English
Transformer insulation aging diagnosis is important for all the condition assessment Dissolved gas analysis (DGA) is one of the most useful techniques and tools to detect the incipient faults in large oil filled transformers. Various methods have been developed to interpret DGA results. Among them are the Key Gas, Rogers Ratio, Logarithmic Nomo graph, Dorenenburg, IEC Ratio and Duval Triangle. This paper uses the DGA data from different cases to test the accuracy and consistency of these methods in interpreting the transformer condition. It also describes the structure and specific features of transformer insulation ageing diagnosis based on artificial neural networks. MATLAB programs using neural network were developed to automate. Also this paper present three fault type, partial discharges (PD), discharges, thermal faults.
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Transformer · Insulation Aging · DGA · Interpretation Methods · Artificial Neural Network (ANN) · Fault Gases