Abstract
With the increasing application of unmanned aerial vehicles (UAVs) to the inspection of high-voltage overhead transmission lines, the study of the safety distance between drones and wires has received extensive attention. The determination of the safety distance between the UAV and the transmission line is of great significance to improve the reliability of the inspection operation and ensure the safe and stable operation of the power grid and inspection equipment. Since there is no quantitative data support for the safety distance of overhead transmission lines in UAV patrol, it is impossible to provide accurate navigation information for UAV safe obstacle avoidance. This paper proposes a mathematical model based on a multi-sensor data fusion algorithm. The safety distance of the line drone is diagnosed. In these tasks, firstly, the physical model of the UAV in the complex electromagnetic field is established to determine the influence law of the UAV on the electric field distortion and analyze the maximum electric and magnetic field strength that the UAV can withstand. Then, based on the main factors affecting the UAV such as the maximum wind speed, inspection speed, positioning error, and the size of the drone, the adaptive weighted fusion algorithm is used to perform first-level data fusion on the homogeneous sensor data. Then, based on the improved evidence, the theory performs secondary fusion on the combined heterogeneous sensor data. According to the final processing result and the type of proposition set, we diagnose the current safety status of the drone to achieve an adaptive adjustment of the safety distance threshold. Lastly, actual measurement data is used to verify the mathematical model. The experimental results show that the mathematical model can accurately identify the safety status of the drone and adaptively adjust the safety distance according to the diagnosis result and surrounding environment information.
Highlights
With the continuous development of power systems, in order to ensure the safe and stable operation of a power system, the power industry needs to conduct regular inspections on overhead transmission lines, grasp the environment around the transmission line and its operation in a timely manner, and deal with potential problems [1,2,3]
Based on the status of the research, this paper proposes an adaptive multi-sensor data fusion algorithm for multi-sensor data fusion on the electromagnetic field strength of the unmanned aerial vehicles (UAVs)’s safe flight, the performance of the UAV control system, and the size of the UAV
In order to detect the safety distance of the inspection UAV according to the real-time data of each sensor under the current unmanned aerial vehicle inspection condition, judging the security status of the current location according to the matching of the data collected by various heterogeneous sensors and the evaluation rules, the patrol UAV can conduct an autonomous obstacle avoidance navigation control according to the decision result, or transmit the decision result to the ground terminal
Summary
With the continuous development of power systems, in order to ensure the safe and stable operation of a power system, the power industry needs to conduct regular inspections on overhead transmission lines, grasp the environment around the transmission line and its operation in a timely manner, and deal with potential problems [1,2,3]. The traditional transmission line inspections are mostly manual. In this way, the inspection line is very hard, and the operation period is very long. Due to its strong maneuverability, simple operation, various forms, high efficiency, and low cost, the unmanned aerial vehicle (UAV) inspection line has been widely used by domestic and foreign power companies for the inspection of transmission lines [5,6].
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