Presentation
A Precise Electrical Disturbance Generator for Neural Network Training with Real Level Output
Author/s | García Delgado, Antonio
León de Mora, Carlos Monedero Goicoechea, Iñigo Luis Ropero Rodríguez, Jorge |
Department | Universidad de Sevilla. Departamento de Tecnología Electrónica |
Publication Date | 2007 |
Deposit Date | 2018-07-06 |
Published in |
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ISBN/ISSN | 978-3-540-76724-4 0302-9743 |
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 ... 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. |
Funding agencies | Ministerio de Ciencia y Tecnología (MCYT). España |
Project ID. | DPI2006-15467-C02-02 |
Citation | García Delgado, A., León de Mora, C., Monedero Goicoechea, I.L. y Ropero Rodríguez, J. (2007). A Precise Electrical Disturbance Generator for Neural Network Training with Real Level Output. En CIARP 2007: 12th Iberoamericann Congress on Pattern Recognition (534-545), Valparaiso, Chile: Springer. |
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