Neural networks identification of eleven types of faults in high voltage transmission lines

Laura Bautista F, Cesar Valencia N, Gerson Portilla F, Alfredo Sanabria, Carlos Pinto, Hernando González A, Carlos Arizmendi P, David Orjuela C

Producción científica: EventosEventos científicosrevisión exhaustiva

Resumen

In power transmission systems faults returning leaving them offline. This problem generates an economic impact on the interested parties, partly because in certain cases transmission lines protections act in a delayed manner or because the data processing generated by electrical protections tends to be a tedious. Artificial intelligence personnel have implemented a number of methods aimed to provide solutions for detection, classification and localization of said faults. In this work, a multilayer neural network capable of performing the process of classifying 11 types of faults in power transmission lines was implemented. As a result, a graphical interface allows users to intuitively visualize the faults.

Idioma originalInglés
Páginas175-184
Número de páginas10
DOI
EstadoPublicada - 2021
Evento6th International Conference on Advanced Engineering Theory and Applications, AETA 2019 - Bogota, Colombia
Duración: 6 nov. 20198 nov. 2019

Conferencia

Conferencia6th International Conference on Advanced Engineering Theory and Applications, AETA 2019
País/TerritorioColombia
CiudadBogota
Período6/11/198/11/19

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