Advanced Dual RNN Architecture for Electrical Motor Fault Classification

Advanced Dual RNN Architecture for Electrical Motor Fault Classification

In recent years, there has been a remarkable increase in the usage of Deep Neural Networks (DNNs) for addressing and solving electrical field problems. This research primarily aims to present an advanced approach to classify different motor faults based on their time-series data by implementing a ne...

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Bibliographic Details
Main Authors: Yousef Alkhanafseh, Tahir Cetin Akinci, Emine Ayaz, Alfredo A. Martinez-Morales
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Condition monitoring
GRU
LSTM
motor faults classification
recurrent neural networks
Online Access:https://ieeexplore.ieee.org/document/10365171/

Internet

https://ieeexplore.ieee.org/document/10365171/

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