A Comparative Research on Power Transformer Fault Diagnosis Based on Several Artificial Neural Networks
نویسندگان
چکیده
There are some deficiencies in the improved three-ratio method even though it has been widely used in power transformer fault diagnosis. Using artificial neural networks, the power transformer fault diagnosis is improved in this article. With Matlab programming, three different kinds of neural networks, which are Radial Basis Function (RBF) neural network, Learning Vector Quantization (LVQ) neural network and Probabilistic Neural Network (PNN), are studied and compared for the performance in power transformer fault diagnosis. In the models of this study, the research results show that power transformer fault diagnosis based on PNN has the best diagnosis identification ratio and the fastest diagnosis identification rate.
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