Optimizing Bearing Fault Diagnosis in Rotating Electrical Machines Using Deep Learning and Frequency Domain Features

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Title:	Optimizing Bearing Fault Diagnosis in Rotating Electrical Machines Using Deep Learning and Frequency Domain Features
Authors:	Eduardo Quiles-Cucarella; Alejandro García-Bádenas; Ignacio Agustí-Mercader; Guillermo Escrivá-Escrivá
Other contributors:	Recezent Slavica Prvulović
Issue Date:	2025
Publication:	Applied Sciences
ISSN:	2076-3417 Applied Sciences-Basel Search Idenfier
Publisher:	Switzerland, Basel: Multidisciplinary Digital Publishing Institute - MDPI
Type:	Editorial works
Collation:	vol. 15 br. 6 str. 3132-3132
DOI:	10.3390/app15063132
WoS-ID:	001453569300001
Scopus-ID:	2-s2.0-105000992287
URI:	https://enauka.gov.rs/handle/123456789/988286
URL:	https://www.mdpi.com/2076-3417/15/6/3132
Metadata source:	(Preuzeto iz KNR-a) Prvulović, Slavica
Note:	Recezent Slavica Prvulović
M-category:	Mp. category will be shown later

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