A Novel Intelligent Fault Diagnosis Method for Rolling Bearings Based on Wasserstein Generative Adversarial Network and Convolutional Neural Network under Unbalanced Dataset

A Novel Intelligent Fault Diagnosis Method for Rolling Bearings Based on Wasserstein Generative Adversarial Network and Convolutional Neural Network under Unbalanced Dataset

Rolling bearings are widely used in industrial manufacturing, and ensuring their stable and effective fault detection is a core requirement in the manufacturing process. However, it is a great challenge to achieve a highly accurate rolling bearing fault diagnosis because of the severe imbalance and...

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Bibliographic Details
Main Authors: Hongtao Tang, Shengbo Gao, Lei Wang, Xixing Li, Bing Li, Shibao Pang
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Sensors
Subjects:
rolling bearings
intelligent fault diagnosis
data imbalance
generative adversarial networks (GAN)
convolutional neural networks (CNN)
Online Access:https://www.mdpi.com/1424-8220/21/20/6754

Internet

https://www.mdpi.com/1424-8220/21/20/6754

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