Transformer fault diagnosis based on euclidean clustering and support vector machines

A new method based on Euclidean clustering and Support Vector Machines is presented and constructed in the paper. According to the Euclidean distances between the transformer’s state sorts, build the multi-classification model of Support Vector Machines. The diagnosing experiments of different transformer testing scenarios show this method can avoid the blindness when building the multi-classifier, and can be used on transformer faults diagnosis commendably.