Wavelet and mathematical morphology as the denoising methods for PD analysis of high voltage transformer windings

N. H. Nik Ali, Muhamad Safwan Abd. Rahman, J. A. Hunter, P. L. Lewin, P. Rapisarda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

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 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 ofperformance of the techniques in terms of noise reduction for this type of application.

Original languageEnglish
Title of host publication33rd Electrical Insulation Conference, EIC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages214-217
Number of pages4
ISBN (Electronic)9781479973521
DOIs
Publication statusPublished - 01 Jan 2014
Event33rd Electrical Insulation Conference, EIC 2015 - Seattle, United States
Duration: 07 Jun 201510 Jun 2015

Publication series

Name33rd Electrical Insulation Conference, EIC 2015

Other

Other33rd Electrical Insulation Conference, EIC 2015
CountryUnited States
CitySeattle
Period07/06/1510/06/15

All Science Journal Classification (ASJC) codes

  • Polymers and Plastics
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Wavelet and mathematical morphology as the denoising methods for PD analysis of high voltage transformer windings'. Together they form a unique fingerprint.

  • Cite this

    Nik Ali, N. H., Abd. Rahman, M. S., Hunter, J. A., Lewin, P. L., & Rapisarda, P. (2014). Wavelet and mathematical morphology as the denoising methods for PD analysis of high voltage transformer windings. In 33rd Electrical Insulation Conference, EIC 2015 (pp. 214-217). [7223494] (33rd Electrical Insulation Conference, EIC 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICACACT.2014.7223494