A study on adaptation lightweight architecture based deep learning models for bearing fault diagnosis under varying working conditions
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Title
A study on adaptation lightweight architecture based deep learning models for bearing fault diagnosis under varying working conditions
Authors
Keywords
Diagnosis, CNN, Normalization, Lightweight, Transfer learning
Journal
EXPERT SYSTEMS WITH APPLICATIONS
Volume 160, Issue -, Pages 113710
Publisher
Elsevier BV
Online
2020-07-08
DOI
10.1016/j.eswa.2020.113710
References
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