Skip to main content
SpringerLink
Log in

Advanced Identification Techniques for Operational Wind Turbine Data

  • Conference paper
  • First Online:
Topics in Modal Analysis, Volume 7

Abstract

During a field test campaign, Sandia National Laboratories acquired operational data both in parked and rotating conditions on a modified MICON wind turbine with the Sensored Rotor 2 experiment. The objective of the test campaign was to acquire data to develop advanced system identification and structural health monitoring techniques. The data includes wind speed, tower deformations, low and high speed shaft rotational speed measurements as well as accelerations and strains on different locations of the blades. Applying Operational Modal Analysis on such data represents a difficult task due to the strong influence of rotor harmonics on the measured data. Accurately identifying and removing the harmonics is required to perform modal parameter identification. In this paper, data acquired with the turbine in both parked and operating conditions will be analyzed and the modal results compared. Several harmonic removal techniques will be applied on the operational data and their efficiency to solve this specific problem analyzed. In addition, a new enhanced identification technique will be applied, that improves the parameter estimation accuracy in the case of very noisy data and also provides uncertainty bounds of the parameters.

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 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 329.99
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. Carne TG, James III GH (2010) The inception of OMA in the development of modal testing for wind turbines. Mech Sys Signal Process 24:1213–1226

    Google Scholar 

  2. Peeters B, Guillaume P, Van der Auweraer H, Cauberghe B, Verboven P, Leuridan J (2004) Automotive and aerospace applications of the PolyMAX modal parameters estimation method. In: Proceedings of IMAC XXII, Dearborn, MI

    Google Scholar 

  3. Peeters B, Dammekens F, Magalhães F, Van der Auweraer H, Caetano E, Cunha A (2006) Multi-run operational modal analysis of the Guadiana cable-stayed bridge. In: Proceedings of IMAC XXIV, St. Louis, MO

    Google Scholar 

  4. Peeters B, Van der Auweraer H, Vanhollebeke H, Guillaume P (2007) Operational modal analysis for estimating the dynamic properties of a stadium structure during a football game. Shock Vib 14(4):283–303

    Google Scholar 

  5. Tcherniak D, Chauhan S, Hansen MH (2010) Applicability limits of operational modal analysis to operational wind turbines. In: Proceedings of IMAC XXVII, Jacksonville, FL

    Google Scholar 

  6. Peeters B, Cornelis B, Janssens K, Van der Auweraer H (2007) Removing disturbing harmonics in operational modal analysis. In: Proceedings of IOMAC, Copenhagen, Denmark

    Google Scholar 

  7. Mohaveny P (2005) Operational modal analysis in the resence of harmonic excitation. PhD dissertation thesis, Technische Universiteit Delft

    Google Scholar 

  8. Heylen W, Lammens S, Sas P (1997) Modal analysis theory and testing. Katholieke Universiteit Leuven, Leuven

    Google Scholar 

  9. Hansen MH, Thomsen K, Fuglsang P (2006) Two methods for estimating aeroelastic damping of operational wind turbine modes from experiments. Wind Energy 9:179–191

    Google Scholar 

  10. White JR (2009) Operational monitoring of horizontal axis wind turbines using inertial measurements. PhD dissertation, Purdue University

    Google Scholar 

  11. White JR, Adams DE, Rumsey MA (2010) Modal analysis of CX-100 rotor blade and micon 65/13 wind turbine. In: Proceedings of IMAC XXVII, Jacksonville, FL

    Google Scholar 

  12. Berg D, Berg J, Wilson D, White J, Resor B, Rumsey M (2011) Design, fabrication, assembly and initial testing of a SMART rotor. In: Proceedings of the 29th ASME wind energy symposium, Orlando, FL, Jan 2011

    Google Scholar 

  13. Adams DE, White JR, Rumsey M, Farrar C (2011) Structural health monitoring of wind turbines: method and application to HAWT. Wind Energy 14:603–623

    Google Scholar 

  14. Randall RB (2002) State of the art in monitoring rotating machinery. In: Proceedings of ISMA 2002, Leuven, Belgium

    Google Scholar 

  15. Bechhoefer E, Kingsley M (2009) A review of time synchronous averaging algorithms. In: Proceedings of the annual conference of the prognostic and health management society, San Diego, CA

    Google Scholar 

  16. Groover CL, Trethewey MW, Maynard KP, Lebold MS (2005) Removal of order domain content in rotating equipment signals by double resampling. Mech Syst Signal Process 19:483–500

    Google Scholar 

  17. Manzato S, Moccia D, Peeters B, Janssens K, White JR (2012) A review of harmonic removal methods for improved operational modal analysis of wind turbines. In: Proceedings of ISMA 2012, Leuven, Belgium

    Google Scholar 

  18. Bogert BP, Healy MJR, Tukey JW (1963) The quefrency alanysis of time series for echoes: cepstrum, pseudo-autocovariance, cross-cepstrum and shape cracking. In: Proceedings of the symposium on time series analysis, New York, pp 209–243

    Google Scholar 

  19. Randall RB (2009) Cepstral methods of operational modal analysis. In: Encyclopedia of structural health monitoring. Wiley, Chichester

    Google Scholar 

  20. Randall RB, Peeters B, Antoni J, Manzato S (2012) New cepstral methods of signal pre-processing for operational modal analysis. In: Proceedings of ISMA 2012, Leuven, Belgium

    Google Scholar 

  21. El-Kafafy M, Guillaume P, Peeters B, Marra F, Coppotelli G (2012) Advanced frequency-domain modal analysis for dealing with measurement noise and parameter uncertainty. In: Proceedings of IMAC XXX, Jacksonville, FL

    Google Scholar 

  22. Peeters B, El-Kafafy M, Guillaume P (2012) The new PolyMAX Plus method: confident parameter estimation even in very noisy cases. In: Proceedings of ISMA 2012, Leuven, Belgium

    Google Scholar 

  23. Bir G (2008) Multiblade coordinate transformation and its application to wind turbine analysis. In: Proceedings of the 2008 ASME wind energy symposium, Reno, Nevada

    Google Scholar 

Download references

Acknowledgements

Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-AC04-94AL85000.

The research presented was performed in the framework of the IWT 120029 project OPTIWIND: Serviceability Optimisation of the Next Generation Offshore Wind Turbines. Finally, the authors would also like to kindly acknowledge Professor R.B. Randall from the University of New South Wales in Australia for his precious support.

Author information

Authors and Affiliations

  1. LMS International, Interleuvenlaan 68, B-3001, Leuven, Belgium

    Simone Manzato, Bart Peeters & Karl Janssens

  2. Sandia National Laboratories, Wind Energy Technologies, Albuquerque, NM, USA

    Jonathan R. White & Bruce LeBlanc

Authors
  1. Simone Manzato
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jonathan R. White
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bruce LeBlanc
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Bart Peeters
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Karl Janssens
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Simone Manzato .

Editor information

Editors and Affiliations

  1. University of Cincinnati, Cincinnati, 45221-0018, Ohio, USA

    Randall Allemang

  2. , The Enterprise Program, Michigan Technological University, Townsend Drive 1400, Houghton, 49931, Mississippi, USA

    James De Clerck

  3. , Dept. of Mechanical Engineering, University of Massachusetts Lowell, Riverside St. 197, Lowell, 01854, Massachusetts, USA

    Christopher Niezrecki

  4. & State University, Department of Mechanical Engineering, Virginia Polytechnic Institute, Randolph Hall 114 T, Blacksburg, 24060, Virginia, USA

    Alfred Wicks

Rights and permissions

Reprints and permissions

Copyright information

© 2014 The Society for Experimental Mechanics

About this paper

Cite this paper

Manzato, S., White, J.R., LeBlanc, B., Peeters, B., Janssens, K. (2014). Advanced Identification Techniques for Operational Wind Turbine Data. In: Allemang, R., De Clerck, J., Niezrecki, C., Wicks, A. (eds) Topics in Modal Analysis, Volume 7. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6585-0_19

Download citation

  • DOI: https://doi.org/10.1007/978-1-4614-6585-0_19

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-6584-3

  • Online ISBN: 978-1-4614-6585-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation