Improvement of Generative Adversarial Network and Its Application in Bearing Fault Diagnosis: A Review

Improvement of Generative Adversarial Network and Its Application in Bearing Fault Diagnosis: A Review

A small sample size and unbalanced sample distribution are two main problems when data-driven methods are applied for fault diagnosis in practical engineering. Technically, sample generation and data augmentation have proven to be effective methods to solve this problem. The generative adversarial n...

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Bibliographic Details
Main Authors:	Diwang Ruan, Xuran Chen, Clemens Gühmann, Jianping Yan
Format:	Article
Language:	English
Published:	MDPI AG 2023-02-01
Series:	Lubricants
Subjects:	generative adversarial network (GAN) bearing fault diagnosis data augmentation loss function modification GAN structure improvement GAN review
Online Access:	https://www.mdpi.com/2075-4442/11/2/74

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