Research On Intelligent Mission Planning Technology Of UAV For Power Patrol Line

With the rapid development of the social economy and the continuous improvement of people's living demand for electricity,the scale of high-voltage transmission lines has been expanded as never before,and the inspection workload of high-voltage transmission lines has also increased rapidly.With the advancement of technology,the traditional manual inspection method is gradually transitioning to the inspection with wire robots,fixed-wing aircrafts and helicopters.However,these types of inspection methods have disadvantages somehow,such as complicated operation,long time of preparation,and inability to hover accurately in the air.In recent years,with the continuous improvement of multi-rotor UAV technology,the technology of intelligent mission planning for the inspection of high-voltage transmission lines based on multi-rotor UAVs has emerged.Multi-rotor UAVs have received increasing attention due to their highly efficiency,easy arrangement,accurate hovering ability and high degree of automation.The technology does not rely on manual operation,and could safely and efficiently complete the intelligent inspection task of the high-voltage transmission line.In this paper,the key technologies of the inspection task planning for high-voltage transmission lines based on multi-rotor UAVs are studied in detail.A modeling method of high-voltage transmission lines based on columnar space is proposed,with the consideration of the complex working environment.The modeling method,which features the related concepts of obstacle avoidance boundary and the obstacle simplification of polygon column,has high modeling precision,less modeling workload and lower complexity of pre-task preparation work.Then the implementation steps of the modeling method of the columnar space for obstacle avoidance and the processing methods of common obstacles modeling are expounded.A hybrid algorithm of particle swarm optimization based on adaptive weight is proposed on account of the routine inspection tasks among the inspection of high-voltage transmission lines.By integrating the adaptive shrinkage factors into the algorithm of particle swarm optimization,the algorithm could enhance the ability to avoid local minima.Then further fine-search for the global extremum through the Powell algorithm is implemented to make up for the poor global search ability of the particle swarm algorithm.At the same time,an algorithm of fusion chemical reaction is proposed.The algorithm introduces the concept of attraction-repulsion in the principle of ant colony foraging,comprehensively considers the information among the real time position,the next POI and the last position.And after synthesizing the above information,the occurrence proportion of each reaction type in the chemical reaction algorithm is adjusted,which leads to obtain the global optimal solution.The simulation results verify the effectiveness of the algorithm.Aiming at the task of the multi-interest point inspection in the inspection of high-voltage transmission lines,an algorithm of artificial potential field ant colony which combines artificial potential field method and ant colony algorithm is proposed.In the process of node search,ants are not only affected by the heuristic information and pheromone,but also by the force of the potential field.Deterministic selection enables ants to circumvent dangerous areas and move to target areas at a faster rate.Probabilistic choices ensure the globality of ant searches.At the same time,a two-container hybrid algorithm of chemical reaction is proposed for 3D path planning of multi-rotor aircraft formation.The algorithm introduces a dual-container strategy,which enhances the ability to avoid the local minimum.Then the crossover operator and genetic operator in the genetic algorithm are introduced to more precisely control the energy state of each newly generated molecule after the chemical reaction occurs.The probability of the occurring chemical reaction is determined by the combination of the average potential energy and the potential energy threshold.The above two algorithms are simulated under multiple environmental conditions.The simulation results verify the effectiveness of the algorithm.In order to solve the problem of path planning of the multi-UAVs collaboration,an algorithm of inspiring particle swarm optimization is proposed.In the algorithm,a mathematical model of the multiple UAVs in both the time and space domains is established firstly,adopting a framework of twostage collaborative planning.Hazard heuristics items are introduced into the algorithm to guide the particles to move away from the dangerous area,and then the synergistic variables and synergistic functions are used to process the cooperative constraints.The simulation results show that the proposed algorithm could obtain the optimal track combination that satisfies the cooperative constraint and least cost.Secondly,for the information consistency problem in the formation cooperation,the concept of“virtual center” is introduced to deal with the situation without preset benchmarks,and the information consistency is ensured by the method of parallel energy minimization.A ground monitoring system(namely the ground station)was designed in order to conduct physical testing.From the perspective of power industry demand,the hardware and software of the ground monitoring system for the drones are designed.In the software solution,the monitoring software of the ground station was developed using the Qt language and based on the SDK development kit of Google Earth.The software could feedback the flight information including route trajectories of the inspection drones in real time.Then the communication interface protocol in the software system is communicated with the drone.Finally,the ground station establishes a data link with the multi-rotor UAVs,issuing the inspection commands.Thus,the UAVs follow the commands to perform the inspection of a certain high-voltage transmission line,feedbacking the task data.