Enhanced Lightweight Multiscale Convolutional Neural Network for Rolling Bearing Fault Diagnosis

Enhanced Lightweight Multiscale Convolutional Neural Network for Rolling Bearing Fault Diagnosis

The vibration signals collected from rolling bearings in industrial systems are highly complex and contain intense environmental noise, which challenges the performance of traditional fault diagnosis methods. Moreover, the applicability of the model in engineering practice, especially in the Industr...

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Bibliographic Details
Main Authors: Yaowei Shi, Aidong Deng, Minqiang Deng, Jing Zhu, Yang Liu, Qiang Cheng
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Rolling bearing fault diagnosis
multiscale convolutional neural network
attention mechanism
residual learning
lightweight
Online Access:https://ieeexplore.ieee.org/document/9274434/

Internet

https://ieeexplore.ieee.org/document/9274434/

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