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

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

Floating wind turbines (FWTs) operate in offshore environments under harsh and varying operating conditions, making frequent in situ monitoring dangerous for maintenance teams and costly for operators. Remote and automated diagnosis, including the stages of detection, identification, and severity ch...

Full description

Saved in:
Bibliographic Details
Main Authors: John S. Korolis, Dimitrios M. Bourdalos, John S. Sakellariou
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Sensors
Subjects:
damage diagnosis
floating wind turbine
varying wind conditions
vibration signals
machine learning methods
Online Access:https://www.mdpi.com/1424-8220/25/4/1170
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/1424-8220/25/4/1170

Similar Items