Research on Real-Time Monitoring Technology of Power Protection System Based on AI

In order to improve the intelligence level of power protection systems, this paper proposes a real-time monitoring method based on artificial intelligence. The improved 1D-CNN model is used to identify the state of the power system, and a fault handling strategy is generated by combining knowledge graph and graph neural network. Data fusion and visualization are achieved through multi view autoencoder. The experimental results show that this method outperforms traditional methods in terms of fault recognition accuracy, positioning error, action time, and strategy generation time, demonstrating its potential application in the field of power protection.