143results about How to "Improve flight safety" patented technology

The invention relates to the technical field of unmanned aerial vehicles, and discloses an inspection unmanned aerial vehicle flight control management method, which comprises the following steps: step 1, an unmanned aerial vehicle obtains environment three-dimensional point cloud data through a laser radar, captures terrain visual information through an RGB camera and a depth camera, obtains real-time position and attitude information of the unmanned aerial vehicle through a GPS and an inertial measurement unit, and obtains the real-time position and attitude information of the unmanned aerial vehicle; and fusing the collected data to construct a spatial grid map, and taking the grid map as input data of path planning. A high-precision space grid map is generated through three-dimensional environment perception and modeling in combination with an unmanned aerial vehicle multi-sensor fusion technology, and a path is updated in real time by using dynamic environment data, and an air route is planned and optimized, so that path dynamic adjustment and energy consumption minimization of the unmanned aerial vehicle in a complex dynamic environment are realized; and the effects of improving the task execution efficiency, reducing the flight energy consumption and improving the flight safety are achieved.

The invention relates to the technical field of unmanned aerial vehicle control, and discloses an unmanned aerial vehicle inspection control system and method based on data analysis, and the method comprises the steps: receiving environment feature data of a target region, and constructing a static environment model; obtaining kinetic parameters of the unmanned aerial vehicle, and calculating a feasible flight envelope in combination with the static environment model; after taking off, the unmanned aerial vehicle collects environment data in real time, and a multi-level environment topology model is constructed; acquiring state data in real time, and judging an obstacle avoidance level; if yes, local path planning is carried out, and an optimal flight path is generated; acquiring trajectory deviation and energy consumption data, dynamically calibrating the flight envelope, and optimizing the flight envelope; according to the method, environment perception, trajectory optimization and online learning are combined, the method is adaptive to a complex environment, and the intelligent level of unmanned aerial vehicle inspection is improved.

The invention relates to the technical field of unmanned aerial vehicle control, in particular to an unmanned aerial vehicle self-adaptive navigation system which comprises an inertial navigation system, a visible light sensor, a data fusion module, a database and a navigation control module. The inertial navigation system provides attitude, speed and acceleration data; the visible light sensor collects an image and obtains environment feature points through deep learning algorithm processing to realize visual positioning; and the data fusion module fuses two kinds of sensor data by using a dynamic weighted Kalman filtering algorithm, and dynamically adjusts the weight according to the environment to optimize the positioning information. The map library and the feature library store environment data to assist in positioning and dynamically update; the navigation control module generates an instruction according to the fused positioning information, and automatically adjusts a flight strategy by considering various factors based on an adaptive control algorithm. The system improves the positioning precision and environmental adaptability, enhances the flight safety and stability, is high in intelligence and autonomy degree, has flexibility and expandability, and can be widely applied to the field of unmanned aerial vehicles.

The invention relates to a method for evaluating the situation awareness ability of a pilot based on a Ti-SA model. The Ti-SA model comprises an eye movement trace multi-dimensional attention enhancement module, an AOI multi-scale comprehensive feature module and a fusion module. The evaluation method comprises the steps of collecting eye movement trace time sequence data and flight training videos of a pilot at continuous moments in real time, and obtaining corresponding AOI fixation time sequence data based on the eye movement trace time sequence data, the flight training videos and a preset AOI subdivision area; preprocessing the eye movement trace time sequence data and the AOI fixation time sequence data; inputting the preprocessed eye movement trace time sequence data into an eye movement trace multi-dimensional attention enhancement module to obtain a category probability value corresponding to the eye movement trace time sequence data; inputting the preprocessed AOI fixation time sequence data into an AOI multi-scale comprehensive feature module to obtain a category probability value corresponding to an AOI fusion feature; and inputting the two category probability values into a fusion module to obtain a predicted situation awareness level.

The invention relates to an unmanned aerial vehicle visual guidance precise landing method, and belongs to the technical field of machine vision and unmanned aerial vehicle control. The method comprises the following steps: capturing surrounding environment information through a camera of an unmanned aerial vehicle to obtain operation environment data, and constructing a flight control model through construction parameters of the unmanned aerial vehicle; setting an expected landing point, extracting a target image from the corresponding operation environment data according to the expected landing point, and establishing visual mapping between the unmanned aerial vehicle and the expected landing point based on the target image; the relative position data and the to-be-flied distance of the unmanned aerial vehicle are calculated according to the visual mapping, and a predicted moving trajectory based on the relative position data and the to-be-flied distance is obtained through a flight control model; and an expected landing point is automatically captured and tracked in the landing process, relative pose information between the unmanned aerial vehicle and the expected landing point is solved in real time, and flight parameters of the unmanned aerial vehicle are adjusted in real time according to the relative pose information and the predicted moving trajectory. Visual guidance precise landing of the unmanned aerial vehicle is realized.

The invention discloses a pilot cognitive load monitoring and early warning method based on electroencephalogram and eye movement data, and the method comprises the steps: 1) designing a pilot different cognitive load state induction experiment paradigm in a simulated flight task scene, and obtaining a multi-modal physiological signal and task performance of a testee during an experiment; wherein the multi-mode physiological signals comprise electroencephalogram signals and eye movement signals; 2) preprocessing the multi-modal physiological signals and task performance, extracting corresponding feature indexes, and fusing and selecting the feature indexes to construct an optimal feature subset; and 3) constructing a cognitive state classification and discrimination model based on the optimal feature subset so as to carry out monitoring and early warning on the cognitive load of the pilot. According to the invention, the cognitive load level of the pilot can be monitored and evaluated, especially the sudden change point of the overload state of the cognitive load is pre-warned, and the flight safety is improved.

The invention relates to a low-altitude economic development form analysis method and system based on a high-density city, and the method comprises the steps: obtaining task address information and task type information of each aircraft, and carrying out the path planning in a preset airspace range according to the task address information and the task type information, obtaining flight path information of each aircraft; acquiring real-time traffic flow and airspace condition information in a preset airspace range, and performing real-time optimization adjustment on the flight path information according to the real-time traffic flow and the airspace condition information; monitoring the activities of the aircrafts in the airspace in real time, obtaining the flight information of each aircraft, and judging whether the corresponding aircraft has a flight violation condition or not according to the flight information; the flight task state is tracked and fed back in real time, the aircraft state and the equipment operation condition in the airspace are monitored, equipment alarm is triggered under the abnormal condition, and preset emergency treatment measures are taken. The method has the effect of improving the low-altitude aircraft management and control efficiency.

The invention discloses a path optimization method and system for unmanned aerial vehicle logistics distribution, and relates to the technical field of unmanned aerial vehicle logistics distribution, and the method comprises the following steps: obtaining all executable distribution paths, screening an unmanned aerial vehicle logistics distribution default execution path, obtaining unmanned aerial vehicle distribution state parameters, and analyzing unmanned aerial vehicle logistics distribution state characterization parameters. Path influence parameters of default distribution sub-paths are collected, unmanned aerial vehicle default distribution sub-path optimization label information is judged, all standby sub-paths are counted, logistics adaptation execution priority values of all the standby sub-paths are analyzed, and therefore unmanned aerial vehicle logistics distribution optimal sub-paths are screened and optimized execution is carried out. The unmanned aerial vehicle distribution efficiency and safety can be improved, complex and changeable meteorological conditions and obstacle conditions can be effectively handled, the distribution time and energy consumption are reduced, the adaptability of the unmanned aerial vehicle in a complex environment is enhanced, and smooth completion of a distribution task is ensured.

The invention relates to the technical field of non-destructive testing, and particularly discloses an aero-engine blade non-destructive flaw detection method for a miniature unmanned aerial vehicle, which comprises the following steps: acquiring stress data of a blade in a use process in real time by using an MEMS sensor, analyzing the data, and identifying a stress concentration area; carrying out real-time monitoring on crack data of the stress concentration area, extracting crack propagation fluctuation characteristics by utilizing a wavelet transform algorithm, and calculating a crack propagation fluctuation index; fatigue strength data of the material is monitored, fatigue failure characteristics are extracted, and a fatigue failure index is generated through a support vector machine algorithm; comprehensively analyzing the crack propagation fluctuation index and the fatigue failure index, and judging whether the blade is in a healthy state or not; and finally, based on the blade health state, determining whether to carry out further detection or maintenance.

The invention discloses an unmanned aerial vehicle safety scheduling optimization algorithm, and relates to the technical field of storage scheduling, and the algorithm comprises the steps: carrying out the modeling of a storage environment based on the position, shape and size information of goods shelves and mechanical equipment in a warehouse, and building a preliminary environment model; and scanning the environment by using a laser radar carried by the unmanned aerial vehicle to obtain environment data in the warehouse, and updating the environment model in real time in combination with the preliminary environment model. According to the unmanned aerial vehicle safety scheduling optimization algorithm, the accuracy and efficiency of a flight path are remarkably improved through an integrated path planning technology, the optimal flight path is customized for the unmanned aerial vehicle in combination with actual conditions of topography and landform of a storage area and obstacle distribution, redundancy and waste in the flight process are reduced, and meanwhile, the unmanned aerial vehicle safety scheduling optimization algorithm has good application prospects. And the path can be dynamically adjusted according to the real-time environment change to effectively deal with emergencies, so that the flight efficiency and safety are further improved.

The invention relates to the technical field of pilot state monitoring, in particular to a pilot state monitoring and flight data real-time synchronous fusion system, which comprises an information acquisition module used for acquiring physiological state information of a pilot and flight data information of an airplane in real time; the intelligent control module is used for controlling the operation of the camera, the electroencephalogram acquisition device and the electrocardiograph; the information processing module is used for carrying out preprocessing operation on the collected pilot physiological state information and the collected aircraft flight data; and the data fusion module is used for fusing the physiological state information of the pilot and the flight data parameters of the aircraft. The early warning assistance module is used for immediately sending out an early warning signal when an abnormality is found; and positioning information and rescue guidance are provided for a pilot under the emergency condition that the aircraft encounters danger. According to the current attention state and the task requirement of the pilot, the system can dynamically adjust the collection frequency and the collection position of the electroencephalogram collection device so as to improve the efficiency and the pertinence of data collection.

The invention discloses a closed space unmanned aerial vehicle intelligent navigation method and system based on three-dimensional reconstruction, and the method comprises the steps: S1, scanning a closed space based on a sensor, and obtaining environment data in the closed space; s2, constructing a three-dimensional model of the closed space by utilizing a three-dimensional reconstruction technology according to the acquired environment data; s3, according to the constructed three-dimensional model, planning a flight path of the unmanned aerial vehicle based on an A * algorithm; s4, monitoring the change of the environmental data in real time in the flight process, and adjusting the flight path according to the change; and S5, matching the real-time position of the unmanned aerial vehicle with the three-dimensional model to realize accurate navigation. According to the method, the three-dimensional model of the closed space can be constructed based on the three-dimensional reconstruction technology, the unmanned aerial vehicle can obtain more accurate space information, so that accurate navigation is realized, the change of environmental data is monitored in real time, the flight path is adjusted according to the change, an improved fuzzy obstacle avoidance algorithm and a backstepping flight control algorithm are combined, obstacles are effectively avoided, and the unmanned aerial vehicle is more accurate in navigation. And the flight safety is improved.

The invention provides a highway unmanned aerial vehicle autonomous inspection method and system, and relates to the technical field of data processing, and the method comprises the steps: receiving a preset inspection path from an inspection starting point to an inspection terminal point; unmanned aerial vehicle sensor information and unmanned aerial vehicle angular velocity information in the inspection process are collected; when an obstacle is detected by the unmanned aerial vehicle sensor information, obstacle avoidance is carried out, and otherwise, whether yawing is carried out or not is detected; generating an obstacle avoidance direction based on a potential field principle, and performing obstacle avoidance according to the obstacle avoidance direction; calculating a yaw angle of the unmanned aerial vehicle according to the angular velocity information of the unmanned aerial vehicle, and judging whether to yaw based on the yaw angle of the unmanned aerial vehicle; correcting the course of the unmanned aerial vehicle according to the yaw angle, and performing inspection along the adjusted course of the unmanned aerial vehicle; collecting real-time video frames of the expressway; constructing a highway abnormal scene recognition model, and outputting an abnormal scene; and uploading the abnormal scene to the holder, and sending out an abnormal prompt. The autonomous inspection efficiency and inspection precision are improved, and the manual intervention frequency and deployment cost are reduced.

The invention aims to provide a flight information management system. The system comprises a data acquisition module, a data interaction module, an unmanned aerial vehicle operation airspace generation management module, an alarm prompt module and a flight plan optimization module. The data acquisition module is used for acquiring real-time data; the data interaction module is used for calculating and processing the collected real-time data, forwarding the data to a message queue, and subscribing and distributing data inside and outside the system through a standardized data interface and a communication protocol; the unmanned aerial vehicle operation airspace generation management module is used for dynamically generating airspace operation limitation information of the unmanned aerial vehicle according to the real-time data; the alarm prompt module is used for generating early warning information according to the real-time data, the flight plan and the airspace operation limitation information; the flight plan optimization module is used for analyzing and evaluating an existing flight plan and determining an optimization strategy. Comprehensive operation situation information is provided for the controller, and the controller is assisted in making an accurate decision.

The invention relates to the technical field of bus control, in particular to a method and system for controlling and monitoring landing light based on a CAN bus. The method comprises the following steps: setting a light control node in an aircraft landing light system, and performing control network connection and landing light local response control on the light control node and a central control unit by using a CAN bus protocol to generate a landing light local response control instruction; starting corresponding landing light in an aircraft landing light system according to the landing light local response control instruction, performing light condition real-time monitoring and judgment analysis, and if the landing light is determined to be in an on-light state, performing brightness non-uniformity control management so as to execute on-state brightness non-uniformity control work; and if it is determined that the landing light working state is a closed state, light operation fault control management is carried out to execute closed state fault adjustment control work. The intelligent level of the landing light control system can be improved.

The invention relates to the technical field of aero-engine control, in particular to an active stability control system based on aero-engine stability margin estimation, which is used for solving the problems that the surge risk cannot be accurately evaluated and the surge phenomenon cannot be prevented through real-time monitoring and dynamic adjustment in the prior art. According to the system, the surge risk can be accurately evaluated through the surge margin estimation module, the surge phenomenon is effectively prevented through real-time monitoring and dynamic adjustment, safe operation of the engine is ensured, the system allows safe operation closer to the performance limit, and therefore the working efficiency and the performance expression are optimized; the module with the self-adaptive capability can be automatically adjusted according to flight conditions, the adaptability of the aircraft in a changeable environment is enhanced, meanwhile, the system carries out intelligent decision making through historical and real-time data, and quick response and high reliability are guaranteed.

The invention relates to an aircraft force comprehensive adjusting device, and belongs to the field of flight control. The device comprises an upper rocker arm, a left rocker arm, a right rocker arm, a middle rocker arm, a bolt and a ball bearing, the upper end A of the upper rocker arm is hinged with the control line system; the upper ends of the left rocker arm and the right rocker arm are fixedly connected with two ends of the upper rocker arm respectively; the bolt penetrates through the middle parts E of the left rocker arm, the middle rocker arm and the right rocker arm; the left rocker arm, the middle rocker arm and the right rocker arm rotate around the bolt through respective ball bearings; the upper end F of the middle rocker arm is hinged with the input end of the booster; the lower ends B of the left rocker arm, the right rocker arm and the middle rocker arm are coaxial and concentric, the lower ends B of the left rocker arm and the right rocker arm are hinged to the structure installation support, and the lower end B of the middle rocker arm is hinged to the output end of the stability augmentation steering engine.

The invention discloses a flying wing layout aircraft landing gear folding and unfolding optimization control method, system and equipment, and relates to the technical field of flying wing layout aircraft control, and the method comprises the steps: employing a numerical simulation calculation method, and obtaining pneumatic data under the influence of a flying wing layout aircraft landing gear hatch cover; on the basis of pneumatic data, the deterioration degree of all states of the flying wing layout aircraft landing gear hatch cover in the folding and unfolding process on the course static instability is analyzed; analyzing the rudder effect of a resistance rudder in each state in the folding and unfolding process of the landing gear hatch cover of the flying wing layout aircraft under the condition of a sideslip angle; according to the analysis result, an undercarriage hatch cover folding and unfolding control strategy and the limiting requirement of the sideslip angle are obtained, and undercarriage folding and unfolding optimization control is carried out. According to the method, a numerical simulation technology is adopted, the aerodynamic characteristic, the operation stability characteristic and the flight control law of the lateral course of the aircraft under the influence of an undercarriage hatch cover are analyzed, an optimized undercarriage folding and unfolding control strategy is designed on the basis, and technical support is provided for development of flying wing layout aircrafts.

The invention relates to an airport ground-air data multi-domain multi-link transmission method, belongs to the technical field of aeronautical communication, solves the problems of limited bandwidth, insufficient coverage, communication delay and limited anti-jamming capability in the prior art, and comprises the following steps: S1, establishing a multi-link transmission system and a dynamic routing selection system of an aircraft system and a ground system; s2, a flight crew of the aircraft system selects an optimal transmission path in a multi-link transmission system through a dynamic routing system to send the data request to a ground system; s3, the ground system obtains a processing result, and the data of the processing result is returned to the aircraft system by selecting an optimal transmission path from the multi-link transmission system through the dynamic routing selection system; s4, the aircraft system obtains the processed information and carries out flight adjustment and decision making; and S5, in the flight process of the aircraft, the aircraft system and the ground system continuously repeat the steps S2 to S4 until the flight is finished.

The invention relates to the technical field of electric power material storage warehouse inspection, in particular to an intelligent inspection system of an electric power material storage warehouse, which comprises a database module used for storing comprehensive information of the electric power material storage warehouse, and a model construction module used for constructing a three-dimensional space model of the electric power material storage warehouse according to the comprehensive information; according to the invention, the feature vectors of the plurality of sub-tasks in each inspection area are constructed and the plurality of sub-tasks are clustered, so that a plurality of relatively balanced task sets can be obtained, the plurality of sub-tasks can be reasonably distributed, all unmanned aerial vehicles in the inspection area can be utilized to the maximum extent, the operation efficiency of the unmanned aerial vehicles is improved, and the working efficiency of the unmanned aerial vehicles is improved. According to the method, the unmanned aerial vehicle can inspect more sub-tasks within the average flight duration, path planning can be carried out on the task set, the shooting point position path and the inspection path of the sub-tasks are balanced, and integrity and continuity of inspection data corresponding to each sub-task are facilitated while the inspection efficiency is ensured.

The invention discloses an unmanned aerial vehicle autonomous obstacle avoidance path planning method and device and a storage medium, and relates to the technical field of unmanned aerial vehicle autonomous navigation. The method comprises the steps that feature information of a target obstacle is acquired through a YOLOv3 model, and the feature information comprises at least one of the following information: the shape, the volume and the color; acquiring position information of the unmanned aerial vehicle; determining a target obstacle avoidance path based on the feature information and the position information of the unmanned aerial vehicle; and generating a control strategy based on the target obstacle avoidance path, wherein the control strategy is used for controlling the flight path of the unmanned aerial vehicle. The technical problem of low reliability of the obstacle avoidance path provided by the traditional algorithm of the unmanned aerial vehicle in the prior art is solved.

The invention discloses an aircraft adaptive interval management and control method and system, and relates to the technical field of air traffic management. An aircraft adaptive interval management and control system comprises a flight conflict basic unit module, a flight conflict scene generation module, a flight conflict resolution module and a flight conflict learning module. According to the method, the aircraft flight conflict scene training set can be constructed by constructing the basic flight unit of the aircraft and generating the flight trajectory vector set and combining the flight conflict generation model; the training set is utilized to train an aircraft autonomous interval management and control model through an improved Markov decision model, so that effective strategy output is realized when a flight conflict occurs; the model is updated through analysis of the test result, the adaptability and accuracy of the autonomous interval management and control model of the aircraft are improved, the flight safety of the aircraft in a complex environment is improved in the process, and the prediction and processing capacity of the model for flight conflicts is enhanced.

The invention relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle route real-time planning method and system, a storage medium and an unmanned aerial vehicle. Determining a target distance between a target unmanned aerial vehicle and a target object in the target area; and according to the target distance, determining a current operation parameter of the target unmanned aerial vehicle, and according to the current operation parameter, adjusting a route of the target unmanned aerial vehicle. According to the invention, the terrain features of the regional three-dimensional point cloud data can be combined to realize real-time planning of the route of the unmanned aerial vehicle, and the flight safety and the flight efficiency are improved.

The invention discloses a low-altitude intelligent cluster flight management method and device, a medium and a product, and relates to the technical field of aviation, and the method comprises the steps: constructing a knowledge graph based on the structured and unstructured data of a low-altitude network connection intelligent carrier; an LSTM model is utilized to analyze spatial domain features in the knowledge graph, and a traffic space-time diagram of the carrier is predicted; dividing a low-altitude airspace based on the traffic space-time diagram, and determining a low-altitude airspace distribution result; according to a low-altitude airspace distribution result, taking the flight safety degree of the carrier as a reward function, taking the time used by the flight path as a value function, and adopting a Q-learning plus traffic factor time penalty algorithm to iterate the initialized low-altitude network connection intelligent carrier path to obtain an optimal path; and according to the low-altitude network connection intelligent carrier cluster, constructing a formation flight cooperative control model with the lowest delay rate as the target. The airspace utilization efficiency and the flight safety of the low-altitude network connection intelligent carrier can be improved.

The invention provides an airborne meteorological radar thunderstorm rapid identification method, and belongs to the technical field of airborne meteorological radars, and the method specifically comprises the steps: carrying out the ground clutter suppression of the obtained airborne meteorological radar three-dimensional echo data; carrying out reflectivity factor calculation on each piece of wave position data in the stereoscopic scanning process to obtain three-dimensional echo reflectivity factor data of the airborne meteorological radar after ground clutter suppression; processing the three-dimensional echo reflectivity factor data after the ground clutter suppression to obtain reflectivity factor data of a two-dimensional plane; extracting a potential thunderstorm region from the reflectivity factor data of the two-dimensional plane; the data of each potential thunderstorm area are traced back to the three-dimensional reflectivity factor data, and the features of a thunderstorm body are counted; and judging the potential thunderstorm area and the counted thunderstorm body features according to the thunderstorm identification feature threshold. Through the processing scheme provided by the invention, the speed and accuracy of thunderstorm identification are improved, and the perception ability of a pilot to a dangerous meteorological area on a flight route is improved.

The present invention discloses a propeller pitch control method and system for an aircraft, and relates to the field of aircraft. The method comprises: monitoring flight state parameters in real time through a sensor module on the aircraft, the parameters including the altitude, speed, acceleration and thrust demand of the aircraft; using a control algorithm to calculate the optimal pitch angle of the current flight stage according to the flight state parameters; transmitting the optimal pitch angle calculated by the controller to the propeller actuator; the propeller actuator adjusts the pitch angle according to the instructions of the controller; monitoring the actual pitch angle through a feedback system, and comparing it with the target pitch angle; adjusting the control strategy in real time according to the comparison result to ensure that the pitch angle of the propeller meets the requirements of the current flight conditions. The technical solution of the present invention can effectively improve the thrust output and flight stability of the aircraft in different flight stages.

The invention discloses a low-altitude flight capacity sensing method and system based on operation identification, and the method comprises the following steps: obtaining the data information of a predicted flight path aircraft, and carrying out the discretization of an airspace; performing airspace flight corridor division processing based on an airspace discretization processing result and predicted flight path aircraft data information; based on the airspace flight corridor division processing result and the airspace opening and closing time, the waiting duration of the aircraft is determined, and a passable airspace flight corridor is judged; determining an affected range of the aircraft and selecting an airspace flight corridor based on the passable airspace flight corridor determination processing result and the predicted flight path aircraft data information; the real-time middle and long distance perception of the aircraft to the aircraft running around is realized, the operation safety problem is solved, the flight amount can be adjusted in advance from a larger range, and the operation risk caused by too high local flight density can be avoided.

The embodiment of the invention relates to the technical field of automatic flight driving, in particular to an automatic flight pilot with a master-slave structure and an aircraft, the automatic flight pilot comprises a main processor, a coprocessor and a crystal oscillator clock, and the main processor is connected with the coprocessor and the crystal oscillator clock. The coprocessor is also respectively connected with each functional module of an aircraft to which the automatic flight pilot belongs; the crystal oscillator clock is used for providing a stable clock signal for synchronous work; the main processor is used for creating and scheduling a plurality of system tasks; the coprocessor is used for collecting data required by each system task from the corresponding function module; the main processor is also used for carrying out data fusion by using a Kalman fusion algorithm, carrying out calculation of a control law and a guidance law based on the fused data, and sending a calculation result to the coprocessor; and the coprocessor is also used for generating a control instruction according to the resolving result and sending the control instruction to the corresponding functional module to complete various system tasks, so that the flight safety is effectively improved.

The invention discloses a double-rotor unmanned aerial vehicle of an independent structure, and belongs to the technical field of unmanned aerial vehicles, the double-rotor unmanned aerial vehicle comprises an unmanned aerial vehicle body, mounting rotors are fixedly connected to the front side and the back side of the unmanned aerial vehicle body, and lower protective covers are fixedly connected to the ends, away from each other, of the two mounting rotors; two lower connecting blocks are fixedly connected to the outer surface of each lower protective cover, an upper protective cover is clamped in each lower protective cover, and compression springs arranged at equal intervals are fixedly connected to the bottom surface of each upper protective cover. According to the double-rotor unmanned aerial vehicle of the independent structure, through cooperation of the installation rotors, the lower protective cover and the upper protective cover, a rotating propeller rotating at a high speed of the double-rotor unmanned aerial vehicle can be protected conveniently, and then through cooperation of a lower connecting block, a compression spring, an installation ring, an upper connecting block and a connecting bolt, the rotating propeller can be protected conveniently; the lower protective cover and the upper protective cover are stably used for protecting the rotating propeller, and the effect of improving the flight safety of the unmanned aerial vehicle is achieved.

The invention relates to the technical field of flying around of aircrafts, in particular to an airport entering and leaving thunderstorm flying around scheme analysis system based on historical flight paths. And obtaining a thunderstorm fly-around scheme of the current aircraft at the airport by combining the meteorological data of the specified area in the specified time period in the future and the geographical map information of the airport and the surrounding area. The method has the beneficial effects that through data analysis and processing, the comparison between the flight historical track based on the geographic map and the flight program design standard track is realized, so that the flight fly-around rule under the thunderstorm weather is obtained, and a pre-fly-around scheme reference under the thunderstorm weather is provided for pilots and controllers. A more reasonable and safer fly-around scheme is formulated, and the thunderstorm weather coping capacity is enhanced. The system aims at improving the flight safety, reducing flight delay and cancellation caused by thunderstorm weather and improving the flight punctuality rate.