Abstract
Operational Modal Analysis (OMA) is one of the branches of experimental modal analysis which allows extracting modal parameters based on measuring only the responses of a structure under ambient or operational excitation which is not needed to be measured. This makes OMA extremely attractive to modal analysis of big structures such as wind turbines where providing measured excitation force is an extremely difficult task. One of the main OMA assumption concerning the excitation is that it is distributed randomly both temporally and spatially. Obviously, closer the real excitation is to the assumed one, better modal parameter estimation one can expect. Traditionally, wind excitation is considered as a perfect excitation obeying the OMA assumptions. However, the present study shows that the aeroelastic phenomena due to rotor rotation dramatically changes the character of aerodynamic excitation and sets limitations on the applicability of OMA to operational wind turbines. The main purpose of the study is to warn the experimentalists about these limitations and discuss possible ways of dealing with them.
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References
Helsen, J., Vanhollebeke, F., Vandepitte, D., Desmet, W.: Some trends and challenges in wind turbine upscaling. In: Proceedings of ISMA International Conference on Noise and Vibration, September 2012, pp. ID-593 (2012)
Pintelon, R., Peeters, B., Guillaume, P.: Continuous-time operational modal analysis in the presence of harmonic disturbances. Mech. Syst. Signal Process. 22(5), 1017–1035 (2008)
Tcherniak, D., Chauhan, S., Hansen, M.H.: Applicability limits of operational modal analysis to operational wind turbines. In: Proulx, T. (ed.) Structural Dynamics and Renewable Energy, vol. 1, pp. 317–327. Springer, New York (2011)
Gioia, N., Daems, P.J., Guillaume, P., Helsen, J.: Long term operational modal analysis for rotating machines. J. Phys. Conf. Ser. 1037 (2018). Measurement and Experimental Techniques
Randall, R.B., Sawalhi, N., Coats, M.: A comparison of methods for separation of deterministic and random signals. Int. J. Cond. Monit. 1(1), 11–19 (2011)
Randall, R.B.: A history of cepstrum analysis and its application to mechanical problems. Mech. Syst. Signal Process. 97, 3–19 (2017)
Peeters, B., Van der Auweraer, H.: PolyMAX: a revolution in operational modal analysis. In: 1st International Operational Modal Analysis Conference (IOMAC), Copenhagen, April (2005)
Peeters, B., Lowet, G., Van der Auweraer, H., Leuridan, J.: A new procedure for modal parameter estimation. Sound Vib. 38(1), 24–29 (2004)
Helsen, J., Peeters, C., Doro, P., Ververs, E., Jordaens, P.J., Wind farm operation and maintenance optimization using big data. In: 2017 IEEE Third International Conference on Big Data Computing Service and Applications (BigDataService), April 6, pp. 179–184. IEEE, Piscataway (2017)
El-Kafafy, M., Colanero, L., Gioia, N., Devriendt, C., Guillaume, P., Helsen, J.: Modal parameters estimation of an offshore wind turbine using measured acceleration signals from the drive train. In: Structural Health Monitoring and Damage Detection, vol. 7, pp. 41–48. Springer, Cham (2017)
Van der Auweraer, H., Peeters, B.: Discriminating physical poles from mathematical poles in high order systems: use and automation of the stabilization diagram. In: Proceedings of IMTC 2004, the IEEE Instrumentation and Measurement Technology Conference, Como (2004)
Magalhaes, F., Cunha, A., Caetano, E.: Online automatic identification of the modal parameters of a long span arch bridge. Mech. Syst. Signal Process. 23(2), 316–329 (2009)
Chauhan, S., Tcherniak, D.: Clustering approaches to automatic modal parameter estimation. In: Proceedings, International Modal Analysis Conference (IMAC) (2008)
Goethals, I., Vanluyten, B., De Moor, B.: Reliable spurious mode rejection using self learning algorithms. In: Proceedings of the International Conference on Noise and Vibration Engineering (ISMA 2004), September 2004, Leuven, pp. 991–1003 (2004)
Devriendt, C., Elkafafy, M., De Sitter, G., Guillaume, P.: Continuous dynamic monitoring of an offshore wind turbine on a monopile foundation. In: ISMA2012 (2012)
Devriendt, C., Weijtjens, W., El-Kafafy, M., De Sitter, G.: Monitoring resonant frequencies and damping values of an offshore wind turbine in parked conditions. In: IET Renewable Power Generation 2014, pp. 433–441 (2014)
Acknowledgements
The authors would like to acknowledge the financial support of VLAIO (Flemish Agency for Innovation & Entrepreneurship) through the SBO project HYMOP and the SIM project MaSiWEC.
Furthermore, the authors would like to acknowledge FWO for their support through the SB grant of N. Gioia and T. Verstraeten.
The authors also thank their partners for delivering the monitoring data.
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Gioia, N., Daems, P.J., Verstraeten, T., Guillaume, P., Helsen, J. (2020). Combining Machine Learning and Operational Modal Analysis Approaches to Gain Insights in Wind Turbine Drivetrain Dynamics. In: Mains, M.L., Dilworth, B.J. (eds) Topics in Modal Analysis & Testing, Volume 8. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-030-12684-1_30
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DOI: https://doi.org/10.1007/978-3-030-12684-1_30
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