Identifying Bearing Faults Using Multiscale Residual Attention and Multichannel Neural Network

Identifying Bearing Faults Using Multiscale Residual Attention and Multichannel Neural Network

To solve the problem of the low signal-to-noise ratio and fault features can only be extracted from a single scale of traditional convolutional neural network (CNN) in vibration-based bearing fault diagnosis, this paper proposes a new multi-scale residual attention and multi-channel network (MSCNet)...

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Bibliographic Details
Main Authors: Chun-Yao Lee, Guang-Lin Zhuo
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Convolutional neural network (CNN)
bearing fault diagnosis
multi-scale feature extraction
multi-channel network
Online Access:https://ieeexplore.ieee.org/document/10068499/

Internet

https://ieeexplore.ieee.org/document/10068499/

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