Equipe 4 SMT

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 …
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