A Federated Adversarial Fault Diagnosis Method Driven by Fault Information Discrepancy

A Federated Adversarial Fault Diagnosis Method Driven by Fault Information Discrepancy

Federated learning (FL) facilitates the collaborative optimization of fault diagnosis models across multiple clients. However, the performance of the global model in the federated center is contingent upon the effectiveness of the local models. Low-quality local models participating in the federatio...

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Bibliographic Details
Main Authors: Jiechen Sun, Funa Zhou, Jie Chen, Chaoge Wang, Xiong Hu, Tianzhen Wang
Format: Article
Language:English
Published: MDPI AG 2024-08-01
Series:Entropy
Subjects:
fault diagnosis
federated learning
information discrepancy
federated adversarial
Online Access:https://www.mdpi.com/1099-4300/26/9/718
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