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Separation of Multiple Partial Discharge Sources Within a High Voltage Transformer Winding using Time Frequency Sparsity Roughness Mapping

Separation of Multiple Partial Discharge Sources Within a High Voltage Transformer Winding using Time Frequency Sparsity Roughness Mapping
Separation of Multiple Partial Discharge Sources Within a High Voltage Transformer Winding using Time Frequency Sparsity Roughness Mapping
Partial discharge (PD) measurements can evaluate integrity of transformers’ condition insulation system. In high voltage (HV) power transformers, the winding system consists of multiple dielectric media all of which can degrade and subsequently exhibit pre-breakdown behavior, the ability to accurately separate between different PD signals generated from different sources is seen as an important function of diagnostic systems. This paper is concerned with the feasibility of locating two types of PD sources; surface and void discharges simultaneously into a HV transformer winding. Based on the fundamental theory using the theory of travelling waves along passive transmission lines, PD produces a signals that will propagate towards both ends of the transformer winding – the bushing and neutral to earth connection point from the source. Thus this paper is based only on measurement data from two wideband radio frequency current transformers (RFCTs) placed at the bushing tap-point to earth and neutral to earth point. After PD pulse extraction and mathematical morphology (MM)decomposition, time frequency sparsity roughness mapping is applied followed by density-based clustering of application with noise (DBSCAN) to separate multiple PD sources and estimate their location.
Multiple partial discharge, transformer winding
225-228
Nik Ali, Nik
91f9aa04-0cd9-4d62-896f-97584753886d
Rapisarda, P
79efc3b0-a7c6-4ca7-a7f8-de5770a4281b
Lewin, P L
78b4fc49-1cb3-4db9-ba90-3ae70c0f639e
Nik Ali, Nik
91f9aa04-0cd9-4d62-896f-97584753886d
Rapisarda, P
79efc3b0-a7c6-4ca7-a7f8-de5770a4281b
Lewin, P L
78b4fc49-1cb3-4db9-ba90-3ae70c0f639e

Nik Ali, Nik, Rapisarda, P and Lewin, P L (2016) Separation of Multiple Partial Discharge Sources Within a High Voltage Transformer Winding using Time Frequency Sparsity Roughness Mapping. CMD 2016 International Conference on Condition Monitoring and Diagnosis 2016, , Xi'an, China. 24 - 27 Sep 2016. pp. 225-228 . (doi:10.1109/CMD.2016.7757802).

Record type: Conference or Workshop Item (Paper)

Abstract

Partial discharge (PD) measurements can evaluate integrity of transformers’ condition insulation system. In high voltage (HV) power transformers, the winding system consists of multiple dielectric media all of which can degrade and subsequently exhibit pre-breakdown behavior, the ability to accurately separate between different PD signals generated from different sources is seen as an important function of diagnostic systems. This paper is concerned with the feasibility of locating two types of PD sources; surface and void discharges simultaneously into a HV transformer winding. Based on the fundamental theory using the theory of travelling waves along passive transmission lines, PD produces a signals that will propagate towards both ends of the transformer winding – the bushing and neutral to earth connection point from the source. Thus this paper is based only on measurement data from two wideband radio frequency current transformers (RFCTs) placed at the bushing tap-point to earth and neutral to earth point. After PD pulse extraction and mathematical morphology (MM)decomposition, time frequency sparsity roughness mapping is applied followed by density-based clustering of application with noise (DBSCAN) to separate multiple PD sources and estimate their location.

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e-pub ahead of print date: 1 December 2016
Published date: 1 December 2016
Venue - Dates: CMD 2016 International Conference on Condition Monitoring and Diagnosis 2016, , Xi'an, China, 2016-09-24 - 2016-09-27
Keywords: Multiple partial discharge, transformer winding
Organisations: EEE

Identifiers

Local EPrints ID: 405049
URI: http://eprints.soton.ac.uk/id/eprint/405049
PURE UUID: 42badeca-3648-4c1f-a33d-f08da622361d

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Date deposited: 23 Jan 2017 15:30
Last modified: 25 Nov 2021 20:03

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Contributors

Author: Nik Nik Ali
Author: P Rapisarda
Author: P L Lewin

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