conference paper
Monitoring transformer oil through dissolved gas analysis is critical for detecting faults early and maintaining the safety of electrical grids. This research evaluates defect diagnostic techniques, specifically comparing the Duval Triangle and Gouda Triangle methods, across 287 oil samples drawn from international standards and laboratory datasets. Across individual evaluations, the Gouda Triangle method reached 88.89 percent accuracy on international benchmark data, outperforming the Duval Triangle method, while the two approaches showed varying specificity and predictive value on laboratory samples. To overcome variations linked to data sources, a combined triangle method was developed. By merging the strengths of both approaches, the combined method raised diagnostic accuracy to 93.16 percent on the international dataset and 88.24 percent on the local laboratory data, offering a more dependable and adaptable diagnostic tool.
Power transformers are critical components of electrical grids, and unexpected breakdowns can cause severe power disruptions. By improving the interpretation of dissolved gas data, diagnostic tools can catch internal faults sooner and more reliably. Better diagnostic accuracy reduces the risk of catastrophic failures, helps operators avoid costly emergency repairs, and supports the continuous delivery of electricity.
This methodology could be incorporated into diagnostic software used by electrical utility operators, maintenance service providers, and transformer testing laboratories. Because the combined method was applied and tested across 287 actual samples from international and laboratory datasets, it demonstrates functional software readiness, though the abstract does not indicate whether it has been integrated into commercial monitoring platforms.
AI-generated from the published abstract. Always read the original work before citing.
Early identification of power transformer disorders is essential to guarantee the safety and continuous functioning of electrical systems. The technique of Dissolved Gas Analysis (DGA) is highly useful in diagnosing problems in oil-filled transformers. In these transformers, the oil functions as both a cooling and insulating medium, effectively reflecting internal stresses. This study presents a comprehensive evaluation of the various defect diagnostic algorithms belonging to either Duval or Gouda Triangle approaches set across different datasets. The samples that were examined were a total of 287, representing 117 samples from IEC TC 10 data, and 170 other samples that derived from Egyptian scientific laboratories. In the IEC TC 10 data set, the Gouda Triangle method (88.89% accuracy) outperformed the Duval Triangle method (85.47%). On the other hand, for Egyptian data, specificity was 76.47% and PPV could be obtained using the Gouda Triangle method and respectively were 65.88% and 94.44% with Duval Triangle method; while in either of these methods. Notably, the use of the Combined Triangle methods, which combine the advantages of both the Duval and Gouda Triangle approaches, led to remarkable improvements in performance, with accuracies of 93.16% for Data 1 and 88.24% for Data 2. This novel methodology provides a more resilient and flexible diagnostic instrument, yielding consistent and dependable outcomes across diverse data sources.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.1109/icateee68170.2025.11406463
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
