Efficient fault diagnosis in rolling bearings lightweight hybrid model

Efficient fault diagnosis in rolling bearings lightweight hybrid model

Abstract To address the issue of low efficiency in feature extraction and model training when traditional deep learning methods handle long time-series data, this paper proposes a Time-Series Lightweight Transformer (TSL-Transformer) model. According to the data characteristics of bearing fault diag...

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Bibliographic Details
Main Authors: Peng Yang, Bozheng Zhang, Jianda Zhao
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Bearing fault detection
LSTM
Transformer
Multi-head attention mechanism
Online Access:https://doi.org/10.1038/s41598-025-96285-z
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https://doi.org/10.1038/s41598-025-96285-z

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