Early Detection of Inter-Turn Short Circuits in Induction Motors Using the Derivative of Stator Current and a Lightweight 1D-ResNet

Early Detection of Inter-Turn Short Circuits in Induction Motors Using the Derivative of Stator Current and a Lightweight 1D-ResNet

This work presents a lightweight and practical methodology for detecting inter-turn short-circuit faults in squirrel-cage induction motors under different mechanical load conditions. The proposed approach utilizes a one-dimensional convolutional neural network (1D-CNN) enhanced with residual blocks...

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Bibliographic Details
Main Authors: Carlos Javier Morales-Perez, David Camarena-Martinez, Juan Pablo Amezquita-Sanchez, Jose de Jesus Rangel-Magdaleno, Edwards Ernesto Sánchez Ramírez, Martin Valtierra-Rodriguez
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Computation
Subjects:
current stator signal
incipient fault
induction motor
inter-turn short circuit
residual neural networks
signal derivative
Online Access:https://www.mdpi.com/2079-3197/13/6/140
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