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Investigation of icing causes on wind turbine rotor blades using machine learning models, minimalistic input data and a full-factorial design


Authors

  • Kreutz, M.
  • Ait Alla, A.
  • Varasteh, K.
  • Lütjen, M.
  • Freitag, M.
  • Thoben, K.-D.

Meta information [BibTeX]

  • Year: 2020, Reviewed
  • Thoben, K.-D. and Dekena, B. and Lang, W. and Trächtler, A. (Editors)
  • In: Procedia Manufacturing, Vol. 52
  • Conference: 5th International Conference on System-Integrated Intelligence, flexible and connected systems in products and production (SysInt) in Bremen, Germany (November 11-13, 2020)
  • Publisher: Elsevier, Amsterdam
  • Pages: 168-173
  • ISSN: 2351-9789
  • DOI: 10.1016/j.promfg.2020.11.030



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Kreutz, M.; Ait Alla, A.; Varasteh, K.; Lütjen, M.; Freitag, M.; Thoben, K.-D.
Investigation of icing causes on wind turbine rotor blades using machine learning models, minimalistic input data and a full-factorial design
In: Thoben, K.-D.; Dekena, B.; Lang, W.; Trächtler, A. (eds.): Procedia Manufacturing, Vol. 52. Elsevier, Amsterdam, 2020, pp. 168-173
(Workgroups: BIBA, BIBA)
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