Abstract
The stability and dynamic response of offshore wind turbines can be affected by the erosion of the foundation, referred to as scour. As an alternative to applying costly scour protection, monitoring of scour development is often performed based on a shift in the fundamental natural frequency of the structure. This paper considers scour detection as an outlier detection problem using features that do not require system identification. A state of the structure is classified as healthy or damaged based on three damage sensitive features extracted from the response signals: auto-regressive model coefficients, unique entries of the response covariance matrix and transmissibility functions. The examination is performed using a numerical monopile model supported by Winkler springs and loaded by random excitation. The results show that, among the presented features, the auto-regressive model coefficients display the highest sensitivity to scour, as the use of this feature allows for detection of scour corresponding to 3 % of the embedded monopile depth even in the presence of noise.
Original language | English |
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Title of host publication | Advances in Engineering Materials, Structures and Systems: Innovations, Mechanics and Applications : Proceedings of the 7th International Conference on Structural Engineering, Mechanics and Computation (SEMC 2019), September 2-4, 2019, Cape Town, South Africa |
Editors | Alphose Zingoni |
Number of pages | 6 |
Publisher | CRC Press |
Publication date | 2019 |
Pages | 1976-1981 |
ISBN (Print) | 9781138386969 |
ISBN (Electronic) | 9780429426506 |
DOIs | |
Publication status | Published - 2019 |
Event | The Seventh International Conference on Structural Engineering, Mechanics and Computation - Cape Town, South Africa Duration: 2 Sept 2019 → 4 Sept 2019 Conference number: 7 http://www.semc.uct.ac.za/ |
Conference
Conference | The Seventh International Conference on Structural Engineering, Mechanics and Computation |
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Number | 7 |
Country/Territory | South Africa |
City | Cape Town |
Period | 02/09/2019 → 04/09/2019 |
Internet address |