Condition monitoring and anomaly detection of wind turbine based on cascaded and bidirectional deep learning networks-Reference-Cited by-同舟云学术

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Condition monitoring and anomaly detection of wind turbine based on cascaded and bidirectional deep learning networks

Published:2022-01 Issue: Volume:305 Page:117925
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Xiang Ling,Yang Xin,Hu Aijun,Su Hao,Wang Penghe

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference33 articles.

1. Review of performance optimization techniques applied to wind turbines;Chehouri;Applied Energy,2015

2. Deterministic and probabilistic multi-step forecasting for short-term wind speed based on secondary decomposition and a deep learning method;Xiang;Energy Conversion and Management,2020

3. Wind turbine condition monitoring: Technical and commercial challenges;Yang;Wind Energy,2014

4. Wind turbine reliability: A comprehensive review towards effective condition monitoring development;Artigao;Applied Energy,2018

5. A Survey on Wind Turbine Condition Monitoring and Fault Diagnosis-Part II: Signals and Signal Processing Methods;Qiao;IEEE Trans Industrial Electronics,2015

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