Machine Learning-Based Damage Diagnosis in Floating Wind Turbines Using Vibration Signals: A Lab-Scale Study Under Different Wind Speeds and Directions.

Korolis JS, Bourdalos DM, Sakellariou JS

Open source

DOI
10.3390/s25041170
Published
2025 Feb 14
Container
Sensors (Basel, Switzerland)
Publisher
Not recorded
Open access
yes

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BibTeX

@article{allodium:10.3390/s25041170,
  title = {Machine Learning-Based Damage Diagnosis in Floating Wind Turbines Using Vibration Signals: A Lab-Scale Study Under Different Wind Speeds and Directions.},
  author = {Korolis JS and Bourdalos DM and Sakellariou JS},
  year = {2025},
  journal = {Sensors (Basel, Switzerland)},
  doi = {10.3390/s25041170},
  url = {https://doi.org/10.3390/s25041170}
}

RIS

TY  - JOUR
TI  - Machine Learning-Based Damage Diagnosis in Floating Wind Turbines Using Vibration Signals: A Lab-Scale Study Under Different Wind Speeds and Directions.
AU  - Korolis JS
AU  - Bourdalos DM
AU  - Sakellariou JS
PY  - 2025
JO  - Sensors (Basel, Switzerland)
DO  - 10.3390/s25041170
UR  - https://doi.org/10.3390/s25041170
ER  -

APA

JS, K., DM, B., & JS, S. (2025). Machine Learning-Based Damage Diagnosis in Floating Wind Turbines Using Vibration Signals: A Lab-Scale Study Under Different Wind Speeds and Directions.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s25041170

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