Skip to main content
SpringerLink
Log in

Experimental study of a turbo-alternator in industrial environment using cyclostationarity analysis

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

Abstract

The cyclostationarity method is used in this paper for the diagnosis of a turbo-alternator working in industrial environment for the detection of the defects generated by rolling bearings, journal bearings, and gears. This study shows the advantage of using such analysis as an aid to diagnosis and decision making before a failure caused by bad vibration monitoring of rotating machinery can be produced. In fact, a cyclostationary signal has some hidden periodicities, which mean that it is not strictly periodic, but some statistical properties of the signal are periodic. This periodicity identifies the spectral correlation by integrating the modulation intensity distribution function that depends only of the cyclic frequency, which is an indicator of the presence of modulations. The method was initially applied on a theoretical signal simulating a single bearing fault. The experimental validation is then performed on the machine faults simulator (MFS) for the detection of a bearing fault, and on a turbo-alternator working in real conditions in industrial environment. The application of this method helped to highlight very clearly the presence of defects on the bearings and the gears, which has been difficult to show especially at low frequency by spectral analysis.

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. Boulenger A, Pachaud C et al (1998) Vibratory diagnosis in maintenance préventive. Dunod, Paris, pp 239–295, ISBN 2100041053

    Google Scholar 

  2. Heng J (2002) Pratique de la maintenance préventive Mécanique - Pneumatique - Hydraulique - Electricité - Froid, 1st edn. Dunod, Paris

    Google Scholar 

  3. Vibro-Meter (1991) The rotating machinery and vibration be havior P/N 561–003 F

  4. Heng J (2005) Pratique de la maintenance préventive Mécanique - Pneumatique - Hydraulique - Electricité - Froid, 2nd edn. Dunod, Paris

    Google Scholar 

  5. Muller A (2005) Contribution to the proactive maintenance of manufacturing system: formalisation of the prognosis process. Ph.D. Thesis, IAEM & Lorraine University. Henri Poincare

  6. Heng J (2011) Pratique de la maintenance préventive Mécanique - Pneumatique - Hydraulique - Electricité - Froid, 3rd edn. Dunod, Paris

    Google Scholar 

  7. Estoque P (2004) A methodological approach numerical and experimental support for the detection and monitoring of vibration fault chipping ball bearing. Ph.D. Thesis, University of Lille

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

    Article  Google Scholar 

  9. Boustany R, Antoni J (2005) A subspace methode for the blind extraction of a cyclostationary source: application to rolling element bearing diagnostics. Mech Syst Signal Process 19:1245–1259

    Article  Google Scholar 

  10. Bonnardot F, Randall RB, Guillet F (2005) Extraction of second-order cyclostationary sources application to vibration analysis. Mech Syst Signal Process 19(6):1230–1244

    Article  Google Scholar 

  11. Urbanek J, Barszcz T, Zimroz R, Antoni J (2012) Application of averaged instantaneous power spectrum for diagnostics of machinery operating under non-stationary operational conditions. Measurement 45:1782–1791

    Article  Google Scholar 

  12. Urbanek J, Barszcz T, Sawalhi N, Randall RB (2011) Comparison of amplitude based and phase based methods for speed tracking in application to wind turbines. Metrol Meas Syst XVIII (2)

  13. Gellermann T (2003) Requirements for condition monitoring systems for wind turbines. AZT Expertentage, 10–11.11.2003, Allianz

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

    Article  Google Scholar 

  15. Gardner WA, Spooner CM (1988) Cyclic spectral analysis for signal detection and modulation recognition. In: Proceedings – IEEE military communications conference, vol. 2, pp 419–24

  16. Makowski R, Zimroz R (2011) Adaptive bearings vibration modeling for diagnosis. Lect Notes Artif Intell 943:248–259

    MathSciNet  Google Scholar 

  17. Randall RB, Antoni J (2011) Rolling element bearing diagnostics—a tutorial. Mech Syst Signal Process 25(2):485–520

    Article  Google Scholar 

  18. Antoni J, Bonnardot F, Raad A, El Badaoui M (2004) Cyclostationary modelling of rotating machine vibration signals. Mech Syst Signal Process 18(6):1285–1314

    Article  Google Scholar 

  19. Taher F, Fakher C, Mohamed H (2005) Numerical and experimental analysis of a gear system with teeth defects. Int J Adv Manuf Technol 71:809–816

    Google Scholar 

  20. D’ Elia G, Delvecchio S, Cocconcelli M, Dalpiaz G (2011) Combining blind separation and cyclostationary techniques for monitoring distributed wear in gearbox rolling bearings. In: Proc. of surveillance, Compiegne, France

  21. Urbanek J, Barszcz T, Antoni J (2013) Time–frequency approach to extraction of selected second-order cyclostationary vibration components for varying operational conditions. Measurement 46:1454–1463

    Article  Google Scholar 

  22. Urbanek J, Barszcz T, Zimroz R, Antoni J (2014) Integrated modulation intensity distribution as a practical tool for condition monitoring. Appl Acoust 77:184–194

    Article  Google Scholar 

  23. Zimroz R, Bartelmus W, Barszcz T, Urbanek J (2012) Wind turbine main bearing diagnosis—a proposal of data processing and decision making procedure under non stationary load condition. Key Eng Mater 518:437–444

    Article  Google Scholar 

  24. Bartelmus W, Zimroz R (2009) A new feature for monitoring the condition of gearboxes in non-stationary operating conditions. Mech Syst Signal Process 23(5):1528–1534

    Article  Google Scholar 

  25. Bonnardot F, Antoni J, Randall RB, M El Badaoui (2004) Enhancement of second order cyclostationary signals. Proceedings of the ICASSP’04, Montreal, Canada, May 17–21

  26. Zimroz R, Millioz F, Martin N (2010) A procedure of vibration analysis form planetary gearbox under non-stationary cyclic operations for instantaneous frequency estimation in time–frequency domain. Proceedings of Condition Monitoring, Stratford upon Avon, UK

  27. Antoni J (2005) Blind separation of vibration components: principales and démonstrations. Mech Syst Signal Process 19:1166–1180

    Article  Google Scholar 

  28. Boustany R, Antoni J (2008) Blind extraction of a cyclostationary signal using reduced-rank cyclic regression—a unifying approach. Mech Syst Signal Process 22:520–541

    Article  Google Scholar 

  29. Gardner WA (1986) Measurement of spectral correlation. IEEE Trans Acoust Speech Sig Process ASSP-34(5)

  30. Zivanovic GD, Gardner WA (1991) Degrees of cyclostationarity and their application to signal detection and estimation. Signal Process 22(3):287–297

    Article  Google Scholar 

  31. Lie T-I, Lee J, Singh P, Liu G (2014) Real-time recognition of ball bearing states for the enhancement of precision, quality, efficiency, safety and automation of manufacturing. Int J Adv Manuf Technol 71:809–816

    Article  Google Scholar 

  32. Technical document, group turbo-alternator GZ1164. Department Maintenance FERTIAL

  33. Presentation of the standard ISO 2372 (1974) International standard ISO 10816 (1995) replaces the standard ISO 2372

  34. Brüel & Kjær vibro (2005) Analyse des vibrations maintenance conditionnelle des machines tournantes. Brüel & Kjær vibro copyright 0906 v.1-B site www.bkvibro.com

Download references

Author information

Authors and Affiliations

  1. University of Badji Mokhtar, Po. Box 12, 23000, Annaba, Algeria

    Tarek Kebabsa

  2. Mechanics & Structures Laboratory, University 8 May 1945, Po. Box 401, 24000, Guelma, Algeria

    Tarek Kebabsa, Nouredine Ouelaa, Mohamed Cherif Djamaa, Riad Khettabi & Abderrazek Djebala

  3. Laboratory of vibration Acoustic, INSA of Lyon, Bâtiment Antoine Saint-Exupéry, 25 bis Avenue Jean Capelle, 69621, Villeurbanne Cedex, France

    Jerome Antoni

Authors
  1. Tarek Kebabsa
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nouredine Ouelaa
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jerome Antoni
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mohamed Cherif Djamaa
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Riad Khettabi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Abderrazek Djebala
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tarek Kebabsa.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kebabsa, T., Ouelaa, N., Antoni, J. et al. Experimental study of a turbo-alternator in industrial environment using cyclostationarity analysis. Int J Adv Manuf Technol 81, 537–552 (2015). https://doi.org/10.1007/s00170-015-7083-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-015-7083-5

Keywords

Search

Navigation