A Deep Learning-Based Method for Bearing Fault Diagnosis with Few-Shot Learning

A Deep Learning-Based Method for Bearing Fault Diagnosis with Few-Shot Learning

To tackle the issue of limited sample data in small sample fault diagnosis for rolling bearings using deep learning, we propose a fault diagnosis method that integrates a KANs-CNN network. Initially, the raw vibration signals are converted into two-dimensional time-frequency images via a continuous...

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Bibliographic Details
Main Authors:	Yang Li, Xiaojiao Gu, Yonghe Wei
Format:	Article
Language:	English
Published:	MDPI AG 2024-11-01
Series:	Sensors
Subjects:	KANs CNN small sample fault diagnosis diffusion network bearing
Online Access:	https://www.mdpi.com/1424-8220/24/23/7516
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