Cointegration for Detecting Structural Blade Damage in an Operating Wind Turbine: An Experimental Study

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

Abstract

Environmental and operational variabilities (EOVs) are known to pose an issue in structural health monitoring (SHM) systems, as these variabilities can mask the effect of structural damage. Numerous approaches to remove, or, at least, mitigate, the effect of EOVs in SHM applications have been proposed and tested through numerical simulations and in experimental studies. One of the approaches that has exhibited promising potential is cointegration, which, in this particular SHM context, is a technique for singling out and removing common signal trends stemming from the EOVs. In the present paper, the cointegration technique is employed to mitigate the effect of certain EOVs in an experimental, vibration-based damage detection analysis of a wind turbine blade under operating conditions. In the experimental campaign, the installed SHM system was recording blade accelerations and different environmental and operational conditions over a 3.5-month period. In the period, one of the blades was treated in its reference state and in damaged states with a trailing edge opening of increasing size. Based on the available data from these different structural states, it is demonstrated how cointegration can be used to successfully detect the introduced damages under conditions not allowing for direct discrimination between damage and EOVs.
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Detaljer

Environmental and operational variabilities (EOVs) are known to pose an issue in structural health monitoring (SHM) systems, as these variabilities can mask the effect of structural damage. Numerous approaches to remove, or, at least, mitigate, the effect of EOVs in SHM applications have been proposed and tested through numerical simulations and in experimental studies. One of the approaches that has exhibited promising potential is cointegration, which, in this particular SHM context, is a technique for singling out and removing common signal trends stemming from the EOVs. In the present paper, the cointegration technique is employed to mitigate the effect of certain EOVs in an experimental, vibration-based damage detection analysis of a wind turbine blade under operating conditions. In the experimental campaign, the installed SHM system was recording blade accelerations and different environmental and operational conditions over a 3.5-month period. In the period, one of the blades was treated in its reference state and in damaged states with a trailing edge opening of increasing size. Based on the available data from these different structural states, it is demonstrated how cointegration can be used to successfully detect the introduced damages under conditions not allowing for direct discrimination between damage and EOVs.
OriginalsprogEngelsk
TitelProceedings of the 37th IMAC, A Conference and Exposition on Structural Dynamics 2019
Udgivelses stedFlorida, Orlando
Publikationsdato2019
StatusAfsendt - 2019
PublikationsartForskning
Peer reviewJa
BegivenhedIMAC XXXVII, A Conference and Exposition on Structural Dynamics 2019 - Rosen Plaza Hotel, Orlando, FL., Orlando , USA
Varighed: 28 jan. 201931 jan. 2019
Konferencens nummer: 37
https://sem.org/imac

Konference

KonferenceIMAC XXXVII, A Conference and Exposition on Structural Dynamics 2019
Nummer37
LokationRosen Plaza Hotel, Orlando, FL.
LandUSA
ByOrlando
Periode28/01/201931/01/2019
Internetadresse

    Forskningsområder

  • Damage detection, Cointegration, Environmental and operational variabilities, Wind turbine application, Structural Health Monitoring
ID: 288789709