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A System for the Generation and Detection of Electrical Disturbances

Authors: Monedero Goicoechea, Iñigo Luis; León de Mora, Carlos; Ropero Rodríguez, Jorge; Vega, José Luis de la; Montaño Asquerino, Juan-Carlos; Elena Ortega, José Manuel;

A System for the Generation and Detection of Electrical Disturbances

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 system, 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, for the generation and detection (by means of neural networks) of electrical disturbances.

Ministerio de Ciencia y Tecnología DPI2002-04420-C03-03.

Country
Spain
Related Organizations
Keywords

Power quality, Electrical disturbance, Wavelet transform, Neural network

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green