A novel hybrid methodology for fault diagnosis of wind energy conversion systems

A novel hybrid methodology for fault diagnosis of wind energy conversion systems

<p>This paper proposes effective Random Forest (RF)-based fault detection and diagnosis for wind energy conversion (WEC) systems. The proposed technique involved two major steps: feature selection and fault classification. Feature selection pre-processing is an important step to increase the a...

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Bibliographic Details
Main Author: Khaled Dhibi (16891524) (author)
Other Authors: Majdi Mansouri (16869885) (author), Mansour Hajji (16869894) (author), Kais Bouzrara (16869906) (author), Hazem Nounou (16869900) (author), Mohamed Nounou (3489386) (author)
Published: 2023
Subjects:
Engineering
Electrical engineering
Environmental engineering
Information and computing sciences
Machine learning
Neighborhood component analysis (NCA)
Equilibrium optimizer (EO)
Random Forest (RF)
Fault diagnosis
Fault classification
Wind energy conversion (WEC)
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