PumpSpectra: An MCSA-Based Platform for Fault Detection in Centrifugal Pump Systems
Hamza Adaika, Zoheir Tir, Mohamed Sahraoui, Khaled Laadjal
Hamza Adaika
حمزة عدايكةResearcher
6
Research output
8
Citations
2
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View allWeighted concepts mined from titles, abstracts and topics of the research output, grouped by field.
- Machine Fault Diagnosis Techniques
- Power Quality and Harmonics
- Control and Systems Engineering
- fault detection
- Fault Detection and Control Systems
- condition monitoring
- Engineering
- motor current signature analysis
- predictive maintenance
- Power Systems Fault Detection
Featured Research Outputs
Research output(6)
View allDeep Learning-Enhanced Fault Detection and Localization in Induction Motor Drives: A ResMLP and TCN Framework
Hamza Adaika, Khaled Laadjal, Zoheir Tir, Mohamed Sahraoui
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 Open access 2
PumpSpectra: An MCSA-Based Platform for Fault Detection in Centrifugal Pump Systems
Hamza Adaika, Zoheir Tir, Mohamed Sahraoui, Khaled Laadjal
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 1-42025Other Closed accessSeveral sources
Diagnosis of Rotor Broken Bar Faults in Induction Motors Using the CNN-Based Current Signal
Hamza Adaika, Zoheir Tir, Mohamed Sahraoui
Pages 764-7682023Other Open access 2