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

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-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.
Original languageEnglish
Title of host publicationProceedings of the 37th IMAC, A Conference and Exposition on Structural Dynamics 2019
EditorsShamim Pakzad
Number of pages8
Volume2
Place of PublicationFlorida, Orlando
PublisherSpringer
Publication date23 May 2019
Pages173-180
ISBN (Print)978-3-030-12114-3
ISBN (Electronic)978-3-030-12115-0
DOIs
Publication statusPublished - 23 May 2019
EventIMAC XXXVII, A Conference and Exposition on Structural Dynamics 2019 - Rosen Plaza Hotel, Orlando, FL., Orlando , United States
Duration: 28 Jan 201931 Jan 2019
Conference number: 37
https://sem.org/imac

Conference

ConferenceIMAC XXXVII, A Conference and Exposition on Structural Dynamics 2019
Number37
LocationRosen Plaza Hotel, Orlando, FL.
CountryUnited States
CityOrlando
Period28/01/201931/01/2019
Internet address

Cite this

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. In S. Pakzad (Ed.), Proceedings of the 37th IMAC, A Conference and Exposition on Structural Dynamics 2019 (Vol. 2, pp. 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. editor / Shamim Pakzad. Vol. 2 Florida, Orlando : Springer, 2019. pp. 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",
author = "Qadri, {Bilal Ali} and Ulriksen, {Martin Dalgaard} and Lars Damkilde and Dmitri Tcherniak",
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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. in S Pakzad (ed.), Proceedings of the 37th IMAC, A Conference and Exposition on Structural Dynamics 2019. vol. 2, Springer, Florida, Orlando, pp. 173-180, Orlando , United States, 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. ed. / Shamim Pakzad. Vol. 2 Florida, Orlando : Springer, 2019. p. 173-180.

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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AU - Damkilde, Lars

AU - Tcherniak, Dmitri

PY - 2019/5/23

Y1 - 2019/5/23

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.

KW - Damage detection

KW - Cointegration

KW - Environmental and operational variabilities

KW - Wind turbine application

KW - Structural Health Monitoring

U2 - 10.1007/978-3-030-12115-0_23

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

M3 - Article in proceeding

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. In Pakzad S, editor, Proceedings of the 37th IMAC, A Conference and Exposition on Structural Dynamics 2019. Vol. 2. Florida, Orlando: Springer. 2019. p. 173-180 https://doi.org/10.1007/978-3-030-12115-0_23