A novel UV-Vis spectroscopy application to measure interfacial tension of transformer oil

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. Due to high sensitivity to various oil parameters and environmental conditions, oil sampling for IFT measurement requires extra precautions. The current technique used to measure IFT of transformer oil is relatively expensive and it takes a long time since the extraction of oil sample, sending it to external laboratory and getting the results back. This paper introduces an alternative 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, and has the potential to be implemented online. Results show that there is a good correlation between oil spectral response and its IFT value. Two artificial intelligence (AI) approaches; artificial neural network (ANN) and fuzzy logic are proposed to model this correlation.

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