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 language | English |
|---|---|
| Title of host publication | 33rd Electrical Insulation Conference, EIC 2015 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 214-217 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781479973521 |
| DOIs | |
| Publication status | Published - 01 Jan 2014 |
| Event | 33rd Electrical Insulation Conference, EIC 2015 - Seattle, United States Duration: 07 Jun 2015 → 10 Jun 2015 |
Publication series
| Name | 33rd Electrical Insulation Conference, EIC 2015 |
|---|
Other
| Other | 33rd Electrical Insulation Conference, EIC 2015 |
|---|---|
| Country | United States |
| City | Seattle |
| Period | 07/06/15 → 10/06/15 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Polymers and Plastics
- Electrical and Electronic Engineering
Cite this
}
Wavelet and mathematical morphology as the denoising methods for PD analysis of high voltage transformer windings. / Nik Ali, N. H.; Abd. Rahman, Muhamad Safwan; Hunter, J. A.; Lewin, P. L.; Rapisarda, P.
33rd Electrical Insulation Conference, EIC 2015. Institute of Electrical and Electronics Engineers Inc., 2014. p. 214-217 7223494 (33rd Electrical Insulation Conference, EIC 2015).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Wavelet and mathematical morphology as the denoising methods for PD analysis of high voltage transformer windings
AU - Nik Ali, N. H.
AU - Abd. Rahman, Muhamad Safwan
AU - Hunter, J. A.
AU - Lewin, P. L.
AU - Rapisarda, P.
PY - 2014/1/1
Y1 - 2014/1/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84978390189&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84978390189&partnerID=8YFLogxK
U2 - 10.1109/ICACACT.2014.7223494
DO - 10.1109/ICACACT.2014.7223494
M3 - Conference contribution
AN - SCOPUS:84978390189
T3 - 33rd Electrical Insulation Conference, EIC 2015
SP - 214
EP - 217
BT - 33rd Electrical Insulation Conference, EIC 2015
PB - Institute of Electrical and Electronics Engineers Inc.
ER -