Ensuring transformer health and accurate fault diagnosis is pivotal for the reliable operation of power system network. Traditional incipient fault diagnostic methods, including DP-1, DP-2, DT-1, DT-4, and IEC, have been employed extensively, but with varied levels of accuracy for different fault categories. In this research, authors introduce a four-gas diagnostic method, an innovative graphical approach that emphasizes analyzing only four gases, with satisfactory diagnostic accuracy while ensuring lower computational burden and higher interpretability. By adopting a set of two equations for graphically determining fault category, the method offers an intuitive understanding of incipient faults in an oil-filled transformer. For this study, a total of 963 different transformer DGA data were utilized. A study was undertaken using the IEC TC 10 database results to assess the effectiveness of the proposed diagnostic method across diverse fault categories. The proposed 4GM method achieved an execution time of 1.46 s, demonstrating better performance in detecting discharge and high thermal faults, while its efficacy in identifying low thermal faults was slightly depleted. The proposed 4GM method stands out as it achieves a balance between accuracy and execution time. This research not only offers insights into the strengths and innovations of the 4GM method but also sets the stage for future advancements in transformer diagnostic techniques.
