Details
| Original language | English |
|---|---|
| Pages (from-to) | 57-60 |
| Number of pages | 4 |
| Journal | Conference Record of IEEE International Symposium on Electrical Insulation |
| Volume | 1 |
| Publication status | Published - 1996 |
| Event | 1996 IEEE International Symposium on Electrical Insulation. Part 2 (of 2) - Montreal, Can Duration: 16 Jun 1996 → 19 Jun 1996 |
Abstract
In this paper, the application of genetic algorithms for Partial Discharge (PD) recognition on transformers on-site is introduced. First, a short description of genetic algorithms is given. Afterwards, the separation of PD from noise signals as one of the main problems for a sensitive PD-measurement on-site is explained. It is shown, that the use of genetic algorithms for the optimization of neural networks allows a sufficient separation of PD from the pulse shaped noises. Furthermore, the use of genetic algorithms for localizing PD origins in transformers is of great promise, if reference signals are available. Here, the application of genetic algorithms is demonstrated on signals measured at the coil of a distribution transformer in laboratory. The limits of the used methods are shown by superposing synthetically generated noises to the measured pulses.
ASJC Scopus subject areas
- Engineering(all)
- Electrical and Electronic Engineering
- Engineering(all)
- Building and Construction
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In: Conference Record of IEEE International Symposium on Electrical Insulation, Vol. 1, 1996, p. 57-60.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - New approach for partial discharge recognition on transformers on-site by means of genetic algorithms
AU - Wenzel, D.
AU - Borsi, H.
AU - Gockenbach, Ernst
N1 - Copyright: Copyright 2004 Elsevier Science B.V., Amsterdam. All rights reserved.
PY - 1996
Y1 - 1996
N2 - In this paper, the application of genetic algorithms for Partial Discharge (PD) recognition on transformers on-site is introduced. First, a short description of genetic algorithms is given. Afterwards, the separation of PD from noise signals as one of the main problems for a sensitive PD-measurement on-site is explained. It is shown, that the use of genetic algorithms for the optimization of neural networks allows a sufficient separation of PD from the pulse shaped noises. Furthermore, the use of genetic algorithms for localizing PD origins in transformers is of great promise, if reference signals are available. Here, the application of genetic algorithms is demonstrated on signals measured at the coil of a distribution transformer in laboratory. The limits of the used methods are shown by superposing synthetically generated noises to the measured pulses.
AB - In this paper, the application of genetic algorithms for Partial Discharge (PD) recognition on transformers on-site is introduced. First, a short description of genetic algorithms is given. Afterwards, the separation of PD from noise signals as one of the main problems for a sensitive PD-measurement on-site is explained. It is shown, that the use of genetic algorithms for the optimization of neural networks allows a sufficient separation of PD from the pulse shaped noises. Furthermore, the use of genetic algorithms for localizing PD origins in transformers is of great promise, if reference signals are available. Here, the application of genetic algorithms is demonstrated on signals measured at the coil of a distribution transformer in laboratory. The limits of the used methods are shown by superposing synthetically generated noises to the measured pulses.
UR - http://www.scopus.com/inward/record.url?scp=0029697191&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:0029697191
VL - 1
SP - 57
EP - 60
JO - Conference Record of IEEE International Symposium on Electrical Insulation
JF - Conference Record of IEEE International Symposium on Electrical Insulation
SN - 0164-2006
T2 - 1996 IEEE International Symposium on Electrical Insulation. Part 2 (of 2)
Y2 - 16 June 1996 through 19 June 1996
ER -