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...

Full description

Saved in:
Bibliographic Details
Main Authors: Hanif Adi Rahmawan, Bambang Lelono Widjianto, Katherin Indriawati, 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
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items