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JOSÉ MANUEL FRESNO published an article in May 2018.
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Guillermo Robles

63 shared publications

Department of Electrical Engineering, Universidad Carlos III de Madrid, Leganés, Spain

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Article 6 Reads 0 Citations 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 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 3 Reads 2 Citations Partial Discharge Spectral Characterization in HF, VHF and UHF Bands Using Particle Swarm Optimization Guillermo Robles, José Fresno, Juan Martinez-Tarifa, Jorge A... Published: 01 March 2018
Sensors, doi: 10.3390/s18030746
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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.
Article 3 Reads 7 Citations Survey on the Performance of Source Localization Algorithms Guillermo Robles, Juan Manuel Martínez-Tarifa, Brian G. Stew... Published: 18 November 2017
Sensors, doi: 10.3390/s17112666
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The localization of emitters using an array of sensors or antennas is a prevalent issue approached in several applications. There exist different techniques for source localization, which can be classified into multilateration, received signal strength (RSS) and proximity methods. The performance of multilateration techniques relies on measured time variables: the time of flight (ToF) of the emission from the emitter to the sensor, the time differences of arrival (TDoA) of the emission between sensors and the pseudo-time of flight (pToF) of the emission to the sensors. The multilateration algorithms presented and compared in this paper can be classified as iterative and non-iterative methods. Both standard least squares (SLS) and hyperbolic least squares (HLS) are iterative and based on the Newton–Raphson technique to solve the non-linear equation system. The metaheuristic technique particle swarm optimization (PSO) used for source localisation is also studied. This optimization technique estimates the source position as the optimum of an objective function based on HLS and is also iterative in nature. Three non-iterative algorithms, namely the hyperbolic positioning algorithms (HPA), the maximum likelihood estimator (MLE) and Bancroft algorithm, are also presented. A non-iterative combined algorithm, MLE-HLS, based on MLE and HLS, is further proposed in this paper. The performance of all algorithms is analysed and compared in terms of accuracy in the localization of the position of the emitter and in terms of computational time. The analysis is also undertaken with three different sensor layouts since the positions of the sensors affect the localization; several source positions are also evaluated to make the comparison more robust. The analysis is carried out using theoretical time differences, as well as including errors due to the effect of digital sampling of the time variables. It is shown that the most balanced algorithm, yielding better results than the other algorithms in terms of accuracy and short computational time, is the combined MLE-HLS algorithm.
CONFERENCE-ARTICLE 21 Reads 1 Citation Planar localization of radio-frequency or acoustic sources with two receivers José Manuel Fresno, Guillermo Robles, Juan Manuel Martínez-T... Published: 14 November 2017
Proceedings, doi: 10.3390/ecsa-4-04892
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In the localization of electromagnetic or acoustic emitters, generally, when a pulse is radiated from a source, the wave will arrive to two receivers at different times. One of the advantages of measuring these time differences of arrival or TDOA is that it is not required a common clock as in other localization techniques based on the time of arrival of the pulse to the receiver. With only two sensors, all the possible points in the plane that would give the same TDOA describe a hyperbola. Using an independent third receiver and calculating the intersection of the three hyperbolas will give the position of the source. Therefore, planar localization of emitters using multilateration techniques can be solved at least with three receivers. This paper presents a method to locate sources in a plane with only two receivers reducing the number of acquisition channels and hence, the cost of the equipment. One of the receivers is in a fixed position and the other describes a circumference around the first one. The TDOA are measured at different angles completing a total turn and obtaining a periodic function, angle versus TDOA, that has all the geometric information needed to locate the source. The paper will show how to derive this function analytically with the distance from the fixed receiver to the source and a bearing angle as parameters. Then, it will be demonstrated that it is possible to fit the curve with experimental measurements to obtain the parameters of the position of the source.

PROCEEDINGS-ARTICLE 5 Reads 0 Citations A combined algorithm approach for PD location estimation using RF antennas Jose Manuel Fresno, Guillermo Robles, Juan Manuel Martinez-T... Published: 01 June 2017
2017 IEEE Electrical Insulation Conference (EIC), doi: 10.1109/eic.2017.8004695
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Conference 4 Reads 0 Citations A survey of time-of-flight algorithms to determine bone positions in movement Jose Manuel Fresno, Romano Giannetti, Guillermo Robles Published: 01 May 2017
2017 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), doi: 10.1109/i2mtc.2017.7969710
DOI See at publisher website