Classification Analytics for Wind Turbine Blade Faults: Integrated Signal Analysis and Machine Learning Approach

Classification Analytics for Wind Turbine Blade Faults: Integrated Signal Analysis and Machine Learning Approach

Wind turbine blades are critical components of wind energy systems, and their structural health is essential for reliable operation and maintenance. Several studies have used time-domain and frequency-domain features alongside machine learning techniques to predict faults in wind turbine blades, suc...

Full description

Bibliographic Details
Main Authors: Waqar Ali, Idriss El-Thalji, Knut Erik Teigen Giljarhus, Andreas Delimitis
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Energies
Subjects:
predictive maintenance
machine learning
diagnostic analytics
erosion fault
crack fault
wind turbine blade
Online Access:https://www.mdpi.com/1996-1073/17/23/5856

Internet

https://www.mdpi.com/1996-1073/17/23/5856

Similar Items