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

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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Bibliographic Details
Main Authors: Yong Yao, Sen Zhang, Suixian Yang, Gui Gui
Format: Article
Language:English
Published: MDPI AG 2020-02-01
Series:Sensors
Subjects:
acoustic-based diagnosis
gear fault diagnosis
attention mechanism
convolutional neural network
Online Access:https://www.mdpi.com/1424-8220/20/4/1233

Internet

https://www.mdpi.com/1424-8220/20/4/1233

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