Attention-Guided Residual Spatiotemporal Network with Label Regularization for Fault Diagnosis with Small Samples

Attention-Guided Residual Spatiotemporal Network with Label Regularization for Fault Diagnosis with Small Samples

Fault diagnosis is of great significance for the maintenance of rotating machinery. Deep learning is an intelligent diagnostic technique that is receiving increasing attention. To address the issues of industrial data with small samples and varying working conditions, a residual convolutional neural...

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Bibliographic Details
Main Authors: Yanlong Xu, Liming Zhang, Ling Chen, Tian Tan, Xiaolong Wang, Hongguang Xiao
Format: Article
Language:English
Published: MDPI AG 2025-08-01
Series:Sensors
Subjects:
fault diagnosis
attention mechanism
residual module
label smoothing regularization
convolutional neural network
small samples
Online Access:https://www.mdpi.com/1424-8220/25/15/4772
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