Application Of GNSS/SINS In Integrated Navigation Of Power Line Inspection UA

At present,the stable operation of the power system is crucial to ensuring the safe operation of the national economy.In order to ensure the stability and safety of the power system,it is necessary to strengthen protective measures such as inspection and maintenance of transmission lines.Unmanned aerial vehicles(UAVs)have the advantages of high efficiency,high flexibility,and low risk in power line patrol and have gradually become the main force of power line patrol.In order to improve the efficiency and positioning accuracy of unmanned aerial vehicle power line inspection,the following research is conducted on the application of GNSS/SINS in the integrated navigation of unmanned aerial vehicles for power line inspection:(1)Aiming at the problem that the GNSS/SINS integrated navigation system is vulnerable to severe environmental impacts during the execution of the electric power line patrol drone task,resulting in significant positioning errors,and the drone cannot effectively complete the line patrol task,the autonomous line patrol method of the electric power line patrol drone is studied.A path planning algorithm based on improved A * algorithm combined with Bezier curve is proposed.This algorithm is based on the traditional A * algorithm,selects diagonal distance as a heuristic function,and adds exponential decay function as a heuristic factor to improve the convergence speed and reduce the number of iterations;Adopting a two-way search strategy to shorten search time;The path is optimized using a Bezier curve to meet actual flight needs.Three types of maps were designed for algorithm verification.Compared with the traditional A * algorithm,this algorithm can reduce the number of expansion nodes and shorten path planning time in each map,enabling fast and efficient acquisition of the optimal path.(2)Aiming at the problem of GNSS/SINS intermittently missing signals in the integrated navigation application of electric power line patrol UAVs,which leads to the divergence of integrated navigation errors,this paper studies how to suppress the divergence of integrated navigation errors.An improved gray neural network-assisted positioning method for GNSS/SINS integrated navigation system is proposed.This method first performs outlier optimization processing on GNSS data that needs to be predicted,then performs network prediction on the processed GNSS data,and finally uses the predicted data to correct errors in SINS.The intermittent loss of GNSS signal of power line patrol UAV in different scenarios is simulated and verified by MATLAB data analysis.The results show that the proposed method can effectively predict GNSS signal missing data in different scenarios,and using prediction data to correct SINS errors can effectively suppress the divergence of integrated navigation errors and improve positioning accuracy.