Research on Human Error Analysis in the Simulated Main Control Room of Nuclear Power Plant Based on EEG Brain Network

Abstract

With the digital development of the control system in the main control room of nuclear power plant (NPP), the reliability of the objective conditions is continuously improved, and the proportion of mistakes caused by the operators themselves increases, which poses a risk to the safe operation of the nuclear power plant. Therefore, it is especially important to analyze the reasons caused by human factors. In this paper, the digital operation interface of the main control room of the nuclear power plant is simulated, 15 subjects are selected to complete the monitoring and judgment process of the digital interface, and the EEG data are collected simultaneously. The cross-correlation analysis method is used to construct the brain network of the EEG data, and the network parameters are analyzed. The results show that the mental load of the subjects may be overloaded when they meet the case of system accidents, which has an impact on subsequent operations. When judging the parameter stimulus, the brain resources occupied are more, and the number of mistakes increases. These results can provide the references for the training of operators in NNP main control room, and are hopeful for the improvement of the digital interface of the NNP's main control room.