Fault Diagnosis Method of Power System Based on Neural Network

Abstract

The power system is disturbed by electromagnetic interference and crosstalk between the transmission link layers in the transmission and distribution process, and it is easy to produce transmission distribution fault. In order to improve the efficiency of fault diagnosis, a method of fault diagnosis for power system based on neural network algorithm is proposed. The multi sensor quantization fusion method is used to carry out electricity. The transmission distribution signal in the power transmission link layer is extracted from the power system, and the transmission distribution signal is decomposed and the association rules are excavated. The spectral analysis model is used to extract the spectral characteristics of the transmission information of the power system, and the fault diagnosis and fault type identification are carried out according to the spectrum difference. The power system fault features are classified and identified by neural network learning algorithm to realize the optimal diagnosis of power system fault. The simulation results show that the method is more accurate and more efficient in the fault diagnosis of power system.