Multi-sensor edge computing architecture for identification of failures short-circuits in wind turbine generators-Reference-Cited by-同舟云学术

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Multi-sensor edge computing architecture for identification of failures short-circuits in wind turbine generators

Published:2021-03 Issue: Volume:101 Page:107053
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Xu Yongzhao,Nascimento Navar Medeiros M.,de Sousa Pedro H. Feijó,Nogueira Fabrício G.,Torrico Bismark C.,Han Tao,Jia Chuanyu,Rebouças Filho Pedro P.

Funder

Dongguan Science and Technology Bureau

National Natural Science Foundation of China

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

Elsevier BV

Subject

Software

Reference49 articles.

1. Key World Energy Statistics,2017

2. Renew. Energy and jobs. Annual review 2019, Irena, URL https://irena.org/publications/2019/Jun/Renewable-Energy-and-Jobs-Annual-Review-2019.

3. Gwec.global Wind report 2018, Gwec, URL https://gwec.net/global-wind-report-2018/.

4. A review of recent advances in wind turbine condition monitoring and fault diagnosis;Lu,2009

5. A survey of health monitoring systems for wind turbines;Wymore;Renew. Sustain. Energy Rev.,2015

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