Evaluating Fault Detection Techniques in Real Electrical Transformers: A Comparative Case of Study
Keywords:
Electrical transformers, Fault detection, Voltage and current monitoring, Diagnostic techniques
Abstract
Transformers are integral to the reliability of electrical networks, necessitating robust diagnostic methods for fault detection. This study conducts a comparative evaluation of three fault detection techniques using real-world data from distribution transformers. The methods analyzed include differential current analysis, correlation-based techniques, and flux linkage increments. Results demonstrate that differential current analysis exhibits the highest sensitivity (93.33\%), detecting faults at 4.41\% of the short-circuit current. Correlation-based methods follow with 86.67\% sensitivity, while flux linkage increments offer lower sensitivity but robust performance at high current levels. This comparative analysis provides actionable insights for enhancing transformer reliability through effective monitoring strategies.
Published
2025-06-12
How to Cite
Guzman-Arteaga , S., Gómez-Arango, S., Sanin-Villa, D., & Buitrago-Villada, M. del P. (2025). Evaluating Fault Detection Techniques in Real Electrical Transformers: A Comparative Case of Study. Statistics, Optimization & Information Computing, 14(1), 352-372. https://doi.org/10.19139/soic-2310-5070-2446
Issue
Section
Research Articles
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