Neural network approach to separate aging and moisture from the dielectric response of oil impregnated paper insulation

This paper presents a study of the impact of two important parameters, moisture and aging of the oil/paper dielectric used as insulation in power transformers.The way in which these two parameters influence different parameters of the Frequency Domain Spectroscopy (FDS) measurements, is emphasized.D...

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Bibliographic Details
Published in:IEEE transactions on dielectrics and electrical insulation 2015-08, Vol.22 (4), p.2176-2184
Main Authors: Betie, A., Meghnefi, F., Fofana, I., Yeo, Z., Ezzaidi, H.
Format: Article
Language:English
Subjects:
Aging
dielectric dissipation factor
Dielectric measurement
Dielectrics
FDS
Frequency measurement
Insulation
Moisture
Moisture measurement
neural networks
paper oil insulation
power factor
Power transformer
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Summary:This paper presents a study of the impact of two important parameters, moisture and aging of the oil/paper dielectric used as insulation in power transformers.The way in which these two parameters influence different parameters of the Frequency Domain Spectroscopy (FDS) measurements, is emphasized.Different FDS parameters were measured by varying the moisturecontent and the aging degree of the oil impregnated paper.The use of two types of neural networks for analysis of the results was necessary in order to help discriminating the impact of moisture and aging on the FDS measurements and, in some cases, to estimate the aging duration of the paper impregnated with oil.
ISSN:1070-9878
1558-4135
DOI:10.1109/TDEI.2015.004731