• DocumentCode
    714836
  • Title

    Automatic classification of wind turbine structural faults using Doppler radar: Proof of concept study

  • Author

    Crespo-Ballesteros, Manuel ; Antoniou, Michail

  • Author_Institution
    Microwave Integrated Syst. Lab. (MISL), Univ. of Birmingham, Birmingham, UK
  • fYear
    2015
  • fDate
    10-15 May 2015
  • Abstract
    This paper explores the possibility in using radar to automatically classify wind turbine faults. As a first step, a number of experiments were conducted in an anechoic chamber with a small wind turbine were different faults were artificially induced. Two basic clustering methods were used. One was based on using different statistical parameters of the corresponding time-domain signatures. The other used Principal Components Analysis (PCA) on the corresponding frequency-domain signatures. Subsequently, a K-NN algorithm was used as the classifier to investigate whether or not automatic classification is fundamentally possible and to provide an initial comparison between the two clustering methods which rely on different signal domains. The proof of concept results presented in the paper indicate that this may indeed be plausible, to encourage further development of this idea.
  • Keywords
    Doppler radar; anechoic chambers (electromagnetic); frequency-domain analysis; principal component analysis; time-domain analysis; wind turbines; Doppler radar; K-NN algorithm; PCA; anechoic chamber; automatic classification; frequency-domain signatures; principal components analysis; statistical parameters; time-domain signatures; wind turbine structural faults; Blades; Classification algorithms; Doppler radar; Radar cross-sections; Time-domain analysis; Wind turbines; Doppler radar; radar target classification; structural health monitoring; wind turbines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Radar Conference (RadarCon), 2015 IEEE
  • Conference_Location
    Arlington, VA
  • Print_ISBN
    978-1-4799-8231-8
  • Type

    conf

  • DOI
    10.1109/RADAR.2015.7131011
  • Filename
    7131011