Wind Turbine Condition Monitoring Using the SSA-Optimized Self-Attention BiLSTM Network and Changepoint Detection Algorithm

Condition-monitoring and anomaly-detection methods used for the assessment of wind turbines are key to reducing operation and maintenance (O&M) cost and improving their reliability. In this study, based on the sparrow search algorithm (SSA), bidirectional long short-term memory networks with a s...

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Detalles Bibliográficos
Autores principales: Yan, Junshuai, Liu, Yongqian, Li, Li, Ren, Xiaoying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10346352/
https://www.ncbi.nlm.nih.gov/pubmed/37447722
http://dx.doi.org/10.3390/s23135873

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10346352/
https://www.ncbi.nlm.nih.gov/pubmed/37447722
http://dx.doi.org/10.3390/s23135873

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