Exploring Quantum Machine Learning and Feature Reduction Techniques for Wind Turbine Pitch Fault Detection

Exploring Quantum Machine Learning and Feature Reduction Techniques for Wind Turbine Pitch Fault Detection

Driven by the development of machine learning (ML) and deep learning techniques, prognostics and health management (PHM) has become a key aspect of reliability engineering research. With the recent rise in popularity of quantum computing algorithms and public availability of first-generation quantum...

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Bibliographic Details
Main Authors: Camila Correa-Jullian, Sergio Cofre-Martel, Gabriel San Martin, Enrique Lopez Droguett, Gustavo de Novaes Pires Leite, Alexandre Costa
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Energies
Subjects:
quantum machine learning
quantum kernels
wind turbine systems
SCADA system
pitch fault diagnostics
feature reduction
Online Access:https://www.mdpi.com/1996-1073/15/8/2792

Internet

https://www.mdpi.com/1996-1073/15/8/2792

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