Reconstructing Stress Resultants in Wind Turbine Towers Based on Strain Measurements
(2021) 4th International Conference on Uncertainty in Mechanical Engineering, ICUME 2021 In Lecture Notes in Mechanical Engineering p.224-235- Abstract
Support structures of offshore wind turbines are subject to cyclic stresses generated by different time-variant random loadings such as wind, waves, and currents in combination with the excitation by the rotor. In the design phase, the cyclic demand on wind turbine support structure is calculated and forecasted with semi or fully probabilistic engineering models. In some cases, additional cyclic stresses may be induced by construction deviations, unbalanced rotor masses and structural dynamic phenomena such as, for example, the Sommerfeld effect. Both, the significant uncertainties in the design and a validation of absence of unforeseen adverse dynamic phenomena necessitate the employment of measurement systems on the support... (More)
Support structures of offshore wind turbines are subject to cyclic stresses generated by different time-variant random loadings such as wind, waves, and currents in combination with the excitation by the rotor. In the design phase, the cyclic demand on wind turbine support structure is calculated and forecasted with semi or fully probabilistic engineering models. In some cases, additional cyclic stresses may be induced by construction deviations, unbalanced rotor masses and structural dynamic phenomena such as, for example, the Sommerfeld effect. Both, the significant uncertainties in the design and a validation of absence of unforeseen adverse dynamic phenomena necessitate the employment of measurement systems on the support structures. The quality of the measurements of the cyclic demand on the support structures depends on (a) the precision of the measurement system consisting of sensors, amplifier and data normalization and (b) algorithms for analyzing and converting data to structural health information. This paper presents the probabilistic modelling and analysis of uncertainties in strain measurements performed for the purposes of reconstructing stress resultants in wind turbine towers. It is shown how the uncertainties in the strain measurements affect the uncertainty in the individual components of the reconstructed forces and moments. The analysis identifies the components of the vector of stress resultants that can be reconstructed with sufficient precision.
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- author
- Kinne, Marko ; Schneider, Ronald and Thöns, Sebastian LU
- organization
- publishing date
- 2021
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Bayesian updating of measurement uncertainties, Reconstruction of stress resultants, Strain measurements
- host publication
- Uncertainty in Mechanical Engineering - Proceedings of the 4th International Conference on Uncertainty in Mechanical Engineering, ICUME 2021
- series title
- Lecture Notes in Mechanical Engineering
- editor
- Pelz, Peter F. and Groche, Peter
- pages
- 12 pages
- publisher
- Springer
- conference name
- 4th International Conference on Uncertainty in Mechanical Engineering, ICUME 2021
- conference location
- Virtual, Online
- conference dates
- 2021-06-07 - 2021-06-08
- external identifiers
-
- scopus:85111379521
- ISSN
- 2195-4364
- 2195-4356
- ISBN
- 9783030772567
- 9783030772550
- DOI
- 10.1007/978-3-030-77256-7_18
- language
- English
- LU publication?
- yes
- additional info
- Funding Information: This work was supported by the German Ministry for Economic Affairs and Energy (BMWi) through grant 03SX449Z. Publisher Copyright: © 2021, The Author(s). Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
- id
- f03fb315-0c20-46aa-bb96-fdfe4b75fbaa
- date added to LUP
- 2021-08-09 07:25:26
- date last changed
- 2024-06-15 13:59:47
@inproceedings{f03fb315-0c20-46aa-bb96-fdfe4b75fbaa,
abstract = {{<p>Support structures of offshore wind turbines are subject to cyclic stresses generated by different time-variant random loadings such as wind, waves, and currents in combination with the excitation by the rotor. In the design phase, the cyclic demand on wind turbine support structure is calculated and forecasted with semi or fully probabilistic engineering models. In some cases, additional cyclic stresses may be induced by construction deviations, unbalanced rotor masses and structural dynamic phenomena such as, for example, the Sommerfeld effect. Both, the significant uncertainties in the design and a validation of absence of unforeseen adverse dynamic phenomena necessitate the employment of measurement systems on the support structures. The quality of the measurements of the cyclic demand on the support structures depends on (a) the precision of the measurement system consisting of sensors, amplifier and data normalization and (b) algorithms for analyzing and converting data to structural health information. This paper presents the probabilistic modelling and analysis of uncertainties in strain measurements performed for the purposes of reconstructing stress resultants in wind turbine towers. It is shown how the uncertainties in the strain measurements affect the uncertainty in the individual components of the reconstructed forces and moments. The analysis identifies the components of the vector of stress resultants that can be reconstructed with sufficient precision.</p>}},
author = {{Kinne, Marko and Schneider, Ronald and Thöns, Sebastian}},
booktitle = {{Uncertainty in Mechanical Engineering - Proceedings of the 4th International Conference on Uncertainty in Mechanical Engineering, ICUME 2021}},
editor = {{Pelz, Peter F. and Groche, Peter}},
isbn = {{9783030772567}},
issn = {{2195-4364}},
keywords = {{Bayesian updating of measurement uncertainties; Reconstruction of stress resultants; Strain measurements}},
language = {{eng}},
pages = {{224--235}},
publisher = {{Springer}},
series = {{Lecture Notes in Mechanical Engineering}},
title = {{Reconstructing Stress Resultants in Wind Turbine Towers Based on Strain Measurements}},
url = {{http://dx.doi.org/10.1007/978-3-030-77256-7_18}},
doi = {{10.1007/978-3-030-77256-7_18}},
year = {{2021}},
}