Mohamed Rachid Mekideche

Corona-Charging and Charge-Decay Characteristics of Nonwoven Filter Media

The surface-potential-decay measurement techniques are commonly employed for the adjustment of Xerox photography processes, development of electrets, and assessment of polyethylene films for cable insulation. In all these situations, it is important to evaluate the surface charge density and compare it to the limit imposed by the dielectric rigidity of atmospheric air. The aim of the experiments reported in this paper is to enhance the efficiency of the corona charging of nonwoven filter media for heat, ventilation, and air-conditioning applications. Samples of nonwoven polypropylene fibrous media were exposed to positive corona discharges from a wire electrode, as the efficiency of the filter can be enhanced when the insulating fibers are electrically charged. The observed surface potential levels and the potential decay characteristics indicate that the charge of the filter is limited by the local discharges that occur inside the fibrous dielectric. The performance of the filter can be further improved by using a triode-type electrode system that assures a uniform distribution of the electric charge at the surface of the filtering media.

Factors That Influence the Decay Rate of the Potential at the Surface of Nonwoven Fabrics After Negative Corona Discharge Deposition

Surface potential decay (SPD) measurements are considered as the most appropriate technique for the investigation of the corona charging of dielectric surfaces. The aim of the experiments reported in the present paper was to point out the peculiarities of SPD in the case of nonhomogeneous dielectrics, such as the nonwoven fabrics employed for heat, ventilation, and air conditioning. This paper reports experimental data collected on two types of polypropylene (PP) media, characterized by different fiber diameters. The experiments were performed on 60 mm × 50 mm samples of nonweaved sheets of PP (sheet thickness: 400 μm; average fiber diameter: 20 μm), in ambient air (temperature: 18°C to 22°C; relative humidity: 25% to 60%). The samples were charged for 10 s by exposing them to the negative corona discharge, using a triode-type electrode arrangement, energized from a dc high-voltage supply. Their surface potential was then measured with an electrostatic voltmeter. The measured data indicate that the charge of the filter is limited by the local discharges that occur inside the fibrous dielectric.

Microwave Characterization Using Least-Square Support Vector Machines

This paper presents the use of the least-square support vector machines (LS-SVM) technique, combined with the finite element method (FEM), to evaluate the microwave properties of dielectric materials. The LS-SVM is a statistical learning method that has good generalization capability and learning performance. The FEM is used to create the data set required to train the LS-SVM. The performance of LS-SVM model depends on a careful setting of its associated hyper-parameters. Different tuning techniques for optimizing the LS-SVM hyper-parameters are studied: cross validation (CV), genetic algorithms (GA), heuristic approach, and Bayesian regularization (BR). Results show that BR provides a good compromise between accuracy and computational cost.

Inverse Problem Methodology for Parameter Identification of a Separately Excited DC Motor

Identification is considered to be among the main applications of inverse theory and its objective for a given physical system is to use data which is easily observable, to infer some of the geometric parameters which are not directly observable. In this paper, a parameter identification method using inverse problem methodology is proposed. The minimisation of the objective function with respect to the desired vector of design parameters is the most important procedure in solving the inverse problem. The conjugate gradient method is used to determine the unknown parameters, and Tikhonov’s regularization method is then used to replace the original ill-posed problem with a well-posed problem. The simulation and experimental results are presented and compared.

Vector controlled permanent magnet synchronous motor (PMSM) drive with stator turn fault

In order to develop an effective detection method and tolerant strategy, a simulation model which can describe accurately the behavior of a PMSM drive with stator turn faults, is absolutely required. In this paper a dynamic model for permanent magnet synchronous motor with a stator inter-turn winding fault is derived in abc-variables. The model is used in vector control for a PMSM drive for both healthy and faulty conditions. As any method should be fully confirmed with a simulation model before being applied to a real system, the stator turn fault vector control strategy for PMSM drive is implemented in MATLAB/SIMULINK. Simulation results show the limit of validity of the proposed strategy and allow proposing a strategy for diagnosis but also for fault tolerant control development.

An Inverse Problem Approach for Parameter Estimation of Interior Permanent Magnet Synchronous Motor

The estimation of d- and q-axis parameters is highly desirable, because they are fundamental parameters to many vector control algorithms in the d-q reference frame for fast and accurate responses. Using the flnite element method (FEM) for the determination of the interior permanent magnet synchronous motor (IPM) reactance provides an accurate means of determining the fleld distribution. However, this method might be time consuming. The magnetic circuit modelling approach has been successfully used to model a variety of electrical machine such as IPM motors. This paper deals with the inverse problem methodology for the identiflcation of d- and q-axis synchronous reactance of an IPM motor. The proposed method uses a measured electromotive force (EMF) to compute the objective function. The machine parameters identifled by the proposed approach are compared to experimental results.

Modeling of Analysis ICP Torch at Atmospheric Pressure With Applied Voltage

In this paper, a new 2-D nonlinear direct-coupled model for the simulation of inductively coupled plasma torches working at atmospheric pressure is presented. Steady fluid flow and temperature equations are simultaneously solved (direct method) using a finite-element formulation for optically thin argon plasmas under the assumptions of local thermodynamic equilibrium and laminar flow. The electromagnetic field equations are formulated in terms of potential vector with applied voltage source.

Model for the behavior of magnetic materials hysteretic taking into account the temperature

The work is to develop a model for magnetic hysteresis taking into account the temperature. We introduced the effect of temperature through behavior as a function of temperature settings and model Jiles Atherton. The results of the model in terms of saturation induction, remanent induction, coercive field and the evolution of hysteresis cycle as a function of temperature are accort with theory and with results given in [1]. A program for calculating field incorporating model hysteresis to study a system of induction heating is also necessary. This program of resolution was developed using the finite element method in 2D. The simulations carried out with this calculation programme we allowedto study the evolution of the hysteresis loop according to the temperature. They also make it possible to deduce the evolution from the losses by hysteresis and eddy currents as a function of temperature.

The combination of adaptive database SDM and multi-output SVM for eddy current testing

Purpose – Eddy current testing (ECT) is a nondestructive testing method for the detection of flaws that uses electromagnetic induction to find defects in conductive materials. In this method, eddy currents are generated in a conductive material by a changing magnetic field. A defect is detected when there is a disruption in the flow of the eddy current. The purpose of this paper is to develop a new noniterative inversion methodology for detecting degradation (defect characterization) such as cracking, corrosion and erosion from the measurement of the impedance variations. Design/methodology/approach – The methodology is based on multi-output support vector machines (SVM) combined with the adaptive database schema design method (SDM). The forward problem was solved numerically using finite element method (FEM), with its accuracy experimentally verified. The multi-output SVM is a statistical learning method that has good generalization capability and learning performance. FEM is used to create the adaptive ...

Optimization of magnets segmentation for eddy current losses reduction in permanent magnets electrical machines

Magnet segmentation is an effective and simple technique for eddy current losses reduction in high power permanent magnets electrical machines. This work aims to study the magnets segmentation effects on eddy current losses in magnets. First, an analysis of eddy currents and associated losses in magnets is made. After, the magnets segmentation effects on losses reduction in the range of the industrial frequencies from few Hz to dozen of kHz are investigated. To achieve these tasks, a 2D non linear model based on finite element analysis is developed under MATLAB environment. The developed model is applied to a synchronous machine with surface mounted permanent magnets. In a second part of the work, we have adopted an optimization process which consists to associate the finite element analysis to genetic algorithm. In this stage of the work, we aim to find the best parameters of magnets segmentation and avoid any segmentations anomaly that appears under some conditions such as skin effect, and which can leads to losses increases instead of their reduction.