Advancing Fault Diagnosis for Parallel Misalignment Detection in Induction Motors Based on Convolutional Neural Networks

Advancing Fault Diagnosis for Parallel Misalignment Detection in Induction Motors Based on Convolutional Neural Networks

Maintenance of machines is highly necessary to prolong the operational lifespan of induction motors. Prioritizing preventive measures is crucial in order to prevent more significant damage to the machinery. One of these measures includes detecting abnormalities, such as misalignment, in the motor sh...

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Bibliographic Details
Main Authors: Hanif Adi Rahmawan, Bambang Lelono Widjianto, Katherine Indrawati, Rizki Mendung Ariefianto
Format: Article
Language:English
Published: Departement of Electrical Engineering, Faculty of Engineering, Universitas Brawijaya 2023-09-01
Series:Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems)
Subjects:
induction motor
misalignment
fft
cnn
Online Access:https://jurnaleeccis.ub.ac.id/index.php/eeccis/article/view/1655

Internet

https://jurnaleeccis.ub.ac.id/index.php/eeccis/article/view/1655

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