Deep Transfer Learning Approach Using Filtered Time‐Frequency Representations of Current Signals for Bearing Fault Detection in Induction Machines

ABSTRACT This paper addresses the challenge of limited labelled data in induction machine fault diagnosis by applying deep transfer learning with convolutional neural networks to classify ball bearing health conditions. Specifically, the objective is to classify ring and cage failures in ball bearin...

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Egile Nagusiak:	Nada El Bouharrouti, Alireza Nemat Saberi, Muhammad Dayyan Hussain Khan, Karolina Kudelina, Muhammad U. Naseer, Anouar Belahcen
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	Wiley 2025-01-01
Saila:	IET Electric Power Applications
Gaiak:	band‐stop filters fault diagnosis rolling bearings time‐frequency analysis
Sarrera elektronikoa:	https://doi.org/10.1049/elp2.70074
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