基于小波变换和人工神经网络的保护模型

采用一种结合小波变换和神经网络原理的模型，来识别电力系统短路故障．用小波变换提取测量信号的特征量，作为多层前向神经网络的输入．对不同的输出要求，采用不同的神经网络，判断出发生故障的相别、性质和位置．实验结果表明，该模型是有效、可行的．

Study for Protection Model Based onWavelet Transformation and Artificial Neural Network

A new model which combines wavelet transformation and artificial neural network to identify the fault in power systems,is proposed.The measured signal is transformed by wavelet and the features of the signal are extracted. Then these features are used as input to a three layer forward neural network. Different neural networks are employed for different output. So the fault property and location can be identified. The experimental results show that this approach is efficient for fault identification.