Advertisement

Structural Identification for Dynamic Strain Estimation in Wind Turbine Towers

  • Mansure Nabiyan
  • Hamed Ebrahimian
  • Babak Moaveni
  • Faramarz Khoshnoudian
Conference paper
Part of the Conference Proceedings of the Society for Experimental Mechanics Series book series (CPSEMS)

Abstract

Fatigue is a common issue in steel structures such as wind turbine towers, which is caused by cyclic wind and wave excitations. Therefore, estimation of the remaining fatigue life of the structural and foundation system is of concern. For this purpose, continuous monitoring of the structure is necessary to obtain strain data at fatigue critical points. Since installing and maintaining strain sensors in critical underwater location is difficult, strain data is often available only from a few sensors at accessible locations. Using these sparse sensors, the strain time histories at fatigue critical points can be estimated using estimation techniques. These techniques can identify the structural system using limited measured response data and a system model. In this paper, we implement a model updating approach followed by modal expansion to estimate the strain time history at critical points in a numerical case study representing an offshore wind turbine tower. The acceleration response of the structure is simulated using a finite element model and polluted with Gaussian white noise to represent measurements. The measurements are then used for model updating and strain estimation. The accuracy of the methods and their robustness to the measurement noise and model uncertainty are investigated. The estimated strain response time histories can later be used as input to an appropriate fatigue damage model to estimate the current state of fatigue damage in the system.

Keywords

System identification Modal parameters Model updating Strain estimation Modal expansion 

Notes

Acknowledgements

Partial support of this study by the National Science Foundation Grant 1254338 is gratefully acknowledged. The opinions, findings, and conclusions expressed in this paper are those of the authors and do not necessarily represent the views of the sponsors and organizations involved in this project.

References

  1. 1.
    Skafte, A., Tygesen, U.T., Brincker, R.: Expansion of mode shapes and responses on the offshore platform Valdemar. In: Dynamics of Civil Structures, vol. 4, pp. 35–41. Springer, Cham (2014)CrossRefGoogle Scholar
  2. 2.
    Iliopoulos, A., et al.: Prediction of dynamic strains on a monopile offshore wind turbine using virtual sensors. In: Journal of Physics: Conference Series. IOP Publishing, USA (2015)Google Scholar
  3. 3.
    Iliopoulos, A., et al.: A modal decomposition and expansion approach for prediction of dynamic responses on a monopile offshore wind turbine using a limited number of vibration sensors. Mech. Syst. Signal Process. 68, 84–104 (2016)CrossRefGoogle Scholar
  4. 4.
    Iliopoulos, A.N., et al.: Continuous fatigue assessment of offshore wind turbines using a stress prediction technique. In: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring. SPIE, UK (2014)Google Scholar
  5. 5.
    Skafte, A., et al.: Experimental study of strain prediction on wave induced structures using modal decomposition and quasi static Ritz vectors. Eng. Struct. 136(Supplement C), 261–276 (2017)CrossRefGoogle Scholar
  6. 6.
    Smyth, A., Wu, M.: Multi-rate Kalman filtering for the data fusion of displacement and acceleration response measurements in dynamic system monitoring. Mech. Syst. Signal Process. 21(2), 706–723 (2007)CrossRefGoogle Scholar
  7. 7.
    Palanisamy, R.P., et al.: Experimental validation of Kalman filter-based strain estimation in structures subjected to non-zero mean input. Smart Struct. Syst. 15(2), 489–503 (2015)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Papadimitriou, C., et al.: Fatigue predictions in entire body of metallic structures from a limited number of vibration sensors using Kalman filtering. Struct. Control Health Monit. 18(5), 554–573 (2011)CrossRefGoogle Scholar
  9. 9.
    Maes, K., et al.: Continuous strain prediction for fatigue assessment of an offshore wind turbine using Kalman filtering techniques. In: 2015 IEEE Workshop on Environmental, Energy and Structural Monitoring Systems (EESMS). IEEE, Trento (2015)Google Scholar
  10. 10.
    Azam, S.E., Chatzi, E., Papadimitriou, C.: A dual Kalman filter approach for state estimation via output-only acceleration measurements. Mech. Syst. Signal Process. 60, 866–886 (2015)CrossRefGoogle Scholar
  11. 11.
    Estrada, I., Real, E., Mirambell, E.: General behaviour and effect of rigid and non-rigid end post in stainless steel plate girders loaded in shear. Part II: extended numerical study and design proposal. J. Constr. Steel Res. 63(7), 985–996 (2007)CrossRefGoogle Scholar
  12. 12.
    Van der Male, P., Lourens, E.: Operational vibration-based response estimation for offshore wind lattice structures. In: Structural Health Monitoring and Damage Detection, vol. 7, pp. 83–96. Springer, Cham (2015)Google Scholar
  13. 13.
    Niu, Y., Klinkov, M., Fritzen, C.: Online force reconstruction using an unknown-input Kalman filter approach. In: Proceedings of the 8th International Conference on Structural Dynamics. EURODYN, Leuven (2011)Google Scholar
  14. 14.
    Maes, K., et al.: Dynamic strain estimation for fatigue assessment of an offshore monopile wind turbine using filtering and modal expansion algorithms. Mech. Syst. Signal Process. 76, 592–611 (2016)CrossRefGoogle Scholar
  15. 15.
    James III, G.H., Carne, T.G., Lauffer, J.P.: The Natural Excitation Technique (NExT) for Modal Parameter Extraction from Operating Wind Turbines. Sandia National Labs., Albuquerque, NM (1993)Google Scholar
  16. 16.
    Juang, J.-N., Pappa, R.S.: An eigensystem realization algorithm for modal parameter identification and model reduction. J. Guid. 8(5), 620–627 (1985)CrossRefGoogle Scholar
  17. 17.
    Heylen, W., Sas, P.: Modal Analysis Theory and Testing. Katholieke Universteit Leuven, Departement Werktuigkunde, Leuven, Belgium (2006)Google Scholar
  18. 18.
    Gan, B.S.: Finite element formulation of beam elements. In: An Isogeometric Approach to Beam Structures, pp. 61–126. Springer, Cham (2018)CrossRefGoogle Scholar
  19. 19.
    Hernandez, E.M., Bernal, D., Caracoglia, L.: On-line monitoring of wind-induced stresses and fatigue damage in instrumented structures. Struct. Control Health Monit. 20(10), 1291–1302 (2013)CrossRefGoogle Scholar

Copyright information

© The Society for Experimental Mechanics, Inc. 2019

Authors and Affiliations

  • Mansure Nabiyan
    • 1
  • Hamed Ebrahimian
    • 2
  • Babak Moaveni
    • 3
  • Faramarz Khoshnoudian
    • 1
  1. 1.School of Civil EngineeringAmirkabir University of TechnologyTehranIran
  2. 2.Department of Mechanical & Civil EngineeringCalifornia Institute of TechnologyPasadenaUSA
  3. 3.Department of Civil and Environmental EngineeringTufts UniversityMedfordUSA

Personalised recommendations