Neural Networks Identification of Eleven Types of Faults in High Voltage Transmission Lines Capítulo

Nombre del libro

AETA 2019 - Recent Advances in Electrical Engineering and Related Sciences

editorial

Springer

Autor

Alfredo Sanabria
Carlos A. Pinto-Díaz
Carlos Arizmendi P
Cesar Hernando Valencia
Gerson Portilla F
Hernando González A
Laura Bautista F

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.

autores

http://vivoweb.org/ontology/core#FacultyMember
Orjuela Cañón, Alvaro David

fecha de publicación

2020-8-11

Área temática

Salud y bienestar

Edición

685

Identificador de objeto digital (DOI)

https://doi.org/10.1007/978-3-030-53021-1_18

Número Estándar Internacional de Libros (ISBN)

9783030530204

Número de páginas

10

Página inicial

175

Última página

184