抄録
This paper presents a fault identification system with the help of neural networks for underground cable transmission systems (UCTS), In order to get the data for transient phenomena in transmission systems we used the package EMTP which models the transient phenomena which is necessary information for fault type identification purpose. Data for various fault types for underground cable system were created and were used for training back-propagation neural networks. For operation of the proposed system a new data is used for testing for fair assessment of the designed system. Normalization of input data is adopted to expect more reliable learning in neural networks. A proper size of the neural network was found via trial and error method, a brute-force method. The system was tested with various fault distances and fault incidence angles and proved its reliability for various situations
