references

Author information

Authors and Affiliations

  1. Department of Power Engineering, Naval University of Engineering, Wuhan, 430033, China

    Dan-chen Zhu, Yong-xiang Zhang & Qun-wei Zhu

Authors
  1. Dan-chen Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yong-xiang Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Qun-wei Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Dan-chen Zhu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhu, Dc., Zhang, Yx. & Zhu, Qw. Fault Diagnosis Method for Rolling Element Bearings Under Variable Speed Based on TKEO and Fast-SC. J Fail. Anal. and Preven. 18, 2–7 (2018). https://doi.org/10.1007/s11668-018-0383-y

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11668-018-0383-y

Keywords

Search

Navigation