Multilocation and Multiscale Learning Framework with Skip Connection for Fault Diagnosis of Bearing under Complex Working Conditions

Multilocation and Multiscale Learning Framework with Skip Connection for Fault Diagnosis of Bearing under Complex Working Conditions

Considering various fault states under severe working conditions, the comprehensive feature extraction from the raw vibration signal is still a challenge for the diagnosis task of rolling bearing. To deal with strong coupling and high nonlinearity of the vibration signal, this article proposes a nov...

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Bibliographic Details
Main Authors: Hongwei Ban, Dazhi Wang, Sihan Wang, Ziming Liu
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Sensors
Subjects:
deep learning
multilocation learning
multikernel learning
multifeature protection
deep convolution encoder (DCE)
bidirectional long short-term memory (BiLSTM)
Online Access:https://www.mdpi.com/1424-8220/21/9/3226

Internet

https://www.mdpi.com/1424-8220/21/9/3226

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