52 results about "Distance analysis" patented technology

The invention discloses an industrial robot intelligent obstacle avoidance control method and system based on visual identification, and relates to the technical field of robot obstacle avoidance control, and the method comprises the steps: carrying out the calibration of a multi-mode visual sensor, obtaining an initial depth map and point cloud information, and combining the visual identification and depth compensation technology; recognizing and positioning obstacles in the operation area, and constructing a dynamic environment map layer; and the current robot state is collected, kinematics calculation and collision distance analysis are carried out, whether obstacle avoidance operation needs to be executed or not is judged, if yes, an obstacle avoidance path is generated in combination with the dynamic environment map layer and the target point location, feasibility verification is carried out after the path is generated, and the path passing the verification serves as an execution track to be issued to the control module. According to the invention, the recognition precision and depth perception integrity of the industrial robot on obstacles in a complex environment are improved, high feasibility of path planning and high-reliability obstacle avoidance capability in a dynamic environment are realized, and the intelligent decision-making level and operation safety of the system are remarkably enhanced.

The invention relates to the technical field of building structure health monitoring, in particular to an unmanned aerial vehicle laser radar-based building point cloud deformation quantitative extraction method, which comprises the following steps of: based on building corner structure characteristics in point cloud data, carrying out quantitative evaluation on the overall inclination state of a building through point cloud segmentation, straight line fitting and angle calculation; based on an ideal plane hypothesis, performing plane fitting and point-to-plane distance analysis on the building facade point cloud in the point cloud data, identifying a local concave-convex deformation area of the building facade, and performing quantitative evaluation; and roof plane detection and wall surface normal vector analysis are carried out based on the point cloud data, and accurate quantification is carried out on parapet wall inclination based on region growth segmentation and PCA principal direction analysis. Through automatic processing and quantitative analysis of an algorithm, subjective errors and inconsistency possibly occurring in a traditional manual evaluation method are avoided, and objectivity and repeatability of an evaluation result are enhanced.

The invention relates to the technical field of image processing, in particular to a concrete member surface defect detection method and system based on image segmentation, and the method comprises the steps: obtaining a surface image of a concrete member, and dividing the surface image into a plurality of image blocks; and performing frequency domain transformation on any image block to obtain a power spectrum. According to the method, the feature space period of each image block is analyzed and calculated through frequency domain transformation, and adaptive weighted fusion is carried out on texture features at different distances by using Gaussian weight on the basis of the feature space period. According to the method, the feature extraction process can dynamically adapt to the physical scale of image local textures, namely, small distance analysis is automatically emphasized on fine textures and large distance analysis is automatically emphasized on rough defects, so that scale-perceived composite texture features are constructed; and the accuracy of identifying the concrete surface defects under the complex texture background is obviously improved.

The invention relates to the technical field of construction management, in particular to a highway construction scheduling optimization method and system based on big data, and the method comprises the following steps: screening abnormal points and calculating a driving distance based on the coordinate data of a transport vehicle, analyzing the matching condition of a track and route planning, and recognizing progress offset and time period rearrangement signals; and dynamically adjusting material putting and equipment operation nodes to obtain a field operation response beat amount. According to the invention, based on big data real-time processing and sequence analysis, time sequence screening and abnormal point elimination are carried out on vehicle coordinate data, remaining road section features are extracted, progress offset is continuously tracked, rhythm offset features are dynamically generated by comparing arrival time and node demands, a periodic trend monitoring and abnormal state identification mechanism is established, and the abnormal state identification accuracy is improved. And dynamically triggering resource allocation time sequence rearrangement, carrying out integrated linkage on data such as a job node state, a material release rhythm and an equipment job window, and realizing resource release rhythm optimization and task parameter self-adaptive adjustment.

The invention discloses an intelligent low-altitude traffic unmanned aerial vehicle situation awareness method and system. The method comprises the steps of image acquisition, perception enhancement border crossing sample generation, boundary distance analysis feature extraction unit design, dynamic cross-specification air situation fusion, airspace anti-change loss calibration, unmanned aerial vehicle situation awareness model design and low-altitude traffic unmanned aerial vehicle situation awareness. The invention belongs to the field of image processing, and particularly relates to an intelligent low-altitude traffic unmanned aerial vehicle situation awareness method and system.According to the scheme, texture constraint loss is constructed, and situation misjudgment caused by detail loss is reduced; based on boundary distance analysis operation, separating low-altitude traffic noise and target features; based on height attitude self-adaptive pooling size design, feature mismatching is avoided; introducing a motion speed compensation factor to correct frame offset caused by high-speed flight of the low-altitude unmanned aerial vehicle; a dynamic noise suppression coefficient is introduced to suppress harmful gradient interference; and the low-altitude traffic unmanned aerial vehicle situation awareness effect is further improved.

The invention relates to the technical field of image recognition and data processing, in particular to a data positioning method, system and equipment for angle distance analysis, and the method comprises the steps: carrying out the preprocessing of to-be-processed image data, and generating a data block information set for the to-be-processed image data after preprocessing through an integrated OCR technology; constructing a relative polar coordinate system according to the reference data blocks in the reference data block set; setting an angle fault-tolerant group to determine data blocks of the same direction group; calculating spatial distances between all the data blocks in the same direction group and the reference data block based on multi-scale distance analysis, and sorting the spatial distances to generate an ordered data block sequence; and according to a preset target sorting position, extracting a data block at a corresponding position from the sorting sequence as positioning target data, and performing visual labeling on the to-be-processed image data based on the positioning target data. The method can effectively adapt to image input under different shooting distances, angles and illumination conditions.

The invention discloses a power line online positioning method based on laser point cloud, and the method specifically comprises the following steps: carrying out the synchronous collection of original point cloud data, RTK position data and IMU attitude data, and building the timestamp association of all data; motion distortion compensation is carried out on the original point cloud data based on IMU attitude data, coordinate system conversion is completed in combination with RTK position data, and distortionless point cloud data under a world coordinate system of the unmanned aerial vehicle is output; power line extraction is carried out, and power line candidate point cloud clusters are obtained through filtering processing and approximate fitting; processing by adopting neighborhood distance analysis, sliding time window management, a least square method and a catenary model method to obtain a power line space fitting curve with a boundary; and density statistics, weighted coordinate calculation and direction vector solution are carried out on the neighborhood point cloud of the power line space fitting curve, and an optimal target point location and a direction vector thereof are determined, so that reliable data support is provided for accurate approaching and observation of the unmanned aerial vehicle.

The application discloses a kind of continuous monitoring methods of coal mine mining overburden rock three-dimensional interstice, belong to coal mining technical field.Through coal mine overburden rock multi-position separation layer monitoring device measurement coal seam mining after the three-dimensional interstice of overburden rock: based on coal seam mining thickness and water conducting fractured zone development height, formulate mining overburden rock interstice monitoring scheme;Perpendicular monitoring borehole is arranged on the surface above the stoping working face, and coal mine overburden rock multi-position separation layer monitoring device is installed in the borehole;Real-time acquisition, storage and analysis monitoring data are acquired by data acquisition box and computer;Based on the advancing distance of coal mining face, the evolution law of single-hole interstice of mining overburden rock is analyzed;Kriging interpolation method is used to predict the unknown point interstice of working face according to the multi-hole monitoring data, and the spatial curved surface visualization model of mining overburden rock interstice is generated.The application can realize the continuous monitoring of the distribution characteristics of overburden rock three-dimensional interstice in the process of coal seam mining, and provide a scientific basis for determining the key parameters of grouting and filling.

The invention relates to the technical field of operation risk early warning, in particular to a visual perception-based high-altitude operation risk early warning system, which comprises an environment monitoring module, a personnel monitoring module, a behavior analysis module, a personnel risk assessment module, an object falling risk assessment module and an early warning generation module. According to the invention, by capturing the actions of the operating personnel in high-altitude operation in real time and identifying the behaviors such as inclination, hyperextension and unstable standing, early warning can be carried out in time when dangerous behaviors occur, the sensitivity and accuracy of early warning are improved, and by combining real-time heart rate and blood pressure monitoring with environment monitoring, risk assessment is more comprehensive, and the risk assessment efficiency is improved. Through real-time monitoring and distance analysis of the position of the object, assessment of the falling risk of the object is more accurate, accidents caused by falling of a tool or the object are effectively prevented, and through comprehensive consideration of various risk factors, an early warning strategy is adjusted in time, more targeted safety measures are provided, and the efficiency and effect of operation safety management are improved.

The invention relates to the technical field of electric power inspection, and discloses an electric power system facility intelligent inspection and safety analysis method, system, device and medium, and the method comprises the steps: carrying out the preprocessing of original laser point cloud data, so as to screen out noise and non-target ground objects; and a multi-branch deep learning network is used to distinguish different types of point cloud and lead point cloud features, and a basis is provided for subsequent lead segmentation. And after the network is established, conducting wire point cloud clustering processing and catenary model fitting can be carried out, such simulation can accurately segment and model the specific condition of a single conducting wire, and the catenary model can also complement the condition of point cloud missing. And meanwhile, a catenary plane decomposition method is adopted during safety distance analysis, and comprehensive evaluation of the safety of the electric power facilities can be realized by combining vegetation invasion and electric tower state evaluation.

The invention discloses an intelligent fully mechanized coal mining face roof weighting display rule automatic analysis system and method and a related device, and belongs to the technical field of coal mine ground pressure. The system comprises a data acquisition unit, a production cycle analysis and determination unit, a working face advancing distance analysis and determination unit, a hydraulic support effective working resistance data extraction unit and a top plate weighting display rule analysis unit, and is used for acquiring time sequence operation data of hydraulic support stand column pressure, advancing jack stroke and coal mining machine position; calculating a daily production cycle number based on the position data of the coal mining machine; calculating the working face advancing distance of each production cycle based on the advancing jack stroke data; extracting the effective working resistance of each hydraulic support and the average working resistance of the hydraulic supports corresponding to each production cycle based on the stand column pressure data; and integrating the data, and automatically calculating the follow-up weighting step pitch, weighting duration and weighting range of the working face roof. According to the invention, automatic and accurate analysis of the roof weighting rule is realized, and the defects of high working intensity, low efficiency and poor accuracy of manual analysis are overcome.

This invention discloses a method for analyzing the safe distance in power transmission line external damage scenarios based on multi-source data, relating to the technical field of power transmission line monitoring. The method includes: acquiring data on the location of the power transmission line using a visual camera and a lidar; extracting features from the image set and point cloud dataset to establish image feature sets and point cloud feature sets; establishing multi-class probability distributions corresponding to pixels and lidar points; constructing image sub-conditional random fields and point cloud sub-conditional random fields; performing cross-modal edge fusion to establish a hybrid conditional random field; constructing the spatial locations of the damaged object and the power transmission line, identifying the minimum distance from the damaged object to the power transmission line, and performing safety warning trigger analysis. This method solves the technical problem in existing technologies of accurately and in real-time monitoring the safe distance between the damaged object and the power transmission line in external damage scenarios, achieving the technical effect of improving the accuracy of power transmission line monitoring and the timeliness of safety warnings.

The invention relates to the technical field of training data analysis, in particular to an intelligent positioning type efficiency monitoring device for tactical training and an application method, and the device comprises an inertial navigation drift identification module, a dynamic position correction module, a behavior path monitoring module, an action offset judgment module and a tactical efficiency evaluation module. According to the method, an inertial navigation drift interval can be identified and stable interval identification extraction can be realized by constructing a joint discrimination condition of a speed change rate sequence and a direction angle change threshold, and path dynamic compensation parameter generation and position estimation correction are completed by combining Euclidean distance difference linear fitting between a GNSS positioning result and an inertial navigation estimation value. Position offset and index distance analysis is carried out in combination with a preset tactical action chain and a training instruction execution time sequence, offset fragments and jumping behaviors in an action sequence are accurately recognized, the accuracy of path coherence sudden change recognition and the quantitative analysis capacity of action execution abnormity are improved, and multi-dimensional dynamic judgment of the efficiency state of the tactical stage is achieved.

The invention provides a brake-by-wire system distance analysis simulation method, system and device and a medium, and belongs to the technical field of vehicles. The method comprises the following steps: calculating a whole vehicle locking torque and a braking torque required by a drive-by-wire brake according to a whole vehicle axle load distribution parameter and a dynamic axle load transfer parameter, determining a motor torque requirement according to the required braking torque, the whole vehicle locking torque and a transmission system parameter, and building a brushless motor dynamic simulation model, a transmission system model and a brake caliper model, the model and a whole vehicle model are subjected to integrated simulation, conversion from the clamping force of the drive-by-wire brake to the braking torque is achieved by inputting the maximum target motor torque, braking distance simulation analysis is achieved, the nonlinear response process of the drive-by-wire brake is accurately simulated, and the braking distance of the drive-by-wire brake is accurately simulated. Scheme decomposition of components such as the power and the highest rotating speed of a motor, the inertia of a rotor, the transmission ratio and the lead of a ball screw can be achieved according to a braking distance simulation result, and performance parameters of all parts in the drive-by-wire brake are determined.

The invention discloses a federated learning worker selection method based on multi-dimensional constraints and a storage medium, and the method comprises the steps that a cloud platform sets a multi-dimensional resource constraint condition and constructs a constraint region according to a federated learning task demand; collecting multi-dimensional attribute information of candidate workers, forming an attribute vector, calculating a comprehensive evaluation value, and carrying out priority ranking on the workers according to the evaluation value to realize preliminary selection; and for all the workers, calculating Euclidean distances between the attribute vectors of the workers and the optimal point and the most secondary point in the boundary of the constraint region, and complementarily selecting a plurality of workers closest to the optimal point and farthest from the most secondary point so as to realize boundary optimization and resource matching. According to the method, multi-dimensional attribute evaluation is combined with spatial distance analysis, the task bottleneck caused by resource limitation is remarkably relieved in the heterogeneous Internet of Things environment, the synchronization waiting time in the federated learning aggregation process is shortened, and the task completion efficiency and the system robustness are improved.

This invention discloses a data visualization processing method for inorganic binder tests, belonging to the field of test data visualization technology. The method includes the following steps: acquiring material compaction test data curves, constructing a multi-primitive view, and uniformly mapping data coordinates and view coordinates; dynamically determining key parameter points of the curve and determining their annotation positions through distance analysis and visual analysis, generating dynamic annotation text boxes. This invention addresses the problems of low automation in binder test data visualization and unattractive annotation of key parameters.

This application relates to the field of game and animation production technology, and in particular to a method for modifying the appearance of animated characters, an electronic device, and a storage medium. This application first identifies the target driving bone from the skeletons of the target character model and adds a modification control component to the target driving bone; it then identifies the target modification controlled object associated with the target driving bone from a pre-set candidate control list; it captures bone pose transformation commands through the modification control component and determines the initial pose data, target pose data, and process pose data of the target character model based on the bone pose transformation commands, and then performs pose distance analysis to obtain a pose distance matrix; it performs radial basis function interpolation calculation based on the pose distance matrix to determine the corresponding modification weights for the process pose data; and finally, it performs character modification on the target modification controlled object to obtain the target animation of the modified character model. This method improves visual expressiveness while ensuring animation production efficiency.

The application discloses a kind of based on gray extremum analysis consolidated abrasive tool surface quality detection method, method includes image acquisition and pre-processing, candidate area positioning and feature point extraction, target area boundary adaptive extraction, region screening and gray difference calculation, particle gray and spatial distribution feature quantization five main steps.Through line scanning camera, surface brightness chart and depth chart are collected, after gray enhancement and filtering pretreatment, local extreme point is extracted as candidate area by line scanning, and target boundary is adaptively generated in combination with cross neighborhood gray contrast and gradient chart dynamic threshold criterion;Effective area is screened by morphological operation and area constraint again, and gray difference is calculated to represent particle height;Finally, multidimensional quantitative evaluation is realized through gray difference histogram, protruding height statistics, nearest neighbor distance analysis and grid uniformity measurement.The application has high sensitivity, high robustness and strong adaptability, and can be embedded in industrial production line to realize automatic, non-contact and high-precision surface quality detection.

The application discloses a kind of wheat variety selection methods based on multi-index merit solution distance analysis, it is related to the field of wheat cultivation, comprising: constructing green low-carbon wheat variety selection index system;Build test field, and cultivation comparison test is carried out to each wheat variety;Sample collection and index determination are carried out to each wheat variety in test field;Data preprocessing is carried out to index determination result;Based on the data after each index preprocessing, principal component analysis is carried out and the common factor weight of each index is calculated;According to each wheat variety and index value and corresponding weight, merit solution distance analysis is carried out and wheat variety is selected according to analysis result.The application method is novel and unique, scientific and reasonable, easy to operate, can be effectively used for green low-carbon wheat variety selection, has very strong practical value, can provide effective technical support for green low-carbon wheat variety selection, can realize the green low-carbon cultivation goal of wheat, has significant economic benefit, ecological benefit, social benefit.

The invention discloses a child warning label automatic identification method and system based on mirror cover production, and relates to the technical field of image processing, and the method comprises the steps: obtaining the shape of a child warning label detection tool, carrying out the position analysis processing of the shape of the child warning label detection tool, and obtaining a child warning label detection result; determining a left detection point coordinate of the child warning label and a right detection point coordinate of the child warning label; and acquiring an identification data set of the child warning label. The method comprises the following steps: firstly, performing shape analysis on a child warning label detection tool, determining a left detection point coordinate of a child warning label and a right detection point coordinate of the child warning label, and then, determining the left detection point coordinate of the child warning label and the right detection point coordinate of the child warning label according to the left detection point coordinate of the child warning label and the right detection point coordinate of the child warning label. Distance analysis and angle analysis are carried out on the to-be-analyzed child warning label, it is guaranteed that the child warning label is installed in a designated area, when the child warning label is installed on an automobile subsequently, a driver can make correct operation according to the child warning label, and the safety of a child is guaranteed.

The application relates to a method for detecting illegal operation of a tool, an embedded terminal and a storage medium. The application uses a target detection algorithm to detect whether a scene image contains a human body and a tool; if yes, the scene image is input into a lightweight OpenPose-CA key point detection algorithm to perform real-time human body and tool key point detection, and the key point set of the human wrist and the tool in each scene image is output; each key point in the key point set in the continuous scene image is connected into a straight line, and the consistency of the hand and the tool action is determined according to whether the shapes and directions of the straight lines are similar, and then whether the human body holds the tool is determined based on the action consistency and the distance between the wrist and the tool key point; the Euclidean distance between the tool key point and the center coordinates of a dangerous area is calculated, and the relationship between the Euclidean distance and a preset threshold is analyzed to determine whether the operation is standard. The method, the embedded terminal and the storage medium provided by the application are lightweight under the condition of ensuring detection accuracy, and are suitable for industrial embedded scenes.

According to the intelligent analysis and early warning method, system and equipment for the landslide monitoring data and the storage medium provided by the invention, the method comprises the following steps: acquiring multi-source data, inputting a constructed landslide movement distance analysis model, outputting landslide movement data, positioning a landslide position according to the landslide movement data, and calculating displacement vector data of each point on the landslide position; and comparing displacement vector data to judge abnormal monitoring points so as to obtain the moving speed of the sliding surface and the depth of the sliding surface, comparing a threshold value, dividing a slope area, accurately delineating the influence range of the landslide by quantitatively analyzing the deformation relevance of each area, and dividing early warning grades based on the proportion of the landslide in the slope area. According to the method, the space proportion and development trend of the landslide mass are dynamically calculated, so that an early warning signal is matched with an actual risk level, the situation of excessive early warning or missing report is effectively avoided, and accurate identification and advanced early warning of landslide disasters are realized by systematically integrating slope deformation characteristics, environmental parameters and visual information.

This invention discloses a method, device, and equipment for evaluating dose limits for organs at risk in tumor radiotherapy planning based on spatial distance analysis, relating to the field of tumor radiotherapy technology. Specifically, based solely on geometric statistics, before dose calculation, a three-dimensional Euclidean distance transformation is used to obtain the shortest distance distribution from all voxels of the organs at risk to the target area after anisotropic normalization, directly forming an individualized dose limit and weight template. The output of this invention is a distance-voxel histogram and its derived cumulative proportions and rates of change, from which several geometric indicators are extracted. Combined with a preset set of geometric rules, individualized suggestions for dose limit thresholds and optimization weights corresponding to different doses are directly obtained. Compared with existing technologies, this invention does not perform dose prediction, nor does it require generating auxiliary contours or performing forward / backward dose calculations. Instead, it provides individualized and executable dose limit and weight suggestions before dose calculation, significantly reducing optimization iterations and improving consistency, with highly interpretable results.

The invention relates to the technical field of computers, in particular to an intelligent scheduling method and system applied to security personnel, and the method comprises the steps: dividing the patrol into double patrol and full patrol based on a patrol time zone in daily patrol task data; acquiring information of each residence time point, and generating basic personnel requirements and emergency personnel requirements based on the change condition of the historical number of people demands of each residence time point; acquiring vehicle information, and distributing a basic security information set corresponding to each piece of parking lot information; on the basis of the patrol time and the specified security information, judging the specified security information in the basic security information set in the same time period, and generating a second security information set after screening personnel IDs through distance analysis; based on emergency personnel requirements, the ID of the parking lot is combined into an emergency group, vehicle matching and personnel matching are carried out based on the emergency group, and an emergency security information set is formed, and the intelligent scheduling method and system have the advantages of realizing intelligent scheduling to improve scheduling rationality and resource utilization rate.

The invention relates to a travelable region labeling method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a target point cloud file corresponding to a target vehicle and a plurality of corresponding multi-view images; inputting the plurality of multi-view images into a feature processing module in a target labeling model to obtain respective corresponding target features of the plurality of multi-view images on the plurality of columns; respectively inputting the target features into a distance analysis module and a type analysis module in a target labeling model, and carrying out driving domain distance analysis and type analysis to obtain target distance labeling data and target type labeling data corresponding to the plurality of multi-view images on the plurality of columns; based on the target distance labeling data and the target point cloud file, determining a drivable domain three-dimensional segmentation region in the target point cloud file; and based on the three-dimensional segmentation region of the travelable region and the target type labeling data, labeling the travelable region of the target point cloud file. According to the embodiment of the invention, the accuracy of travelable region labeling can be improved.

Methods, devices, and systems and geolocation of a target device in three-dimensional space are provided. A method according to one example involves identifying device signals within an area of operation including one or more signal source signals and one or more target device signals. The method involves calculating an estimated position of the target device within the area of operation based on a three-dimensional distance analysis of the target device relative to a signal source using the one or more signal source signals and the one or more target device signals. The method involves generating a mapping of the area of operation including a three-dimensional representation of the estimated position of the target device.

The application discloses a light guide plate defect sample enhancement and detection integrated method and relates to the technical field of light guide plate detection, which comprises the following steps: marking all the net points based on the front view of the light guide plate; acquiring the same-distance defect features by using the same-distance analysis method; acquiring the adjacent-distance net point analysis method; when the defect detection is performed on the light guide plate, the defect sample area and the influence detection area in the light guide plate are acquired; the application is used to solve the problem that in the existing light guide plate defect sample enhancement and detection method, the net point defect detection in the light guide plate cannot be based on the defect type of the net point, the defect hidden danger caused by the influence of the net point cannot be effectively analyzed, and the defect detection precision is low.

The invention discloses a remote sensing satellite data receiving antenna optimization design method and device, a medium and a product, and the method comprises the steps: calling a slope distance analysis model to calculate a slope distance between a remote sensing satellite and a data receiving system according to a user-defined remote sensing satellite data receiving duration demand and in combination with preset remote sensing satellite orbit data; calling an elevation angle analysis model according to the slope distance to analyze and calculate a receiving elevation angle; calling a receiving G / T value analysis model, comprehensively analyzing a slope distance, a receiving elevation angle and a data downloading rate, and determining a receiving G / T value demand when the link is stable; and calling a remote sensing satellite dispersion radius and a receiving multi-beam analysis model, determining the dispersion radius according to the receiving elevation angle, and determining the maximum satellite number in a regression period under the limitation of the elevation angle to obtain a simultaneous multi-beam number index. According to the method, the application scene and the system efficiency are taken as the fundamental principle, and the conversion from experience driving to application driving and the optimal solution of the overall performance of the system are realized.

The invention discloses an imaging method, device and equipment based on a single-transmitting single-receiving pulse radar, and a medium. The method comprises the following steps: receiving an imaging instruction, and reading detection data acquired by a detection radar; preprocessing the sampling data of each aperture contained in the detection data to obtain preprocessed data; screening the preprocessed data to obtain effective sampling data of each aperture, and further determining background information corresponding to the effective sampling data; performing distance analysis on the effective sampling data of each aperture according to an analysis rule and background information to obtain a corresponding analysis array; and performing coherent accumulation on the signal value of each aperture in the analytic array to obtain imaging information. According to the imaging method based on the single-transmitting and single-receiving pulse radar, the accurate imaging information of the target object is obtained through coherent superposition by adopting a multi-aperture detection and signal processing algorithm, so that the detectability of a centimeter-level target is remarkably enhanced, and the imaging resolution and accuracy are improved.

The application discloses a music-based psychological consultant matching method and system, which constructs a music-psychology mapping database, extracts music multi-level audio features to train a supervised learning model, and establishes a mapping relationship between the features and psychological dimensions. The music selection data of the visitor is obtained through an adaptive pairing comparison method, the presentation strategy is dynamically adjusted, the response delay is recorded, the psychological dimension vector of the selected music is weighted and aggregated, and a structured psychological portrait containing continuous value coordinates and clinical labels is decoded and generated. The psychological portrait and the consultant style vector are mixed and matched in a unified feature space, the cosine similarity and the Euclidean distance are combined to analyze the emotional resonance and the feature complementarity, the recommendation list is output after being filtered by the clinical knowledge weighting and the hard rule. The application can non-verbally capture the real-time and deep psychological state of the visitor through music preference, construct a multi-dimensional psychological vector, realize high-fitting-degree matching with the consultant, and improve the matching accuracy and the first consultation success rate.