307results about How to "Full Coverage Guaranteed" patented technology

The invention relates to the technical field of data management, in particular to an intelligent supervision method and system based on big data, and the method comprises the following steps: S1, multi-source data collection: collecting multi-source data in real time; s2, data preprocessing and spatio-temporal feature extraction: preprocessing the collected multi-source data, and extracting spatio-temporal features from the preprocessed multi-source data; s3, performing multi-dimensional risk assessment based on spatial-temporal characteristics: performing risk assessment on behaviors and states of the supervision objects by applying a multi-dimensional risk assessment algorithm; s4, dynamic early warning: in combination with a preset early warning rule, automatically triggering dynamic early warning, and providing a corresponding risk coping suggestion; and S5, supervision strategy optimization: optimizing and updating a supervision strategy through a self-learning mechanism based on a risk assessment result and feedback of dynamic early warning. According to the invention, the accuracy and response speed of risk identification are improved, so that the supervision work is more flexible and efficient.

The invention discloses a multi-unmanned aerial vehicle maritime search and rescue path planning method based on multi-target particle swarm optimization. The method comprises the steps that S1, an area to be searched and rescued is converted into a two-dimensional search and rescue area; s2, performing grid decomposition on the two-dimensional search and rescue area; s3, obtaining a probability map through a Gaussian mixture model; s4, establishing an unmanned aerial vehicle search and rescue multi-target collaborative optimization function; s5, solving the function based on a hybrid particle swarm optimization algorithm to obtain an optimal solution; and generating a specific search and rescue path of the unmanned aerial vehicle according to the solved optimal solution. According to the method, an unmanned aerial vehicle search and rescue multi-target collaborative optimization function is established, the unmanned aerial vehicle is guided to execute the search and rescue task by taking resource balanced allocation, maximum path safety, preferential coverage of a high-risk area and minimum energy consumption as targets, task allocation, path planning and energy management are improved, multi-target optimization of multi-unmanned aerial vehicle search and rescue path planning is realized, and the search and rescue efficiency is improved. An accurate flight path is formulated for each unmanned aerial vehicle, comprehensive coverage of search and rescue tasks is ensured, and the search and rescue efficiency and success rate are remarkably improved.

The invention discloses an intelligent construction site safety monitoring method and system fused with a multi-modal large model, and relates to the technical field of building construction.The method comprises the steps that based on a Linux system platform, an Nginx server is used as a static website server to be combined with a camera to request video stream data, a client side and the Nginx server are connected, configuration is conducted according to a configuration file, and the Nginx server is connected with the client side; and sending response data according to an HTTP request of the client, and carrying out video online monitoring and image recognition real-time processing on the construction area. According to the invention, through detailed scene division and targeted safety guide formulation and in combination with a visual language model-based few-sample scene identification method, different scenes can be accurately identified, and it is ensured that monitoring meets actual requirements; through cooperation of the personnel article wearing detection module and the article attribute detection module, deep and comprehensive monitoring of personnel protection equipment and behaviors is realized; depth estimation and three-dimensional collision detection ensure full coverage of a monitoring scene.

The invention provides a water body image splicing method and device based on cooperation of an unmanned aerial vehicle and an unmanned ship, and belongs to the technical field of image processing, and the method comprises the steps: determining a first driving path of the unmanned ship based on a shooting region and a preset image splicing proportion, determining a second driving path and a plurality of shooting center points of the unmanned aerial vehicle based on the first driving path; calculating an image offset based on a plurality of water area images collected by the unmanned aerial vehicle at the plurality of shooting center points; the image offset is the offset between the position of the unmanned ship in the image and a plurality of shooting center points; and splicing the plurality of water area images based on the image offset. According to the water body image splicing method and device based on cooperation of the unmanned aerial vehicle and the unmanned ship provided by the invention, the problems that the images deviate and cannot be spliced when a large-area water area is monitored in the prior art can be solved.

The invention relates to the field of hybrid power transmission line fault maintenance, in particular to a sectional type multi-sensor detection hybrid power transmission line fault rapid positioning and diagnosing system, which comprises the following modules: a distributed fault positioning module, a fault diagnosis module, a fault diagnosis module and a fault diagnosis module, rapidly positioning a fault point according to the instantaneous traveling wave signal of the line by adopting a traveling wave measurement technology; and the data acquisition and transmission module is used for summarizing the line instantaneous traveling wave signal data acquired by each sensor and transmitting the data to the intelligent data analysis platform. Through the distributed fault positioning module, a fault point can be quickly positioned in an extremely short time, the fault searching time is greatly shortened, the emergency response capability of a power grid is improved, the overall coverage of the whole hybrid power transmission line is ensured through the installation mode of the distributed sensor, and no matter which position the fault occurs, the fault point can be quickly positioned. And fault signals can be captured and processed in time.

The invention provides an unknown target collection-oriented mobile robot motion planning method. The method comprises the following steps of S1, synchronously constructing a grid map in a moving process of a mobile robot; s2, extracting a boundary region and a passable region; s3, the mobile robot continuously explores the environment; s4, the exploration degree of the local environment is judged according to the balance function; s5, if the exploration of the local environment is completed, the mobile robot collects targets in the task area; s6, the mobile robot completes ascertainment of the sub-regions and region coverage collection; step S7, when all unknown environments are detected and all task area targets are collected, the unknown target collection task is completed; the unknown target collection motion planning method of the mobile robot is good in performance, the mobile robot can rapidly complete exploration of an unknown environment and collection of targets in a task area, and task requirements can be effectively met.

The invention relates to a radiation control method and device applied to a mobile C-shaped arm, equipment and a medium, and the method comprises the steps: obtaining the radiation data of each direction of a to-be-detected region corresponding to a skeleton instrument, and determining the radiation intensity of the to-be-detected region according to the radiation data of each direction; under the condition that the radiation intensity exceeds a preset threshold value, according to a difference value between the radiation intensity and the preset threshold value, obtaining an adjustment parameter through a trained neural network PID model; and adjusting operation parameters of the skeleton instrument according to the adjustment parameters. The C-shaped arm skeleton instrument has the effect of improving the anti-radiation performance and safety of the C-shaped arm skeleton instrument.

The invention relates to the technical field of intelligent monitoring, in particular to a large-scene multi-target on-site holographic intelligent monitoring comprehensive management system, which comprises a device determination module, a plurality of initial monitoring devices and a control module, the model construction module obtains and analyzes a plurality of initial monitoring video data, and constructs an initial monitoring model; the grade determination module determines an initial number of preset monitoring targets and determines an initial importance grade; the anomaly recognition module determines an initial monitoring frequency, performs monitoring based on the initial monitoring frequency, and recognizes an initial anomaly event based on an initial monitoring result; the degree analysis module analyzes the initial abnormal event and gives an alarm based on the comparison result of the initial severity, or adjusts the initial monitoring frequency, monitors the sub-region corresponding to the abnormal event in real time based on the adjusted monitoring frequency, analyzes the real-time monitoring result, gives an alarm based on the analysis result, or continues monitoring. According to the invention, the comprehensive accuracy of monitoring is improved.

The invention provides a test method and device, and the method comprises the steps: obtaining a code submission record; determining a code change file based on the code submission record; performing calling relation analysis on the code change file to determine a target interface influenced by code change; wherein the target interface is an externally exposed interface influenced by code change; searching a target test case associated with the target interface from existing test cases; and testing based on the target test case to obtain a test result. According to the method, the interface influenced by the code change is identified based on the code submission record, and the proper test case is searched from the existing test cases based on the influenced interface, so that the comprehensive coverage of the influenced area can be ensured, the test accuracy is improved, and the completeness of the test scene and the test quality can be ensured under the condition that the software complexity is increased.

The invention discloses an unmanned aerial vehicle self-adaptive inspection method based on multi-layer characterization learning, which comprises two stages of automatic coarse inspection and self-adaptive fine inspection, and learns the space structure, component characteristics and disease characteristics of a bridge layer by layer. In the automatic rough detection stage, in combination with a spatial clustering post-processing method and a point cloud semantic segmentation network, instance attributes of bridge components are quickly learned. Then, the point cloud space is compressed and converted by using a simulation view field model and a dimension reduction technology, and the unmanned aerial vehicle is guided to carry out efficient and comprehensive space patrol in plane geometry. In the adaptive fine detection stage, a space-channel two-dimensional optimized hybrid convolution structure Light-PVIT is utilized to learn and extract disease features in the automatic coarse detection stage as prior information. The information guides the unmanned aerial vehicle to carry out fine detection on a disease area in a small field of view. According to the unmanned aerial vehicle self-adaptive inspection method, the bridge inspection efficiency and precision are remarkably improved, and reliable technical support is provided for bridge maintenance work.

The invention relates to the technical field of image processing, and discloses an autonomous exploration method, device and equipment of a small unmanned aerial vehicle, and a storage medium. The method comprises the following steps: performing three-dimensional rasterization processing on a closed pipeline environment to obtain a three-dimensional grid map represented by voxels; performing classification marking processing on the three-dimensional grid map to obtain a classification map containing idle voxels, occupied voxels and unknown voxels; performing local exploration planning processing on the classification map to obtain a local unmanned aerial vehicle exploration path; performing global exploration planning processing on the classification map to obtain a global unmanned aerial vehicle exploration path; and performing real-time execution and dynamic adjustment processing on the local unmanned aerial vehicle exploration path and the global unmanned aerial vehicle exploration path to obtain closed pipeline exploration data. According to the invention, the autonomous exploration efficiency and accuracy of the small unmanned aerial vehicle are improved.

The invention relates to the technical field of grassland monitoring, in particular to an adjustable grassland remote sensing monitoring system and method, and the system comprises a data preprocessing module, a variation trend analysis module, a self-adaptive remote sensing parameter configuration module, a grassland monitoring network layout optimization module and a remote sensing observation and intelligent estimation module. The data preprocessing module integrates historical remote sensing and ground actual measurement data and provides a data basis for subsequent analysis; the change trend analysis module calculates the change rate and the standard deviation of the key features and identifies the change trend of the grassland ecological environment; the adaptive remote sensing parameter configuration module adaptively adjusts remote sensing monitoring parameters, and the monitoring efficiency is improved; the grassland monitoring network layout optimization module optimizes the layout of the remote sensing detection unit and improves the efficiency of the monitoring network; and remote sensing observation and intelligent estimation use a spatial interpolation method to estimate the value of a future observation point, so that the workload of field measurement is reduced. The method is used for solving the technical problem that the current grassland monitoring management effect is poor.

The invention belongs to the technical field of artificial intelligence and coal mine production, and particularly relates to a coal gangue detection method based on multi-angle perception and mixed scale Transform feature aggregation, which comprises the following steps: firstly, acquiring a real-time video image of a conveying belt through a multi-angle camera device, and fully covering each area on the conveying belt; secondly, performing feature extraction and aggregation on the video image by adopting a mixed scale Transform model, fully fusing feature information under different scales, and enhancing the recognition capability of the model on the coal gangue; and finally, the aggregation features are analyzed by using a coal gangue detection algorithm, and high-precision coal gangue detection is realized. Real-time video images of the conveying belt are obtained through the multi-angle camera device, all areas of the conveying belt are fully covered, and therefore any blind area and any dead angle are eliminated. Advanced image preprocessing technologies such as de-noising and image enhancement are combined, so that the definition and detail performance of the image are remarkably improved.

The invention discloses a production optimization method and system for animal blood-made protein powder, particularly relates to the technical field of production monitoring, and aims to solve the problem that the existing method is difficult to effectively identify the potential hidden danger of the cavitation effect caused by ultrasonic waves in the production process of the animal blood-made protein powder. The method comprises the following steps: capturing harmonic characteristics of ultrasonic signals, and identifying an acoustic energy dense region in combination with a spectrum analysis algorithm; constructing a turbulence disturbance intensity graph model, and analyzing the distribution characteristic change of the dissolved gas in combination with a graph embedding learning algorithm; determining a cavitation potential risk area based on the identified first and second potential risk areas; in the cavitation potential risk area, the comprehensive influence of the bubble group synergistic effect and the heat effect is evaluated by analyzing the complexity of bubble interaction energy distribution and the diffusion degree of local high temperature; and finally, determining a cavitation hidden danger caused by ultrasonic waves by calculating a cavitation influence coefficient, and optimizing production process parameters according to a determination result.

The invention discloses a hydraulic power plant safety inspection method and system based on a block chain technology, and relates to the technical field of block chains, and the method comprises the steps: processing inspection data, equipment sensor data and environment data through the block chain technology; routing inspection task scheduling is carried out based on a particle swarm optimization algorithm; performing matching analysis on the inspection data by using an improved dynamic time warping algorithm; and providing inspection adjustment suggestions and equipment maintenance suggestions according to the analysis result. According to the method, the block chain technology is adopted to record the inspection data, so that the integrity and the real-time performance of the data are ensured, human errors and data omission are reduced, and the data processing efficiency is improved; and by adopting a particle swarm optimization algorithm, according to actual inspection requirements and resource limitation, an inspection plan is dynamically adjusted, task allocation and path planning are optimized, and the inspection efficiency and the coverage rate are improved.

The invention relates to the technical field of building maintenance management, and discloses a building use process maintenance management system and method based on artificial intelligence, and the system comprises a building maintenance control module, a building maintenance problem recognition processing module, and a building maintenance problem output module. An unmanned aerial vehicle carries a cloud lens to accurately collect an outer wall state image of a real-time inspection position of a building outer wall, and intelligent identification of a damage problem type of the building outer wall is carried out by combining an intelligent search algorithm and scientifically preset image information of different building outer wall damage types; based on an artificial intelligence algorithm, building outer wall damage type identification information and standard stored different building outer wall damage type repair process information are combined to carry out intelligent assessment on a damage repair scheme of the building outer wall, and meanwhile, building outer wall damage position coordinates are searched autonomously; intelligent data analysis of a building outer wall damage repair scheme and a damage position is realized, and intelligence and reliability of building maintenance operation are improved.

The invention relates to the technical field of plate processing, in particular to a plate laminating deviation rectifying method, a deviation rectifying assembly and a plate processing device. The method comprises the following steps: firstly, obtaining the offsets of a film in an unwinding section, a gluing section and a fitting section, calculating the offset degree x and the offset speed S according to the offsets of three positions, then comparing S with an offset speed threshold value S1, if S is greater than S1, increasing the gluing width, then controlling a plate to rotate nX / N along the offset direction of the film, and finally, adjusting the offset degree x and the offset speed S to be equal to the offset degree x; and the film releasing roller is controlled to move (N-n) A / N in the axial reverse deviation direction, that is, the relative deviation degree of the film and the plate becomes zero by adjusting the film and the plate at the same time, and finally the gluing assembly is controlled to move nB / N in the deviation direction, and the gluing width is reduced. According to the offset degree and the offset speed of the thin film, the positions and the gluing width of the plate, the film releasing roller and the gluing assembly are adjusted, the redundancy of the thin film and the thin film gluing area arranged for coping with the offset of the thin film is reduced, and therefore waste of materials is reduced.

The invention provides a deslagging device and method for vertical shaft construction, and belongs to the technical field of vertical shaft construction auxiliary equipment.The deslagging device for vertical shaft construction comprises a sliding supporting mechanism, a well mouth supporting mechanism, a rotating disc, a plurality of slag shoveling mechanisms, a plurality of transverse conveying mechanisms and a longitudinal conveying mechanism located in the middle of a vertical shaft; the sliding supporting mechanism is arranged in the vertical shaft in a sliding mode and fixed to the designated position of the shaft wall through an abutting piece. The well mouth supporting mechanism is installed at the well mouth position of the vertical shaft and provided with a lowering assembly used for lowering the sliding supporting mechanism into the vertical shaft. The rotating disc is rotationally installed on the face, facing the shaft bottom of the vertical shaft, of the supporting frame, the multiple slag shoveling mechanisms are distributed at the bottom of the rotating disc in the circumferential direction of the rotating disc, the multiple transverse conveying mechanisms are correspondingly arranged on one sides of the slag shoveling mechanisms and used for conveying the slag to the longitudinal conveying mechanism, and the longitudinal conveying mechanism is used for conveying the slag out of the vertical shaft. The slag discharging efficiency can be improved, and meanwhile the slag discharging device is not limited by slag characteristics and using conditions.

The invention discloses a literature review generation method and device, electronic equipment and a readable storage medium. The method comprises the following steps: acquiring a review theme and a plurality of literatures; clustering processing is conducted on the multiple literatures, multiple literature clusters are generated, and each literature cluster comprises at least two similar literatures; generating a chapter text corresponding to each literature cluster through a large language model based on the overview theme and the plurality of literature clusters; and generating a literature review based on the plurality of chapter texts. Through the combination of the clustering technology and the large language model, the problem that the input length is limited when the large language model generates the review is solved, and the efficiency and quality of literature extraction are effectively improved.

The invention discloses a purification method and a purification device for crystallized magnesium, and relates to the field of magnesium metal smelting. The method comprises the following steps: under the protection of an inert atmosphere, firstly carrying out pressure-applying melting treatment on a magnesium material to be smelted, and then carrying out pressure-applying filtering treatment on a product obtained after the melting treatment, so as to complete the flux-free smelting process of the magnesium material. And meanwhile, the metal magnesium liquid and most of the oxide shells are separated by utilizing the liquidity difference between the liquid metal magnesium and the solid oxide shells. Compared with a conventional smelting process without pressure application, the method has the advantages that the melting rate of the crystallized magnesium can be remarkably increased, most of oxide impurities are removed, a series of pollution problems caused by flux use are solved from the source, and low-cost, high-efficiency and high-quality smelting of the crystallized magnesium is realized.

The invention relates to an offshore wind turbine large-diameter steel pipe pile scouring solidified soil cover protection and construction method, a reinforcing steel cylinder is arranged in a scouring pit at the bottom of a wind turbine steel pipe pile, the wind turbine steel pipe pile can be effectively protected, and direct scouring of water flow to the wind turbine steel pipe pile is avoided; an annular reinforcing mesh is arranged below the solidified soil quilt, and underwater concrete is injected into the annular reinforcing mesh, so that the injected underwater concrete is prevented from being scoured and taken away by water flow, and the durability of the reinforced structure is improved; the solidified soil is integrally put down in place through the suspension support, so that the situation that wrinkles appear when the solidified soil sinks to the water bottom is avoided, and it is effectively guaranteed that the solidified soil covers the scouring pit; the fan steel pipe pile is sleeved with the suspension support through the floating steel cylinder, the suspension support is controlled to float and sink along the fan steel pipe pile by adjusting the air bag, and the problems of hoisting and positioning are effectively solved.

The invention provides a software demand document analysis and test case automatic generation method and system based on a large language model, and the method comprises the following steps: obtaining a software demand document, and analyzing the software demand document to obtain analysis information; carrying out blocking on the analysis information to obtain blocking information; generating a corresponding cue word based on the block information and a test case design method specified by a user to call a large language model, and generating a test case corresponding to the block information based on the cue word; summarizing and formatting the test cases and then displaying the test cases; according to the method, the efficiency and accuracy of test case writing are remarkably improved, the test coverage range is expanded, and the method flexibly adapts to demand changes, so that the software test process is optimized.

The invention provides a falling-into-water identification method based on artificial intelligence, and belongs to the technical field of target identification. Preprocessing the data; water area detection; target detection and posture recognition; behavior recognition and early warning; identifying a drowning state; and real-time alarm and cloud processing are carried out. By combining target detection, human body posture recognition, behavior recognition and early warning technologies, the invention provides an efficient, accurate and real-time drowning recognition method, various defects in the prior art are overcome, and the intelligent level of water area safety monitoring is remarkably improved.

The invention discloses a full-coverage path planning method and system for a cleaning robot, and relates to the technical field of cleaning robots, and the method comprises the steps: recording a track through edge cleaning, forming an edge track grid, and expanding to construct an edge map; then, determining a bow scanning direction based on a map, and searching and pairing bow scanning path points to form a complete path point set; the robot selects a bow-sweeping starting point according to the current pose, determines the main sweeping direction and the supplementary sweeping direction, and executes bow-sweeping path sweeping; after sweeping is completed, path points which are not swept are detected in sequence, and a new arch sweeping starting point is selected for iterative sweeping; in the process, the robot can collect obstacle information in real time for obstacle avoidance replanning, and it is ensured that cleaning is not omitted. Through accurate path planning and an intelligent obstacle avoidance strategy, the cleaning efficiency and the coverage rate of the cleaning robot are improved, the method is suitable for various complex environments, full automation and intelligence of cleaning operation are achieved, and the user experience is greatly improved.

A fiber composite material compression strength estimation method based on 3D printing comprises the following steps: collecting sample data, determining process parameters, preparing a sample, and compressing, testing and recording data; preprocessing the original data to form a data set; secondly, constructing a recurrent neural network model, capturing a long-term dependency relationship by utilizing the sequence data processing capability of the recurrent neural network model to estimate the strength, training through a training set, optimizing the performance by using a verification set, and evaluating through a test set to determine a final model; and finally, inputting new sample material characteristics and printing parameters into the model to obtain an intensity estimation value. The method has an effective evaluation verification and updating mechanism, and can adapt to different environments and material characteristic changes.

The invention discloses a radiotherapy planning method and system based on biological optimization, and the method comprises the steps: carrying out the fusion of a positron emission computed tomography (PET) image and a computed tomography (CT) image, carrying out the sketching of a biological target region according to the threshold value of a developer standard uptake value (SUV), and meanwhile, carrying out the sketching of an endangered organ; setting physical constraints for the biological target region and the organ at risk, and performing primary optimization to obtain a primary dose result; setting biological constraints for the biological target region and the organ at risk based on the primary dose result; and constructing an objective function containing a biological constraint penalty term and a physical constraint penalty term, and obtaining a final radiotherapy plan through iterative optimization. According to the method, a biological target region is used for replacing a traditional target region, a tumor region is depicted finely, a plan optimization model combining biological constraint and physical constraint is used, the dose coverage of the target region can be ensured, meanwhile, the dose of a crisis organ is reduced, and finally a plan meeting clinical requirements is generated.

The utility model relates to a welding smoke purification device which comprises a workbench, an air draft assembly used for conducting air draft on the upper end face of the workbench is arranged on the workbench, the air draft assembly comprises an air draft part, an adjusting assembly used for adjusting the position of the air draft part, an air pump and an air draft pipe, and the adjusting assembly is arranged on the workbench; the adjusting assembly comprises a supporting frame, a rotating part and a sliding part, the lower end of the supporting frame is fixedly installed on the workbench, the upper end of the rotating part is rotationally connected to the lower end face of the supporting frame along the horizontal plane, and the sliding part is slidably arranged on the rotating part in the length direction of the rotating part; the side, close to the workbench, of the air draft part is provided with an air draft opening used for allowing smoke to enter the air draft part, one end of the air draft pipe communicates with the air draft part, and the air pump is arranged at the end, away from the air draft part, of the air draft pipe.

The invention relates to the technical field of unmanned aerial vehicles, discloses an unmanned aerial vehicle operation method, an unmanned aerial vehicle and a storage medium, and is used for solving the problem that original route planning is not matched with a target land parcel. The unmanned aerial vehicle operation method comprises the following steps: acquiring an original route plan and land parcel information of a target land parcel, wherein the original route plan comprises a plurality of parallel route segments with the same spacing; according to the original route plan and the land parcel information, determining whether the original route plan satisfies a land parcel coverage condition; if the original route plan does not meet the plot coverage condition, determining a to-be-adjusted route segment from the plurality of route segments; the original parameters of the to-be-adjusted route segment are adjusted to obtain a target route plan, and the original parameters at least comprise the broadcast breadth; and controlling the unmanned aerial vehicle to work based on the target route plan.

The invention discloses a device and a method for improving the reliability of a thermocouple at a channel cooling section in a temperature rise stage, and belongs to the technical field of substrate glass manufacturing. The device effectively solves the problem of fixing the thermocouple by forming a notch in a thermocouple piece and arranging the thermocouple in the notch of a groove-shaped structure, so that the reliability of the thermocouple is improved. And the device is more stable and reliable in the use process. The notch is bent upwards, so that a local cavity is formed between the interior of the notch and the cooling pipe body, and the cavity structure is enough for flexible movement of a thermocouple temperature measurement spot welding point. The position of a temperature measuring point of the thermocouple is crucial to the accuracy of a measuring result. According to the device, the root of the thermocouple (the temperature measuring point of the welding type thermocouple) is accurately arranged in the notch, so that good contact between the temperature measuring point and a measured object is ensured, and the temperature measuring accuracy is improved. Through the sliding thermocouple structure, the problem of large-area damage of the top thermocouple in the temperature rise stage is solved, and the reliability of the thermocouple is improved.

The invention relates to the field of unmanned aerial vehicle coverage control and image quality optimization, and discloses an image quality optimization control method for covering an aerial photography area by a multi-unmanned aerial vehicle system, which comprises the following steps: S1, establishing an image quality function based on pixel density and camera view angle, the description module is used for describing the coverage effect of the multi-unmanned-aerial-vehicle system in the convex polygon area; s2, task area division: dividing the task area of each unmanned aerial vehicle by adopting an extended Voronoi segmentation method; and S3, designing a distributed controller, and realizing local optimal deployment of the unmanned aerial vehicle based on the designed distributed controller. A new image quality function is introduced, and the coverage control of the multi-unmanned aerial vehicle system is optimized by combining the pixel density and the lens distortion, so that the defect that the characteristics of an optical camera are not fully considered in the prior art is overcome, and the optimal deployment of the unmanned aerial vehicle is realized. And the quality of the aerial image and the complete coverage of the target area are obviously improved.