Few-Shot Learning-Based Light-Weight WDCNN Model for Bearing Fault Diagnosis in Siamese Network

Few-Shot Learning-Based Light-Weight WDCNN Model for Bearing Fault Diagnosis in Siamese Network

In this study, bearing fault diagnosis is performed with a small amount of data through few-shot learning. Recently, a fault diagnosis method based on deep learning has achieved promising results. Most studies required numerous training samples for fault diagnosis. However, at manufacturing sites, i...

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Bibliographic Details
Main Authors: Daehwan Lee, Jongpil Jeong
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Sensors
Subjects:
few-shot learning
Siamese Network
WDCNN (Deep Convolutional Neural Networks with Wide First-layer Kernels)
Depthwise Separable Convolution layer
bearing fault diagnosis
Online Access:https://www.mdpi.com/1424-8220/23/14/6587

Internet

https://www.mdpi.com/1424-8220/23/14/6587

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