State Monitoring and Fault Diagnosis of Power Internet of Things Devices based on Artificial Intelligence

In the context of the development of the power industry towards digitalization and intelligence, it is of great importance to monitor the status and diagnose faults of equipment in the power Internet of Things (PIoT). This article intends to combine the theory and methods of Artificial Intelligence (AI), and use real-time data analysis and deep learning methods to conduct online monitoring and early fault diagnosis of various devices in the PIoT. In the monitoring of the status of PIoT devices, the monitoring time is 7 days, and the error rate is not higher than 1.25%. Only the first day has the highest error rate, and the fifth day has an error rate of 0.37%. This article significantly improves the fault diagnosis accuracy of PIoT equipment by applying and optimizing new artificial intelligence algorithms, laying a theoretical and technical foundation for its further research and application.