55 results about "Area coverage" patented technology

The invention relates to a wide-area coverage area high-precision deformation monitoring method based on an InSAR technology, and the method comprises the steps: obtaining the InSAR monitoring data of a plurality of data sources for a wide-area coverage area, carrying out the registration of the InSAR monitoring data, screening interference pairs according to the coherence, carrying out the interference pair combination of a single-view complex image set obtained through registration, and obtaining a single-view complex image set; performing time sequence analysis according to the interference pair combination result to generate a time sequence interference image; performing phase filtering and phase unwrapping on the time sequence interference image; for the time sequence interference image after phase unwrapping, baseline parameters are corrected based on a nonlinear least square method, and atmospheric delay errors are corrected based on a GACOS atmospheric delay model; according to the processed image, constructing a wide-area surface deformation rate map and a preset application scene surface deformation rate map, and analyzing the spatio-temporal evolution law of the wide-area surface deformation rate map and the preset application scene surface deformation rate map; and finally, visually displaying the wide-area surface deformation rate diagram, the preset application scene surface deformation rate diagram and the spatio-temporal evolution law analysis result.

The invention relates to the technical field of intelligent control of engineering machinery, and provides a tower crane hoisting whole process dynamic mapping and sensing coverage method and system. The method comprises the following steps: respectively mounting two rotary radars on a rotatable bracket of the tower crane; the current hoisting operation stage of the tower crane is obtained in real time; switching a shooting view angle of the double-radar module according to the hoisting operation stage, and controlling the double-radar module to obtain continuous point cloud data of the corresponding operation stage; tower crane operation parameters are collected, and continuous lifting hook tracks are generated in combination with continuous point cloud data obtained by the double-radar module; identifying a dynamic obstacle and a static background contained in the target monitoring space from the continuous point cloud data, and constructing a construction environment point cloud model; performing space-time registration on the construction environment point cloud model and the physical coordinate system, and establishing a global dynamic map; and a dynamic sensing area coverage map is constructed by fusing the continuous lifting hook track and the global dynamic map, so that the real-time sensing of the space environment of the tower crane hoisting operation is realized.

The invention discloses a convex area coverage path planning method and system for an autonomous sweeper, which are applied to the technical field of path planning of autonomous mobile robots, and the method comprises the steps: generating an area coverage parallel track through a self-adaptive direction track generation algorithm based on a rotary caliper; the method comprises the following steps: constructing a GTSP model based on a region coverage parallel track, and standardizing the GTSP model into an ATSP model by adopting Noon-Bean conversion; and solving the ATSP model by adopting an LKH-VNS hybrid search algorithm to obtain a path planning result. According to the method, efficient and intelligent path planning is realized through adaptive direction orbit generation, standardized modeling from the GTSP to the ATSP and collaborative optimization of the LKH-VNS hybrid search algorithm.

The invention provides a fixed-wing unmanned aerial vehicle cooperative area coverage monitoring optimization deployment method. The method comprises the steps of determining an effective coverage area of multi-unmanned aerial vehicle combined area coverage monitoring according to a space detection probability of an unmanned aerial vehicle to a target and a time monitoring probability generated by operation of the unmanned aerial vehicle; determining deployment parameters of an effective coverage area according to two-machine parallel and cooperative area coverage monitoring; and according to the deployment parameters of the effective coverage area, establishing a gridding multi-machine collaborative area coverage monitoring deployment scheme taking a square as a unit. According to the invention, through the space detection probability and the time monitoring probability, the effective coverage area of multi-aircraft joint area coverage monitoring can be determined more comprehensively and accurately, theoretical support is provided for flexible application of the multi-fixed-wing unmanned aerial vehicle in area coverage monitoring scenes such as border patrol and disaster rescue, and a multi-aircraft cooperative area coverage monitoring deployment scheme has the advantages of high efficiency and high reliability. The effective monitoring area is increased, the number of used unmanned aerial vehicles is reduced, and the cooperative efficiency of the unmanned aerial vehicle cluster is effectively improved.

A system and method that automatically monitors product use, such as the type and amount of agricultural and / or horticultural product stored in and dispensed from a cartridge over time and / or by geographic location. Monitored data are stored in memory such as a tag on the cartridge and may be transmitted to a server for storage, aggregation, and analysis. The cartridge may be authenticated before being authorized for use for the benefit of a current user in dispensing the product. The cartridge may be refilled after confirmation of authorization codes on the cartridge and refilling equipment tags. The cartridge may be calibrated automatically based on the bulk density or other parameter of the product in the cartridge. Data may be aggregated from a plurality of cartridges automatically. As-applied data from individual cartridges may be used to verify, independent of operator input, treated area coverage and product application rate.

The application relates to the technical field of intelligent control of engineering machinery, and provides a tower crane hoisting whole-process dynamic mapping and perception coverage method and system. The method comprises the following steps: installing two rotating radars on rotatable supports of a tower crane; acquiring a current hoisting operation stage of the tower crane in real time; switching the shooting angles of the two radar modules according to the hoisting operation stage, and controlling the two radar modules to acquire continuous point cloud data of the corresponding operation stage; collecting tower crane operation parameters, combining the continuous point cloud data acquired by the two radar modules to generate a continuous hook trajectory; identifying dynamic obstacles and static backgrounds contained in a target monitoring space from the continuous point cloud data, and constructing a construction environment point cloud model; performing space-time registration on the construction environment point cloud model and a physical coordinate system, and establishing a global dynamic map; fusing the continuous hook trajectory and the global dynamic map to construct a dynamic perception area coverage map, and realizing real-time perception of the space environment of the tower crane hoisting operation.

The invention relates to an air route planning method for multi-machine area coverage search based on an improved K-Means algorithm. The method comprises the following steps: using an improved mixed K-Means clustering division strategy; the method comprises the following steps: dividing a target area into a plurality of sub-areas, taking projection points of a starting point and an ending point of multi-unmanned aerial vehicle cooperation at the boundary of the target area as fixed clustering centers, automatically selecting initial values of other clustering centers, and determining a polygonal boundary of the sub-area corresponding to each clustering center based on all the clustering centers; on the basis of preset unmanned aerial vehicle path parameters and polygon boundary information, generating a broken line type coverage path with the minimum total cost for each sub-region, and obtaining a path point sequence of each sub-region; and for the path point sequence of each sub-region, according to a minimum turning radius constraint condition, obtaining a smooth airway path satisfying kinematics constraint. According to the method, the technical problem that the adaptability is insufficient due to the fact that the coverage integrity cannot be guaranteed and path flight cannot be considered in the existing scheme is solved.

The application provides a full-area coverage path planning method and device for a mowing robot, a terminal and a medium. The method comprises the following steps: abstracting an environment map by setting a virtual boundary line of one or more target mowing areas; determining a long-axis direction of a bow shape for each target mowing area and rotating each target mowing area; dividing the one or more target mowing areas into one or more sub-areas based on the boundary points of the rotated target mowing areas; performing path planning for each target mowing area based on the long-axis direction of the bow shape of the target mowing area; and connecting the bow-shaped paths of the target mowing areas based on a navfn algorithm to obtain a full-area coverage path corresponding to the environment map. The application can realize full-area coverage path planning, has a high coverage rate even for a complex mowing area, has a low repetition rate, and greatly increases the path planning efficiency of the mowing robot.

This invention relates to a multi-satellite joint regional coverage planning method based on an improved multi-objective evolutionary algorithm, comprising the following steps: decomposing the area to be covered into discrete strip sets of all remote sensing satellites based on the imaging conditions of each satellite; binary encoding the strips in the discrete strip sets, using all encoded individuals as input to the improved multi-objective evolutionary algorithm, which employs a combination of the NSGA-III and S-CDAS algorithms to achieve an extreme solution preservation mechanism; constructing a multi-objective optimization model composed of multiple objective functions, and solving the multi-objective optimization model using the improved multi-objective evolutionary algorithm to obtain the regional coverage result. The improved multi-objective evolutionary algorithm in this invention can preserve extreme solutions, thus achieving satisfactory regional coverage results, and can also optimize the rationality of the regional coverage scheme from other objective dimensions.

The invention provides a message relay forwarding method based on vehicle-road cooperation, and aims to solve the problem that RSU (road side unit) or OBU (on-board unit) cannot effectively receive target information due to shielding, signal interference and other factors. The method comprises the following steps: firstly, comprehensively evaluating the communication quality of peripheral communication equipment to obtain key indexes including signal strength (RSSI), signal-to-noise ratio (SNR), bit error rate (BER) and the like; and screening out a reliable vehicle list of which the communication quality meets the requirement based on an evaluation result. And then, a K-means clustering algorithm is adopted to perform clustering processing on surrounding reliable vehicles, and a clustering number range (such as 1-K) is limited, so that the effectiveness and coverage rationality of a clustering result are ensured, and over-scattered vehicle distribution is avoided. In each cluster, a vehicle located or closest to the cluster center is selected as a relay node, and the relay node broadcasts target information, so that message diffusion in each cluster coverage area is efficiently realized. According to the mechanism, the area coverage capability and the service reliability of the target information are remarkably improved.

This invention provides a method for optimizing unmanned surface vessel (USV) area coverage paths based on constrained reinforcement learning, belonging to the technical field of autonomous navigation and path planning for marine unmanned systems. Each USV acts as an intelligent agent, and the USV area coverage path optimization problem is modeled as a constrained Markov decision process. The constraint condition is that the difference between the optimized path and the planned path is within a preset area. The reinforcement learning framework consists of: a policy network outputting an action probability distribution based on the current environmental state; a reward evaluation network evaluating the expected rewards of states and actions; and a cost evaluation network evaluating the expected cumulative cost of state-action pairs. With the goal of maximizing policy entropy and expected rewards, the penalty strength of the cost constraint is dynamically adjusted using Lagrange multipliers, jointly optimizing the policy network, reward evaluation network, and cost evaluation network. The minimum coverage requirement is modeled as a hard constraint condition for policy optimization, ensuring navigation safety and the integrity of the mission area coverage.

This invention relates to a method, device, and medium for multi-agent coverage search and task allocation path optimization. The specific method includes: scenario construction and problem description, which describes the characteristics of the task area, the attributes of agents and targets, and clarifies the area coverage search problem and the target task allocation problem; area coverage model design, which establishes a minimum task time model objective function and constraints, and then solves the area coverage model; and task allocation strategy and path planning algorithm, which, considering agent speed and target attributes, combines a greedy strategy and a genetic algorithm to allocate target exploration tasks to agents, optimize target exploration paths, and reduce total task time. Compared with existing technologies, this invention improves the efficiency of marine area search and target exploration through multi-agent cooperation, achieving full area coverage search and accurate target exploration.

The invention provides a high-precision troposphere delay modeling method, device and equipment under a sparse GNSS (Global Navigation Satellite System) site, and belongs to the technical field of spatial scientificity, and the method comprises the steps: calculating an initial ZTD (Zero Time Division) value of a real GNSS site through a first preset empirical model, constructing a ZTD residual time sequence by combining a GNSS actually measured ZTD value, analyzing a periodic signal, constructing a residual model to obtain a ZTD residual, and calculating the ZTD residual according to the ZTD residual. Further obtaining a ZTD improved value of the GNSS real station; based on a second preset empirical model in which an error correction term is introduced, virtual sites are arranged in the sparse region, and ZTD values of the virtual sites are generated; performing weighted fusion on the real and virtual ZTD values through a variance component estimation method to obtain a unified ZTD observation data set; and adopting spherical crown harmonic analysis to solve the adaptation coefficient, constructing a continuous ZTD model, outputting full-region data, and generating a high-resolution and high-precision ZTD map. According to the method, the defect that sparse GNSS station data coverage is insufficient is effectively overcome, and troposphere delay modeling precision, space continuity and area coverage integrity are remarkably improved.

The invention discloses a visual marking method and equipment based on fusion positioning, and a medium, belongs to the technical field of airport scene monitoring and management, and aims to solve the problems that the recognition accuracy is reduced, the high computing power requirement is needed, the real-time monitoring adaptability is poor, and the recognition efficiency is high due to the fact that existing airport scene monitoring is easily shielded by vision. And accurate geographical location information is difficult to obtain. The method comprises the following steps: performing coverage calculation of a maximum monitoring area on a visible area on an airport map to obtain a polygonal visible area; acquiring positioning terminal signals of key equipment and workers in an airport range; carrying out conversion processing of related camera point locations on a real-time geographic coordinate system in the real-time position information to obtain a camera coordinate system; performing conversion processing on the camera coordinate system to obtain a two-dimensional image coordinate system; mapping the two-dimensional image coordinate system into a polygonal visible area; and performing shielding labeling display on part of shielding targets in the initial labeling display information to obtain fused labeling display information.

The invention belongs to the technical field of collaborative interception guidance, and particularly relates to a bias differential game collaborative interception method based on region coverage. The method comprises the steps of establishing a probability distribution model of a target in an interception plane, performing Monte Carlo sampling, and converting a coverage strategy design into an optimal coverage problem of a finite center point in the interception plane; segmenting, iteratively solving the standard maneuver of each interceptor through a Voronoi diagram method to obtain the standard maneuver aTsi of each interceptor; and based on the standard maneuvering aTsi of each interceptor, deploying to a corresponding optimal array position and carrying out offset item design of a differential game guidance law to jointly realize the offset of the coverage range of each interceptor, and finally completing the optimal coverage and interception of the target. According to the method provided by the invention, the defects that an existing disc coverage model has limitation on maneuvering distribution simplification and only a fixed solution can be applied mechanically are overcome; the miss distance and the overload demand of the interceptor are obviously reduced, and the interception efficiency is improved.

This invention discloses a method for optimizing the layout of airport noise monitoring points based on a genetic algorithm. The method involves dividing the monitoring area into grids based on a noise prediction contour map; calculating the distance from any point within the monitoring area to the monitoring point; defining the probability of whether a point is covered by a monitoring point; calculating the sensing probability based on distance and monitoring point reliability parameters; establishing a joint sensing probability model and calculating the area coverage rate; setting a coverage rate optimization objective function; introducing multi-objective constraints; and using a genetic algorithm to optimize the comprehensive benefit function. A dynamic point quantity control mechanism is introduced to gradually reduce the number of monitoring points, outputting a simplified monitoring point layout scheme while maintaining the coverage rate above a set threshold. The optimization process of this invention fully incorporates the actual airport point layout constraints, reducing the number of monitoring points and prioritizing the elimination of redundant points, while maintaining a relatively stable overall coverage rate, significantly reducing equipment installation, maintenance, and data processing costs.

The invention relates to a UUV coverage path energy efficiency optimization method and an offshore surveying and mapping system, and the method comprises the following steps: obtaining a satellite remote sensing image, multi-beam sounding data and underwater topographic data of an offshore region, recognizing a sea-land boundary contour, and constructing an offshore seabed three-dimensional surveying and mapping region model; a UUV energy consumption model is constructed, a surveying and mapping area coverage rate maximization and total energy consumption minimization are taken as targets, a surveying and mapping area model is combined, an intelligent optimization algorithm is adopted to carry out global path planning, and a UUV surveying and mapping operation path is determined; the underwater environment is monitored in real time through a sensor carried by the UUV, whether an original planned path is feasible or not is judged, and when the original planned path is not feasible, local path re-planning is carried out by taking minimization of extra energy consumption as a target and adopting an improved path search algorithm. Compared with the prior art, the method has the effects of improving the accuracy and integrity of a surveying and mapping area, reducing the energy consumption of the UUV, improving the surveying and mapping efficiency and the like.

Embodiments of the present application provide a map processing method, device and self-moving equipment. The map processing method comprises: acquiring at least one of working state information of a current working process of the self-moving equipment in a working area and a real-time obstacle map, the working state information comprising at least one of positioning quality and working area coverage rate, the real-time obstacle map being obtained based on real-time images collected in a moving process; determining whether to update at least one of an original visual feature map and an original obstacle map used by the self-moving equipment according to at least one of the working state information and the real-time obstacle map, the original visual feature map being used for positioning of the self-moving equipment in the working area, and the original obstacle map being used for path planning of the self-moving equipment; if the update is needed, acquiring an image frame of the working area, and updating at least one of the original visual feature map and the original obstacle map using the image frame. The method can update the map in time.

The application discloses a kind of based on machine vision's magnetic force polishing state detection method, equipment and medium, it is related to surface processing quality control technical field, including the dynamic image of the contact area of magnetic brush and workpiece is collected, obtains the image sequence of the contact area of magnetic brush and workpiece, extracts and smooths the upper boundary of magnetic brush, constructs the time series of upper boundary disturbance rate of magnetic brush;Magnetic brush trajectory coverage heat map is constructed, under-coverage, over-coverage and normal coverage area are divided, and area coverage index is calculated;Fusion upper boundary disturbance rate time series of magnetic brush and area coverage index, construct magnetic force polishing state feature vector, train random forest model, generate real-time magnetic force polishing risk grade label, adjust magnetic field intensity, obtain magnetic brush polishing supplement point set, generate magnetic brush polishing supplement trajectory.Magnetic force polishing process is quantified tracking in real time to the disturbance state, accurately identify magnetic force polishing state and implement regional compensation, improve polishing quality and process stability.

The invention discloses a method for generating a satellite communication beam. The method comprises the following steps: acquiring boundary coordinates of a target geographic corridor and converting the boundary coordinates into satellite angular domain representation; extracting a skeleton curve of a corridor based on the angular domain boundary, and establishing a parameterized beam pattern model distributed along the skeleton curve; constructing a beam forming weight optimization problem which comprises a coverage gain constraint distributed along the skeleton curve and a continuity constraint between adjacent sampling positions on the skeleton curve; and solving the optimization problem to obtain a complex weight vector, and loading the complex weight vector to the beam forming network to drive the phased-array antenna. According to the invention, dimension reduction is carried out on a two-dimensional area coverage problem through skeleton curve modeling, and stable energy transition of a wave beam along a curved corridor is ensured by utilizing a continuous constraint explicit mode, so that the problems of difficult optimization convergence and discontinuous coverage in long and narrow non-convex area coverage are effectively solved.

The invention discloses a uranium mineralization zone identification method and system based on multi-source remote sensing data fusion, and relates to the technical field of geological exploration, and the method comprises a multi-source data obtaining module which obtains multi-platform and multi-band remote sensing data, and the remote sensing data comprises optical remote sensing data, microwave remote sensing data and auxiliary data; constructing a uranium ore zone feature database based on the remote sensing data; the data preprocessing module is used for carrying out noise elimination, atmospheric interference removal and geometric distortion correction on the remote sensing data; the feature extraction and fusion module is used for extracting uranium mineralization zone sensitive features from the preprocessed multi-source data and carrying out cross-modal fusion, and the cross-modal fusion comprises feature layer fusion and decision-making layer fusion; an anomaly detection and geological analysis module; a result output and verification module; according to the method, all-weather, total-factor and non-blind-area coverage of a complex terrain area can be achieved, the exploration range is not limited to roads and gentle zones any more, and the coverage rate of a potential metallogenic zone is increased.

The invention relates to the technical field of water surface pollution monitoring, in particular to a water surface floating object intelligent identification and path planning method, which comprises the following steps: firstly, calculating a solar elevation angle based on real-time time and a geographic position, and determining an environment illumination gear in combination with a seasonal model; and adaptively loading image processing parameters and a detection model to perform initial target identification. Afterwards, target features are extracted through a feature analyzer, difficult categories of the target features are judged, a special module is dynamically called for fine recognition, and a result set with geographic coordinates and labels is output. And calculating an operation priority based on a target category, a label and spatial distribution, and generating an operation instruction to drive the operation in combination with path planning modes such as cluster form intelligent selection point clearing, area coverage or tracking monitoring and the like. New images are collected in real time during execution and fed back to a process starting point, a complete self-adaptive closed loop of sensing, decision making, execution and feedback is formed, and the intelligence level and the operation efficiency of floating object cleaning in a complex environment are remarkably improved.

A transducer device for delivering a tumor treatment field to a body of a subject, the transducer device comprising: an array of electrodes configured to be positioned over the body of the subject with a front face of the array facing the body of the subject, the array comprising electrode elements positioned in existing electrode positions arranged around a centroid of the array; an anisotropic material layer electrically coupled to the array of electrodes and located on a front side of the front face of the array; and at least one void space in the array of electrodes, which void space can enclose at least a portion of an area coverage corresponding to an area coverage of at least one existing electrode location and can be superimposed on at least a portion of the at least one existing electrode location by rotating the array about the center of mass.

The application discloses an unmanned cleaning vehicle area coverage optimization scheduling method and system, and particularly relates to the field of environmental sanitation scheduling, and is used for solving the problems that the area to be reswept is difficult to be accurately identified, the path of the reswept task is difficult to be inserted along the way, and the service delay is difficult to be quantitatively evaluated in the scene where temporary obstacles frequently occur, and is achieved by the following steps: generating a basic label with cleaning marks and obstacle marks based on a road section, constructing a reswept area record and merging to form a reswept task path, introducing an along-the-way overlap distance ratio and a service delay offset time, calculating a task allocation priority coefficient through a pre-defined scheduling matching model, cooperatively allocating between the reswept task path and a regular cleaning task, and combining an actual cleaning trajectory to feed back and adjust the reswept area identification rule and the reswept task path generation strategy, so as to realize the closed-loop optimization scheduling of the area coverage of the unmanned cleaning vehicle.

The application provides a tilt photography-based aircraft platform site selection method, and belongs to the field of unmanned aircraft management and optimization. The technical scheme is as follows: a multi-objective optimization model is established after a semantic three-dimensional scene model and a platform site selection characteristic field are sequentially constructed by collecting original task data; and site selection output data for flight task planning are obtained after the multi-objective optimization model is solved. The application has the beneficial effects that: the application uses a semantic three-dimensional scene, introduces a geometric uncertainty field, a semantic value field and a constraint field, and realizes joint site selection through view analysis and multi-objective optimization, so that the key area coverage rate and imaging quality can be improved, and the blind area and invalid flight can be reduced under the premise of meeting airspace safety and regulations.

The application discloses a navigation interference resource scheduling method based on regional coverage, which comprises the following steps: first, a cooperative interference scene of regional full coverage is built; then, key indexes influencing interference coverage effect are quantitatively processed; next, a mathematical optimization function and constraint conditions of a multi-target scheduling problem to be solved under the condition of limited interference resources are given; finally, a resource scheduling model of navigation interference is constructed, and a global coverage navigation interference resource scheduling problem is solved by using a boundary enhanced virtual force algorithm with an adaptive distance threshold. The navigation interference resource scheduling method based on regional coverage is complete and reliable, and the regional coverage effect of navigation interference is improved.

This invention belongs to the field of power system analysis technology, and discloses a method, system, equipment, and medium for phased state estimation of power systems. The method includes: calculating the node admittance matrix based on the power system topology and branch parameters; configuring SCADA and PMU at the corresponding nodes of the power system to construct a measurement-state Jacobian matrix H; acquiring SCADA and PMU measurement data and performing time synchronization processing on the two types of measurement data; using a GM estimator to perform nonlinear robust state estimation on the SCADA measurement data to obtain a first estimation result; combining the first estimation result with the PMU measurement data, and performing linear robust state estimation on the combined data to obtain the power system state estimation result. By performing phased and differentiated processing on the two types of measurement data, the complementary advantages of SCADA's wide-area coverage and PMU's high-precision measurement are fully utilized, significantly improving the accuracy and reliability of state estimation in mixed measurement environments.

The invention discloses a planar region coverage path generation method, computer equipment and a storage medium. The planar region coverage path generation method comprises the following steps: acquiring related parameters of a planar region to obtain a polygonal region to be planned; decomposing the polygonal region to be planned to obtain a plurality of sub-regions without obstacles; generating four kinds of scanning lines in the sub-regions; constructing a weighted graph model of which sub-regions comprise four scanning lines; according to the weighted graph models of all the sub-regions, obtaining all global scanning lines of the polygonal region; global search optimization is carried out on all the scanning lines, and a total scanning line with the shortest global total path length is obtained; and performing path restoration on the total scanning line to obtain a complete planar region coverage path generation graph. According to the planar region coverage path generation method, the computer equipment and the storage medium, better performance can be obtained when the planar region coverage path is generated.

The invention relates to a real-time area coverage method and device for medium-orbit area observation constellations, and the method comprises the steps: carrying out the subarea division of a target area, and uniformly generating sampling points and area mask vectors corresponding to the sampling points in the target area; according to the pointing information of the satellites to the target area at the current moment, obtaining a single-satellite instantaneous coverage mask vector of each satellite to the sampling point; counting the coverage multiple number of each sampling point to obtain an instantaneous multiple coverage vector; obtaining an instantaneous region coverage vector according to the instantaneous multiple coverage vector and the region mask vector; according to the instantaneous region coverage vector, calculating an instantaneous i-fold coverage proportion of the sub-region at the current moment; taking a pointing vector formed by all satellites as a decision variable, and constructing a target function according to an instantaneous i-fold coverage proportion; and solving the objective function by adopting a particle swarm algorithm to obtain an optimal pointing vector so as to realize area coverage. According to the invention, a real-time area coverage area observation task can be realized.

This application discloses a method and system for surface strengthening process identification and coverage detection, relating to the field of intelligent surface detection technology. The method involves fluorescently treating the workpiece surface to obtain a fluorescence image of the treated surface. A trained deep learning dual-branch network is then used to output the probability of the strengthening process category and the coverage of the strengthened region. The deep learning dual-branch network includes a feature extraction module, a process discrimination branch network, and a coverage segmentation branch network. The feature extraction module generates a fused feature map from the fluorescence image of the workpiece surface. The process discrimination branch network uses a convolutional block attention mechanism to obtain the strengthening process category probability from the fused feature map. The coverage segmentation branch network uses an encoder-decoder semantic segmentation network to determine the coverage of the strengthened region based on the strengthening process category probability and the fused feature map. This application enables accurate discrimination of surfaces with different strengthening processes and precise quantitative detection of coverage.