Title :
A new technique to measure interfacial tension of transformer oil using UV-Vis spectroscopy
Author :
Abu Baka, Norazhar ; Abu-Siada, A. ; Islam, S. ; El-Naggar, M.F.
Author_Institution :
Curtin Univ., Perth, WA, Australia
Abstract :
Interfacial tension (IFT) and acid numbers of insulating oil are correlated with the number of years that a transformer has been in service and are used as a signal for transformer oil reclamation. Oil sampling for IFT measurement calls for extra precautions due to its high sensitivity to various oil parameters and environmental conditions. The current used technique to measure IFT of transformer oil is relatively expensive, requires an expert to conduct the test and it takes long time since the extraction of oil sample, sending it to external laboratory and getting the results back. This paper introduces a new technique to estimate the IFT of transformer oil using ultraviolet-to-visible (UV-Vis) spectroscopy. UV-Vis spectral response of transformer oil can be measured instantly with relatively cheap equipment, does not need an expert person to conduct the test and has the potential to be implemented online. Results show that there is a good correlation between oil spectral response and its IFT value. Artificial neural network (ANN) approach is proposed to model this correlation.
Keywords :
neural nets; power engineering computing; surface tension; transformer oil; ultraviolet spectroscopy; visible spectroscopy; ANN approach; IFT; UV-Vis spectral response; UV-Vis spectroscopy; artificial neural network; insulating oil sampling; transformer insulation oil interfacial tension measure; ultraviolet-to-visible spectroscopy; Artificial neural networks; Correlation; Mathematical model; Oil insulation; Power transformer insulation; Spectroscopy; Artificial neural network; Interfacial tension; Transformer insulation oil; UV-Vis spectroscopy;
Journal_Title :
Dielectrics and Electrical Insulation, IEEE Transactions on
DOI :
10.1109/TDEI.2015.7076831