Learning Attention Representation with a Multi-Scale CNN for Gear Fault Diagnosis under Different Working Conditions

The gear fault signal under different working conditions is non-linear and non-stationary, which makes it difficult to distinguish faulty signals from normal signals. Currently, gear fault diagnosis under different working conditions is mainly based on vibration signals. However, vibration signal ac...

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Detalles Bibliográficos
Autores principales: Yao, Yong, Zhang, Sen, Yang, Suixian, Gui, Gui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070631/
https://www.ncbi.nlm.nih.gov/pubmed/32102405
http://dx.doi.org/10.3390/s20041233

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070631/
https://www.ncbi.nlm.nih.gov/pubmed/32102405
http://dx.doi.org/10.3390/s20041233

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