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Special Issue “UHF and RF Sensor Technology for Partial Discharge Detection”

Special Issue Information


Dear Colleagues,

Condition monitoring (CM) of high-voltage (HV) insulation systems is essential for establishing a correct diagnosis regarding the health of these costly and safety-critical industrial assets, as well as for implementing practical condition-based-maintenance (CBM) regimes. The assets being monitored may include rotating machines, power transformers, HV cables and accessories, air-insulated-substations (AIS), gas-insulated-switchgear (GIS) and overhead lines. Recent advances have seen widespread development of non-contact electromagnetic wave sensors for detecting and locating partial discharges and electrical arcs. These sensors play an important role in periodic testing, continuous monitoring or ‘fingerprinting’ of RF emissions from HV equipment. Practical applications of UHF and other RF techniques are leading to the development of new sensors and associated solutions for signal acquisition, processing, analysis and interpretation, which in turn require new approaches to decision making about the condition of assets being monitored.

The aim of this Special Issue is to report on recent advances relating to the following themes: (1) non-contact electromagnetic sensors (RF, UHF, near field, electric, magnetic, etc.) used for detecting signals emitted by insulation defects either internally, or external to the equipment in question; (2) practical methods for integrating these sensors into real equipment for use in condition monitoring; (3) case studies and examples of implementation of the techniques in an industrial or laboratory setting; (4) sensor models to support the design process or for predicting their response (using data-driven modeling approaches, for example); and (5) bridging the gap between condition monitoring research and subsequent decision making using these technologies, possibly in combination with other monitoring parameters.

Prof. Dr. Ricardo Albarracín
Prof. Dr. Martin D. Judd
Prof. Dr. Guillermo Robles
Prof. Dr. Pavlos Lazaridis
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs).

A combined algorithm approach for PD location estimation using RF antennas

J. M. Fresno, G. Robles, J. M. Martínez-Tarifa and B. G. Stewart, “A combined algorithm approach for PD location estimation using RF antennas,” 2017 IEEE Electrical Insulation Conference (EIC), Baltimore, MD, USA, 2017, pp. 384-387.
doi: 10.1109/EIC.2017.8004695

Abstract— To locate the positions of partial discharge sources in free space at least four RF antennas are arranged in a suitable
spatial geometry to detect the radiated electromagnet energy from the discharge. The time-difference-of-arrival (TDOA) between the signals from each antenna are then used within multi-lateration equations to determine the position of the source. The iterative Hyperbolic Least Squares (HLS) method and the non-iterative Maximum Likelihood Estimator (MLE) method are two common techniques used in the literature to solve the multi-lateration equations. This paper investigates the ability of combining MLE and HLS to improve location accuracy and maintain fast location computation time. To this end HLS, MLE and the combined MLEHLS method are evaluated in terms of location accuracy and computation performance for three spatial antenna configurations, namely Square, Pyramidal and Trapezoidal arrangements. The location accuracies for each method are evaluated for theoretical TDOA values and also for the case when a finite sampling rate of 10G samples-per-second is considered; the latter is implemented through appropriate rounding up of TDOA values by one sample time. It is shown that MLE-HLS produces improved location accuracy compared with HLS and MLE for both theoretical and finite sampled TDOA values. In addition, it is shown that MLE-HLS improves significantly the computation time over the iterative HLS method.

Keywords— Antenna theory; Mathematical model; Maximum likelihood estimation; Partial discharges; Position measurement; location algorithms; partial discharges; radio-frequency localization