Description
Structural health monitoring (SHM) systems are used to monitor the structural properties of wind turbines, both onshore and offshore. They offer the possibility to monitor the fatigue life consumption and the resonance frequencies of the substructures over time. Especially in offshore wind these systems have found wider adoption as design uncertainties motivate monitoring. One goal of SHM is to track the resonance frequencies of the substructure to detect changes in the boundary conditions. However, research has shown that the resonance frequencies of the rotor can also be observed from a SHM system on the tower. The rotor’s resonance frequencies are sensitive to changes of mass of the blade and thus to the deposition of ice on the blades. The question arises whether observing the rotor frequencies from the tower is accurate enough to reliably detect icing.In this study, a 12m wind turbine blade was instrumented and placed in OWI-lab’s climate chamber to test the sensitivity of the SHM system to icing and temperature. The blade was cooled to -10°C and icing was applied in a controlled manner. Data was processed using automated OMA to monitor the evolution of the natural frequencies over time and a normalization model was used to compensate for temperature-induced changes in the frequencies.
In parallel, the concept was tested on an onshore Enercon 2MW turbine equipped with a portable SHM device. Measurements were collected during the winter of 2020-2021 at a site where icing conditions are fairly common. A methodology was developed to estimate the resonance frequencies of the wind turbine and track the frequencies of the rotor both during operation and standstill. The results were consistent with previous observations that the rotor frequencies can be reliably monitored from the tower. A machine learning strategy was then used to detect any sudden drops in the frequencies, which would indicate the presence of ice on the blades.
Period | 24 May 2023 |
---|---|
Event title | WESC 2023 |
Event type | Conference |
Location | Glasgow, United Kingdom |
Degree of Recognition | International |
Documents & Links
Related content
-
Datasets