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Documentos generados por los docentes e investigadores de la Universidad en su labor de investigación científica producida o editada por los departamentos y centros de la Universitat Politècnica de València.
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Browsing Investigación by Author "563824"
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- PublicationCorrelations between Background Radiation Inside a Multilayer Interleaving Structure, Geomagnetic Activity, and Cosmic Radiation: A Fourth-Order Cumulant-Based Correlation Analysis(MDPI AG, 2020-03) Iglesias-Martínez, Miguel E.; Castro Palacio, Juan Carlos; Scholkmann, Felix; Milián-Sánchez, Victor; Fernández de Córdoba Castellá, Pedro José; Mocholí Salcedo, Antonio; Mocholí-Belenguer, Ferran; Kolombet, Valeriy A.; Panchelyuga, Victor A.; Verdú Martín, Gumersindo Jesús; Dpto. de Física Aplicada; Dpto. de Ingeniería Química y Nuclear; Dpto. de Matemática Aplicada; Escuela Técnica Superior de Ingeniería del Diseño; Instituto Universitario de Matemática Pura y Aplicada; Escuela Técnica Superior de Ingeniería Industrial; Instituto Universitario de Seguridad Industrial, Radiofísica y Medioambiental; Centro de Tecnologías Físicas: Acústica, Materiales y Astrofísica; AGENCIA ESTATAL DE INVESTIGACION[EN] Time-series of background radiation (measured inside a multilayer structure), geomagnetic activity, and cosmic-ray activity has been analyzed using linear correlation analysis and a new correlation measure based on the one-dimensional component of the fourth-order cumulant. The new method is proposed based on the fact that the cumulant of a random process is zero if it is of Gaussian nature. The results show that this methodology is useful for detecting correlations between the analyzed time-series
- PublicationDetection of adjacent and non-adjacent bar breakages in induction motors via convolutional analysis of sound signals(MDPI AG, 2020-10) Iglesias Martínez, Miguel Enrique; Fernández de Córdoba Castellá, Pedro José; Antonino Daviu, José Alfonso; Conejero Casares, José Alberto; Instituto de Tecnología Eléctrica; Dpto. de Matemática Aplicada; Dpto. de Ingeniería Eléctrica; Instituto Universitario de Matemática Pura y Aplicada; Escuela Técnica Superior de Ingeniería Industrial; Escuela Técnica Superior de Ingeniería Informática; Generalitat Valenciana; Agencia Estatal de Investigación; European Regional Development Fund; Ministerio de Economía y Competitividad[EN] We apply power spectral analysis based on covariance function and spectral subtraction to detect adjacent and non-adjacent bar breakages. We get a spectral pattern when the signal presents one or various broken bars, independent of the relative position of the bar breakages. The proposed algorithm gives satisfactory results about detectability compared to some previous researches. Additionally, we also present illustrations of faults and signal to noise in the noise reduction stage.
- PublicationDetection of nonadjacent rotor faults in induction motors via spectral subtraction and autocorrelation of stray flux signals(Institute of Electrical and Electronics Engineers, 2019-10) Iglesias-Martínez, Miguel Enrique; Fernández de Córdoba Castellá, Pedro José; Antonino Daviu, José Alfonso; Conejero Casares, José Alberto; Instituto de Tecnología Eléctrica; Dpto. de Matemática Aplicada; Dpto. de Ingeniería Eléctrica; Instituto Universitario de Matemática Pura y Aplicada; Escuela Técnica Superior de Ingeniería Industrial; Escuela Técnica Superior de Ingeniería Informática; Agencia Estatal de Investigación; European Regional Development Fund; Ministerio de Economía y Competitividad[EN] In this paper, statistical signal processing techniques are applied to electromotive force signals captured in external coil sensors for adjacent and nonadjacent broken bars detection in induction motors. An algorithm based on spectral subtraction analysis is applied for broken bar identification, independent of the relative position of the bar breakages. Moreover, power spectrum analyses enable the discrimination between healthy and faulty conditions. The results obtained with experimental data prove that the proposed approach provides good results for fault detectability. Moreover, the identification of the faults, and the signal correlation indicator to prove the results are also presented for different positions of the flux sensor.
- PublicationDevelopment of algorithms of statistical signal processing for the detection and pattern recognitionin time series. Application to the diagnosis of electrical machines and to the features extraction in Actigraphy signals(Universitat Politècnica de València, 2020-06-08) Iglesias Martínez, Miguel Enrique; Antonino Daviu, José Alfonso; Conejero Casares, José Alberto; Fernández de Córdoba Castellá, Pedro José; Instituto de Tecnología Eléctrica; Dpto. de Matemática Aplicada; Dpto. de Ingeniería Eléctrica; Instituto Universitario de Matemática Pura y Aplicada; Escuela Técnica Superior de Ingeniería Industrial; Escuela Técnica Superior de Ingeniería Informática[ES] En la actualidad, el desarrollo y aplicación de algoritmos para el reconocimiento de patrones que mejoren los niveles de rendimiento, detección y procesamiento de datos en diferentes áreas del conocimiento resulta un tema de gran interés. En este contexto, y específicamente en relación con la aplicación de estos algoritmos en el monitoreo y diagnóstico de máquinas eléctricas, el uso de señales de flujo es una alternativa muy interesante para detectar las diferentes fallas. Asimismo, y en relación con el uso de señales biomédicas, es de gran interés extraer características relevantes en las señales de actigrafía para la identificación de patrones que pueden estar asociados con una patología específica. En esta tesis, se han desarrollado y aplicado algoritmos basados en el procesamiento estadístico y espectral de señales, para la detección y diagnóstico de fallas en máquinas eléctricas, así como su aplicación al tratamiento de señales de actigrafía. Con el desarrollo de los algoritmos propuestos, se pretende tener un sistema dinámico de indicación e identificación para detectar la falla o la patología asociada que no depende de parámetros o información externa que pueda condicionar los resultados, sólo de la información primaria que inicialmente presenta la señal a tratar (como la periodicidad, amplitud, frecuencia y fase de la muestra). A partir del uso de los algoritmos desarrollados para la detección y diagnóstico de fallas en máquinas eléctricas, basados en el procesamiento estadístico y espectral de señales, se pretende avanzar, en relación con los modelos actualmente existentes, en la identificación de fallas mediante el uso de señales de flujo. Además, y por otro lado, mediante el uso de estadísticas de orden superior, para la extracción de anomalías en las señales de actigrafía, se han encontrado parámetros alternativos para la identificación de procesos que pueden estar relacionados con patologías específicas.
- PublicationFeature extraction and similarity of movement detection during sleep, based on higher order spectra and entropy of the actigraphy signal: Results of the Hispanic Community Health Study/Study of Latinos(MDPI AG, 2018) Iglesias-Martinez, Miguel Enrique; García Gómez, Juan Miguel; Sáez Silvestre, Carlos; Fernández de Córdoba Castellá, Pedro José; Conejero Casares, José Alberto; Dpto. de Física Aplicada; Instituto Universitario de Tecnologías de la Información y Comunicaciones; Dpto. de Matemática Aplicada; Instituto Universitario de Matemática Pura y Aplicada; Escuela Técnica Superior de Ingeniería Industrial; Escuela Técnica Superior de Ingeniería Informática; European Commission; Ministerio de Economía y Competitividad[EN] The aim of this work was to develop a new unsupervised exploratory method of characterizing feature extraction and detecting similarity of movement during sleep through actigraphy signals. We here propose some algorithms, based on signal bispectrum and bispectral entropy, to determine the unique features of independent actigraphy signals. Experiments were carried out on 20 randomly chosen actigraphy samples of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) database, with no information other than their aperiodicity. The Pearson correlation coefficient matrix and the histogram correlation matrix were computed to study the similarity of movements during sleep. The results obtained allowed us to explore the connections between certain sleep actigraphy patterns and certain pathologies.
- PublicationFluctuations in measured radioactive decay rates inside a modified Faraday cage: Correlations with space weather(Nature Publishing Group, 2020-05-22) Milián-Sánchez, V.; Scholkmann, F.; Fernández de Córdoba Castellá, Pedro José; Mocholí Salcedo, Antonio; Mocholí-Belenguer, Ferran; Iglesias-Martínez, M. E.; Castro Palacio, Juan Carlos; Kolombet, V. A.; Panchelyuga, V. A.; Verdú Martín, Gumersindo Jesús; Dpto. de Física Aplicada; Dpto. de Ingeniería Química y Nuclear; Dpto. de Matemática Aplicada; Escuela Técnica Superior de Ingeniería del Diseño; Instituto Universitario de Matemática Pura y Aplicada; Escuela Técnica Superior de Ingeniería Industrial; Instituto Universitario de Seguridad Industrial, Radiofísica y Medioambiental; Centro de Tecnologías Físicas: Acústica, Materiales y Astrofísica; GENERALITAT VALENCIANA; AGENCIA ESTATAL DE INVESTIGACION; Universitat Politècnica de València; Ministry of Science and Higher Education of the Russian Federation[EN] For several years, reports have been published about fluctuations in measured radioactive decay time-series and in some instances linked to astrophysical as well as classical environmental influences. Anomalous behaviors of radioactive decay measurement and measurement of capacitance inside and outside a modified Faraday cage were documented by our group in previous work. In the present report, we present an in-depth analysis of our measurement with regard to possible correlations with space weather, i.e. the geomagnetic activity (GMA) and cosmic-ray activity (CRA). Our analysis revealed that the decay and capacitance time-series are statistically significantly correlated with GMA and CRA when specific conditions are met. The conditions are explained in detail and an outlook is given on how to further investigate this important finding. Our discovery is relevant for all researchers investigating radioactive decay measurements since they point out that the space weather condition during the measurement is relevant for partially explaining the observed variability.
- PublicationHigher-order spectral analysis of stray flux signals for faults detection in induction motors(UP4 Institute of Sciences, S.L., 2020-07) Iglesias Martínez, Miguel E.; Antonino Daviu, José Alfonso; Fernández de Córdoba Castellá, Pedro José; Conejero Casares, José Alberto; Instituto de Tecnología Eléctrica; Dpto. de Matemática Aplicada; Dpto. de Ingeniería Eléctrica; Instituto Universitario de Matemática Pura y Aplicada; Escuela Técnica Superior de Ingeniería Industrial; Escuela Técnica Superior de Ingeniería Informática; Generalitat Valenciana; Agencia Estatal de Investigación; Ministerio de Economía y Competitividad[EN] This work is a review of current trends in the stray flux signal processing techniques applied to the diagnosis of electrical machines. Initially, a review of the most commonly used standard methods is performed in the diagnosis of failures in induction machines and using stray flux; and then specifically it is treated and performed the algorithms based on statistical analysis using cumulants and polyspectra. In addition, the theoretical foundations of the analyzed algorithms and examples applications are shown from the practical point of view where the benefits that processing can have using HOSA and its relationship with stray flux signal analysis, are illustrated.
- PublicationMachinery Failure Approach and Spectral Analysis to Study the Reaction Time Dynamics over Consecutive Visual Stimuli: An Entropy-Based Model(MDPI AG, 2020-11) Iglesias-Martinez, Miguel E.; Hernaiz-Guijarro, Moises; Castro Palacio, Juan Carlos; Fernández de Córdoba Castellá, Pedro José; Isidro San Juan, José María; Navarro-Pardo, Esperanza; Dpto. de Física Aplicada; Dpto. de Matemática Aplicada; Escuela Técnica Superior de Ingeniería del Diseño; Instituto Universitario de Matemática Pura y Aplicada; Escuela Técnica Superior de Ingeniería Industrial; Centro de Tecnologías Físicas: Acústica, Materiales y Astrofísica; AGENCIA ESTATAL DE INVESTIGACION[EN] The reaction times of individuals over consecutive visual stimuli have been studied using an entropy-based model and a failure machinery approach. The used tools include the fast Fourier transform and a spectral entropy analysis. The results indicate that the reaction times produced by the independently responding individuals to visual stimuli appear to be correlated. The spectral analysis and the entropy of the spectrum yield that there are features of similarity in the response times of each participant and among them. Furthermore, the analysis of the mistakes made by the participants during the reaction time experiments concluded that they follow a behavior which is consistent with the MTBF (Mean Time Between Failures) model, widely used in industry for the predictive diagnosis of electrical machines and equipment.
- PublicationRotor fault detection in induction motors based on time-frequency analysis using the bispectrum and the autocovariance of stray flux signals(MDPI AG, 2019-02-02) Iglesias-Martínez, Miguel E.; Antonino Daviu, José Alfonso; Fernández de Córdoba Castellá, Pedro José; Conejero Casares, José Alberto; Instituto de Tecnología Eléctrica; Dpto. de Matemática Aplicada; Dpto. de Ingeniería Eléctrica; Instituto Universitario de Matemática Pura y Aplicada; Escuela Técnica Superior de Ingeniería Industrial; Escuela Técnica Superior de Ingeniería Informática; Ministerio de Economía y Competitividad[EN] The aim of this work is to find out, through the analysis of the time and frequency domains, significant differences that lead us to obtain one or several variables that may result in an indicator that allows diagnosing the condition of the rotor in an induction motor from the processing of the stray flux signals. For this, the calculation of two indicators is proposed: the first is based on the frequency domain and it relies on the calculation of the sum of the mean value of the bispectrum of the flux signal. The use of high order spectral analysis is justified in that with the one-dimensional analysis resulting from the Fourier Transform, there may not always be solid differences at the spectral level that enable us to distinguish between healthy and faulty conditions. Also, based on the high-order spectral analysis, differences may arise that, with the classical analysis with the Fourier Transform, are not evident, since the high order spectra from the Bispectrum are immune to Gaussian noise, but not the results that can be obtained using the one-dimensional Fourier transform. On the other hand, a second indicator based on the temporal domain that is based on the calculation of the square value of the median of the autocovariance function of the signal is evaluated. The obtained results are satisfactory and let us conclude the affirmative hypothesis of using flux signals for determining the condition of the rotor of an induction motor.
- PublicationThe VHE SED modelling of Markarian 501 in 2009(Oxford University Press, 2020-02) Sahu, S.; López Fortín, C. E.; Iglesias Martínez, M. E.; Nagataki, S.; Fernández de Córdoba Castellá, Pedro José; Dpto. de Matemática Aplicada; Instituto Universitario de Matemática Pura y Aplicada; Escuela Técnica Superior de Ingeniería Industrial; Universidad Nacional Autónoma de México; Japan Society for the Promotion of Science; Ministry of Education, Culture, Sports, Science and Technology, Japón[EN] The high energy blazar, Markarian 501 was observed as a part of multi-instrument and multiwavelength campaign spanning the whole electromagnetic spectrum for 4.5 months during March 15 to August 1, 2009. On May 1, Whipple 10 m telescope observed a very strong gamma-ray flare in a time interval of about 0.5 h. Apart from this flare, high state and low state emissions were also observed by Whipple, VERITAS and MAGIC telescopes. Using the photohadronic model and accounting for the absorption of the extragalactic background light to these very high energy gamma-rays, excellent fits are obtained for the observed spectra. We have shown that the intrinsic spectrum for low state emission is flat, however, for high and very high states this is a power-law with slowly increasing exponent.