A transformer plays a key role in electric power distribution system; therefore, when the transformer fails, several electrical components may get affected. As a result, diagnosing the deterioration of transformers is important for the management of electric power distribution system. The furfural content in the insulating oil of a transformer is widely used as an indicator of deterioration because furfural is generated by the decomposition of insulating paper. However, analyzing the furfural content is time consuming because of the requirement of a professional and the complexity of the diagnosis process. In this study, we propose a novel method for analyzing the amount of furfural in the insulating oil based on near-infrared spectroscopic data obtained using the developed portable spectrometer, which can be used for the on-site analysis at transformer installation sites. We selected wavenumbers with high correlation coefficients between the furfural content of oil and the spectroscopic data and estimated the furfural content by partial least squares regression. The results suggest that the furfural content can be analyzed in a few minutes using a small amount of oil through a portable diagnostic device.
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