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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 |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Methodology forEvaluation and Intelligent Prediction of Fire and Safety Systems in an Electrical Power Plant Using Artificial Intelligence.pdf | Health, Safety and Environment (HSE) | 1,09 MB | Adobe PDF | View/Open |
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