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Sep 2026
Transformer fault diagnosis based on Fisher criterion and BKA-optimized KELM
To improve the quality of extracting characteristic parameters of dissolved gases in transformer oil and the accuracy of fault diagnosis, this paper proposes a new method for transformer fault diagnosis based on the Fisher criterion and the Black-winged Kite Algorithm (BKA) to optimize the Kernel Extreme Learning Machi...
Bo Yang, Ying Li, Yu-Peng Li
· European Conference on Elect... · 0 citations
Open access
Sep 2026
Transformer fault diagnosis using dissolved gas analysis: a hybrid ensemble model with data preprocessing
Failures and guaranteed dependability of the electrical grid, early fault diagnosis in power transformers is essential. By examining gas ratios suggestive of faults, dissolved gas analysis (DGA) continues to be a vital component for transformer health monitoring. Using four preprocessing techniques raw data, min-max no...
F. Z. Boudjella, Souhila Boudjella, Nasiru Yahaya Ahmed et al.
· International Journal of Pow... · 0 citations
Open access
Aug 2026
A Machine Learning Framework for Improved Fault Diagnosis in Service Transformers Using Dissolved Gas Analysis
This article explores machine learning techniques (MLTs) as a modern alternative to enhance the interpretation of DGA data for early-stage fault detection in service transformers, and demonstrates that random forest and gradient boosting outperform others, achieving up to 98% accuracy.
Rupali Balabantaraya, A. Chatterjee, A. Sahoo et al.
· Electrica · 0 citations
Open access
Sep 2026
Transformer Fault Diagnosis Method Based on Multidimensional Feature Fusion and Self-Adaptive Synthetic Over-Sampling Using a Least Squares Support Vector Machine Optimized by Experience Exchange Strategy
As critical equipment in power systems, the reliable operation of power transformers is directly linked to the overall safety of the power grid. Traditional fault diagnosis methods based on dissolved gas analysis generally rely on a single gas feature, which inevitably causes misjudgment and suffers from inadequate acc...
Shuang Wang, Yuen Wen, Jun-Wei Yao et al.
· Energies · 0 citations
Open access
2026
INDMM: Intelligent Numerical Duval Modification Model for Identifying Transformer Fault
Oil-paper insulation is considered the most popular method for insulating the windings within power transformers because of its ability to withstand high electrical and thermal stress. During the life time of power transformers, oil-paper insulation is aged, and hydrocarbon gases are released. Dissolved gas analysis (D...
R. El-Aal, D. Mansour, A. Hassan et al.
· Jordan journal of electrical... · 0 citations
Open access
2026
Hybrid Dempster–Shafer and Random Forest Machine Learning Approach for Fault Diagnosis and Condition Assessment of Power Transformers
Dissolved gas analysis is a widely used tool for the early detection of faults in power transformers. However, conventional interpretation methods, such as Rogers, Doernenburg, Key Gas method, and the Duval graphical methods, may yield different diagnoses for the same sample because of their distinct criteria, gas rati...
Helen J. Alarcon Carizales, A. R. Romero-Quete, S. Rivera-Rodríguez
· IEEE Access · 0 citations