81 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 building engineering management, in particular to a building water supply and drainage system based on a building BIM (Building Information Modeling), which comprises a pipeline drawing generation module, an interface arrangement verification module, an arrangement space detection module, an operation data monitoring module and a fluid risk early warning module. According to the method, standardized drawing mapping of the pipeline trend, size and node layout is achieved through structured extraction of the BIM model, it is ensured that drawing output is complete and consistent, interface offset is automatically compared, abnormal arrangement is accurately recognized, the installation accuracy is improved, component conflicts can be pre-judged through space node clear distance analysis, field coordination is assisted, and the construction efficiency is improved. The method comprises the following steps: monitoring flow velocity pressure of a key drainage section, screening abnormal nodes, filing a hydraulic state, analyzing high-frequency risk points in a time sequence, marking continuous abnormity, providing operation early warning support, constructing drawing generation, arrangement verification, space coordination and a data feedback closed-loop process, and improving construction design accuracy and system operation stability.

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 discloses an AI-based unmanned aerial vehicle routing inspection path planning method and system, and relates to the technical field of unmanned aerial vehicle intelligent path planning, and the method comprises the steps: achieving the reasonable division and task distribution of an unmanned aerial vehicle routing inspection region through the combination of a K-means clustering method and a greedy algorithm; according to the method, the balance of sub-region division and the rationality of unmanned aerial vehicle load are improved while the routing inspection coverage rate is guaranteed, an initial routing inspection path conforming to energy consumption and path constraints is generated through combination of an A * algorithm and three-dimensional search space modeling, conflict detection is performed on the initial path through combination of a space-time distance analysis method and an indicator function method, and the routing inspection efficiency is improved. The security and robustness of the unmanned aerial vehicle group in a dynamic scene are enhanced, the collaborative path optimization based on the time-limited reward is realized by combining the AI model serialization action with the multi-agent DQN model, and the multi-unmanned aerial vehicle collaboration efficiency and task completion degree are effectively 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 discloses an intelligent cleanliness detection device and method, and belongs to the technical field of air cleanliness detection.The intelligent cleanliness detection device comprises a detector, a moving part, a data acquisition unit, a state prediction unit used for generating an air state prediction value, a state judgment unit and a control unit, the moving direction analysis unit is used for acquiring the wind speed of the space where the detector is located at present and generating the moving distance; the moving control unit is used for controlling the moving assembly to drive the detector to move according to the optimal moving direction and the moving distance; the pollutant diffusion trend can be predicted according to the real-time environmental parameters, the detection path can be automatically adjusted, the pollutant diffusion trend can be dynamically tracked, the detection path can be automatically adjusted, and the detection accuracy and efficiency are improved.

The invention discloses an identification intercommunication analysis method and system for heterogeneous science and technology resources, and relates to the technical field of identification analysis, and the method comprises the steps: collecting heterogeneous science and technology resource data, carrying out the hierarchical definition of triple nodes, analyzing the attribute association degree, and carrying out the weak association elimination through a SimHash screening technology, and analyzing the attribute similarity among the resources based on the attribute vector distance of the triple node data, and performing matching analysis of function vectors according to the support information of the resources to the functions to establish the function association of the resources. According to the method, a multi-dimensional supplementary association mechanism is provided for function association values based on task function support conditions among resources through definition and matching of function vectors, attribute weights of attribute similarity are adjusted based on dynamic loads, the real-time states of the resources have a dynamic adjustment effect on the association weights, and the dynamic load adjustment effect of the resources is improved. And the adaptation flexibility of the system is improved.

The invention belongs to the technical field of fire-fighting management, and discloses a fire-fighting management system based on artificial intelligence, which comprises a fire-fighting intelligent management system, and the fire-fighting intelligent management system comprises an information acquisition unit; the fire-fighting spraying module is electrically connected with the spraying device in the target place and controls the spraying device to carry out primary fire extinguishing on the target place under the condition that a fire disaster occurs; and the distance analysis unit is used for sending the fire information of the target place to the fire-fighting center at the nearest distance. According to the invention, the path analysis unit is arranged, and the optimal route is selected from the plurality of routes, so that the fire-fighting equipment can smoothly arrive at the target site.

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 present invention discloses a method for analyzing the distance between a power transmission line and a tree line based on monocular vision, which belongs to the field of visual analysis and distance measurement technology. The method comprises obtaining the length of a preset transmission line section, marking the length as an inspection length, collecting relevant data of trees on both sides of the inspection length, marking the trees as preset trees, wherein the relevant data includes height data of the trees on both sides and distance data between the ends of the branches of each tree and the preset transmission line section; collecting growth changes of the preset trees in time periods based on the distance data, wherein the time periods are divided into different temperature sections, and a database is constructed based on the collected growth changes; the present invention performs monocular vision collection on the preset trees and analyzes the growth data of different temperature sections, thereby providing more reliable data support for the distance changes between the preset trees and the preset transmission line section in future time periods in addition to the monocular vision data, thereby reducing the potential risks between the tree branches and the preset transmission line section.

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 application discloses a kind of based on big data's marine environment monitoring and early warning method and system, it is related to marine environment monitoring technical field, the method includes: through the sensor in monitoring site real-time collection environmental data and transmission to database;Using positioning technology obtains the position information of each monitoring site, and the distance between randomly selected reference monitoring site and corresponding contrast monitoring station is calculated;The change trend of environmental data is analyzed, and the propagation speed of abnormal environmental data is determined based on the analysis result;Distance and propagation speed are combined, and the arrival time of abnormal environmental data from reference monitoring site to contrast monitoring station is calculated using linear propagation algorithm;According to the alarm starting time set by arrival time, and publish warning information.The application realizes real-time monitoring and data collection to marine environment by deploying monitoring site and integrating sensor technology, provides comprehensive, accurate information basis for subsequent data analysis and early warning.

The present invention discloses a method for analyzing the total travel distance of multiple modes of transportation based on traffic distribution, which belongs to the technical field of calculation, estimation or counting. The method includes the following steps: clarifying the research area and time period; dividing traffic areas; constructing a road network and a bus line network; calculating the line network density and average station spacing of buses in the traffic area; conducting a questionnaire survey on residents' transportation travel; constructing a traffic distribution matrix and performing traffic distribution; calculating the non-linear coefficient of residents' transportation travel within the traffic area; constructing a calculation model for the distance from passengers to bus stops; and calculating the total travel distance of various transportation modes. The present invention comprehensively analyzes all aspects of the integrated transportation system, organically combining travel on the road network, travel within the traffic area, and travel by passengers to bus stops. It can systematically analyze the entire process of residents' transportation travel and accurately calculate the total travel distance of multiple transportation modes.

The invention discloses a digital mechanical equipment safety distance analysis system based on artificial intelligence, and the system obtains equipment operation parameters and surrounding environment three-dimensional information through multi-dimensional data collection and binocular vision image collection, carries out the safety distance analysis through an optimized support vector machine model after preprocessing and feature extraction, and achieves the safety distance analysis of the equipment. Equipment parameters such as load weight and temperature are introduced into model training to construct an influence model, and adaptive noise reduction based on operation frequency and a compensation model based on vibration parameters are adopted in binocular vision processing. The system generates an early warning signal and a control instruction according to an analysis result, realizes intelligent adjustment of the equipment operation state, effectively overcomes the defects of weak data processing capability and lack of intelligent decision making in the traditional technology through multi-unit cooperation and algorithm optimization, remarkably improves the accuracy of safety distance analysis and system adaptability, and improves the safety distance analysis efficiency. And safe operation of digital mechanical equipment is ensured.

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.

The invention provides a bearing temperature monitoring method in the starting process of a large fluid machine, and the method comprises the steps: obtaining a state vector, and constructing a time window vector through a sliding time window; by calculating the distance between the time window vectors, uniformly distributed time window vectors are selected for model construction; carrying out vector distance analysis on the state vector of the monitoring time period to obtain the output of the model; and constructing a bearing temperature early warning vector based on the reconstruction output at the continuous monitoring moment, and realizing bearing temperature monitoring. According to the invention, the temperature of the bearing in the starting process of the large-scale fluid machinery can be effectively monitored, early warning is carried out in time when a fault risk exists, and the method has high accuracy and sensitivity.

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 power transmission line external damage scene safety distance analysis method based on multi-source data, and relates to the related technical field of power transmission line monitoring, and the method comprises the steps: carrying out the data collection of the position of a power transmission line through a visual camera and a laser radar; respectively carrying out feature extraction on the image set and the point cloud data set, and establishing an image feature set and a point cloud feature set; establishing multi-class probability distribution corresponding to the pixel points and the laser points; constructing an image sub-conditional random field and a point cloud sub-conditional random field; executing cross-modal connection edge fusion, and establishing a hybrid conditional random field; and spatial position construction of the external broken object and the power transmission line is carried out, the minimum distance from the external broken object to the power transmission line is identified, and safety early warning trigger analysis is carried out. The technical problem that in the prior art, it is difficult to accurately monitor the safety distance between an external breaking object and the power transmission line in the external breaking scene of the power transmission line in real time is solved, and the technical effect of improving the monitoring accuracy of the power transmission line and the safety early warning timeliness is achieved.

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.