Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.636800
Title: Evaluation of multilateration algorithms used to locate radiated partial discharge in HV environments
Author: El Mountassir, Othmane
Awarding Body: Glasgow Caledonian University
Current Institution: Glasgow Caledonian University
Date of Award: 2014
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Abstract:
Partial discharges (PD) are electrical discharges which occur when the insulation of equipment under high voltage stress starts to break down. As their presence provides early warning of equipment failure, detection and location of PD is important for monitoring/assessing the state of equipment. This thesis evaluates the performance of time-difference-of-arrival (TDOA) algorithms and algorithms for locating PD sources -in three dimensions. The complex nature of the statistics associated with location results of iterative and non-iterative algorithms is demonstrated for the first time. Evaluation of iterative and non-iterative location algorithms performance was completed through simulating a range of PD positions with different antenna arrangements. Analysis demonstrates that ability to determine PD position, and location accuracy, is influenced by the error bound, number of iterations and initial values for the iterative algorithms, and antenna arrangement for both iterative and non-iterative algorithms. A novel approach for selecting adequate error bounds and iteration number, using results of non-iterative methods, is proposed, thus solving some iterative methods dependencies. Regarding noise influence on location performance, results indicate that, when applied to individual TDOA, iterative algorithms can eliminate positions with high noise levels while non-iterative algorithm outputs are greatly influenced by noise. A normality test can be used to improve and quantify the accuracy of possible PD location by assessing confidence levels. Location results depend on signal-to-noise ratio (SNR) in acquired data when using a specific sampling rate and the TDOA algorithm used. Higher sampling rate for data capture does not always provide more accurate location results.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.636800  DOI: Not available
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