Localization of turn-to-turn fault in transformers using Artificial Neural Networks and winding transfer function

To automate the procedure of localizing turn-to-turn faults in transformers windings, a method is proposed by employing of Artificial Neural Networks (ANN). For this purpose, a specially made distribution transformer winding is used as a test object to approve the capability of proposed method. This winding is appropriately designed to perform short circuit faults between any two desired adjacent turns. Then the frequency response of winding in both healthy and faulty conditions is measured using the Low Voltage Impulse (LVI) test. Extracted features from frequency responses are used to train and test the proposed ANN. The results show that this method is able to determine the location of turn-to-turn fault in winding.