Instrumentation dans l'industrie pétrochimique
Permanent URI for this collectionhttps://dspace.univ-boumerdes.dz/handle/123456789/10962
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Item Contrôle et supervision d’un générateur d'Azote par un «API S-7 1500»(Université M’Hamed Bougara Boumerdès : Faculté des Hydrocarbures et de la Chimie, 2024) Zidhane, Ahmed Ridha; Sadi, Seifeddine; Beddek, Karim (Promoteur)Notre Projet de fin d'études vise à concevoir et automatiser un générateur d'azote en utilisant le logiciel TIA Portal de Siemens, combinant ainsi programmation, automatisation industrielle et conception d'interfaces homme-machine (HMI) pour optimiser le processus de génération d'azote.Item Automatisation et supervision de l’unité de déshydratation par adsorption (UDA) via un automate programmable industriel «S7-300 »(Université M’Hamed Bougara Boumerdès : Faculté des Hydrocarbures et de la Chimie, 2024) Yaalaoui, Tej Eddine; Chaouch, Fouad; Khebli, Abdelmalek (Promoteur)Le Travail développé dans ce mémoire a porté sur « Automatisation et supervision de l’unité de déshydratation par adsorption (UDA) via un automate programmable industriel S7-300 ». Ce travail a été mené au sein d’une unité opérationnelle de traitement de gaz de SONATRACH (Tin Fouyé Tabankort). Cette station étant prévue d’être rénovée, le présent travail s’est focalisé sur la modernisation du système de pilotage et de supervision de l’Unité de déshydratation par adsorption (UDA) de la section fermeture gaz lift, à l’aide de l’automate S7-300 de SIEMENS. Cette action a notamment porté sur l’insertion d’un réseau de capteurs et transmetteurs intelligents. Les résultats enregistrés se sont traduits par l’amélioration de la sécurité des installations, l’accroissement du taux de disponibilité de l’outil industriel, ainsi que le confort de l’opérateur.Item Detection and localization of brain tumor by Deep Learning models(Université M’Hamed Bougara Boumerdès : Faculté des Hydrocarbures et de la Chimie, 2024) Salhi, Mohammed Nadjib Allah; Lachekhab (Kahoul), Fadhila (Promoteur)Healthcare MRI for brain tumor is a critical aspect of modern medicine, particularly in diagnosing and treating neurological disorders. Brain tumors pose significant health risks, and early detection is key to successful treatment outcomes. Traditional diagnostic methods often involve manual interpretation of MRI images by skilled radiologists, which can be time-consuming and subject to human error. Recent advancements in medical imaging and AI have paved the way for more efficient and accurate diagnosis of brain tumors using Deep Learning algorithms. This study proposes a Deep Learning-powered MRI-based system for automated detection and localization of brain tumors. Utilize Convolutional Neural Networks (CNNs) to analyze MRI scans and classify them into two classes: "Tumor" and "No tumor." To train and evaluate the four models, a dataset comprising of MRI images with corresponding labels indicating the presence or absence of tumors is utilized and then localization of a tumor if it exists. Evaluation metrics such as accuracy, F1-score, Precision and Confusion Matrix are employed to assess the performance of the models in distinguishing between tumor and non-tumor cases. The results demonstrate the efficacy of the proposed approach in accurately identifying brain tumors from MRI scans.Item Study of the «XGF868I» flare gas flow meter solution at the «HBNS Oil Field» with addressing its lack of data integration into the «ICSS» control system(Université M’Hamed Bougara Boumerdès : Faculté des Hydrocarbures et de la Chimie, 2024) Radjouh, Abderraouf; Chaib, Ahmed (Promoteur)This Thesis addresses the lack of detailed flare gas data and diagnostic data from XGF868i flow meters in the ICSS control system at the Groupement Berkine HBNS site. The solution includes creating 17 analog points, each one representing specific data retrieved from the flow meters via Modbus communication. Advanced configurations, such as alarm and historical data settings, were established for analysis and troubleshooting. Additionally, HMIs were developed for six flares, providing easy access from the control room and also enabling remote access through the Honeywell E-server solution. These enhancements contribute to safer, more efficient, and environmentally responsible operations.Item Comparative interactions analysis of «APC» and «PID» controllers in Distillation column at Skikda «GL1K» complex(Université M’Hamed Bougara Boumerdès : Faculté des Hydrocarbures et de la Chimie, 2024) Marref, Akram Wanisse; Kremis, Khalid; Khebli, Abdelmalek (Promoteur)The Objective of this thesis is to evaluate the performance of Honeywell's Advanced Process Control (APC) system in multivariable processes and to compare it with traditional PID controllers. This study was conducted at the GL1K complex in Skikda, which specializes in the liquefaction of natural gas. We examined the effectiveness of APC in managing the complex interactions within the process, focusing on key performance indicators such as stability, efficiency, and product quality. The results demonstrated that APC significantly improves process performance and reduces variability compared to conventional PID controllers. This research highlights the advantages of advanced control strategies in optimizing industrial operations and ensuring superior control over multivariable systems.Item Evolving cloud-based fault monitoring system for an industrial gas turbine(Université M’Hamed Bougara Boumerdès : Faculté des Hydrocarbures et de la Chimie, 2024) Fadel, Mohamed Saout El Hak; Messaoudi, Mohammed Rida; Habbi, Hacene (Promoteur)The Thesis focuses on the development and implementation of an evolving fault monitoring system for an industrial gas turbine. Building on our study of turbine during our internship, this work is dedicated to creating an evolving cloud-based system of AnYa-type to detect and identify different fault scenarios in the industrial gas turbine. This model leverages real-time data and non-parametric methods to adapt to dynamic environments, enhancing efficiency and reliability in complex systems. Our efforts have been directed towards building this monitoring system to ensure continuous learning and adaptation, ultimately improving operational performance under normal and fault modes.Item Estimation of the level and temperature liquid of a two-tank coupled system subject to disturbances(Université M’Hamed Bougara Boumerdès : Faculté des Hydrocarbures et de la Chimie, 2024) Cheikh, Brahim Said; Youssef, Tewfik (Promoteur)This Thesis examines the application of estimation techniques to determine non-measurable state variables in a two-tank coupled system, a widely used dynamic model in industrial processes. It emphasizes the Luenberger observer algorithm as an effective estimation method. Given the inherent limitations in direct measurement, state estimation is vital for ensuring accurate process control and fault detection. The study encompasses control system theory, the modeling and linearization of the two-tank system, and the use of the Luenberger observer to estimate both measurable and non-measurable variables. Results indicate that while full-state observation delivers precise estimates, partial-state observation provides reliable approximations, highlighting the value of estimation in maintaining robust control under varying conditions and disturbances.Item Automatisation d’un système de ramonage de chaudière par automate programmable «Siemens S7-300»(Université M’Hamed Bougara Boumerdès : Faculté des Hydrocarbures et de la Chimie, 2024) Boukhelifi, Mohamed El Amine; Hammal, Yasser; Khelassi, Abdelmadjid (Promoteur)Nous Visons à créer un système de ramonage automatique d'une chaudière en utilisant un automate programmable Siemens S7-300 afin d'optimiser le fonctionnement et d'améliorer le rendement de celle-ci, dans le cadre de notre projet réalisé dans la raffinerie d'Alger. Ce système offre la possibilité de nettoyer les composants de la chaudière et de retirer automatiquement les dépôts de résidus et de cendres des gaz de combustion, ce qui permet d'obtenir une solution plus économe et plus performante.Item PLC control systems in natural gas processing : solutions for back pressure problems(Université M’Hamed Bougara Boumerdès : Faculté des Hydrocarbures et de la Chimie, 2024) Berkane, Aimen; Debbeche, Aimene Anis Taki Eddine; Beddek, Karim (Promoteur)This Dissertation addresses back pressure issues in industrial air dryer systems by replacing check valves with solenoid valves and a cam timer with a PLC. Conducted at Sonatrach GL1/K, the study achieve the reengineered setup using Triconex PLC and AVEVA InTouch HMI software, confirming improved functionality and reliability. This solution solves back pressure problem, enhances performance of the air dryer and reduces maintenance costs.Item Pressur control system for «Vessel D20» in the refinery of Algeirs «RA1G» using «S7-300»(Université M’Hamed Bougara Boumerdès : Faculté des Hydrocarbures et de la Chimie, 2024) Benkhedidja, Yamina; Kesraoui, Mohamed (Promoteur)Industrial installations in the oil and gas domain present risks to people, the environment, and equipment, hence the need to implement safety systems for these high-risk installations to comply with regulatory requirements. To ensure safer, more reliable, and uninterrupted operations and to reduce opera- tional risks to a maximum ownership value, we have opted to carry out this work to maintain pressure in the D20 vessel of unit 780 (utility 1), which serves as the instrument air supply for the ADU unit.