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Guillermo Robles   Dr.  University Educator/Researcher 
Affiliations
Universidad Carlos III de Madrid
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This is what I am: http://electrica.uc3m.es/grobles/

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Guillermo Robles published an article in February 2019.
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Top co-authors See all
B. Tellini

36 shared publications

Department of Energy, Systems, Land and Constructions Engineering, University of Pisa, Pisa, Italy

José Manuel Fresno

12 shared publications

Department of Electrical Engineering, Universidad Carlos III de Madrid, Leganés, 28911 Madrid, Spain;(J.M.F.);(J.M.M.-T.)

Jorge&nbspalfredo&nbspardila- Rey

10 shared publications

Department of Electrical Engineering, Universidad Técnica Federico Santamaría, Santiago de Chile

C. Zappacosta

5 shared publications

Emilio Parrado-Hernández

4 shared publications

Department of Signal Processing and Communications, Universidad Carlos III de Madrid, Leganés, 28911 Madrid, Spain

66
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79
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Publication Record
Distribution of Articles published per year 
(2002 - 2019)
Total number of journals
published in
 
22
 
Publications See all
Article 0 Reads 0 Citations Online condition monitoring of MV cable feeders using Rogowski coil sensors for PD measurements M. Shafiq, K. Kauhaniemi, G. Robles, M. Isa, L. Kumpulainen Published: 01 February 2019
Electric Power Systems Research, doi: 10.1016/j.epsr.2018.10.038
DOI See at publisher website ABS Show/hide abstract
Condition monitoring is a highly effective prognostic tool for incipient insulation degradation to avoid sudden failures of electrical components and to keep the power network in operation. Improved operational performance of the sensors and effective measurement techniques could enable the development of a robust monitoring system. This paper addresses two main aspects of condition monitoring: an enhanced design of an induction sensor that has the capability of measuring partial discharge (PD) signals emerging simultaneously from medium voltage cables and transformers, and an integrated monitoring system that enables the monitoring of a wider part of the cable feeder. Having described the conventional practices along with the authors’ own experiences and research on non-intrusive solutions, this paper proposes an optimum design of a Rogowski coil that can measure the PD signals from medium voltage cables, its accessories, and the distribution transformers. The proposed PD monitoring scheme is implemented using the directional sensitivity capability of Rogowski coils and a suitable sensor installation scheme that leads to the development of an integrated monitoring model for the components of a MV cable feeder. Furthermore, the paper presents forethought regarding huge amount of PD data from various sensors using a simplified and practical approach. In the perspective of today’s changing grid, the presented idea of integrated monitoring practices provide a concept towards automated condition monitoring.
Article 0 Reads 0 Citations Multiple Partial Discharge Source Localization in Power Cables Through Power Spectral Separation and Time-Domain Reflect... Guillermo Robles, Muhammad Shafiq, Juan Manuel Martinez-Tari... Published: 01 January 2019
IEEE Transactions on Instrumentation and Measurement, doi: 10.1109/tim.2019.2896553
DOI See at publisher website
PROCEEDINGS-ARTICLE 0 Reads 0 Citations Statistical correlation between partial discharge pulses magnitudes measured in the HF and UHF range J. M. Martinez-Tarifa, G. Robles, J. M. Fresno, J. A. Ardila... Published: 01 July 2018
2018 IEEE 2nd International Conference on Dielectrics (ICD), doi: 10.1109/icd.2018.8514603
DOI See at publisher website
PROCEEDINGS-ARTICLE 1 Read 0 Citations Statistical correlation between partial discharge pulses magnitudes measured in the HF and UHF range J. M. Martinez-Tarifa, G. Robles, J. M. Fresno, J. A. Ardila... Published: 01 July 2018
2018 IEEE 2nd International Conference on Dielectrics (ICD), doi: 10.1109/icd.2018.8468369
DOI See at publisher website
Article 6 Reads 1 Citation Radio-Frequency Localization of Multiple Partial Discharges Sources with Two Receivers Guillermo Robles, José Manuel Fresno, Juan Manuel Martínez-T... Published: 03 May 2018
Sensors, doi: 10.3390/s18051410
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
Spatial localization of emitting sources is especially interesting in different fields of application. The focus of an earthquake, the determination of cracks in solid structures, or the position of bones inside a body are some examples of the use of multilateration techniques applied to acoustic and vibratory signals. Radar, GPS and wireless sensors networks location are based on radiofrequency emissions and the techniques are the same as in the case of acoustic emissions. This paper is focused on the determination of the position of sources of partial discharges in electrical insulation for maintenance based on the condition of the electrical equipment. The use of this phenomenon is a mere example of the capabilities of the proposed method but it is very representative because the emission can be electromagnetic in the VHF and UHF ranges or acoustic. This paper presents a method to locate more than one source in space with only two receivers, one of them in a fixed position and the other describing a circumference around the first one. The signals arriving from the different sources to the antennas are first separated using a classification technique based on their spectral components. Then, the individualized time differences of arrival (TDOA) from the sources collected at different angles describe a function, angle versus TDOA, that has all the geometric information needed to locate the source. The paper will show how to derive these functions for any source analytically with the position of the source as unknown parameters. Then, it will be demonstrated that it is possible to fit the curve with experimental measurements of the TDOA to obtain the parameters of the position of each source. Finally, the technique is extended to the localization of the emitter in three dimensions.
Article 4 Reads 3 Citations Partial Discharge Spectral Characterization in HF, VHF and UHF Bands Using Particle Swarm Optimization Guillermo Robles, José Manuel Fresno, Juan Manuel Martínez-T... Published: 01 March 2018
Sensors, doi: 10.3390/s18030746
DOI See at publisher website PubMed View at PubMed ABS Show/hide abstract
The measurement of partial discharge (PD) signals in the radio frequency (RF) range has gained popularity among utilities and specialized monitoring companies in recent years. Unfortunately, in most of the occasions the data are hidden by noise and coupled interferences that hinder their interpretation and renders them useless especially in acquisition systems in the ultra high frequency (UHF) band where the signals of interest are weak. This paper is focused on a method that uses a selective spectral signal characterization to feature each signal, type of partial discharge or interferences/noise, with the power contained in the most representative frequency bands. The technique can be considered as a dimensionality reduction problem where all the energy information contained in the frequency components is condensed in a reduced number of UHF or high frequency (HF) and very high frequency (VHF) bands. In general, dimensionality reduction methods make the interpretation of results a difficult task because the inherent physical nature of the signal is lost in the process. The proposed selective spectral characterization is a preprocessing tool that facilitates further main processing. The starting point is a clustering of signals that could form the core of a PD monitoring system. Therefore, the dimensionality reduction technique should discover the best frequency bands to enhance the affinity between signals in the same cluster and the differences between signals in different clusters. This is done maximizing the minimum Mahalanobis distance between clusters using particle swarm optimization (PSO). The tool is tested with three sets of experimental signals to demonstrate its capabilities in separating noise and PDs with low signal-to-noise ratio and separating different types of partial discharges measured in the UHF and HF/VHF bands.
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