Liste des publications
Precipitation kinetics and mechanical behavior in a solution treated and aged dual phase stainless steel
The precipitation kinetics and the mechanical behaviour in a solution treated and aged dual phase stainless steel (DSS) are investigated. X-Ray diffraction, transmission and scanning electron microscopy techniques are used to characterize the microstructure and to identify its constituents. The precipitation kinetics analysis shows that the ferrite to σ phase transformation follows the modified Johnson Mehl Avrami (JMA) model containing an impingement parameter c that is adjusted to 0.3. Activation energies calculation leads to conclude that interface reaction is the main mechanism that controls the σ phase formation. Detailed analysis of the extent of the different tensile deformation domains reveals the significant contribution of both σ phase particles and dislocation accumulation to the strain hardening of the material Voir les détails
Mots clés : alloys, aging, microstructure, mechanical properties
Spatial convolution of a stress field analyzed by X-ray diffraction
X-ray stress analysis suffers from homogeneity limitations of the stress field in the analyzed volume. When this homogeneity is not fulfilled, it is possible to reduce the irradiated volume down to stress homogeneity achievement. New limitation however occurs : the diffracting sites become too few for stress homogenization. We show that the diffractometry analysis corresponds to a spatially convoluted stress field. The inverse convolution problem is posed. An example of regularization method is given. Voir les détails
Mots clés : XRD stress measurement, spatial convolution, stress gradient, inverse problem
Characteristics of a high Tc superconducting rectangular microstrip patch on uniaxially anisotropic substrate
Resonant characteristics of a high Tc superconducting rectangular microstrip patch printed on uniaxially anisotropic substrate are investigated using a full-wave spectral analysis in conjunction with the complex resistive boundary condition. The uniaxial medium shows anisotropy of an electric type as well as anisotropy of a magnetic type. Both permittivity and permeability tensors of the substrate are included in the formulation of the dyadic Green’s function of the problem. The accuracy of the analysis is tested by comparing the computed results with previously published data for several anisotropic substrate materials. Numerical data of the resonant frequency and bandwidth as a function of electric anisotropy ratio are presented. Variations of the resonant frequency and bandwidth with the magnetic anisotropy ratio are also given. Finally, results showing the influence of the temperature on the resonant frequency and quality factor of the high Tc superconducting rectangular microstrip patch on a uniaxial substrate are also given. Voir les détails
Mots clés : superconducting microstrip patch, Anisotropic substrate, Permittivity and permeability tensors
Bacterial foraging optimisation and method of moments for modelling and optimisation of microstrip antennas
A novel technique applying bacterial foraging optimisation (BFO) in conjunction with the method of moments (MOM) is developed to calculate accurately the resonant frequency and bandwidth of rectangular microstrip antenna of any dimension and of any substrate thickness. The resonant frequency results obtained by using (BFO/MOM) algorithm are in very good agreement with the experimental results available in the literature. The computation time is greatly reduced as compared with the classical MOM. Furthermore, the idea of this paper can be used for calculating the various parameters of microstrip antennas of different structures and geometries. Voir les détails
Mots clés : method of moments, microstrip antennas, natural frequencies, bacterial foraging, Computation time, Different structure, Method of moments (MOM), Modelling and optimisation, Novel techniques, Rectangular-microstrip antennas, Substrate thickness
MULTI-OBJECTIVE PREDICTIVE CONTROL: A SOLUTION USING METAHEURISTICS
The application of multi objective model predictive control approaches is significantly limited with computation time associated with optimization algorithms. Metaheuristics are general purpose heuristics that have been successfully used in solving difficult optimization problems in a reasonable computation time. In this work , we use and compare two multi objective metaheuristics, Multi-Objective Particle swarm Optimization, MOPSO, and Multi-Objective Gravitational Search Algorithm, MOGSA, to generate a set of approximately Pareto-optimal solutions in a single run. Two examples are studied, a nonlinear system consisting of two mobile robots tracking trajectories and avoiding obstacles and a linear multi variable system. The computation times and the quality of the solution in terms of the smoothness of the control signals and precision of tracking show that MOPSO can be an alternative for real time applications. Voir les détails
Mots clés : Model predictive control, Metaheuristcis, Multiobjective Optimization
Deposition of tin(II) sulfide thin films by ultrasonic spraypyrolysis: Evidence of sulfur exo-diffusion
Tin Sulfide (SnS) thin films were deposited by ultrasonic spray pyrolysis technique, on glass substrate heated at 280 °C, with different deposition times. The used precursor SnCl2 and thiourea are dissolved in methanol. X-ray diffraction (XRD) analysis indicates that films are mainly composed with orthorhombic SnS phase at low deposition time. With increasing deposition time, the hexagonal SnS2 phases become dominant. SnO2 and metallic Sn phases have been detected with increasing deposition time. Scanning electron microscopy (SEM) observations reveal that films surfaces are rough with the presence of bubbles due to S2 gas exo-diffusion from the bulk during film growth. A model of S gas formation is presented. Voir les détails
Mots clés : Tin Sulfide Thin films Spray pyrolysis
Chemical Sensor Array Modeling: Application to Resistive Based Chemo Sensors
The aim of paper is to develop analytical mathematical models that describe the thermo dynamical equilibrium of resistive chemical sensor arrays /mixture of vapors multi-system. By using the Gibbs Duhem formalism, state equations in differential form, that the variations of intensive quantities (e.g. sensors partial sensitivity) as function of the gas mixture components concentrations and sensor array parameters describe, have been developed. Moreover, the responses of the sensor arrays as function of gas mixture components concentrations were modeled. Voir les détails
Mots clés : resistive chemo-sensors, sensor array, vapors mixture, modeling, Metal Oxide Sensors (MOS), Conducting Polymer Sensors
Fuzzy Particle Swarm Optimization for Manufacturing Systems
Particle Swarm Optimization (PSO) is proposed in our research to generate Fuzzy Controller, a fuzzy logic control (FLC) is proposed to control manufacturing system presented by m-machine line as an m-order state-space. As results indicated, use particle swarm optimization (PSO) method for optimizing a fuzzy logic controller (FLC) for manufacturing system is better than that of fuzzy logic control (FLC) not optimized and applying fuzzy keeping the production demand. Voir les détails
Mots clés : Particle Swarm Optimization, PSO, fuzzy logic control, FLC, manufacturing system
PSO Optimization with Autoregressive Modeling and Support Vector Machines for Bearing Fault Diagnosis
As an effective tool in pattern recognition and machine learning, support vector machine (SVM) has been adopted abroad. In developing a successful SVM classifier, extracting feature is very important. This paper proposes the application of Autoregressive Modeling to SVM for feature extraction. To improve the classification accuracy for bearing fault prediction, particle swarm optimization (PSO) is employed to simultaneously optimize the SVM kernel function parameter and the penalty parameter. The results have shown feasibility and effectiveness of the proposed approach Voir les détails
Mots clés : machine learning, Support vector machine, SVM, Autoregressive Modeling, feature extraction
Modeling, control and fault diagnosis of an isolated wind energy conversion system with a self-excited induction generator subject to electrical faults
In this paper, a contribution to modeling and fault diagnosis of rotor and stator faults of a Self-ExcitedInduction Generator (SEIG) in an Isolated Wind Energy Conversion System (IWECS) is proposed. In orderto control the speed of the wind turbine, while basing on the linear model of wind turbine system about aspecified operating point, a new Fractional-Order Controller (FOC) with a simple and practical designmethod is proposed. The FOC ensures the stability of the nonlinear system in both healthy and faulty conditions.Furthermore, in order to detect the stator and rotor faults in the squirrel-cage self-excited inductiongenerator, an on-line fault diagnostic technique based on the spectral analysis of stator currents ofthe squirrel-cage SEIG by a Fast Fourier Transform (FFT) algorithm is used. Additionally, a generalizedmodel of the squirrel-cage SEIG is developed to simulate both the rotor and stator faults taking iron loss,main flux and cross flux saturation into account. The efficiencies of generalized model, control strategyand diagnostic procedure are illustrated with simulation results. Voir les détails
Mots clés : Wind energy conversion systems, fault detection and diagnosis, SEIG, Fractional-Order Controllers