Radial deformation detection and localization in transformer windings: A terminal measured impedance approach

Radial deformations (RD) in transformer windings pose a significant threat to their reliability, potentially leading to increased losses, reduced lifespan, and catastrophic failures. Existing methods for detecting and localizing RD often rely on complex techniques such as model fitting, circuit synthesis, and individual disc access, limiting their practicality and generalizability. This paper introduces a novel, non-invasive approach for diagnosing RD faults in transformer windings using terminal impedance measurements. By analysing the winding’s frequency response and directly calculating ladder network model parameters from these measurements, the proposed method effectively detects and assesses the severity of RD faults based on capacitance changes. A robust eigenvalue-based technique is developed to accurately pinpoint the fault location within the winding. The proposed method is rigorously validated through circuit and Finite Element Method simulations, as well as experimental studies on a high-voltage transformer, demonstrating high accuracy in diagnosing RD faults across various scenarios, including single- and multiple-disc displacements, non-uniform winding configurations, and varying severities of buckling. This work provides a valuable tool for condition monitoring and predictive maintenance of power transformers, enabling early fault detection and mitigation to enhance operational reliability. • A novel algorithm locates radial deformations in windings using terminal data only. • No need for disc terminal access, circuit synthesis, training data, or model fitting. • Avoids large datasets and complex computations common in AI-based methods. • Validated for fault severity and disc-level localization in diverse fault scenarios.