Skip to main content
Top

2023 | OriginalPaper | Chapter

15. Digital Twinning of Modeling for Offshore Wind Turbine Drivetrain Monitoring: A Numerical Study

Authors : Vahid Jahangiri, Mohammad Valikhani, Hamed Ebrahimian, Sauro Liberatore, Babak Moaveni, Eric Hines

Published in: Model Validation and Uncertainty Quantification, Volume 3

Publisher: Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Failures in wind turbine drivetrain system including gearbox, bearings, and generator accounts for more than 60% of total wind turbine downtime. In this study, a mechanics-based digital twin technology is proposed to update drivetrain models parameters using measured data and predict the mechanics-based demand in drivetrain components. With the proposed mechanics-based digital twin, the alternations in the structural model parameters can be monitored and identified for damage diagnosis purposes. The proposed technology is implemented on a numerical torsional model of a wind turbine drivetrain system to update the drivetrain model using simulated data and predict the mechanics-based demand in drivetrain components. Implementation of this approach is used to update the failure models and estimate the remaining useful life of drivetrain components including gears and shafts.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literature
1.
go back to reference Pfaffel, S., Faulstich, S., Rohrig, K.: Performance and reliability of wind turbines: a review. Energies. 10(11), 1904 (2017)CrossRef Pfaffel, S., Faulstich, S., Rohrig, K.: Performance and reliability of wind turbines: a review. Energies. 10(11), 1904 (2017)CrossRef
2.
go back to reference Perišić, N., Kirkegaard, P.H., Pedersen, B.J.: Cost-effective shaft torque observer for condition monitoring of wind turbines. Wind Energy. 18(1), 1–19 (2015) Perišić, N., Kirkegaard, P.H., Pedersen, B.J.: Cost-effective shaft torque observer for condition monitoring of wind turbines. Wind Energy. 18(1), 1–19 (2015)
3.
go back to reference Moghadam, F.K., Rebouças, G.F.d.S., Nejad, A.R.: Digital twin modeling for predictive maintenance of gearboxes in floating offshore wind turbine drivetrains. Forschung im Ingenieurwesen. 85(2), 273–286 (2021)CrossRef Moghadam, F.K., Rebouças, G.F.d.S., Nejad, A.R.: Digital twin modeling for predictive maintenance of gearboxes in floating offshore wind turbine drivetrains. Forschung im Ingenieurwesen. 85(2), 273–286 (2021)CrossRef
4.
go back to reference Nejad, A.R., Guo, Y., Gao, Z., Moan, T.: Development of a 5 MW reference gearbox for offshore wind turbines. Wind Energy. 19(6), 1089–1106 (2016)CrossRef Nejad, A.R., Guo, Y., Gao, Z., Moan, T.: Development of a 5 MW reference gearbox for offshore wind turbines. Wind Energy. 19(6), 1089–1106 (2016)CrossRef
5.
go back to reference Ebrahimian, H., Astroza, R., Conte, J.P., Papadimitriou, C.: Bayesian optimal estimation for output-only nonlinear system and damage identification of civil structures. Struct. Control Health Monit. 25(4), e2128 (2018)CrossRef Ebrahimian, H., Astroza, R., Conte, J.P., Papadimitriou, C.: Bayesian optimal estimation for output-only nonlinear system and damage identification of civil structures. Struct. Control Health Monit. 25(4), e2128 (2018)CrossRef
6.
go back to reference Nabiyan, M.-S., Khoshnoudian, F., Moaveni, B., Ebrahimian, H.: Mechanics-based model updating for identification and virtual sensing of an offshore wind turbine using sparse measurements. Struct. Control Health Monit. 28, e2647 (2021)CrossRef Nabiyan, M.-S., Khoshnoudian, F., Moaveni, B., Ebrahimian, H.: Mechanics-based model updating for identification and virtual sensing of an offshore wind turbine using sparse measurements. Struct. Control Health Monit. 28, e2647 (2021)CrossRef
7.
go back to reference Jonkman, J., Butterfield, S., Musial, W., Scott, G.: Definition of a 5-MW reference wind turbine for offshore system development No. NREL/TP-500-38060. National Renewable Energy Lab. (NREL), Golden (2009)CrossRef Jonkman, J., Butterfield, S., Musial, W., Scott, G.: Definition of a 5-MW reference wind turbine for offshore system development No. NREL/TP-500-38060. National Renewable Energy Lab. (NREL), Golden (2009)CrossRef
8.
go back to reference Jonkman, J.M., Buhl Jr, M.L.: FAST user’s guide, vol. 365, p. 366.8. National Renewable Energy Laboratory, Golden (2005) Jonkman, J.M., Buhl Jr, M.L.: FAST user’s guide, vol. 365, p. 366.8. National Renewable Energy Laboratory, Golden (2005)
Metadata
Title
Digital Twinning of Modeling for Offshore Wind Turbine Drivetrain Monitoring: A Numerical Study
Authors
Vahid Jahangiri
Mohammad Valikhani
Hamed Ebrahimian
Sauro Liberatore
Babak Moaveni
Eric Hines
Copyright Year
2023
DOI
https://doi.org/10.1007/978-3-031-04090-0_15