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Catégorie C SMT

Zeghichi, L., Mokhnache Leila, and M. Djebabra. 2016. “Effect of Applied Electric Field and Pressure on the Electron Avalanche Growth, e-ISSN 2415-1513”. WSEAS TRANSACTIONS on ELECTRONICS 7. Publisher's Version Abstract
The purpose of this paper is to mimic, using the Monte Carlo Simulation, the electron avalanche growth by tracking individual paths of charged particles; the effect of space charge is included by solving the Poisson equation. An electronic avalanche is produced, when an electric field, sufficiently intense, is applied to a gas. At some stage of formation of free electrons and ions; the electronic avalanche becomes a conductor channel, and then self sustainment of the discharge. The simulation is carried out in O2 gas for two different pressures, under the effect of uniform electrical fields. The streamer breakdown criterion for the different applied uniform fields is examined.
Nabil, Benhadda, et al. 2014. “Study of the Influence of Conductive Defect Characteristics on Eddy Current Differential Probe Signal, ISSN 1582-4594”. Journal of Electrical Engineering Volume 14 : pp 350-357. Publisher's Version Abstract
Nowadays, numerical modelling has become an interesting tool for determining impedance variations due to various conductive flaws in eddy current nondestructive evaluation systems. These kinds of defects, rarely treated in the published works, are taken into consideration in the modelling while introducing them as electrically conductive volumes with a finite electric resistivity. This step is very important since it permits to improve qualitatively several models developed so far by many authors whose consider the defect as loss of material only. However, in several applications, the defect can occur with a finite resistivity such as impurity, small burns and micro-solder. On the other hand, even though the defect appears with a loss of materials, som e polluting materials can fill the affected region. Indeed, the volume of the initial defect will be completely or partially occupied by these conducting pollutant materials. This paper deals with the effect of physical and geometrical characteristics of such kind of defects on the differential sensor response. Furthermore, the necessity of taking the defect electric conductivity (as an important parameter) into account will be explained, in order to develop a reliable and accurate inverse method allowing a full characterization of conductive defects.
Saliha, Boudraa, and Mokhnache Leila. 2014. “ Artificial neural networks for predicting the gassing tendency under electrical discharge in insulating oil for extended time, ISSN 1582-4594 ”. Journal of Electrical Engineering 14 (2) : pp 45-52. Publisher's Version Abstract
This study will focus on the investigation of the effect of electrical discharge on physical, chemical, electrical properties of transformer oil, and on the development of a mathematical model describing the gassing of insulating oil under electrical discharge, using the information contained in the measured values. For predicting the gassing tendency for extensive ageing periods, we use the model developed, for an intelligent system design. The predictor's parameters are chosen based on their influence degree by the electrical field. Various scenarios were considered. The study was carried on two types of fluids, under electrical stress for different ages. The 6802, 6181 and 924 ASTM tests methods were used for the measurements of parameters in degradation. All the results obtained are summarized and compared. The properties which are strongly dependent have been specified, a multiple linear regression model for each fluid as a function of its DDP, DDF, turbidity and aging period is developed. This model is for the estimation of the gas quantity cumulated under electrical discharge. The prediction is made, by implanting the stepwise regression results into a neural network system, which has been tested on experimental results obtained from laboratory samples, and high prediction accuracy has been achieved.
Boudraa, S., and Mokhnache Leila. 2013. “A Multi Regression Approach For Predicting The Age Of Transformer Oil In Thermal/Electrical Degradation, e-ISSN 2278-0181”. International Journal of Engineering Research & Technology Vol 2 (Issue 5 ) : pp. 1004-1008. Publisher's Version Abstract
Power transformers are considered capital investments in the infrastructure of every power system in the world. They are the heart of electric power distribution and transmission systems, and it is essential that they function properly. It is knowing that insulating fluid is highly used in a composite or impregnated dielectric system with reference to both dielectric strength and ease of contamination, many investigators have devoted great efforts to investigate fluidsbehaviours under operating conditions.The objective of this study is to examine the gassing tendency under electrical discharge of aged and unaged mineral oil, and analyze the parameters in degradation, with the aim to see the most significant parameters which can really presents the degradation severity.In this regard, various scenarios were considered. The study was carried on new and aged oil submitted electrical field. The 6802, 6181 and 924 tests are used in measure of parameters in degradation.In this work, the water contents, Interfacial tension, and gas pressure generated,are considered as a parametersignificant of degradation process.These parameters were used as inputsin approach model for prediction the transformer age (life), the result show that the water can be used for detection of early stage of degradation
Keltoum, Benlarbi, Mokrani Lakhdar, and Mokhnache Leila. 2013. “An Improved Proportional Integral Estimator of the Stator Resistance for a Direct Torque Controlled Induction Motor, ISSN 1934-8975”. Journal of Energy and Power Engineering Volume 7 (11) : pp. 2144-2155. Publisher's Version Abstract
In this paper, an improved PI (proportional integral) stator resistance estimation for a DTC
(direct torque controlled) induction motor is proposed. This estimation method is based on
an on-line stator resistance correction regarding the variations of the stator current
estimation error. In fact, the input variable of the PI estimator is the stator current estimation
error. The main idea is to tune accurately the stator resistance value relatively to the
evolution of the stator current estimation error gradient to avoid the drive instability and …