A novel diagnosis methodology of gear oil for wind turbine combining Stepwise multivariate regression and clustered federated learning framework

A novel diagnosis methodology of gear oil for wind turbine combining Stepwise multivariate regression and clustered federated learning framework

Abstract Data-driven approaches demonstrate significant potential in accurately diagnosing faults in wind turbines. To enhance diagnostic performance, we introduce a clustered federated learning framework (CFLF) for wind gear oil diagnosis. Initially, a stepwise multivariate regression (SMR) model i...

Full description

Saved in:
Bibliographic Details
Main Authors: Huihui Han, Ye Zhao, Hao Jiang, Muxin Chen, Song Zhou, Zihan Lin, Xin Wang, Boman Mao, Xinyue Yang, Yuchun Li
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Stepwise multivariate regression
Gear oil evaluation
Clustered federated learning framework
Wind turbines
Online Access:https://doi.org/10.1038/s41598-025-06826-9
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items