2020 Paris Spring International Scientific Meeting, May 16th, 2020

https://eciperu.net/category/eci-paris/

2019 Paris Autumn International Scientific Meeting, November 15 th, 2019

Ecole Normale Supérieur (ENS) de Paris
Salle L367, ENS-Paris, 24 Rue Lhomond, Paris

Inscripción para expositores: 
Presenters register link here

Inscripción para participantes: 
Participants register link here

Conferencistas:

MENCARAGLIA Denis
Directeur de Recherche CNRS,
Laboratoire Génie électrique et électronique de Paris  (GeePs) (UMR 8507 CNRS / CentraleSupelec – Universités UPMC et UPSud)
«III-V on Si : Monolithically integrated GaAs crystals on Si by CBE-ELO for Si based multispectral solar cells »

BARICHIVICH Jonathan
Chercheur, Laboratoire LSCE (Laboratoire des Sciences du Climat et de l’environnement) – CEA-SACLAY
«Recent intensification of the hydrological cycle in Amazonia»

SCHWEITZER  Patrick
Lorraine University, Institut Jean Lamour (Nancy), N2EV Department – Measurement and Electronic Architectures Group.
“Arcing fault detection in low voltage network (230 Volts AC and 270 Volts HVDC)”

CHAMORRO Diego
Associate Professor, Université d’Evry
« Estudio de regularidad Holderiana en Ecuaciones de transporte difusion »

BRUNEAU Olivier
Professeur des Universités, Université Paris-Saclay
Laboratoire LURPA (Laboratoire Universitaire de Recherche en Production Automatisée)
«Improved transparency and accuracy of robots and exoskeletons through  modeling and control»

ORDONEZ José
Chercheur CNRS
Laboratoire PPRIM, Université de Poitiers
“Heat transport by surface electromagnetic waves propagating along polar nanofilms”

DE OLIVERA Rodrigo
Associate Professor, Université de Versailles St. Quentin en Yvelines
SIDEAL : une plateforme logicielle pour le traitement de signal et les télécoms (exposé en français

MONTOYA Modesto
Profesor Universidad Nacional de Ingeniera (UNI) – PERU
“Double Energy and Time-Energy methods applied to the measuring of prompt neutron multiplicity as a function of mass in fission of actinides ”

LINARES Jorge
Professeur des Universités, Université de Versailles St. Quentin en Yvelines / Paris Saclay
Laboratoire GEMAC
« Pressure and Matrix effects on 2D spin crossover nanoparticles studied by Ising-like model »

Libro de resúmenes
SCHWEITZER  Patrick
“Arcing fault detection in low voltage network (230 Volts AC and 270 Volts HVDC)”
ABSTRACT: Arcing fault detection in domestic networks (50 Hz operating frequency and 230 V supply voltage) is an important subject for industrials and researchers since many years.
Protection devices are mainly based on the power line current and are inserted at the level of the general supply source in dwelling units. The challenge for fault detection algorithms is to have good performances under different circuit configurations in which series arcing faults are difficult to identify (masking loads, transient effect ….)
For example we have developed several algorithm perform the fault detection, in particular the Kalman Filter, which has the major advantage of allowing regular temporal estimation through an on-line digital processing structure, unlike the other methods of the literature that perform detection over a  predefined sliding time window. The decision block is done by a Fuzzy logic approach.
On the same, DC power grids have expanded widely in recent years. In the aeronautics sector, voltage supply levels tend to increase from 28 VDC to 270 VDC. The detection of electrical failures and more specifically electric arcs faults detection becomes absolutely necessary because of great danger they present. I will present a series arc faults detection method, based on a frequency analysis associated with a decision block, developed in our laboratory.
The detection performance needs to be further improved and combined with efficient decision methods (Neural Netwoks, …).

C.V.
SCHWEITZER  Patrick
Associate professor, Lorraine University, Institut Jean Lamour (Nancy), N2EV Department – Measurement and Electronic Architectures Group.
Research themes : Development of detection algorithms for series arc fault detection in low power AC and DC electrical networks associated to artificial intelligence techniques for the decision part.
Collaboration with industrialists for theses: Hager, Leach-Esterline and one Peruvian financing.
– Jinmy Lezama (2014), Detecting Arc Faults in the Domestic Electrical networks.
– Jean Baptiste Humbert (2018), Study and detection of electric arc faults in a 270V HVDC avionics electrical network.
– Edwin Calderon (2019), Locating and Detecting Arc Faults in the Domestic Electrical Network.
– Duc Vu (2019), Artificial intelligence applied to the detection of electric arc faults in the domestic electrical network.

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