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At the Faculty of Chemical Engineering and Technology University of Zagreb on April 5th, 2023, our colleague Vedran Đurina, an employee of the Laboratory for Physical and Chemical Testing at our Laboratory Center, successfully defended the doctoral thesis entitled
“Assessment of physico-chemical properties of insulating oils by molecular spectroscopy techniques with use of chemometric methods and artificial neural networks”.
Abstract
The goal of this thesis was to develop computational models which will predict physico-chemical properties of mineral insulating oils from their molecular spectra with a high level of confidence, and through which information is provided on oil ageing and any chemical impurities present. Along with model development, the relationships between physico-chemical properties of oils were investigated to contribute to a better understanding of information provided by the tests. Analyses of significant spectral regions in molecular spectra were performed, signals which vary with changes in physico-chemical properties were determined, and the responsible chemical species were identified.
Based on the measured physico-chemical oil properties, correlation curves were made between different oil properties. Relationships were investigated between properties that are indicators of the chemical composition of oils, between properties which are indicators of oil ageing, as well as interdependences between properties which describe oil composition and ageing.
The results presented in this thesis imply the possibility of using spectroscopic assessment methods in supplementing the existing laboratory measurement methods, as well as in the development of simple measurement devices which could monitor the physico-chemical properties of insulating oils in the field or during equipment operation.
Scientific Contribution
New knowledge about the influence of oil aging on their spectra enables a better understanding of the changes in parts of the molecular spectra of insulating oils depending on their composition. Correlations of physico-chemical oil properties with data available in their molecular spectra were determined. Computational models have been prepared for predicting the basic physico-chemical properties of insulating oils from molecular spectra, which may be applied for non-destructive oil analysis.
