Research on UAV Discharge Detection Technology of Transmission Line Based on the Concept of General Inductance Calculation

This project intends to study a cluster scheduling method of UAV based on connection-sensor-computing collaboration. First, the historical location and service requirements of search and rescue objects are obtained from the sensing equipment. The real-time location of search and rescue targets and the real-time forecast of service requirements are realized through the short-time storage network. According to the prior knowledge obtained, the positioning and energy allocation are optimized, and the efficiency evaluation is based on the benefit of the communication rate of search-and-rescue personnel to reduce the bandwidth cost. Through online monitoring of the operating status of the UAV (including the user's historical geographical location and service requirements), the dynamic operation of the UAV can be predicted. This provides prior knowledge for the operational management of the UAV. Secondly, considering the load limits of the UAV, an optimization method for UAV positioning based on K-sums was designed to balance the load of the UAV. The reinventive learning method is used to achieve the optimal distribution of UAV transmission energy. This method can guarantee the communication quality of search and rescue personnel under the condition of limited network transmission. The experiment proves that the search and rescue target is constructed according to the signal and noise comparison under the static condition. This method can increase the utilization rate of search and rescue mission by more than 20%. This provides a guarantee for the business services of rescue workers in emergency disaster relief scenarios.