Analysis and Diagnostic Methods for Fault Detection in Industrial Three-Phase Asynchronous Machines

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dc.contributor.authorGUERMOUZ Mohamed Amine
dc.contributor.authorESSID Abderrahmane
dc.contributor.authorDEKHANE Azzeddine (Encadrant)
dc.date.accessioned2025-11-17T12:44:38Z
dc.date.available2025-11-17T12:44:38Z
dc.date.issued2025
dc.description.abstractThis project recognizes a promising alternative diagnostic approach to fault detection in industrial three-phase asynchronous motors. These motors are significant for industrial operations in power plants and manufacturing businesses. As part of the work undertaken with SKD Power Plant and SIDER El Hadjar, more reliability and predictive maintenance have been achieved through the application of vibration analysis and Motor Current Signature Analysis (MCSA). The limitations of physical, visual inspections and reactive maintenance are acknowledged within the project. More importantly, real industrial measurements were performed as well as a modeling/simulation effort using MATLAB/Simulink. The presence of mechanical (bearing faults) and electrical (voltage unbalance) anomalies were both diagnosed. The combination of time-domain and frequency-domain analysis has provided evidence for early and accurate fault detection. The project has highlighted the benefits of using new, non-invasive diagnostic techniques in the industrial landscape of Algeria to support improved operational efficiencies and reduce the risk of unplanned outages.
dc.identifier.urihttp://dspace.ensti-annaba.dz:4000/handle/123456789/909
dc.language.isoen
dc.publisherECOLE NATIONALE SUPERIEURE DE TECHNOLOGIE ET D’INGENIERIE - ANNABA
dc.titleAnalysis and Diagnostic Methods for Fault Detection in Industrial Three-Phase Asynchronous Machines
dc.typeThesis
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