Fault Diagnosis of Semi-Supervised Electromechanical Transmission Systems Under Imbalanced Unlabeled Sample Class Information Screening

Fault Diagnosis of Semi-Supervised Electromechanical Transmission Systems Under Imbalanced Unlabeled Sample Class Information Screening

In the health monitoring of electromechanical transmission systems, the collected state data typically consist of only a minimal amount of labeled data, with a vast majority remaining unlabeled. Consequently, deep learning-based diagnostic models encounter the challenge of scarcity in labeled data a...

Full description

Saved in:
Bibliographic Details
Main Authors: Chaoge Wang, Pengpeng Jia, Xinyu Tian, Xiaojing Tang, Xiong Hu, Hongkun Li
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Entropy
Subjects:
semi-supervised learning
fault identification
information quantity screening mechanism
data imbalance
cost-sensitive strategy
Online Access:https://www.mdpi.com/1099-4300/27/2/175
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/1099-4300/27/2/175

Similar Items