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Driving innovations in manufacturing: Open Access research from DMEM

Strathprints makes available Open Access scholarly outputs by Strathclyde's Department of Design, Manufacture & Engineering Management (DMEM).

Centred on the vision of 'Delivering Total Engineering', DMEM is a centre for excellence in the processes, systems and technologies needed to support and enable engineering from concept to remanufacture. From user-centred design to sustainable design, from manufacturing operations to remanufacturing, from advanced materials research to systems engineering.

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A combined algorithm approach for PD location estimation using RF antennas

Fresno, José Manuel and Robles, Guillermo and Martinez-Tarifa, Juan Martínez and Stewart, Brian G. (2017) A combined algorithm approach for PD location estimation using RF antennas. In: 2017 IEEE Electrical Insulation Conference (EIC). IEEE, Piscataway, NJ. ISBN 9781509039654

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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.