Collaborative Optimization of CNN and GAN for Bearing Fault Diagnosis under Unbalanced Datasets

Collaborative Optimization of CNN and GAN for Bearing Fault Diagnosis under Unbalanced Datasets

Convolutional Neural Network (CNN) has been widely used in bearing fault diagnosis in recent years, and many satisfying results have been reported. However, when the training dataset provided is unbalanced, such as the samples in some fault labels are very limited, the CNN’s performance reduces inev...

Full description

Bibliographic Details
Main Authors: Diwang Ruan, Xinzhou Song, Clemens Gühmann, Jianping Yan
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Lubricants
Subjects:
fault data generation
Convolutional Neural Network (CNN)
Generative Adversarial Network (GAN)
bearing fault diagnosis
unbalanced datasets
Online Access:https://www.mdpi.com/2075-4442/9/10/105

Internet

https://www.mdpi.com/2075-4442/9/10/105

Similar Items