Abstract
System identification is the main goal when performing modal testing of mechanical structures. In cases where only the structural responses are measured, the identification technique is addressed in the literature as operational modal analysis (OMA). Applications of OMA are found in structures where the excitation from the ambient can not be removed or it is the only possible one. Since the ambient forces can not be measured, the identification of the modal parameters is possible if some hypotheses about its random nature are made. In this paper, the modal identification of a small and flexible wind turbine blade is performed under the OMA framework. Although the tested structure was in laboratory condition, traditional experimental modal analysis was not possible due to the small size and high flexibility of the blade. Therefore, this paper demonstrates the importance of OMA in the modal identification of this type of structure (simultaneously light and flexible). An artificially generated wind was used instead as source of excitation, which presented good properties necessary for OMA (stationarity and broadband frequency). The stochastic subspace identification method was used to identify the modal parameters, leading to good identification in a prescribed frequency band of interest. A procedure to analyze and validate the experimental results is also given at the end.
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References
Rainieri C, Fabbrocino G (2014) Operational modal analysis of civil engineering structures. Springer, New York
Rodrigues J (2004) Identificação Modal Estocástica. PhD thesis, University of Porto
Brincker R, Ventura C (2015) Introduction to operational modal analysis. Wiley, West Sussex
Peeters B, Ventura CE (2003) Comparative study of modal analysis techniques for bridge dynamic characteristics. MSSP 17(5):965–988
Peeters B (2000) System identification and damage detection in civil engineering. PhD thesis, Katholieke Universiteit Leuven
Reynders E, Pintelon R, De Roeck G (2008) Uncertainty bounds on modal parameters obtained from stochastic subspace identification. MSSP 22(4):948–969
Reynders E, Maes K, Lombaert G, De Roeck G (2016) Uncertainty quantification in operational modal analysis with stochastic subspace identification: validation and application. MSSP 66–67:13–30
Mellinger P, Döhlerm M, Mevel L (2016) Variance estimation of modal parameters from output-only and input/output subspace-based system identification. J Sound Vib 379:1–27
Liu Y (2011) Bridge health monitoring. Maintenance and safety. Trans Tech Publications, Bach
Farrrar CR, Worden K (2013) Structural health monitoring: a machine learning perspective. Wiley, West Sussex
Deraemaeker A, Worden K (2012) New trends in vibration based structural health monitoring. Springer, Vienna
Manzato S, White JR, LeBlanc B, Peeters B, Janssens K (2013) Advanced identification techniques for operational wind turbine data. Top Modal Anal 7:195–209
Peeters B, De Roeck G (2000) One-year monitoring of the Z24-Bridge: environmental effects versus damage events. Earthq Eng Struct Dyn 30(2):149–171
Maeck J, Peeters B, De Roeck G (2001) Damage identification on the Z24 bridge using vibration monitoring. Smart Mater Struct 10:512–517
Peeters B, Couvreur G, Razinkov O, Kündig C, Van der Auweraer H, De Roeck G (2009) Continuous monitoring of the Øresund bridge: system and data analysis. Struct Infrastruct Eng 5:395–405
Di Lorenzo E, Kosova G, Musella U, Manzato S, Peeters B, Marulo F, Desmet W (2015) Structural health monitoring challenges on the 10-MW offshore wind turbine model. J Phys 628:012081
Overschee PV, De Moor B (1996) Subspace identification for linear systems. Kluwer Academic Publishers, Leuven
Peeters B, De Roeck G (1999) Reference-based stochastic subspace identification for output-only modal analysis. MSSP 13(6):855–878
Peeters B, De Roeck G (2000) Reference based stochastic subspace identification in civil engineering. Inverse Probl Sci Eng 8(1):47–74
Reynders E, De Roeck G (2008) Reference-based combined deterministic-stochastic subspace identification for experimental and operational modal analysis. MSSP 22(3):617–637
Wagner GB, Foiny D, Lima R, Sampaio R (2017) Operational modal analysis under wind load using stochastic subspace identification. In: Proceedings of the 17th international symposium on dynamic problems of mechanics, São Sebastião, Brazil
Juang J (1994) Applied system identification. Prentice Hall, Englewood Cliffs
Cursi ES, Sampaio R (2015) Uncertainty quantification and stochastic modeling with Matlab. Elsevier, ISTE Press, London
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The authors acknowledge the support given by FAPERJ, CNPq and CAPES.
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Wagner, G., Lima, R. & Sampaio, R. Modal identification of a light and flexible wind turbine blade under wind excitation. J Eng Math 133, 3 (2022). https://doi.org/10.1007/s10665-022-10210-1
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DOI: https://doi.org/10.1007/s10665-022-10210-1