Abstract: In view of the sensor fault of nuclear power plant, the sensor was trained by adopting improved back propagation (BP) neural network method, and the dynamic model bank in different states was set up. The system was detected by using BP neural network in real time. When the sensor goes wrong, it will be controlled by reconstruction. Taking pressurizer as the case, a simulation experiment was performed on the nuclear power plant simulator. The results show that the proposed method is valid for the fault tolerant control of sensor faults in nuclear power plant.