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.
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References
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
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
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
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
Tcherniak D, Chauhan S, Hansen MH (2010) Applicability limits of operational modal analysis to operational wind turbines. In: Proceedings of IMAC XXVII, Jacksonville, FL
Peeters B, Cornelis B, Janssens K, Van der Auweraer H (2007) Removing disturbing harmonics in operational modal analysis. In: Proceedings of IOMAC, Copenhagen, Denmark
Mohaveny P (2005) Operational modal analysis in the resence of harmonic excitation. PhD dissertation thesis, Technische Universiteit Delft
Heylen W, Lammens S, Sas P (1997) Modal analysis theory and testing. Katholieke Universiteit Leuven, Leuven
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
White JR (2009) Operational monitoring of horizontal axis wind turbines using inertial measurements. PhD dissertation, Purdue University
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
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
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
Randall RB (2002) State of the art in monitoring rotating machinery. In: Proceedings of ISMA 2002, Leuven, Belgium
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
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
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
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
Randall RB (2009) Cepstral methods of operational modal analysis. In: Encyclopedia of structural health monitoring. Wiley, Chichester
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
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
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
Bir G (2008) Multiblade coordinate transformation and its application to wind turbine analysis. In: Proceedings of the 2008 ASME wind energy symposium, Reno, Nevada
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.
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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
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DOI: https://doi.org/10.1007/978-1-4614-6585-0_19
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