Please use this identifier to cite or link to this item: https://dspace.univ-ouargla.dz/jspui/handle/123456789/41986
Title: Methodology forEvaluation and Intelligent Prediction of Fire and Safety Systems in an Electrical Power Plant Using Artificial Intelligence
Authors: SETTOU, Belkhir
Bennadji, Mohammed Fadhl Allah
Salhi, Mohammed Nacer
Ramdani, Sid Ahmed
Keywords: Artificial Intelligence
Fire Safety
Power Plant
Predictive Maintenance
Risk Assessment
HMN3
HSE
Intelligence Artificielle
Sécurité Incendie
Centrale Électrique
Maintenance Prédictive
Évaluation des Risques
HMN3
HSE
Issue Date: 2026
Publisher: Institute of Technology
Abstract: This study explores the enhancement of fire safety in gas-fired power plants through the integration of Artificial Intelligence (AI). The research analyzes major fire hazards, including electrical faults, gas leaks, transformer failures, and arc flash incidents. It highlights the role of AI in predictive maintenance, intelligent fire detection, risk assessment, and emergency response optimization. A case study of the HMN3 power plant demonstrates how intelligent technologies can improve reliability, reduce accidents, and strengthen industrial safety. The findings confirm that AI-based safety systems offer a proactive approach to risk prevention while supporting sustainable and efficient power generation.
Description: Health, Safety and Environment (HSE)
URI: https://dspace.univ-ouargla.dz/jspui/handle/123456789/41986
Appears in Collections:Département de Génie Appliqué Licence

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