Bearing Fault Diagnosis under Variable Speed Using Convolutional Neural Networks and the Stochastic Diagonal Levenberg-Marquardt Algorithm

This paper presents a novel method for diagnosing incipient bearing defects under variable operating speeds using convolutional neural networks (CNNs) trained via the stochastic diagonal Levenberg-Marquardt (S-DLM) algorithm. The CNNs utilize the spectral energy maps (SEMs) of the acoustic emission...

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Detalles Bibliográficos
Autores principales: Tra, Viet, Kim, Jaeyoung, Khan, Sheraz Ali, Kim, Jong-Myon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751511/
https://www.ncbi.nlm.nih.gov/pubmed/29211025
http://dx.doi.org/10.3390/s17122834

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751511/
https://www.ncbi.nlm.nih.gov/pubmed/29211025
http://dx.doi.org/10.3390/s17122834

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