Deep Learning-Enhanced Fault Detection and Localization in Induction Motor Drives: A ResMLP and TCN Framework
Hamza Adaika, Khaled Laadjal, Zoheir Tir, Mohamed Sahraoui
Hamza Adaika
حمزة عدايكةChercheur
6
Productions
9
Citations
2
Indice h
Noter ce chercheur1 avis
La moyenne apparaît à partir de 3 avis.
2026
2025
Comparative Deep Learning for RGB-Based PV Surface Fault Classification Using ResNet50 and EfficientNetB0 with Real-Time Deployment
Mosbah Laouamer, Mohammed Adaika, Souhaib Remha, Abdelkader Mahmoudi, Hamza Adaika
International Journal of Electrical and Electronics ResearchVolume 13، (4)، Pages 7122025Article Accès ouvert 2
Enhancing Maintenance Agility in Water Desalination Plants via Explainable MCSA: A Case Study on Workflow Integration and Diagnostic Efficiency
Hamza Adaika, Zoheir Tir, Mohamed Sahraoui, Mohammed Adaika, Khaled Laadjal
Pages 1-42025Communication Accès fermé✔ Validé par une unité
PumpSpectra: An MCSA-Based Platform for Fault Detection in Centrifugal Pump Systems
Hamza Adaika, Zoheir Tir, Mohamed Sahraoui, Khaled Laadjal
2023
Diagnosis of Rotor Broken Bar Faults in Induction Motors Using the CNN-Based Current Signal
Hamza Adaika, Zoheir Tir, Mohamed Sahraoui
Pages 764-7682023Communication Accès ouvert✔ Validé par une unité 2
A New Rotor Broken Bar Fault Diagnosis by Using CNN Based Current Signal of An Induction Motor
ADAIKA Hamza, TIR Zoheir, SAHRAOUI Mohamed
2023Communication Accès ouvert✔ Validé par une unité