158 results about "Flight height" patented technology

The invention discloses an aircraft wake flow real-time monitoring method based on laser radars, and the method comprises the steps: collecting the real-time wake flow data in a five-side approaching stage of a front aircraft through a plurality of laser radar devices, and determining the space coordinates and three-dimensional contour of the edge of a wake flow region through an edge detection algorithm; according to the coordinates of the left and right edges and the upper and lower edges of the wake flow area, the front and tail flow areas are displayed in real time; the method comprises the following steps: intercepting a two-dimensional cross section of a front aircraft tail flow area at a rear aircraft real-time flight height, calculating a rolling instability index generated by the two-dimensional cross section area to a rear aircraft wing, determining a wake flow minimum safety interval according to a preset rolling instability index threshold value, and displaying the wake flow minimum safety interval on an air traffic control system radar interface in real time, thereby realizing the purpose that in a five-side approach stage of an aircraft, the flight speed of the aircraft is increased. The front aircraft wake flow area and the rear aircraft wake flow area are displayed in real time, and the minimum safety interval of the front aircraft and the rear aircraft considering the real-time flight height is considered, so that an air traffic controller can clearly know the real-time state and the potential risk of the aircraft wake flow, and the wake flow monitoring accuracy and the flight safety are improved.

The invention relates to the technical field of electric power, in particular to an unmanned aerial vehicle route automatic planning method and system for a complex space of a transformer substation. Analyzing at least one inspection task instruction input by a user to obtain a task type corresponding to each inspection task instruction and a data acquisition requirement corresponding to the task type; according to a preset three-dimensional semantic map of the transformer substation and the data acquisition requirement of each inspection task instruction, a flight route of at least one unmanned aerial vehicle is automatically generated by adopting a path planning algorithm, and the flight route comprises a waypoint sequence, a flight height, a shooting angle and a holder action instruction; the three-dimensional semantic map comprises no-fly zone information in the transformer substation, a plurality of devices, the position of each device, the device type, the electrification attribute and the safety rule label. And controlling the corresponding unmanned aerial vehicle to inspect target equipment in the transformer substation according to the flight route of each unmanned aerial vehicle. And large-scale and standardized inspection operation is realized.

The invention relates to the technical field of unmanned aerial vehicle flight control, in particular to a control method of an inspection unmanned aerial vehicle, which comprises the following steps of: in response to a preset inspection instruction, obtaining a current target area wind speed, terrain information and a plurality of humidity values fed back by a plurality of humidity sensors arranged at different heights; flight parameters are constructed based on the wind speed and terrain information of the target area, heat distribution cloud charts at different heights are generated during the period, and the drip irrigation amount in the target area is calculated based on the heat distribution cloud charts. According to the control method of the inspection unmanned aerial vehicle, the flight path can be dynamically optimized through a wind speed self-adaptive flight height adjustment mechanism in combination with single effective width calculation of the thermal imager, and meanwhile, the ground heat distribution data of the same target area are collected at different heights in later data processing, so that the control precision of the inspection unmanned aerial vehicle is improved. And meanwhile, in combination with the environment humidity corresponding to different heights, the interference of the flight height and the environment humidity on the thermal imaging data is reduced, and the environment data acquisition precision is remarkably improved.

The invention discloses an unmanned aerial vehicle control system and method for agricultural seeding, relates to the technical field of unmanned aerial vehicle control, and solves the technical problems of seed falling path deviation and seeding precision reduction caused by the fact that route generation depends on preset topographic data and position points but real-time environment change is not considered in the prior art. The first flight height of the unmanned aerial vehicle at the current wind speed is obtained; acquiring the real-time horizontal offset of the unmanned aerial vehicle based on the first flight height; based on the first flight height and the real-time horizontal offset, determining a target position of the seed falling in the to-be-sown area; the actual depth of the seeds embedded into the soil is calculated through the kinetic energy theorem; judging whether the actual depth is within a preset normal embedding depth range or not; the real-time flight speed of the unmanned aerial vehicle in the flight process is obtained, and the unmanned aerial vehicle is controlled to complete sowing according to the real-time flight speed and the real-time flight speed; according to the invention, the deviation of a seed falling path is corrected, and the seeding precision is improved.

The invention belongs to the technical field of unmanned system intelligent control and path planning, and discloses a multi-unmanned aerial vehicle path planning method based on a multi-population grey wolf optimization algorithm, and the specific technical scheme comprises the steps: 1, building an environment model and constraint conditions of unmanned aerial vehicle three-dimensional path planning; 2, constructing a multi-target cost function including fuel consumption cost, flight height cost, threat area cost, time cooperation cost and space cooperation cost; 3, optimizing the multi-target cost function by adopting a multi-population grey wolf optimization algorithm to obtain an optimal flight path; according to the method, the global search capability is remarkably enhanced, and the multi-group clustering strategy and the periodic convergence factor act together, so that the algorithm can effectively jump out of local optimum, a path scheme closer to global optimum is found in a complex solution space, the convergence speed and the calculation precision are greatly improved, the collaborative planning effect is excellent, and the method is suitable for large-scale popularization and application. The method shows strong environmental adaptability and robustness, and has a very high practical application value.

The invention discloses a distribution network unmanned aerial vehicle ground simulation flight method and device based on AI vision and a medium, and the method comprises the steps: collecting a first real-time image in a flight direction in real time in a height calibration stage before an unmanned aerial vehicle flies to a next target tower pole; dynamically adjusting the height of the unmanned aerial vehicle according to the image width ratio of the distribution wire in the first real-time image until the target tower safety height is reached; after the unmanned aerial vehicle flies over the target tower pole according to the target safety height, a second real-time image in the flight direction is collected in real time through the visual sensor; and according to the image width ratio of the power distribution wire in each second real-time image and the real-time positioning information of the unmanned aerial vehicle, controlling the unmanned aerial vehicle to perform flight height change with the height fluctuation of the power distribution wire in the flight direction by taking the target tower pole as a starting point, and according to the technical scheme of the embodiment of the invention, autonomous height adjustment of the unmanned aerial vehicle is realized through visual intelligent analysis; the equipment cost and the operation complexity are greatly reduced, and the inspection efficiency and quality of the unmanned aerial vehicle are remarkably improved.

The invention discloses an AI-based unmanned aerial vehicle automatic positioning and navigation system, and the system comprises an unmanned aerial vehicle body which obtains a starting point coordinate through a navigation module by manually inputting a terminal point coordinate and a planned flight time length value t, flies to the terminal point coordinate at a flight speed value V1 and a flight height value H1 from the starting point coordinate, automatically completes a flight task, and automatically judges a return flight; and the monitoring unit is used for acquiring an initial electric quantity value Q of the unmanned aerial vehicle body, transmitting the initial electric quantity value to the coordinate unit, monitoring the output power of the storage battery in real time during flight, and generating a feedback signal and transmitting the feedback signal to the correction unit when abnormal output power is generated during flight. The problems that when an existing unmanned aerial vehicle automatic positioning navigation system is used, the endurance problem of the unmanned aerial vehicle is not considered, and the unmanned aerial vehicle cannot return or even falls in the flight process in the actual flight process are solved.

The invention relates to the technical field of inspection planning, in particular to an unmanned aerial vehicle low-altitude inspection planning system and method based on dangerous case analysis. According to the method, multi-dimensional calculation including flight complexity assessment, flight height danger, building density danger and the like is carried out, dynamic and static risks are integrated, finally, building collision danger and risk assessment results of all areas are integrated to obtain a global route danger assessment result, and a route with the minimum danger is selected according to the global route danger assessment result. According to the whole scheme, multi-dimensional and comprehensive risk assessment is realized, various factors such as environment and building are considered, related standard requirements are met, and the flight risk of the unmanned aerial vehicle can be effectively reduced.

The multi-degree-of-freedom bionic bird flapping-wing aircraft comprises a flight assembly and a fuselage, and a driving assembly and a direction control assembly are arranged on the fuselage; a motor of the driving assembly drives a rotating shaft through a gear transmission mechanism. The flying assembly comprises wing modules which are symmetrically arranged and a linkage driving mechanism, and the linkage driving mechanism converts the rotating motion of the rotating shaft into vertical flapping of the wing modules and different folding angles of the wing modules; the direction control assembly comprises an empennage connected with the fuselage, an empennage steering device, an empennage lifting device and a wing twisting device; the empennage steering device drives the empennage to deflect around the vertical axis of the fuselage to adjust the flight direction of the aircraft; the empennage lifting device drives the empennage to deflect around the transverse axis of the fuselage to adjust the flight height of the aircraft; the wing twisting device drives the wing module to rotate around the longitudinal axis of the wing to adjust the pitch angle of the wing module. According to the invention, flapping folding and twisting can be realized, and a flying function which is extremely similar to that of a real bird is provided.

The invention relates to the technical field of city model construction, and discloses a smart city 3D model construction method and system, and the method comprises the steps: S1, enabling an unmanned aerial vehicle to fly over a city according to a preset flight path, dynamically calculating a proper flight height according to the height of a building and the pitch angle of a camera in the flight process, and automatically adjusting the flight height; the flight height is dynamically adjusted according to the building height and the camera pitch angle in the flight process of the unmanned aerial vehicle, and the coverage range and the resolution of image acquisition are ensured; in combination with the real-time analysis capability of the edge calculation module, data defects can be quickly identified and laser radar supplementary acquisition can be triggered, so that the data acquisition efficiency and integrity are remarkably improved; and finally, through multi-source data fusion and automatic modeling of the cloud processing platform, a high-precision and high-reality smart city 3D model is constructed, and a reliable three-dimensional digital basis is provided for city management and planning.

The invention relates to the technical field of low-altitude flight management, in particular to a low-altitude traffic management system and method based on multi-modal fusion. The method comprises the following steps: collecting flight height information in a low-altitude airspace, and performing layered labeling on the low-altitude airspace based on the flight height information to obtain labeled layers; acquiring flight constraint condition information of the labeled layer, and performing flight constraint on the aircraft in the labeled layer based on the flight constraint condition information; collecting starting point position information and terminal point position information of the flight task, and generating an initial flight path based on the starting point position information and the terminal point position information; the initial flight path is optimized based on the obstacle information, the final flight path is generated, the aircraft executes the flight task based on the final flight path, and the resource utilization rate of the low-altitude airspace and the low-altitude flight management efficiency can be improved.

The invention introduces a tethered unmanned aerial vehicle follow-up and precise landing target system, which comprises a multi-level visual target, and the visual target sequentially comprises a central positioning area, a target positioning area and a target positioning area from the center to the periphery, and the central positioning area is formed by arranging four aruco marks of a first size in a 2 * 2 array mode; the middle transition area is formed by arranging eight aruco marks of the first size in the upper direction, the lower direction, the left direction and the right direction of the center positioning area; four aruco marks of a second size are respectively arranged at the left upper part, the right upper part, the left lower part and the right lower part of the central positioning area; the peripheral auxiliary area is formed by arranging four aruco marks of a third size at four corners of the whole visual target respectively; the maximum peripheral frame is an aruco mark of a fourth size, and the outer frame of the aruco mark of the fourth size forms the outermost layer area of the whole target. According to the invention, continuous and stable visual features can be provided for the mooring unmanned aerial vehicle at different flight heights and attitudes, and the landing reliability is improved.

The invention discloses an anti-explosion method and system for a vertical fixed-wing unmanned aerial vehicle, the unmanned aerial vehicle and a medium, and the anti-explosion method comprises the steps: monitoring the operation conditions of motors of all rotor assemblies in real time, and determining a fault motor when an abnormality occurs; performing first stability control on other motors without faults, the control surface of the fixed wing and the control surface of the empennage according to the fault motor; acquiring the current flight height of the unmanned aerial vehicle, and performing landing control on the unmanned aerial vehicle according to the current flight height until the unmanned aerial vehicle lands to the ground; and performing fault detection processing on the unmanned aerial vehicle, and generating a fault processing flow record. The fault motor can be accurately identified and positioned in the landing process of the unmanned aerial vehicle, and corresponding emergency measures are taken according to the position relation of the fault motor, so that the unmanned aerial vehicle can maintain stability in the air and stably land on the ground, the phenomenon of explosion of the unmanned aerial vehicle is effectively avoided, and the safety of the unmanned aerial vehicle is improved. And the landing safety and stability of the unmanned aerial vehicle are ensured.

The invention relates to the technical field of aircraft route planning, in particular to an aircraft control method and system for preventing long-distance flight collision, and the method comprises the steps: obtaining the offset distance between an aircraft and a set route at each moment in the flight process, and the measurement distance between the aircraft and a nearest obstacle; obtaining the dynamic stability of the aircraft in each time interval; determining the long-term balance degree of the aircraft in each time interval based on the autocorrelation of the flight heights of the aircraft at all moments in each time interval and the linear growth trend of the distance between the aircraft and the starting point in each time interval in combination with the fluctuation condition of extreme value distribution in the flight speeds of the aircraft at all moments in the time interval; and correcting a Q value updating method in the depth Q network, and performing route planning on the aircraft by using the corrected depth Q network. Therefore, the long-distance flight collision risk of the aircraft is reduced.

The invention is suitable for the technical field of flight height prediction, and particularly relates to a flight height prediction method based on a neural network, and the method comprises the steps: collecting sensor data of a passenger plane, and inhibiting outlier data points through a dynamic truncation mechanism based on a distribution quantile threshold; dividing the sensor data by adopting a time sequence slice division strategy to obtain a training set and a verification set, and constructing a prediction feature set based on the training set and the verification set; and constructing a flight height prediction model, training the flight height prediction model through the prediction feature set, and predicting the flight height based on the trained flight height prediction model. According to the invention, a normalization technology is applied to carry out data reduction on a flight time sequence signal, a parallel network structure comprising a multi-scale convolution kernel feature extraction layer and an attention weight distribution module is designed, and gradient iteration is carried out on a Huber loss function through an optimizer for dynamically adjusting a learning rate. And the characterization capability of the model on the nonlinear change mode of the flight state is obviously improved.

The invention relates to a resource orchestration method and device for a collaborative network, equipment, a storage medium and a program product. Comprising the following steps: constructing an optimization model taking maximization of total satisfaction, minimization of service duration and minimization of energy consumption of an unmanned aerial vehicle as targets; the total satisfaction is the sum of the satisfaction of each target area, the service duration is the sum of the sensing duration, the transmission duration, the calculation time and the flight time corresponding to each target area, and the energy consumption of the unmanned aerial vehicle is the sum of the sensing energy consumption, the transmission energy consumption, the flight energy consumption and the hovering energy consumption corresponding to each target area; solving the optimization model under the constraint of a preset constraint condition to obtain a computing resource allocation strategy and a sensing communication strategy; comprise computing time, sensing duration, service sequences, flight heights and transmission power of various computing resources. By adopting the method, multi-target collaborative optimization is realized, namely, the service duration and the energy consumption of the unmanned aerial vehicle are minimized while the total satisfaction degree of the system is maximized.

The invention belongs to the technical field of aircraft fuel tank inerting, and particularly relates to a method for calculating the shedding rate of a catalyst coating of an ozone converter in single flight. Comprising the following steps: S1, acquiring the mass M of a catalyst coating of the ozone converter; s2, acquiring flight profile data, wherein the flight profile data comprises a relationship H (t) between the flight height H and time t of the aircraft, time h required by one flight cycle of the aircraft, and time t1 and t2 for starting working and closing of an inerting system; s3, the relation m (H) between the mass m of dust contained in unit volume of entrained air in the entrained air of the inerting system and the flight height H is obtained; s4, the air entraining flow Q of the inerting system is obtained; s5, obtaining a guarantee value F and a dust holding capacity M1 of the minimum replacement interval of the filter; and S6, calculating the single flight shedding rate mu of the catalyst coating of the ozone converter.

The invention discloses a take-off and landing guiding method and device for a manned vertical take-off and landing aircraft, and the method comprises the steps: carrying out the automatic division of a flight guiding stage through the entering and exiting logic based on the flight height, the vertical speed and the horizontal speed; automatically activating a first guide mode in a vertical takeoff stage and a vertical landing stage according to a short-distance target point alignment principle, and automatically activating a second guide mode in an acceleration climbing stage, a cruise stage and a deceleration descending stage based on a track deviation and speed guide cooperation principle; respectively configuring special guidance symbols and general flight information of the first guidance mode or the second guidance mode; the guidance available state is combined, a corresponding guidance state notice is generated according to the flight guidance stage, and the guidance available state judgment basis comprises sensor data validity, GPS positioning accuracy not larger than a first preset value and inertial navigation system error smaller than a second preset value; according to the invention, visual and accurate flight guidance information meeting the requirements of different flight stages can be provided for pilots.

A primary guidance energy management method in the atmospheric layer of an aircraft comprises the steps of establishing a flight trajectory dynamic adjustment strategy based on real-time Mach number feedback in the rising stage of the aircraft, and when thrust is lower than a nominal value, adopting a trajectory height lifting strategy and utilizing potential energy reserve to compensate kinetic energy loss, meanwhile, energy efficiency optimization is achieved by reducing aerodynamic resistance; when the thrust is supernormal, the flight height is actively reduced, and dynamic deceleration is carried out through the strong damping effect of the dense atmosphere; in the pull-up section of the aircraft, an attack angle-ballistic inclination angle cooperative control algorithm is introduced, a cooperative energy management guidance method based on attack angle feedforward and ballistic inclination angle feedback is deduced through sensitivity analysis of an attack angle instruction of the pull-up section, and active dissipation of speed errors is achieved through nonlinear aerodynamic resistance generated by large-attack-angle flight. The method is particularly suitable for atmospheric guidance of hypersonic aircrafts, and a robust solution is provided for parameter uncertainty of a solid rocket power system.

The application provides a fixed-wing aircraft airspeed calibration flight test method based on a standard machine. The method comprises the following steps: determining the weight of the fixed-wing aircraft as a first weight, setting the aircraft to a specified take-off configuration, and taking off according to a take-off procedure; the standard machine flies to a specified airspace according to a plan; at an initial specified flight height, a tow cone is released to a specified length, and the tow cone can obtain an accurate static pressure value in the current area without being affected by a spoiler; the flap and slot wing configuration of the fixed-wing aircraft is set to a first flap and slot wing configuration; the aircraft is trimmed at a given speed; the speed in the above step is set to other speeds within the speed envelope of the first flap and slot wing configuration, and the steps are repeated; the standard machine obtains airspeed errors under the first flap and slot wing configuration and different speeds; and the airspeed errors under the first flap and slot wing configuration and different speeds are fitted to obtain an airspeed correction curve under the first weight, the first flap and slot wing configuration. More accurate airspeed errors can be obtained.

The invention provides a busy waypoint traffic capacity simulation evaluation method based on a release interval. The method comprises the following steps: step 1, preprocessing flight track data of a flight; step 2, extracting waypoint operation characteristic parameters; step 3, waypoint traffic capacity evaluation simulation; according to the method, traffic flow distribution conditions of different height layers at waypoints, passing-point flight release time interval distribution, aircraft model hybrid ratio and other characteristic data are counted based on historical data, a waypoint topological structure is combined, a busy flight height layer of a busy waypoint serves as an experimental scene, and the simulation evaluation method is constructed.

A UAV control method, a device, a UAV, and a storage medium are provided. The method includes: obtaining a UAV's take-off position; obtaining a height map of an area around the take-off position; determining height information of a highest target in the area around the take-off position based on the height map; determining a relative height between the highest target and the take-off position based on the height information of the highest target; determining a restricted flight altitude of the UAV relative to the take-off position based on the relative height, and controlling the UAV based on the restricted flight altitude; where the restricted flight altitude is greater than or equal to the relative height. It thus can ensure flight safety while offering more reasonable and user-friendly flight flexibility and freedom.

The invention discloses an unmanned aerial vehicle control method for territorial space planning, and relates to the technical field of unmanned aerial vehicle control, and the method comprises the steps: obtaining an attitude angle anomaly coefficient data set, a flight speed data set and a flight height data set of an unmanned aerial vehicle, calculating a flight stability coefficient data set of the unmanned aerial vehicle, and sending out a flight anomaly analysis instruction; after the flight anomaly analysis instruction is received, calculating a flight anomaly index of the unmanned aerial vehicle, and sending out a flight anomaly early warning of the unmanned aerial vehicle; after a flight abnormity early warning of the unmanned aerial vehicle is received, calculating an overlapping degree coefficient and an image quality coefficient of the image data, and calculating a sampling abnormity index of the image data; according to the method, the flight anomaly index of the unmanned aerial vehicle and the sampling anomaly index of the image data are acquired, the land data acquisition anomaly index is calculated, the re-flight position of the unmanned aerial vehicle is marked, and the unmanned aerial vehicle is controlled to perform data acquisition on the re-flight position again, so that the data anomaly position can be accurately positioned, and the accuracy and integrity of land data acquisition are ensured.

The invention provides a probabilistic load design method for an aerospace vehicle, which comprises the following steps of: 1, acquiring historical actually-measured high-altitude wind data of a single wind field as input, and generating a quasi-real-time wind correction trajectory according to the wind data; 2, adopting an active load shedding control scheme based on acceleration feedback to obtain an active load shedding control law; 3, performing six-degree-of-freedom Monte Carlo targeting flight simulation based on the quasi real-time wind correction trajectory, adding an active load shedding control law in simulation, calculating a static load of each section of the aerospace vehicle corresponding to each second point, and obtaining an axial force, a shearing force and a bending moment load of each station; and step 4, mapping the static load to a plurality of flight height layers of the aerospace vehicle, and carrying out statistics on load probability distribution at different flight heights to obtain a load envelope of each station along the axial direction of the aerospace vehicle under the condition of the single wind field. According to the method, multidisciplinary collaborative optimization is realized, and the design margin is reduced while the reliability is ensured.

The invention discloses a posture-controllable suspension mounting device for power station line inspection, and the device comprises a bag body which is used for providing buoyancy; the multiple driving rotor wings are arranged, and the driving rotor wings are evenly distributed in the circumferential direction of the capsule body; and the multi-sensing comprehensive detector is hung below the bag body through a connecting piece. The six-degree-of-freedom maneuvering ability is achieved through the buoyancy characteristic of the helium bag body carrier platform and the eight-rotor-wing propelling system with the eight driving rotor wings, the device can easily reach the position near overhead lines in complex terrain areas such as mountainous areas and river-crossing sections, and the constraint of the terrain on routing inspection work is eliminated; meanwhile, the flight height can be flexibly adjusted, lines with different erection heights can be close to each other in a short distance, a detection blind area formed due to the fact that traditional manual inspection cannot reach is effectively eliminated, and the space coverage rate of line inspection is greatly increased.

The present application relates to a kind of ground effect wing ship longitudinal coefficient estimation method and its aerodynamic characteristic analysis system, belong to the technical field of ground effect wing ship. It covers preliminary design ground effect wing ship scheme, design and manufacture wind tunnel model, obtain data by 3 times variable flight height test, and utilize these data to deduce the mathematical expression of ground effect wing ship longitudinal aerodynamic coefficient, estimate the longitudinal aerodynamic characteristic in any flight height state by the mathematical expression of ground effect wing ship longitudinal aerodynamic coefficient, to simplify test procedure, reduce test number. The present application significantly reduces the workload of model blowing test by combining theoretical analysis with a small amount of test data, shortens the research and development cycle, reduces the consumption of funds. At the same time, the method can accurately obtain the key partial derivative and relative ground effect height in the stability calculation of ground effect wing ship, improve the design efficiency and accuracy, and has important promoting effect on the development and application of ground effect wing ship technology.

Embodiments of the present invention relate to a method of controlling an aircraft and a flight control device for an aircraft, an aircraft with such flight control device and a storage medium. The method includes: determining a flight mode adopted by the aircraft in a non-static state; if the flight mode is an absolute hovering mode, determining a target speed of the aircraft according to a current flight speed, a current flight height and a first preset hovering height of the aircraft and a remote control speed set for the aircraft by remote control device; if the flight mode is a relative static hovering mode, determining the target speed of the aircraft according to a relative flight speed, the current flight height, a second preset switching hovering height and the remote control speed; and controlling the aircraft to fly according to the target speed.

The invention discloses a flying robot inspection system and method based on the Internet of Things, and relates to the technical field of big data analysis. Complete flight data of multiple devices of the same type and the same specification are screened, each inspection state characteristic parameter and the corresponding power consumption value are analyzed and separated in a structured mode, and a double power consumption value prediction mechanism is constructed; according to the method, data subsets are split by a flight state characteristic parameter factory, an exclusive service interface is configured, a first inspection power consumption value is output through a neural network model based on historical common data training, and a second inspection power consumption value is obtained through cooperative training by combining real-time parameters and recent historical data intercepted by a height return flight sliding window; the minimum inspection power consumption value needed by return flight is accurately calculated by constructing the return flight height mapping table, the return flight request is generated through comparison of the remaining electric quantity, the risks of contact loss and falling damage caused by insufficient electric quantity of the flying and climbing robot are effectively avoided, the safety and reliability of inspection operation are greatly improved, and stable application of equipment in complex scenes is guaranteed.

The application discloses an enhanced multi-strategy whale migration optimization UAV path planning method and system, and belongs to the technical field of civil path planning. The method comprises the following steps: constructing a three-dimensional path planning model of a mountainous environment; establishing a comprehensive objective function, wherein a highly relevant dynamic threat range model is adopted for threat cost, a flight height is adopted for dynamic adjustment of a threat source influence radius, and a flight stage is adopted for adaptive adjustment of weight coefficients of each cost item; S3 adopts an initialization strategy based on a good point set theory to generate an initial candidate path, and adopts a golden section ratio to generate an initial population with uniform distribution; S4 adopts an enhanced multi-strategy whale migration optimization algorithm for iterative optimization, calculates a population diversity index D(t), and adaptively selects a Lévy flight strategy or a Cauchy distribution disturbance strategy according to comparison between D(t) and a preset threshold value and a current iteration number; and S5 judges a termination condition and outputs an optimal path. The application improves the safety and efficiency of path planning.

The invention provides an active pneumatic control system based on an electroactive polymer fiber array and a miniature flight detection device, belongs to the technical field of miniature robots and intelligent materials, and aims to solve the problem that a passive wind power aircraft cannot be actively controlled. The control system comprises a fiber array composed of a plurality of independent EAP flexible fibers, and a control module capable of applying accurate electric signals to specified fibers. The electric signals drive the fibers to generate reversible deformation, so that the collective pneumatic form of the fiber array is changed. The detection device mainly comprises a detector main body, a fiber system and an attitude control system. The fiber system is composed of a fiber array and is unfolded in a natural state to form a windward sail face providing pneumatic elasticity. The attitude control system symmetrically or asymmetrically drives the fiber array through a control module, changes the three-dimensional configuration of the sail surface, adjusts the aerodynamic characteristics in real time, and achieves the precise control of the flight height and direction. The passive aircraft is suitable for a deep space exploration environment.