Transient identification in composite conductor circuits using fuzzy neural network

This paper presents a method for transient identification in composite conductor circuits using fuzzy neural networks (FNN), in which a special designed detector is employed to capture transient signals induced by faults and switching operations, which produces training samples for the fuzzy neural network. A digital modeling is conducted on a typical 400 kV composite conductor circuit, and the test results have proven that the FNN is able to identify a fault or a switching operation under various system and fault conditions.