dc.contributor.author |
Tsarabaris, PT |
en |
dc.contributor.author |
Karagiannopoulos, CG |
en |
dc.contributor.author |
Bourkas, PD |
en |
dc.contributor.author |
Theodorou, NJ |
en |
dc.date.accessioned |
2014-03-01T01:55:30Z |
|
dc.date.available |
2014-03-01T01:55:30Z |
|
dc.date.issued |
2006 |
en |
dc.identifier.issn |
1472-8915 |
en |
dc.identifier.uri |
https://dspace.lib.ntua.gr/xmlui/handle/123456789/27761 |
|
dc.subject |
high voltage insulators |
en |
dc.subject |
leakage current |
en |
dc.subject |
self-organized neural networks |
en |
dc.subject.classification |
Computer Science, Artificial Intelligence |
en |
dc.subject.classification |
Engineering, Electrical & Electronic |
en |
dc.subject.other |
FLASHOVER |
en |
dc.subject.other |
SURFACES |
en |
dc.subject.other |
DIELECTRICS |
en |
dc.subject.other |
INCEPTION |
en |
dc.subject.other |
FOG |
en |
dc.title |
A classification of the leakage current pulses of high voltage contaminated porcelain insulators using neural network a self-organized neural network |
en |
heal.type |
journalArticle |
en |
heal.language |
English |
en |
heal.publicationDate |
2006 |
en |
heal.abstract |
This paper proposes a classification system for leakage current values on high voltage porcelain insulators, and presents the results, which derived. The proposed system can be divided into two parts: the first part consists of a high sampling rate and high precision measuring system and the second part consists of a self-organized neural network, which is responsible for the classification of the leakage current patterns. The analysis of the results showed that current values, which are measured, could be divided into three categories. The first category consists of low amplitude (less than 3.62 mA) leakage current values, which are located in a rather linear region of the leakage current waveform. Current values of the second and third category have medium (from 3.62 mA to 10.21 mA) and high (greater than 10.21 mA) amplitudes respectively, and belong to a strictly non-linear area of the waveform. Those values constitute short and long width pulses and are attributed to the presence of partial discharges and arcs on the insulator surface. The results of this work are being analyzed and physical interpretations on the above classification are attempted. The system can probably be helpful in the further investigation of the phenomena observed on contaminated industrial insulators as well as an alarm device for heavily polluted insulators, which are in service. |
en |
heal.publisher |
C R L PUBLISHING LTD |
en |
heal.journalName |
ENGINEERING INTELLIGENT SYSTEMS FOR ELECTRICAL ENGINEERING AND COMMUNICATIONS |
en |
dc.identifier.isi |
ISI:000238062000004 |
en |
dc.identifier.volume |
14 |
en |
dc.identifier.issue |
1 |
en |
dc.identifier.spage |
39 |
en |
dc.identifier.epage |
45 |
en |