Diagnosis of leakage degree of steam generator tube based on time series neural network

Aiming at the leakage of the steam generator U-shaped tube, a method based on time series neural network is proposed to diagnoze the leakage degree of steam generator tube. Firstly, the leakage mechanism of the steam generator U-shaped tube of the nuclear power plant is analyzed, its mathematical model is constructed, the direct characteristic parameters of leakage are extracted, and then the indirect characteristic parameters are extracted according to Fisher score method. Secondly, data samples are generated from the pretreated time series data by sliding time window method, which is used as the input of time series neural network. Based on Back propagation (BP) algorithm, the five-layer neural network system is trained to get the time series neural network model of the leakage of steam generator U-shaped tube. Finally, the time series test data of the leakage of steam generator U-shaped tube during nuclear power operation are simulated. The simulation shows that the time series neural network is with better effectiveness and generalization ability in dealing with evolutionary events, which is of a reference value for fault diagnosis research. (authors)