The transformer is the most essential component in electrical power transmission. Once a transformer is installed, it is generally used for decades. When failure occurs in a transformer, serious problems can arise, and numerous electrical components that depend on the transformer may be affected. Thus, deterioration diagnosis of transformers is important. The furfural content in the insulating oil of a transformer is widely used as an indicator of transformer deterioration, as furfural is generated by decomposition of the insulating paper. Although the degree of transformer deterioration can be estimated by measuring the furfural content, this measurement is time-consuming. This paper proposes a novel method for estimating the amount of furfural contained in insulating oil within a short time. The method is realized by combining spectroscopic analysis in the visible region with a pattern recognition technique. The effectiveness of the proposed method is verified through a series of experiments.
This study proposes a novel method for estimation of the acid value and the furfural contained in the insulating oil of an oil-filled transformer based on the information received from the color of the insulating oil. A spectrometer analysis is carried out on insulating oils. The color data, represented as L*, a*, and b*, are measured, and it is found that these values change on a certain trajectory in accordance with the degradation of the insulating oil. Subsequently, a method for the estimation of acid value and the furfural is proposed based on the trajectory. Finally, the effectiveness of the proposed method is verified through experimental procedures.
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