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Dual-Channel Rolling Bearing Fault Diagnosis Method Based on ACNN-LFSwin Transformer

Rolling bearings are components commonly used in mechanical equipment. Traditional methods struggle to classify signals with numerous complex features in a multi-noise environment. They often rely on classical deep learning models for performing fault diagnosis using one-dimensional data, failing to...

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Autor principal: HUO Jiuyuan, LI Xin, CHANG Chen, ZHANG Yaonan
Formato: Artigo
Lenguaje:Inglês
Publicado: Editorial Office of Computer Engineering 2026-05-01
Colección:Jisuanji gongcheng
Materias:
rolling bearing|fault diagnosis|convolutional neural network (cnn)|short-time fourier transform (stft)|swin transformer
Acceso en línea:https://www.ecice06.com/fileup/1000-3428/PDF/20260535.pdf
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