Improved Conditional Domain Adversarial Networks for Intelligent Transfer Fault Diagnosis

Improved Conditional Domain Adversarial Networks for Intelligent Transfer Fault Diagnosis

Intelligent fault diagnosis encounters the challenges of varying working conditions and sample class imbalance individually, but very few approaches address both challenges simultaneously. This article proposes an improvement network model named ICDAN-F, which can deal with fault diagnosis scenarios...

Full description

Bibliographic Details
Main Authors: Haihua Qin, Jiafang Pan, Jian Li, Faguo Huang
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Mathematics
Subjects:
fault diagnosis
transfer learning
domain adaptation
conditional domain adversarial network
class imbalance
Online Access:https://www.mdpi.com/2227-7390/12/3/481

Internet

https://www.mdpi.com/2227-7390/12/3/481

Similar Items