Characterizing the FRA curves of transformer tertiary helical windings by deriving transfer functions from FRA data

Interpreting frequency response analysis (FRA) data presents a formidable challenge in transformer fault diagnosis. Previous attempts to derive transfer functions (TF) for characterizing FRA curves have been both desirable and unsuccessful. The collected FRA data aims to represent the mechanical conditions of the transformer windings under examination. Nonetheless, the techniques applied to FRA results for assessing mechanical integrity face inherent uncertainty due to the lack of a direct link between the measured data and the electrical characteristics of an equivalent circuit (EC) consisting of resistance, inductance, and capacitance (RLC) components. As such, a rigorous analysis of the FRA data becomes crucial for a comprehensive assessment and interpretation of the mechanical state of these windings. The proposed investigation into TF is designed to offer a detailed mathematical interpretation of FRA characteristics, potentially enabling the early detection of potential faults through the derived TF and relevant parameters. This research paper revolves around the computation of TFs for power transformer helical windings. Consequently, a strong correlation emerges between the recorded FRA curves and the computed TF curves, affirming the precision of TF estimation and its significant contribution to advance FRA technology.