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

Resumé

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
RedaktørerShamim Pakzad
Antal sider8
Vol/bind2
Udgivelses stedFlorida, Orlando
ForlagSpringer
Publikationsdato23 maj 2019
Sider173-180
ISBN (Trykt)978-3-030-12114-3
ISBN (Elektronisk)978-3-030-12115-0
DOI
StatusUdgivet - 23 maj 2019
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

Emneord

  • Damage detection
  • Cointegration
  • Environmental and operational variabilities
  • Wind turbine application
  • Structural Health Monitoring

Citer dette

Qadri, B. A., Ulriksen, M. D., Damkilde, L., & Tcherniak, D. (2019). Cointegration for Detecting Structural Blade Damage in an Operating Wind Turbine: An Experimental Study. I S. Pakzad (red.), Proceedings of the 37th IMAC, A Conference and Exposition on Structural Dynamics 2019 (Bind 2, s. 173-180). Florida, Orlando: Springer. https://doi.org/10.1007/978-3-030-12115-0_23
Qadri, Bilal Ali ; Ulriksen, Martin Dalgaard ; Damkilde, Lars ; Tcherniak, Dmitri. / Cointegration for Detecting Structural Blade Damage in an Operating Wind Turbine: An Experimental Study. Proceedings of the 37th IMAC, A Conference and Exposition on Structural Dynamics 2019. red. / Shamim Pakzad. Bind 2 Florida, Orlando : Springer, 2019. s. 173-180
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title = "Cointegration for Detecting Structural Blade Damage in an Operating Wind Turbine: An Experimental Study",
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.",
keywords = "Damage detection, Cointegration, Environmental and operational variabilities, Wind turbine application, Structural Health Monitoring",
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year = "2019",
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Qadri, BA, Ulriksen, MD, Damkilde, L & Tcherniak, D 2019, Cointegration for Detecting Structural Blade Damage in an Operating Wind Turbine: An Experimental Study. i S Pakzad (red.), Proceedings of the 37th IMAC, A Conference and Exposition on Structural Dynamics 2019. bind 2, Springer, Florida, Orlando, s. 173-180, IMAC XXXVII, A Conference and Exposition on Structural Dynamics 2019, Orlando , USA, 28/01/2019. https://doi.org/10.1007/978-3-030-12115-0_23

Cointegration for Detecting Structural Blade Damage in an Operating Wind Turbine: An Experimental Study. / Qadri, Bilal Ali; Ulriksen, Martin Dalgaard; Damkilde, Lars; Tcherniak, Dmitri.

Proceedings of the 37th IMAC, A Conference and Exposition on Structural Dynamics 2019. red. / Shamim Pakzad. Bind 2 Florida, Orlando : Springer, 2019. s. 173-180.

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

TY - GEN

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AU - Qadri, Bilal Ali

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AU - Damkilde, Lars

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PY - 2019/5/23

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N2 - 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.

AB - 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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KW - Environmental and operational variabilities

KW - Wind turbine application

KW - Structural Health Monitoring

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DO - 10.1007/978-3-030-12115-0_23

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SN - 978-3-030-12114-3

VL - 2

SP - 173

EP - 180

BT - Proceedings of the 37th IMAC, A Conference and Exposition on Structural Dynamics 2019

A2 - Pakzad, Shamim

PB - Springer

CY - Florida, Orlando

ER -

Qadri BA, Ulriksen MD, Damkilde L, Tcherniak D. Cointegration for Detecting Structural Blade Damage in an Operating Wind Turbine: An Experimental Study. I Pakzad S, red., Proceedings of the 37th IMAC, A Conference and Exposition on Structural Dynamics 2019. Bind 2. Florida, Orlando: Springer. 2019. s. 173-180 https://doi.org/10.1007/978-3-030-12115-0_23