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Gil-De-castro A.,Research Group PAIDI TIC 168 | Gil-De-castro A.,University of Cordoba, Spain | Moreno-Munoz A.,Research Group PAIDI TIC 168 | Moreno-Munoz A.,University of Cordoba, Spain | De La Rosa J.J.G.,University of Cadiz
Przeglad Elektrotechniczny | Year: 2010

Cordoba is an inland province of southern Spain, in the north-central part of the autonomous community of Andalusia. This paper presents the quantity of power that will be necessary to install for covering the electrical consumption of Cordoba's population. Multicriteria has been the followed method with selection of criteria and options for the new and renewable energy technologies assessment based on the analysis and synthesis of parameters under the information deficiency method. Source


De La Rosa J.J.G.,Research Group PAIDI TIC 168 | De La Rosa J.J.G.,University of Cadiz | Moreno-Munoz A.,Research Group PAIDI TIC 168 | Moreno-Munoz A.,University of Cordoba, Spain | And 4 more authors.
Measurement: Journal of the International Measurement Confederation | Year: 2010

In this paper we present the operation results of a portable computer-based measurement equipment, conceived to perform non-destructive testing of suspected termite infestations. Its signal processing nucleus is the spectral kurtosis (SK), whose pattern allows the targeting of alarms and activity signals. Data have been also de-noised using the discrete wavelet transform (DWT) in order to study its potential complementarity to SK. The DWT keeps the successive approximations of the termite emissions, supposed more non-Gaussian (less noisy) and with less entropy than the detail coefficients. For a given mother wavelet, the maximum acceptable level in the wavelet decomposition tree, which preserves the insects' emissions features, depends on the comparative evolution of the approximations vs. details' entropies, and the value of the global SK associated to the approximation of the separated signals. The paper explains the detection criterion by showing different types of real-life recordings (alarms, activity, and background). © 2010 Elsevier Ltd. All rights reserved. Source


De La Rosa J.J.G.,Research Group PAIDI TIC 168 | De La Rosa J.J.G.,University of Cadiz | Aguera-Perez A.,Research Group PAIDI TIC 168 | Palomares-Salas J.C.,Research Group PAIDI TIC 168 | And 3 more authors.
Measurement: Journal of the International Measurement Confederation | Year: 2012

This paper presents the performance results of a Virtual Instrument (VI) based in Case-Based Reasoning (CBR), conceived to online monitor the power-quality. The PC-based instrument receives data through a DAQ board and a differential probe, while maintaining economy by eliminating the extra network construction and hardware. Being flexible, presents an user-friendly interface and a large data storage capacity, since it uses the hard disk. The computational guts of the instrument are based in third and fourth-order statistics (along with the variance), which enhance detection capability and reject noise influence. A time-domain sliding window sweeps the register under test and offers a time-variation pattern which reflects the deviation of the statistical estimator with respect to the steady state. This three-valued time-series comprises variance, skewness and kurtosis evolution, and constitutes a triple input to the innovative CBR module, which in turn is capable of distinguishing electrical anomalies among five categories (the sixth is reserved to the healthy signal): non-50 Hz, 50-Hz-asymmetrical, 50-symmetrical non-sinusoidal, swell and sag. Online surveillance tests developed over the local electrical network show acceptable accuracy (96%). © 2012 Published by Elsevier Ltd. All rights reserved. Source


Aguera-Perez A.,Research Group PAIDI TIC 168 | Carlos Palomares-Salas J.,Research Group PAIDI TIC 168 | De La Rosa J.J.G.,Research Group PAIDI TIC 168 | De La Rosa J.J.G.,University of Cadiz | And 4 more authors.
Measurement: Journal of the International Measurement Confederation | Year: 2011

This paper deals with the detection of power quality anomalies which preserve the frequency of the power line, in particular sags and swells. Three statistical estimators have been used (variance, skewness and kurtosis) to enhance characterization of these anomalies. The proposed measurement strategy is funded in the tuning of the signal under test via a sliding window over which computation is performed. Then, the calculation of the statistical features reveals the inherent properties of the signal: amplitude, frequency and symmetry. The work primarily examines a number of synthetics in order to extract the theoretical statistical features. Then the algorithm is corroborated using real-life signals, obtaining an accuracy of 83%. This experience is part of the design of an instrument for the measurement of the power quality. © 2011 Elsevier Ltd. All rights reserved. Source


de la Rosa J.J.G.,Research Group PAIDI TIC 168 | de la Rosa J.J.G.,University of Cadiz | Aguera-Perez A.,Research Group PAIDI TIC 168 | Aguera-Perez A.,University of Cadiz | And 4 more authors.
Przeglad Elektrotechniczny | Year: 2011

In this paper a smart automatic classification of PQ transients is performed attending to their amplitudes and frequencies, and the extreme of higher-order cumulants. Feature extraction stage is double folded. First, these statistical measurements reveal the hidden geometry for a constant amplitude or frequency, conforming the 2D clustering grace to the third and fourth-order features associated to each signal anomaly, coupled to the 50-Hz power line. Precisely the main contribution of the work is the novel finding that the maxima and the minima of the higher-order cumulants distribute according to curves families, each of which associated to the transient's frequency or amplitude. Given a statistical order, each datum in a curve corresponds to the initial amplitude (or constant frequency), and to a couple of extremes (min-max) associated to the statistical estimator. The random grouping along each curve reveals the a priori hidden geometry, linked to the subjacent electrical phenomenon. Secondly, the regular surface grid in the input space (amplitude-frequency) experiments a transformation to the output space which is developed by the higher-order statistics. Once the geometry in the feature space has been found, we show the computational intelligence modulus, based in Self-Organizing Maps, which performs satisfactory learning along each frequency and amplitude curve. Performance of a four-neuron network with different geometries is shown, confirming the curves' patterns. Source

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