Quantifying Electric and Thermal Transformer Criticalities in Electric Arc Furnaces: A Fuzzy Logic-Based Analysis

Electric arc furnace transformers are integral to steel mill operations, providing the necessary high current magnitudes. Traditional maintenance strategies for these transformers primarily rely on offline diagnostic tests, which compute their health index and estimate the remaining lifespan using mathematical approaches. Given that various factors can introduce stress and lead to transformer degradation, it becomes crucial to have an effective assessment system in place. This research introduces specialized fuzzy models designed to evaluate the critical states of individual components, deliver a comprehensive health index, and project the transformer’s remaining lifespan. Furthermore, a decision-making framework is developed to identify malfunctioning components based on collected data. The incorporation of fuzzy rules and a color-coded health indication system enhances the model’s applicability. This research offers invaluable insights for professionals and researchers dedicated to the maintenance and refurbishment of furnace transformers.