The Fault Diagnosis of a Transformer Using Neural Network and Transfer Function

A transformer is one of the most important elements in the power network. Transformer faults could cause costly repairs and be dangerous to personnel. To avoid this, its reliable operation has great significance and, therefore, the diagnosis system of the transformer is necessitated. The dissolved gas-in-oil analysis (DGA) is the worldwide popular method of detecting faults such as a hot spot or partial discharges inside the transformer. DGA, however, is not a reliable technique to identify aging phenomena and mechanical faults including insulation failure, inter-turn short, etc. To overcome the drawbacks of DGA, the transfer function method is used to identify effectively these kinds of the mechanical faults. The transformer has a unique transfer function independent of the shape of the input waveform, which can be evaluated through sweep test. This transfer function changes by winding ...