A combined algorithm approach for PD location estimation using RF antennas

Fresno, José Manuel; Robles, Guillermo Cortés; Martínez-Tarifa, Juan Manuel; Stewart, Brian G.

doi:10.1109/eic.2017.8004695

Cited by 7 publications

(3 citation statements)

References 10 publications

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“…A combined algorithm based on the MLE algorithm outlined in Section 2.2.3 and the HLS algorithm outlined in Section 2.1.2 was previously proposed in [ 28 ]. The MLE algorithm reports two feasible solutions, with one of them closer to the actual source position than the other.…”

Section: Localization Techniquesmentioning

confidence: 99%

Survey on the Performance of Source Localization Algorithms

Fresno

Robles

Martínez-Tarifa

et al. 2017

Sensors

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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.

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Section: Localization Techniquesmentioning

confidence: 99%

Survey on the Performance of Source Localization Algorithms

Fresno

Robles

Martínez-Tarifa

et al. 2017

Sensors

Self Cite

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“…The location approximation of PDs is achievable by antenna measurements and proper signal processing [7], [8]. The most important part of this processing is the noise filtering of the measured signals [9]- [11], because it directly affects the positioning accuracy of the measuring system.…”

Section: Introductionmentioning

confidence: 99%

Developing a Filtering Algorithm for Partial Discharge Location Approximation Using the Emitted Electromagnetic Signals of Corona Discharges

Szirtes

Cselko

Ibáñez

2021

IEEE Trans. on Ind. Applicat.

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The aim of this article is to create a novel filtering algorithm for the emitted electromagnetic signals of corona discharges, using the special time-domain features of the continuous wavelet transform. The first part of this article therefore focuses on the time-domain examination of these signals to find characteristic features that are compatible with the wavelet transform. The second part of this article utilizes these features to create and validate the filtering algorithm. This is an important step toward creating an accurate three-dimensional partial discharge location approximation system that could contribute to preventing and finding partial-discharge-related faults. In the presented research, needle-plane corona discharge sources with different geometries are tested at both ac and dc voltages.

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“…Therefore, in this study, the feasibility of PD DOA in AISs was investigated using a UHF wireless sensor array and RSSI values. A statistical approach based on the RSSI and maximum likelihood estimator (MLE) [20][21][22] is proposed. The basic idea is that the RSSI values are collected by the UHF sensor array, and the location of the PD source is estimated by the power pattern of the designed UHF sensor array and MLE.…”

Section: Introductionmentioning

confidence: 99%

Partial discharge direction‐of‐arrival estimation in air‐insulated substation by UHF wireless array and RSSI maximum likelihood estimator

Han

Luo

Sheng

et al. 2020

IET Generation, Transmission & Distribution

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The quick detection and localization of partial discharge (PD) in an air-insulated substation (AIS) based on ultrahigh-frequency (UHF) sensor arrays are efficient for power equipment monitoring. The adopted UHF PD time difference of arrival (TDOA) methods mainly use the time difference of electromagnetic wave signals. Thus, the system requires both a high sampling rate and time synchronization accuracy, leading to a high cost and large size. In this study, the feasibility and accuracy of PD DOA in an AIS were investigated using a UHF wireless sensor array and the received signal strength indicator. First, the power pattern of the designed UHF wireless sensor array was obtained via an offline experiment. Then, a statistical approach to the PD DOA method based on the maximum likelihood estimator was employed to obtain the preliminary DOA result. Finally, interpolation and clustering algorithms were used to improve the accuracy of the DOA. A laboratory test was conducted. The average error of the PD DOA was less than 6°, and the cost-effectiveness and portability were clearly improved.

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A combined algorithm approach for PD location estimation using RF antennas

Cited by 7 publications

References 10 publications

Survey on the Performance of Source Localization Algorithms

Survey on the Performance of Source Localization Algorithms

Developing a Filtering Algorithm for Partial Discharge Location Approximation Using the Emitted Electromagnetic Signals of Corona Discharges

Partial discharge direction‐of‐arrival estimation in air‐insulated substation by UHF wireless array and RSSI maximum likelihood estimator

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