Fault diagnosis of rotating parts integrating transfer learning and ConvNeXt model

Fault diagnosis of rotating parts integrating transfer learning and ConvNeXt model

Abstract This paper proposes a fault diagnosis method for rotating machinery that integrates transfer learning with the ConvNeXt model (TL-CoCNN), addressing challenges such as small sample sizes and varying operating conditions. To meet the input requirements of the model while minimizing feature l...

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Bibliographic Details
Main Authors: Zhikai Xing, Yongbao Liu, Qiang Wang, Junqiang Fu
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Fault diagnosis
Transfer learning
Varying operating conditions
Pre-trained ConvNeXt model
Online Access:https://doi.org/10.1038/s41598-024-84783-5
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