A Novel Framework for Early Pitting Fault Diagnosis of Rotating Machinery Based on Dilated CNN Combined With Spatial Dropout

A Novel Framework for Early Pitting Fault Diagnosis of Rotating Machinery Based on Dilated CNN Combined With Spatial Dropout

Pitting corrosion of rotating machinery is one of the most common faults in industrial engineering. The convolutional neural network (CNN) is increasingly applied to the fault diagnosis. However, the conventional CNN method will reduce the feature dimension of the collected signal and cause the loss...

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Bibliographic Details
Main Authors: Xueyi Li, Xiangwei Kong, Zhendong Liu, Zhiyong Hu, Cheng Shi
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Deep learning
dilated convolutional neural network
fault diagnosis
rotating machinery
spatial dropout
Online Access:https://ieeexplore.ieee.org/document/9353535/

Internet

https://ieeexplore.ieee.org/document/9353535/

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