Abstract
In high-voltage (HV) power equipment, degradation of insulation has been main concern for protection of equipment. This is due to occurrence of partial discharges (PD) activity within HV insulating systems which can be initiated from different types of local internal or external defects. Thus, partial discharge (PD) identification and classification are important for diagnostic insulation systems problems in order to ensure maintenance process can be carried out effectively and hence improve reliability and durable operation of HV equipment. In this work, the relation of the observable statistical characteristics from PD data with the characteristic of the defect is an important factor to determine the defect inside insulation system. Ultimately, the statistical parameters obtained from PD data can be used to classify different PD sources occur inside HV insulation system. Thus, the objective of this paper is to produce a unique pattern according to discharge source using statistical method. Several statistical parameters such as mean, variance, standard deviation, skewness and kurtosis have been used and analysed.
| Original language | English |
|---|---|
| Pages (from-to) | 537-543 |
| Number of pages | 7 |
| Journal | Indonesian Journal of Electrical Engineering and Computer Science |
| Volume | 6 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - Jun 2017 |
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All Science Journal Classification (ASJC) codes
- Signal Processing
- Information Systems
- Hardware and Architecture
- Computer Networks and Communications
- Control and Optimization
- Electrical and Electronic Engineering
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Classification of partial discharge sources using statistical approach. / Ren, L. W.; Rahman, M. S.Abd; Ariffin, A. Mohd.
In: Indonesian Journal of Electrical Engineering and Computer Science, Vol. 6, No. 3, 06.2017, p. 537-543.Research output: Contribution to journal › Article
TY - JOUR
T1 - Classification of partial discharge sources using statistical approach
AU - Ren, L. W.
AU - Rahman, M. S.Abd
AU - Ariffin, A. Mohd
PY - 2017/6
Y1 - 2017/6
N2 - In high-voltage (HV) power equipment, degradation of insulation has been main concern for protection of equipment. This is due to occurrence of partial discharges (PD) activity within HV insulating systems which can be initiated from different types of local internal or external defects. Thus, partial discharge (PD) identification and classification are important for diagnostic insulation systems problems in order to ensure maintenance process can be carried out effectively and hence improve reliability and durable operation of HV equipment. In this work, the relation of the observable statistical characteristics from PD data with the characteristic of the defect is an important factor to determine the defect inside insulation system. Ultimately, the statistical parameters obtained from PD data can be used to classify different PD sources occur inside HV insulation system. Thus, the objective of this paper is to produce a unique pattern according to discharge source using statistical method. Several statistical parameters such as mean, variance, standard deviation, skewness and kurtosis have been used and analysed.
AB - In high-voltage (HV) power equipment, degradation of insulation has been main concern for protection of equipment. This is due to occurrence of partial discharges (PD) activity within HV insulating systems which can be initiated from different types of local internal or external defects. Thus, partial discharge (PD) identification and classification are important for diagnostic insulation systems problems in order to ensure maintenance process can be carried out effectively and hence improve reliability and durable operation of HV equipment. In this work, the relation of the observable statistical characteristics from PD data with the characteristic of the defect is an important factor to determine the defect inside insulation system. Ultimately, the statistical parameters obtained from PD data can be used to classify different PD sources occur inside HV insulation system. Thus, the objective of this paper is to produce a unique pattern according to discharge source using statistical method. Several statistical parameters such as mean, variance, standard deviation, skewness and kurtosis have been used and analysed.
UR - http://www.scopus.com/inward/record.url?scp=85020480357&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85020480357&partnerID=8YFLogxK
U2 - 10.11591/ijeecs.v6.i3.pp537-543
DO - 10.11591/ijeecs.v6.i3.pp537-543
M3 - Article
AN - SCOPUS:85020480357
VL - 6
SP - 537
EP - 543
JO - Indonesian Journal of Electrical Engineering and Computer Science
JF - Indonesian Journal of Electrical Engineering and Computer Science
SN - 2502-4752
IS - 3
ER -