Ensemble Capsule Network with an Attention Mechanism for the Fault Diagnosis of Bearings from Imbalanced Data Samples

In order to solve the problem of imbalanced and noisy data samples for the fault diagnosis of rolling bearings, a novel ensemble capsule network (Capsnet) with a convolutional block attention module (CBAM) that is based on a weighted majority voting method is proposed in this study. Firstly, the com...

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Detalles Bibliográficos
Autores principales: Xu, Zengbing, Lee, Carman Ka Man, Lv, Yaqiong, Chan, Jeffery
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9332463/
https://www.ncbi.nlm.nih.gov/pubmed/35898042
http://dx.doi.org/10.3390/s22155543

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9332463/
https://www.ncbi.nlm.nih.gov/pubmed/35898042
http://dx.doi.org/10.3390/s22155543

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