Fault detection in wind turbine generators using a meta-learning-based convolutional neural network-Reference-Cited by-同舟云学术

Fault detection in wind turbine generators using a meta-learning-based convolutional neural network

Published:2023-10 Issue: Volume:200 Page:110528
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Qiao Likui,Zhang Yuxian,Wang Qisen

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference46 articles.

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3. Monitoring and identifying wind turbine generator bearing faults using deep belief network and EWMA control charts;Li;Front. Energy Res.,2021

4. Getting more from the wind: Recent advancements and challenges in generators development for wind turbines;Chang;Sustain. Energy Technol. Assess.,2022

5. Fault-tolerant control of wind turbines: A benchmark model;Odgaard;IEEE Trans. Control Syst. Technol.,2013

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