Skip to main content
SpringerLink
Log in

Feature Extraction Based on Cyclic Adaptive Filter for Gearbox Fault Diagnosis

  • Conference paper
  • First Online:
9th WCEAM Research Papers

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

Abstract

The feature extraction of gears and rolling element bearings under strong background noise are of great importance for the gearbox fault diagnosis. In this paper, a method based on cyclic adaptive filter is applied to gearbox fault diagnosis. Firstly, adaptive line enhancer is used for the periodical component extraction, and then the residual signal will be filtered by cyclic Wiener filter. Based on the proposed method, the condition of each parts of gearbox can be well monitored, and the transient fault feature can be effectively detected. The effectiveness of the method is demonstrated by simulation and experimental validation.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Brie D, Tomczak M, Oehlmann H (1997) A gear crack detection by adaptive amplitude and phase demodulation mechanical. Mech Syst Signal Process 11:149–167

    Article  Google Scholar 

  2. Raad A, Antoni J, Randall B, Sidahmed M (2002) Gear vibration modelling and fault characterization. In: International conference on noise and vibration engineering (ISMA2002). Leuven, Belgium, pp 1487–1495

    Google Scholar 

  3. He J, Chen J, Bi G, Zhou FC (2005) Frequency-demodulated analysis based on cyclostationarity for local fault detection in gears. Key Eng Mater 293–294:87–94

    Article  Google Scholar 

  4. Antoni J (2007) Cyclic spectral analysis in practice. Mech Syst Signal Process 21:597–630

    Article  Google Scholar 

  5. Antoni J (2007) Cyclic spectral analysis of rolling-element bearing signals: facts and fictions. J Sound Vib 304:497–529

    Article  Google Scholar 

  6. Antoni J (2009) Cyclostationarity by examples. Mech Syst Signal Process 23:987–1036

    Article  Google Scholar 

  7. Gardner WA, Napolitano A, Paura L (2006) Cyclostationarity: half a century of research. Signal Process 86:639–697

    Article  MATH  Google Scholar 

  8. Antoni J, Randall RB (2004) Unsupervised noise cancellation for vibration signals: Part 1—evaluation of adaptive algorithms. Mech Syst Signal Process 18:89–101

    Article  Google Scholar 

  9. Antoni J, Randall RB (2004) Unsupervised noise cancellation for vibration signals: Part 2—a novel STFT algorithm. Mech Syst Signal Process 18:103–117

    Article  Google Scholar 

  10. Antoni J (2005) Blind separation of vibration components: principles and demonstrations. Mech Syst Signal Process 19:1166–1180

    Article  Google Scholar 

  11. Gardner WA (1986) The spectral correlation theory of cyclostationary. Signal Process 11:13–36

    Article  Google Scholar 

  12. Gardner WA (1993) Cyclic Wiener filtering: theory and method. IEEE Trans Commun 41:151–163

    Article  MATH  Google Scholar 

  13. Bonnardot F, Randall RB, Guillet F (2005) Extraction of second-order cyclostationary sources–application to vibration analysis. Mech Syst Signal Process 19:1230–1244

    Article  Google Scholar 

  14. Gardner WA (1994) Cyclostationarity in communications and signal processing, 1st edn. IEEE Press, New York

    MATH  Google Scholar 

  15. Gardner WA (1991) On the spectral coherence of nonstationary process. IEEE Trans Signal Process 39:424–430

    Article  Google Scholar 

  16. McFadden PD, Smith JD (1984) Model for the vibration produced by a single point defect in a rolling element bearing. J Sound Vib 96(1):69–82

    Article  Google Scholar 

  17. McFadden PD, Smith JD (1985) The vibration produced by multiple point defects in a rolling element bearing. J Sound Vib 98(2):263–273

    Article  Google Scholar 

  18. Antoni J, Randall RB (2002) Differential diagnosis of gear and bearing faults. ASME J Vib Acoust 124:165–171

    Article  Google Scholar 

  19. Randall RB, Antoni J, Chobsaard S (2001) The relationship between spectral correlation and envelope analysis in the diagnostics of bearing faults and other cyclostationary machine signals. Mech Syst Signal Process 15:945–962

    Article  Google Scholar 

  20. Ming Y, Chen J, Dong GM (2011) Weak fault feature extraction of rolling bearing based on cyclic Wiener filter and envelope spectrum. Mech Syst Signal Process 25(5):1773–1785

    Article  Google Scholar 

  21. Yu DJ, Cheng JS, Yang Y (2005) Application of EMD method and Hilbert spectrum to the fault diagnosis of roller bearings. Mech Syst Signal Process 19(2):259–270

    Article  Google Scholar 

Download references

Acknowledgments

Support for this work from Natural Science Foundation of China (Approved Grants: 51105243 and 51035007) is gratefully acknowledged.

Author information

Authors and Affiliations

  1. State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, 200240, China

    Guangming Dong, Jin Chen & Ying Ming

Authors
  1. Guangming Dong
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jin Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ying Ming
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Guangming Dong .

Editor information

Editors and Affiliations

  1. Department of Engineering and Technology Management, University of Pretoria, Pretoria, South Africa

    Joe Amadi-Echendu

  2. Dynacon Consulting Engineers (Pty) Ltd, Johannesburg, South Africa

    Changela Hoohlo

  3. Asset Institute, Brisbane, Queensland, Australia

    Joe Mathew

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Dong, G., Chen, J., Ming, Y. (2015). Feature Extraction Based on Cyclic Adaptive Filter for Gearbox Fault Diagnosis. In: Amadi-Echendu, J., Hoohlo, C., Mathew, J. (eds) 9th WCEAM Research Papers. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-15536-4_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-15536-4_15

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-15535-7

  • Online ISBN: 978-3-319-15536-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation