Fault Diagnosis of Wind Turbine Generators Based on Stacking Integration Algorithm and Adaptive Threshold.

Tang, Zhanjun; Shi, Xiaobing; Zou, Huayu; Zhu, Yuting; Yang, Yushi; Zhang, Yajia; He, Jianfeng

Tang, Zhanjun; Shi, Xiaobing; Zou, Huayu; Zhu, Yuting; Yang, Yushi; Zhang, Yajia; He, Jianfeng.

Afiliação

Tang Z; Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China.
Shi X; Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China.
Zou H; Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China.
Zhu Y; Key Laboratory of Artificial Intelligence in Yunnan Province, Kunming 650500, China.
Yang Y; Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China.
Zhang Y; Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China.
He J; Yunnan Open University, Kunming 650500, China.

Sensors (Basel) ; 23(13)2023 Jul 06.

Article em En | MEDLINE | ID: mdl-37448048

Assuntos

Algoritmos; Fontes de Energia Elétrica; Teorema de Bayes; Aprendizado de Máquina; Portugal

Palavras-chave

EDP; WTG; adaptive threshold; fault diagnosis; machine learning; stacking integration algorithm

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fontes de Energia Elétrica / Algoritmos Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo

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XML

PubMed Links

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fontes de Energia Elétrica / Algoritmos Idioma: En Ano de publicação: 2023 Tipo de documento: Article