Skip to main content

Part of the book series: Applied Condition Monitoring ((ACM,volume 14))

  • 1585 Accesses

Abstract

The chapter presents the introduction to the subject of condition monitoring of wind turbine drivetrains. First, two types of wind turbine drivetrains, i.e. geared and gearless, are presented, but the drivetrain monitoring refers mostly to the geared design. Modern turbines are in vast majority designed as pitch controlled, i.e. changing a pitch angle of main rotor blades. Such a design feature has very important consequences for the vibration analysis due to continuous variability of the operational speed. The impact of differences between stall control and pitch control on the vibration behavior is presented. The main part of the chapter is the presentation of drivetrain components and vibration patterns (also called characteristic frequencies) they generate. This is fundamental knowledge if one wants to detect and identify the cause of a fault. Varying operational conditions are a key factor influencing vibrations of wind turbines. Due to inherent variability of the wind, both frequency and amplitude of vibration components change. The patterns of typical process parameters are presented on real data. The change in wind speed may cause an increase of vibration features, which certainly does not mean any deterioration of the technical state. Such an operating pattern must be taken into account when trying to diagnose a wind turbine. Vibration monitoring is the subject of this book, though it is only one out of many condition monitoring methods. The chapter briefly presents—apart from vibrations—other analysis methods: ultrasonic with Acoustic Emission, oil, electrical parameters and SCADA data.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover 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. Hau E (2013) Wind turbines. Fundamentals, technologies, application, economic. Springer-Verlag Berlin Heidelberg

    Google Scholar 

  2. Burton T, Jenkins N, Sharpe D, Bossanyi E (2011) Wind energy handbook, 2nd edn

    Book  Google Scholar 

  3. Randall RB (2011) Vibration-based condition monitoring. Industrial, aerospace and automotive applications. Wiley, Chichester

    Book  Google Scholar 

  4. Rao JS (1996) Handbook of condition monitoring. Elsevier, Oxford

    Google Scholar 

  5. Klein U (2003) Schwingungsdiagnostische Beurteilung von Maschinen und Anlagen (Vibrodiagnostic assessment of machines and devices). Stahleisen Verlag, Duesseldorf (in German)

    Google Scholar 

  6. Barszcz T, Bielecka M, Bielecki A, Wójcik M (2012) Wind speed modelling using Weierstrass function fitted by a genetic algorithm. J Wind Eng Ind Aerod 109:68–78

    Article  Google Scholar 

  7. Richardson LF (1926) Atmospheric diffusion shown on a distance-neighbour graph. Proc R Soc Lond A 110:730–737

    Google Scholar 

  8. Bielecki A, Barszcz T, Wójcik M (2015) Modelling of a chaotic load of wind turbines drivetrain. Mech Syst Sig Process 54–55:491–505

    Article  Google Scholar 

  9. MarketsandMarkets Research Private Ltd. (2018) Machine condition monitoring market, by product (Vibration Monitoring, Thermography, Ultrasound Emission, Lubricating Oil Analysis, Corrosion Monitoring, and Motor Current Signature Analysis), component, application, and geography—Global forecast to 2024

    Google Scholar 

  10. Randall RB (1987) Frequency analysis. Bruel & Kjaer, Naerum

    Google Scholar 

  11. Jardine AK, Lin D, Banjevic D (2006) A review on machinery diagnostics and prognostics implementing condition based maintenance. Mech Syst Sig Process 20(7):1483–1510

    Article  Google Scholar 

  12. García Márquez FP, Tobias AM, Pinar Pérez JM, Papaelias M (2012) Condition monitoring of wind turbines: techniques and methods. Renew Energy 46:169–178

    Article  Google Scholar 

  13. Nie M, Wang L (2013) Review of condition monitoring and fault diagnosis technologies for wind turbine gearbox. Procedia CIRP 11:287–290

    Article  Google Scholar 

  14. Siegel D, Zhao W, Lapira E, Abuali M, Lee J (2014) A comparative study on vibration-based condition monitoring algorithms for wind turbine drive trains. Wind Energ 17:695–714

    Article  Google Scholar 

  15. Aye SA, Heyns PS, Thiart CJH (2016) Diagnostics of slow rotating bearings using a novel DAI based on acoustic emission. In: Chaari F, Zimroz R, Bartelmus W, Haddar M (eds) Advances in condition monitoring of machinery in non-stationary operations. CMMNO 2014. Applied condition monitoring, vol 4. Springer, Cham

    Google Scholar 

  16. Mba D (2003) Acoustic emissions and monitoring bearing health. Tribol Trans 46(3):447–451

    Article  Google Scholar 

  17. He Y, Friswell MI, Zhang X (2009) Defect diagnosis for rolling element bearings using acoustic emission. J Vibr Acoust 131(6):1–10

    Article  Google Scholar 

  18. Loutas TH, Roulias D, Pauly E, Kostopoulos V (2011) The combined use of vibration, acoustic emission and oil debris on-line monitoring towards a more effective condition monitoring of rotating machinery. Mech Syst Sig Process 25:1339–1352

    Article  Google Scholar 

  19. Benbouzid MEH (1999) Induction motors faults detection and localization using stator current advanced signal processing techniques. IEEE Trans Power Electron 14:14–22

    Article  Google Scholar 

  20. Thomson WT, Culbert I (2017) Current signature analysis for condition monitoring of cage induction motors: industrial application and case histories. Wiley-IEEE Press

    Google Scholar 

  21. Tautz-Weinert J, Watson SJ (2017) Using SCADA data for wind turbine condition monitoring—a review. IET Renew Power Gen 11(4):382–394

    Article  Google Scholar 

  22. Chen B, Zappalá D, Crabtree CJ, Tavner PJ (2014) Survey of commercially available SCADA data analysis tools for wind turbine health monitoring. Durham University

    Google Scholar 

  23. Barszcz T, Randall RB (2009) Application of spectral kurtosis for detection of a tooth crack in the planetary gear of a wind turbine. Mechanical Systems and Signal Processing 23 (4):1352–1365

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tomasz Barszcz .

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Barszcz, T. (2019). Introduction. In: Vibration-Based Condition Monitoring of Wind Turbines. Applied Condition Monitoring, vol 14. Springer, Cham. https://doi.org/10.1007/978-3-030-05971-2_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-05971-2_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-05969-9

  • Online ISBN: 978-3-030-05971-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics