A Deep-Learning-Based Health Indicator Constructor Using Kullback–Leibler Divergence for Predicting the Remaining Useful Life of Concrete Structures

This paper proposes a new technique for the construction of a concrete-beam health indicator based on the Kullback–Leibler divergence (KLD) and deep learning. Health indicator (HI) construction is a vital part of remaining useful lifetime (RUL) approaches for monitoring the health of concrete struct...

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Detalles Bibliográficos
Autores principales: Nguyen, Tuan-Khai, Ahmad, Zahoor, Kim, Jong-Myon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9146863/
https://www.ncbi.nlm.nih.gov/pubmed/35632097
http://dx.doi.org/10.3390/s22103687

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9146863/
https://www.ncbi.nlm.nih.gov/pubmed/35632097
http://dx.doi.org/10.3390/s22103687

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