Aviation arc fault diagnosis based on weight direct determined neural network

A diagnosis method for the aviation fault arc is proposed in this paper, which is a multi-input weights direct determination (WDD) network. Characteristics of arc current are used for aviation arc fault detection. Arc fault samples are acquired with the help of a self-made arc generator. Feature vectors are obtained from the current of the samples with the wavelet transforming. After training, the fault diagnosis network is verified with the test samples. The result shows that the method has a better performance for aviation fault arc recognition with a simple algorithm.