Abstract
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 37th IMAC, A Conference and Exposition on Structural Dynamics 2019 |
| Editors | Shamim Pakzad |
| Number of pages | 8 |
| Volume | 2 |
| Place of Publication | Florida, Orlando |
| Publisher | Springer |
| Publication date | 23 May 2019 |
| Pages | 173-180 |
| ISBN (Print) | 978-3-030-12114-3 |
| ISBN (Electronic) | 978-3-030-12115-0 |
| DOIs | |
| Publication status | Published - 23 May 2019 |
| Event | IMAC XXXVII, A Conference and Exposition on Structural Dynamics 2019 - Rosen Plaza Hotel, Orlando, FL., Orlando , United States Duration: 28 Jan 2019 → 31 Jan 2019 Conference number: 37 https://sem.org/imac |
Conference
| Conference | IMAC XXXVII, A Conference and Exposition on Structural Dynamics 2019 |
|---|---|
| Number | 37 |
| Location | Rosen Plaza Hotel, Orlando, FL. |
| Country | United States |
| City | Orlando |
| Period | 28/01/2019 → 31/01/2019 |
| Internet address |
Cite this
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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 proceeding › Article in proceeding › Research › peer-review
TY - GEN
T1 - Cointegration for Detecting Structural Blade Damage in an Operating Wind Turbine: An Experimental Study
AU - Qadri, Bilal Ali
AU - Ulriksen, Martin Dalgaard
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 -