Damage detection methods on wind turbine blade testing with wired and wireless accelerometer sensors

Mark Mollineaux, Konstantinos Balafas, Kim Branner, Per Hørlyk Nielsen, Angelo Tesauro, Anne Kiremidjian, Rajagopal Ramesh

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    Abstract

    Testing   was   performed   on   a   34   meter   blade   at   a   facility   in   DTU   Risø   Campus,
    featuring   both   wired   accelerometers   and   low­power   MEMs­based   wireless
    accelerometers. Testing was focused on an induced delamination area on the trailing
    edge of the blade, which was subject to various configurations in order to simulate
    different   degrees   of   damage.   Excitation   was   performed   in   two   ways:   near   the
    delamination zone in a simulation of operational wind excitations, and with a bar
    designed to excite torsional modes of the wind turbine blade. 
    We compare the data collected from the wireless sensors against wired sensors to
    demonstrate their performance. We explore methods for determining damage. We first
    explore results of autoregressive coefficients for indicating damage levels. Finally, we
    demonstrate the use of damage sensitive features from the wavelet transforms of input
    and output signals to provide a method suitable for non­stationary blade excitations. 
    Original languageEnglish
    Title of host publicationProceedings of the 7th European Workshop on Structural Health Monitoring
    Number of pages8
    Publication date2014
    Pages1863-1870
    Publication statusPublished - 2014
    EventEuropean Workshop on Structural Health Monitoring - Nantes, France
    Duration: 8 Jul 201411 Jul 2014
    http://www.ewshm2014.com/

    Workshop

    WorkshopEuropean Workshop on Structural Health Monitoring
    Country/TerritoryFrance
    CityNantes
    Period08/07/201411/07/2014
    Internet address

    Keywords

    • Structural Health Monitoring
    • Damage Detection
    • Wind Turbine
    • Wireless sensing
    • Wavelets

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