Clustering Federated Learning for Bearing Fault Diagnosis in Aerospace Applications with a Self-Attention Mechanism

Clustering Federated Learning for Bearing Fault Diagnosis in Aerospace Applications with a Self-Attention Mechanism

Bearings, as the key mechanical components of rotary machinery, are widely used in modern aerospace equipment, such as helicopters and aero-engines. Intelligent fault diagnosis, as the main function of prognostic health management systems, plays a critical role in maintaining equipment safety in aer...

Full description

Bibliographic Details
Main Authors: Weihua Li, Wansheng Yang, Gang Jin, Junbin Chen, Jipu Li, Ruyi Huang, Zhuyun Chen
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Aerospace
Subjects:
fault diagnosis
clustered federated learning
self-attention mechanism
data privacy
Online Access:https://www.mdpi.com/2226-4310/9/9/516

Internet

https://www.mdpi.com/2226-4310/9/9/516

Similar Items