A Data-Driven Framework for Small Hydroelectric Plant Prognosis Using Tsfresh and Machine Learning Survival Models

Maintenance in small hydroelectric plants (SHPs) is essential for securing the expansion of clean energy sources and supplying the energy estimated to be required for the coming years. Identifying failures in SHPs before they happen is crucial for allowing better management of asset maintenance, low...

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Detalles Bibliográficos
Autores principales: de Santis, Rodrigo Barbosa, Gontijo, Tiago Silveira, Costa, Marcelo Azevedo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824278/
https://www.ncbi.nlm.nih.gov/pubmed/36616612
http://dx.doi.org/10.3390/s23010012

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824278/
https://www.ncbi.nlm.nih.gov/pubmed/36616612
http://dx.doi.org/10.3390/s23010012

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