Fault detection and identification for control systems in floating offshore wind farms: A supervised Deep Learning methodology-Reference-Cited by-同舟云学术

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Fault detection and identification for control systems in floating offshore wind farms: A supervised Deep Learning methodology

Published:2024-10 Issue: Volume:310 Page:118678
ISSN:0029-8018
Container-title:Ocean Engineering
language:en
Short-container-title:Ocean Engineering

Author:

Fernandez-Navamuel Ana^ORCID,Peña-Sanchez Yerai,Nava Vincenzo^ORCID

Publisher

Elsevier BV

Reference91 articles.

1. Parameter Estimation and Inverse Problems;Aster,2005

2. A Multi-Turbine Approach for Improving Performance of Wind Turbine Power-Based Fault Detection Methods;Aziz;Energies,2022

3. Deep learning for automated drivetrain fault detection;Bach-andersen;Wind Energy,2017

4. A Comprehensive Review on Signal-Based and Model-Based Condition Monitoring of Wind Turbines: Fault Diagnosis and Lifetime Prognosis;Badihi;Proc. IEEE,2022

5. Gradient-based optimization of hyperparameters;Bengio;Neural Comput.,2000

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