Research On Key Technology Of Air Emergency Rescue

n recent years,all kinds of natural disasters and emergencies have occurred frequently in China,most of which are accidental and destructive and have brought huge threats and losses to people’s life,property safety,and social economy.Emergency rescue is an important means to deal with all kinds of sudden natural disasters and emergencies.Aviation emergency rescue has many good characteristics,including fast speed,high rescue efficiency,and strong professionalism.It has become an important part of emergency rescue in various countries.Due to the late start,aviation emergency rescue in China is still lack of standardized,efficient,and professional aviation emergency rescue system.The thesis takes China’s aviation emergency rescue system as the research point to improve the efficiency of aviation emergency rescue.The focus of the thesis includes the optimal deployment of key rescue points in aviation emergency rescue,multi objectives & multi tasks scheduling optimization and rescue helicopter route planning optimization.The thesis proposes the corresponding algorithms to solve them.The main research contents of this thesis are as follows:Through researching on the optimization of aviation emergency rescue deployment,an improved welzl algorithm(SS welzl)is proposed to solve the minimum circle coverage of rescue points,and a grid method is proposed to solve the multi circle area coverage.SS welzl algorithm has made many effective improvements based on welzl algorithm.In order to solve the problem of high recursive complexity,cyclic calculation is used to replace recursive calculation.In order to solve the problem of point selection in the cycle process,the effectiveness of coverage point selection is improved by triangle screening strategy.Direct pruning for invalid points effectively improves the calculation efficiency.Comparative experiments show that SS welzl algorithm can effectively optimize the coverage deployment of rescue center.For the multi circle area coverage problem,this thesis proposes to use the efficient optimal hexagonal cellular grid method and the high-precision coverage density grid method to solve it.The simulation experiments show that both cellular grid method and density grid method can effectively solve the rescue area coverage optimization problem.The execution efficiency of honeycomb grid method is higher,and the result of density grid method is better.About the multi-objective and multi-constraint scheduling optimization problem of aviation emergency rescue,an improved particle swarm optimization algorithm(mmopso)is proposed.To resolve the problem of insufficient particle diversity,a topological strategy of grouping effect,we use small group classification and small group optimal particle(leader)participating in global competition.For the iterative optimal selection problem,the combination of historical optimal selection and alternative set is used to solve it.Aiming at the problem of insufficient cross-border diversity of particles,the gravity rebound mechanism is adopted to ensure the diversity and exploration ability of particles.In view of the increase of computational complexity caused by the high density of small particles,the concentration optimization strategy based on Markov distance is adopted to simplify the particles.Simulation results show that compared with the popular MOPSO and NSGA-II,mmopso algorithm has better convergence,distribution and computational performance.The mean value of convergence measure SP is 1.5-2 times that of the comparison algorithm.The mean value of DM1,a measure of distribution,increased by 10%-20%.For the problem of route planning optimization of aviation emergency rescue,a two-stage route planning method is proposed,which is solved by global static route planning based on Improved Particle Swarm Optimization and local dynamic route planning based on improved artificial potential field method.For the problem of global static route planning of rescue helicopter before flight,based on the flight characteristics of helicopter,an improved particle swarm optimization algorithm based on multi obstacle distance to construct the risk fitness function is adopted,which can effectively avoid obstacles in the route.Aiming at the problem of unreachable target points and local minima that may arise from the artificial potential field method,the artificial potential field is set in different areas of safety area,repulsion area,mixed potential field area and gravity area,different gravity and repulsion functions are constructed according to different areas,the calculation formula of resultant force is improved,and the gradient difference and equipotential line method are used to solve the obstacles in the route and near the target point in dynamic route planning,Shock flight of rescue helicopter or inaccessibility of target point;Simulation results show that the improved PSO global static route planning algorithm has better safety and smoothness than the standard PSO route planning algorithm,although the distance is increased;Compared with the ordinary artificial potential field algorithm,the improved artificial potential field local dynamic route planning algorithm has better obstacle avoidance ability and anti-offset ability.To sum up,this thesis studies the key problems such as rescue center deployment optimization,aviation emergency rescue multi-objective scheduling optimization and helicopter route planning,analyzes the key factors and target conditions in the problem,transforms it into a target optimization problem,and puts forward different methods to solve the problem.Simulation experiments verify the feasibility and effectiveness of these algorithms.These methods provide a different theoretical guidance for the construction of aviation emergency rescue system.