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A Precise Electrical Disturbance Generator for Neural Network Training with Real Level Output

  • Antonio García
  • Carlos León
  • Iñigo Monedero
  • Jorge Ropero
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4756)

Abstract

Power Quality is defined as the study of the quality of electric power lines. The detection and classification of the different disturbances which cause power quality problems is a difficult task which requires a high level of engineering expertise. Thus, neural networks are usually a good choice for the detection and classification of these disturbances. This paper describes a powerful tool, developed by the Institute for Natural Resources and Agrobiology at the Scientific Research Council (CSIC) and the Electronic Technology Department at the University of Seville, which generates electrical patterns of disturbances for the training of neural networks for PQ tasks. This system has been expanded to other applications (as comparative test between PQ meters, or test of effects of power-line disturbances on equipment) through the addition of a specifically developed high fidelity power amplifier, which allows the generation of disturbed signals at real levels.

Keywords

Power quality electrical disturbance neural network 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Antonio García
    • 1
  • Carlos León
    • 1
  • Iñigo Monedero
    • 1
  • Jorge Ropero
    • 1
  1. 1.Escuela Técnica Superior de Ingeniería Informática, Departamento de Tecnología Electrónica, Avda, Reina Mercedes s/n, 41012 SevillaSpain

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