Network Automation Monitoring System for Electric Power Inspection Robots Based on Deep Reinforcement Learning
The automatic monitoring system of electric power inspection robot communication network based on deep reinforcement learning is studied to improve the reliability and timeliness of communication network inspection data transmission.Through the data acquisition module of the system,the historical data and real-time data of the target robot communication network are obtained and stored in the original acquisition database together.The data in the database is processed by the data processing module to reduce redundancy and improve data accuracy.Combined with the vulnerability detection scanner of the automatic monitoring module,the abnormal data is obtained from the processed historical data,stored in the historical anomaly database,and the deep reinforcement learning algorithm of the module is invoked to realize the automatic monitoring of the real-time data of the target communication network with the historical anomaly data as input.The results show that the system has low bit error rate,short transmission delay and good comprehensive performance of data transmission.It can realize anomaly monitoring of historical data and real-time data of target communication network,and the accuracy of monitoring results is higher than 97%,and the monitoring time is short,the timeliness is better,and the comprehensive performance is superior.
deep reinforcement learningpower inspection robotnetwork automation monitoringvulnerability detection
万方数据
维普
