Rolling bearing fault diagnosis under small sample conditions based on WDCNN-BiLSTM Siamese network

Rolling bearing fault diagnosis under small sample conditions based on WDCNN-BiLSTM Siamese network

Abstract Rolling bearings are a crucial component in rotating machinery, essential for ensuring the smooth functioning of the entire system. However, their vulnerability to damage necessitates the implementation of effective fault diagnosis. Traditional deep learning methods often struggle due to th...

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Bibliographic Details
Main Authors: Chenxu Bian, Chunni Jia, Jibo Li, Xiangjun Chen, Pei Wang
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:Scientific Reports
Subjects:
Rolling bearing
Small sample
Fault diagnosis
Siamese neural network
Deep learning
Online Access:https://doi.org/10.1038/s41598-025-12370-3
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