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

abstract

  • 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.

publication date

  • 2020-8-11

edition

  • 685

keywords

  • Artificial intelligence
  • Economics
  • Electric lines
  • Electric potential
  • Graphical user interfaces
  • Multilayer neural networks
  • Neural networks
  • Personnel
  • Power transmission

ISBN

  • 9783030530204

number of pages

  • 10

start page

  • 175

end page

  • 184