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Model-Agnostic Meta-Learning for Fault Diagnosis of Induction Motors in Data-Scarce Environments with Varying Operating Conditions and Electric Drive Noise

Fuente: arXiv

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Dettagli Bibliografici
Autori principali:	Pourghoraba, Ali, KhajueeZadeh, MohammadSadegh, Amini, Ali, Vahedi, Abolfazl, Agah, Gholam Reza, Rahideh, Akbar
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Systems and Control
Accesso online:	Acceder al recurso
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