Intelligent fault diagnosis of rolling bearing based on novel CNN model considering data imbalance
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-022-03196-x.pdf
Reference34 articles.
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4. Jia F, Lei Y, Lin J, Zhou X, Lu N (2016) Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data. Mech Syst Signal Process 72–73:303–315
5. Zhao M, Zhong S, Fu X, Tang B, Pecht M (2020) Deep Residual Shrinkage Networks for Fault Diagnosis. IEEE Trans Ind Inf 16(7):4681–4690
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