Automatic Analysis System for Monitoring and Diagnosing the Condition of Transformer Insulating Oils

Mineral insulating oil degrades over time due to oxidation, accelerated by metallic compounds, oxygen, water, and heat. This degradation leads to color changes, acidic compound formation, and, in advanced stages, sludge precipitation. Monitoring these changes requires periodic chemical, physical-chemical, and chromatographic analyses, which can be time-consuming and costly. This work presents a pilot unit that simulates transformer conditions and enables real-time, automated measurement of oil color, dissolved oxygen, conductivity, and pH, allowing for reliable degradation diagnostics. The results indicated an upward trend in analyzed parameters, showing that degradation begins quickly. The obtained values provided a more precise diagnosis of oil condition. The statistical correlations further justify the findings, demonstrating the effectiveness of automated monitoring. Implementing this automation can significantly reduce equipment downtime and unnecessary laboratory analyses, with chemical tests serving as confirmation.