Research of integrating prior knowledge into abnormal behavior recognition model of EV charging station

In recent years, the number of EV (Electric Vehicle) charging stations has surged, the safety literacy of charging personnel is uneven. However, the number of station O&M personnel is limited, which seriously affects the safe and efficient operation of EV charging stations. The AI algorithms can be used to detect the abnormal behavior happening in the station and alarm to intervene in time. Existing AI algorithms face the challenge of small sample size and many types of abnormal behaviors during the training process, which leads to poor generalization of the neural network model and large detection error. This study attempts to integrate prior knowledge into the abnormal behavior recognition model based on neural network, so as to improve the accuracy of the algorithm. The field data verification shows that the performance of the proposed algorithm is improved compared with the traditional algorithm, and the problem of small samples and low accuracy of abnormal behavior detection is effectively overcome.