A Semi-Supervised Fault Diagnosis Method Based on Improved Bidirectional Generative Adversarial Network

A Semi-Supervised Fault Diagnosis Method Based on Improved Bidirectional Generative Adversarial Network

With the assumption of sufficient labeled data, deep learning based machinery fault diagnosis methods show effectiveness. However, in real-industrial scenarios, it is costly to label the data, and unlabeled data is underutilized. Therefore, this paper proposes a semi-supervised fault diagnosis metho...

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Bibliographic Details
Main Authors: Long Cui, Xincheng Tian, Xiaorui Shi, Xiujing Wang, Yigang Cui
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Applied Sciences
Subjects:
generative adversarial networks
semi-supervised learning
fault diagnosis
wasserstein distance
Online Access:https://www.mdpi.com/2076-3417/11/20/9401

Internet

https://www.mdpi.com/2076-3417/11/20/9401

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