Dr. Boualem MERAINANI

Research: Condition-Based Maintenance, Prognostics and Health Management. Teaching: -- Modeling and simulation of electromechanical systems (Models for the control of electric actuators). -- Electrotechnic. -- Control of electromechanical actuators. -- Measurement chain. -- Monitoring and diagnosis.

My thesis involved: • Development of: -Electromechanical model. -Intelligent fault diagnostic algorithm capable to achieve an optimal exploitation of the vibration signals by using an advanced signal processing techniques. • Experimental validation using real world data: Induction motor driven mechanical system with bearing faults. Spur gearbox in which the pinion have a variety of faults.

PROFAS B+ fellowship holder: - Worked as scientist researcher within MOCIS team (Méthodes et Outils pour la Conception Intégrée de Systèmes at CRISTAL laboratory (Centre de Recherche en Informatique, Signal et Automatique de Lille). The objective of the training is to validate the developed fault detection and diagnostic method for Electro-Mechanical systems. Expertise exploited: Knowledge of dynamical system modelling, Fault feature extraction, Dimension reduction and State classification methods.

Expertise in : 1. Modelling of electromechanical systemes with effect of faults. 2. Fault diagnosis of rotating machinery, (fault feature extraction, dimension reduction and classification techniques) 3. Prediction of faults and assessment of remaining useful life.

Masters in mechanical engineering, option : Mechatronics. Subject: New method for fault detection in induction machines : square current signature analysis Modeling, Fault detection based Motor current signature analysis.

Mechanical engineering, option : Mechatronics.