Application of Improved BP Algorithm in Fault Diagnosis of Nuclear Power Equipment

The error back propagation（BP） training algorithm for artificial neural networks was improved,by adjusting the coefficient of neuron according to the size of the training error,and an improved genetic algorithm used to improve the structure and weight of the traditional BP neural network simultaneously in this paper,which greatly increased the convergence rate of the training algorithm.The artificial neural network technology and the improved BP network training algorithm were applied to the nuclear power plant fault diagnosis.The fault of the break of the steam generator inverted U-tube in the nuclear power plant was taken as the example,and the fault diagnosis model was established.The simulation results showed that the application of this algorithm is feasible.