摘要
A neural network method used to identify the different operating states of transformers has been proposed and established.It is superior to the traditional transformer protective principles and can correctly identify,within half cycle from the fault inception,the internal faults,magnetizing inrush current state,external faults and switching on the internal faults of a no load transformer.In addition,this method has broad availability and high fault tolerant ability.A lot of simulations have demonstrated its superiority.
提出一种用于变压器运行和故障状态识别的神经网络方法．此方法优于传统的变压器保护原理，能正确识别变压器的内部故障、励磁涌流、外部故障及空载合于内部故障等不同状态，具有广泛的实用性和很高的容错能力．大量仿真结果证明了此方法的优越性．
