The University of Southampton
University of Southampton Institutional Repository

Wavelet and mathematical morphology as the de-noising methods for PD analysis of high voltage transformer windings

Wavelet and mathematical morphology as the de-noising methods for PD analysis of high voltage transformer windings
Wavelet and mathematical morphology as the de-noising methods for PD analysis of high voltage transformer windings
Partial discharge (PD) analysis is one of the most important techniques to evaluate the condition of the insulation systems within high voltage (HV) transformers. However, in typical field environments, measurements of PD signals can be distorted by noise sources. This greatly reduces the ability to identify PD sources in HV transformer windings. Therefore, denoising methods in PD analysis are very important. In recent years, several noise reduction techniques have been proposed for application in PD analysis. The common types of discharge events that may occur within high voltage transformer windings namely void, surface, corona and floating discharge have been experimentally generated. Each type of discharge was injected into different locations along a HV transformer winding and then measured using two wideband radio frequency current transformers (RFCTs) positioned at each end of the winding. Then, either the Discrete Wavelet Transform (DWT) and or Mathematical Stationary Wavelet Transform (SWT) or Mathematical Morphology (MM) were applied to reduce the noise in the raw captured PD signals. This paper presents the comparison of performance of the techniques in terms of noise reduction for this type of application.
partial discharge, de-noising, transformer windings
978-1-4799-7354-5
214-217
Nik Ali, N.H.
91f9aa04-0cd9-4d62-896f-97584753886d
Abd Rahman, M.S.
8217f865-63cf-4fa4-9f2b-19589bbdb2f0
Hunter, J.A.
dae3e13b-a97e-4e81-a617-20ab6965da3c
Lewin, P.L.
78b4fc49-1cb3-4db9-ba90-3ae70c0f639e
Rapisarda, P.
79efc3b0-a7c6-4ca7-a7f8-de5770a4281b
Nik Ali, N.H.
91f9aa04-0cd9-4d62-896f-97584753886d
Abd Rahman, M.S.
8217f865-63cf-4fa4-9f2b-19589bbdb2f0
Hunter, J.A.
dae3e13b-a97e-4e81-a617-20ab6965da3c
Lewin, P.L.
78b4fc49-1cb3-4db9-ba90-3ae70c0f639e
Rapisarda, P.
79efc3b0-a7c6-4ca7-a7f8-de5770a4281b

Nik Ali, N.H., Abd Rahman, M.S., Hunter, J.A., Lewin, P.L. and Rapisarda, P. (2015) Wavelet and mathematical morphology as the de-noising methods for PD analysis of high voltage transformer windings. 2015 IEEE Electrical Insulation Conference (EIC), Seattle, United States. 07 - 10 Jun 2015. pp. 214-217 .

Record type: Conference or Workshop Item (Paper)

Abstract

Partial discharge (PD) analysis is one of the most important techniques to evaluate the condition of the insulation systems within high voltage (HV) transformers. However, in typical field environments, measurements of PD signals can be distorted by noise sources. This greatly reduces the ability to identify PD sources in HV transformer windings. Therefore, denoising methods in PD analysis are very important. In recent years, several noise reduction techniques have been proposed for application in PD analysis. The common types of discharge events that may occur within high voltage transformer windings namely void, surface, corona and floating discharge have been experimentally generated. Each type of discharge was injected into different locations along a HV transformer winding and then measured using two wideband radio frequency current transformers (RFCTs) positioned at each end of the winding. Then, either the Discrete Wavelet Transform (DWT) and or Mathematical Stationary Wavelet Transform (SWT) or Mathematical Morphology (MM) were applied to reduce the noise in the raw captured PD signals. This paper presents the comparison of performance of the techniques in terms of noise reduction for this type of application.

Text
0538-000028.pdf - Version of Record
Download (263kB)

More information

Published date: 7 June 2015
Venue - Dates: 2015 IEEE Electrical Insulation Conference (EIC), Seattle, United States, 2015-06-07 - 2015-06-10
Keywords: partial discharge, de-noising, transformer windings
Organisations: EEE

Identifiers

Local EPrints ID: 378066
URI: http://eprints.soton.ac.uk/id/eprint/378066
ISBN: 978-1-4799-7354-5
PURE UUID: 07cf64ab-8bd3-4d0e-b335-8806b5375bdd
ORCID for P.L. Lewin: ORCID iD orcid.org/0000-0002-3299-2556

Catalogue record

Date deposited: 15 Jun 2015 17:14
Last modified: 15 Mar 2024 02:43

Export record

Contributors

Author: N.H. Nik Ali
Author: M.S. Abd Rahman
Author: J.A. Hunter
Author: P.L. Lewin ORCID iD
Author: P. Rapisarda

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×