43 results about "Division algorithm" patented technology

The invention discloses a contour and filling direction adaptive path planning and SLM support-free forming method, which has the following beneficial effects that a low-angle overhanging region is separated based on a region division algorithm, a scanning vector is controlled by a contour on the basis of contour features of complex structure features and an overhanging direction recognition algorithm, and the accuracy of the contour and filling direction adaptive path planning and SLM support-free forming method is improved. The expansion direction of the lower surface area is a filling direction, and adaptively generating a scanning path and the filling direction; different from a conventional path filling strategy, the method can meet the complex structure characteristics of a curved surface, a round hole, rotation, a special-shaped runner, a curved surface and the like, and the scanning line vector and the filling direction of a lower surface area adapt to the structure contour characteristics, so that the influence of the placing position and the scraper direction on the forming thermal strain accumulation and the lower surface forming quality is reduced; according to the method, the high-quality and stable forming requirements of the low-angle feature of 30 degrees or below of existing mainstream metal materials can be met, and the data processing time cost, the powder material consumption and the post-processing time in the whole forming process are effectively reduced.

The invention relates to the technical field of big data processing and data integration, in particular to a Kettle-based database dynamic sub-table processing method and system, which comprises the following steps: receiving sub-table configuration parameters through a Kettle graphical interface, the sub-table configuration parameters comprising a fragmentation key, a sub-table algorithm and a sub-table number; table division rule metadata is loaded, a dynamic table division strategy engine is constructed, and the strategy engine supports Hash fragmentation, range fragmentation and time fragmentation algorithms; the construction of the dynamic table division strategy engine comprises the following steps: automatically recommending a table division algorithm based on data sampling analysis; providing a Grouping script interface to support a user-defined fragmentation rule; maintaining table division rule version history, and supporting rule rollback; the method has the beneficial effects that the large table is split into the plurality of sub-tables according to the specified rule, so that the data volume of a single table is remarkably reduced, query and update operations can focus on data in a smaller range, and the query response speed and the update efficiency are greatly improved.

The application provides a high-resolution reconstruction method for sheet microstructure modeling, and relates to the technical field of metal structure reconstruction. The application obtains sheet thickness and average grain size by performing morphology and EBSD characterization on a metal material, compiles a microstructure reconstruction program based on a space segmentation algorithm and a sheet division algorithm, and establishes a microstructure reconstruction model; the three-dimensional reconstruction model closest to the real microstructure is obtained by adjusting the control parameters in the reconstruction program, namely sheet orientation, grain distribution and iteration number; the application can quickly and accurately reconstruct the sheet microstructure, and the generated microstructure model has high compatibility and can be transplanted to various finite element software for simulation analysis.

The invention discloses a power distribution network multi-point source storage cluster dynamic division and hybrid collaborative voltage treatment method, and belongs to the technical field of power system operation and control, and the method comprises the steps: constructing a cluster dynamic division comprehensive index based on a scale index and a sensitivity consistency index; proposing a cluster dynamic division algorithm based on division indexes, and ensuring that the sensitivity in the same cluster tends to be consistent after division; identifying a key bus according to the bus voltage offset, calculating the required voltage regulation quantity, determining a cluster hybrid collaborative algorithm control target, constructing a priority index, and establishing a reactive power and active power compensation sequence based on the priority index; the voltage violation of the key bus is eliminated with the purpose of minimizing the power compensation requirement, and the adjustment of the large-range bus voltage is realized. According to the method, voltage out-of-limit can be effectively suppressed in the high-photovoltaic-permeability power distribution network, the utilization rate of reactive compensation is remarkably increased, the demand of active compensation is reduced, and the service life of equipment is prolonged while control fairness is considered.

A system is provided robustly protects important information from high-level cyberattacks and physical destruction, including cryptographic analysis using quantum computers and electromagnetic pulse attacks, while enabling restoration without theft by a third party. The system encrypts and partitions file data using predetermined encryption and division algorithms based on a customer specified parameter, allots each file data to multiple sets of distributed file management groups comprising node groups at multiple bases in different regions of the world, distributes and records the file data to be saved in the nodes located at each base that belong to corresponding distributed file management groups, generates and encrypts index information of each distributed and recorded corresponding file data, and records the index information in node groups of a specified base in the consortium chain.

The invention discloses a storage chip aging prediction method and device based on topological sorting and a medium, and relates to the technical field of chip aging tests.The method comprises the steps that an initial static topological graph is constructed based on a predefined internal dependency relationship of a storage chip; collecting performance monitoring data of the storage chip, performing time sequence relevance identification, and generating a dynamic dependency edge; fusing the dynamic dependent edge with the initial static topological graph to generate a mixed topological graph; decomposing the mixed topological graph through a graph community division algorithm to generate a plurality of sub-graph communities; performing topological sorting on each sub-graph community to generate a functional component test sequence of each sub-graph community; and respectively executing an aging test task on each sub-graph community and the corresponding functional component test sequence through a plurality of distributed test nodes to generate a plurality of pieces of performance parameter attenuation data. According to the method, the performance monitoring data and the static topology are fused, the hybrid topological graph of the chip is constructed, and the problem of relevance deficiency caused by data separation is solved.

The application discloses a numerical control machine tool positioning precision compensation method based on a position instruction frequency division algorithm. The method can comprise: establishing a starting origin and a detection end point of numerical control machine tool feed shaft positioning precision detection; measuring the length of the detection stroke and the positioning error of the feed shaft between the starting origin and the detection end point through a laser interferometer; according to the length of the detection stroke and the positioning error, iteratively optimizing a position instruction frequency division numerator and a position instruction frequency division denominator; and according to the iteratively optimized position instruction frequency division numerator and the position instruction frequency division denominator, compensating the positioning precision of the numerical control machine tool. The positioning precision of the numerical control machine tool feed shaft is measured through the laser interferometer, the numerical control machine tool positioning precision compensation method based on the position instruction frequency division algorithm is established, and the positioning precision of the numerical control machine tool can be improved.

The invention provides a self-adaptive gridding FPGA (Field Programmable Gate Array) waveform assembly line dynamic reconstruction method and system, which introduces a self-adaptive gridding algorithm, depends on modeling and safe sequence planning based on DAG (Directed Acyclic Graph), and an assembly line parallel scheduling and integrated time sequence calibration mechanism. The problems that in an existing FPGA waveform dynamic reconstruction technology, the resource fragmentation problem is caused by static partition, the system reliability risk is caused by component dependence management deficiency, and the reconstruction delay is large and the real-time performance is poor due to a serial reconstruction mode are solved. According to the method, the utilization rate of FPGA logic resources is remarkably increased, the safety and controllability of the reconstruction process are achieved, the overall reconstruction time is greatly shortened, and meanwhile the processing precision after reconstruction is guaranteed through self-adaptive time sequence calibration. And an efficient hardware dynamic reconstruction solution is provided for application scenes with extremely high requirements on real-time performance and reliability, such as software defined radio and integrated radio frequency systems.

The application discloses a large-scale multi-mode traffic parallel simulation method and system based on CPU and GPU, relates to the technical field of traffic control, and comprises the following steps: acquiring traffic road networks to be simulated and multi-mode traffic demand data, dividing the traffic road networks to be simulated and the multi-mode traffic demand data based on a preset dynamic spectrum division algorithm to obtain a multi-mode traffic network division result; performing dynamic congestion detection and information feedback processing on the multi-mode traffic network division result based on a preset cross-process congestion feedback algorithm and an MPI communication optimization strategy to obtain congestion state information; inputting the congestion state information into a pre-established microscopic traffic intelligent agent model to perform microscopic behavior parallel calculation, and outputting microscopic behavior data based on the limitation of a regionalized Bucket communication mechanism; and performing simulation processing based on the microscopic behavior data to obtain a final traffic parallel simulation result, so that the simulation precision and efficiency are significantly improved.

The embodiment of the invention discloses a website layout optimization method and device, electronic equipment and a storage medium, and relates to the artificial intelligence field and the financial science and technology field, and the method comprises the steps: obtaining a plurality of to-be-evaluated websites in a preset region, and the subjective appeal of a user for website layout optimization in the preset region; determining a predefined unsupervised melon score algorithm or supervised melon score algorithm as a target melon score algorithm according to the subjective appeal of the user for network layout optimization in the preset area; according to the method, the target melon score algorithm is adopted to predict the final resource melon score rate of each to-be-evaluated website, and website layout optimization is performed in the preset area according to the final resource melon score rate of each to-be-evaluated website, so that the resource melon score rate of each to-be-evaluated website can be accurately determined, and the website layout in the preset area is effectively optimized.

The invention discloses a post-grouting monitoring method and system for a cast-in-place column, and the method comprises the steps: carrying out the partitioning of a three-dimensional distribution data set of a grouting material through employing a grid division algorithm, and determining a coverage range, aiming at a business scene problem that the distribution of the grouting material in an underground space is not uniform, and the deformation of a soil body is difficult to control in real time; and soil deformation and stress change are monitored in real time by using a distributed optical fiber sensing technology. And when deformation exceeds a threshold value, constructing a spatial correlation model of the grouting point and soil deformation through a finite element analysis algorithm, calculating a correlation coefficient of offset and deformation, determining a dynamic adjustment direction of grouting parameters, optimizing grouting flow and pressure by adopting a gradient descent algorithm, and updating grouting material distribution data. According to the method, three-dimensional accurate positioning of the grouting material is achieved in the post-grouting process of the cast-in-place column, real-time space correlation is conducted on positioning data and surrounding soil deformation data, and the grouting monitoring effect is improved.

The invention relates to the technical field of coal unloading machine intelligent control, in particular to an intelligent coal unloading machine coal unloading control system and method.An environment fusion sensing unit fuses coal pile point cloud data of a three-dimensional laser scanner and RGB-D camera texture information, a real-time digital twinborn model is constructed through hierarchical semantic segmentation, and a real-time digital twinborn model is constructed; and the autonomous decision planning unit adopts a layered optimization strategy, divides coal unloading grids by a global layer heuristic space division algorithm, plans a grab bucket, generates a spiral progressive cabin cleaning track of a self-adaptive entry point based on the curvature gradient of the coal pile by a local layer, and plans the spiral progressive cabin cleaning track of the self-adaptive entry point based on the curvature gradient of the coal pile. The dynamic posture adjusting unit is used for dynamically correcting the cut-in angle, the excavation depth and the swing amplitude of the grab bucket by collecting excavation resistance moment data and combining with the coal pile thickness to build a coal hardness grading model, and the closed-loop vibration suppression control unit is used for generating a vibration suppression signal by adopting an active damping controller of a Lyapunov stability theory, so that the optimal energy consumption of the grab bucket is realized.

The invention relates to the technical field of building engineering construction, and discloses an engineering deployment method based on a construction stage, and the method comprises the following steps: obtaining basic engineering data and real-time construction dynamic data of a construction project through a multi-source collection device, and generating a standardized construction data set; based on the standardized construction data set, performing construction stage division processing by adopting an intelligent division algorithm, and outputting construction stage division data; a standardized construction data set is formed by integrating multi-source data, construction stage division data is generated based on an intelligent division algorithm, the objectivity and consistency of division of different construction stages are guaranteed, meanwhile, the whole construction process is dynamically divided through the clustering analysis and time sequence pattern recognition technology, the construction progress change is adapted in real time, and the construction efficiency is improved. The accuracy of stage division is ensured, and the rationality and adaptability of project deployment are improved.

The present application belongs to the technical field of coal mine safety, and particularly relates to a dynamic threshold division and multi-factor early warning algorithm model for gas emission of a working face, a dynamic threshold division algorithm model, which comprises an FC-Kmeans model and a GA genetic algorithm model, the FC-Kmeans model comprises two stages: initialization of a clustering center and updating of the clustering center, the GA genetic algorithm model is a GA model based on a fitness function, and is used for clustering quality evaluation of a clustering result output by the FC-Kmeans model; a multi-factor algorithm model, which comprises a Transformer model and a MOA model, the Transformer model is composed of three parts of input, encoder structure and output, and embedding of the MOA model enables information entering the input part of the Transformer model to first enter a multi-head attention layer to extract information, and the multi-head attention layer is composed of multiple self-attention layers. The two models can dynamically divide a threshold range corresponding to a gas early warning level, and comprehensively early warn a real-time state, a fluctuation state and a trend state of gas emission of the working face.

The embodiment of the invention provides an STL (Standard Template Library) grid region division and re-subdivision method and device based on feature preservation. The method comprises the following steps: acquiring an initial grid container; subdividing triangular units in the initial grid container based on a longest edge bisection algorithm; the subdivided triangular units are stored in a subdivision grid container; feature boundary extraction is carried out on triangular units in the subdivided grid container in a dihedral angle threshold value judgment mode; on the basis of the feature edges of the triangular units in the subdivided grid container, performing feature curved surface division on the triangular units in the subdivided grid container through a curved surface division algorithm based on depth-first search to obtain a plurality of feature curved surfaces; and through harmonic mapping and an AFT-Delaunay method, parameterization is carried out on the characteristic curved surface, and mesh generation of the characteristic curved surface is completed. In this way, key geometric features such as sharp edges and ridges of the model can be accurately recognized, the dependence on the initial grid quality is reduced, and the generated grid quality is greatly improved.

The invention provides a commercial vehicle energy consumption accurate metering and analysis method and system based on multi-source data fusion, and the system comprises a vehicle-end multi-dimensional sensing module which is used for collecting electrical parameters, load, high-precision positioning and gradient, and environment and battery temperature data; the data preprocessing and fusion module is used for carrying out preliminary screening based on a commercial vehicle working condition characteristic threshold value and a 3 sigma principle and innovatively fusing load and slope data to carry out type judgment on electrical parameter anomalies; the precise energy consumption calculation module is used for calculating net power consumption through a difference method by adopting a dynamic interval division algorithm and taking each kilometer as a unit, so that accumulated errors are avoided; and the self-adaptive transmission and cloud processing module is used for adjusting a data transmission strategy according to a network condition and processing mass data by adopting a distributed architecture. According to the invention, contextualization, high-precision analysis and deep attribution of commercial vehicle energy consumption are realized.

The invention relates to the technical field of seismic data processing, and particularly discloses an offset superposition data frequency division method and device, and the method comprises the steps: mapping a frequency to a wave number through employing a frequency dispersion relation in imaging; converting the wave number into a frequency operator; performing frequency division on the offset superposition data based on a frequency operator to obtain a frequency division result of the current frequency band; and repeating the steps to obtain frequency division results of all frequency bands. According to the method, a set of offset superposition data frequency division algorithm with low calculation amount is researched and developed by utilizing a wave equation frequency dispersion relation, the time-consuming step of prestack depth offset is not carried out, and the frequency division is directly carried out by utilizing an offset superposition data body, so that the effect close to prestack frequency division is achieved on the premise of keeping high efficiency, the high efficiency of calculation is ensured, and the calculation efficiency is improved. The problem of huge calculation amount of pre-stack frequency division and the problem of unidirectional wavenumber approximation of post-stack frequency division are solved.

The application provides a kind of intelligent factory quality inspection method and system based on machine vision, by collecting the multi-angle three-dimensional point cloud image and corresponding surface texture image of target workpiece under different illumination conditions, obtain multi-source quality inspection data group, carry out cross-modal feature registration, construct multi-modal feature space, carry out discretization processing to multi-modal feature space by grid division algorithm, generate standardized feature vector set, then carry out multi-scale topological structure analysis, calculate the persistent homology group between features to extract the feature correlation mode of different grid units, generate the difference feature atlas describing the difference of space structure, finally call the preset defect sensitive area weight model to carry out area weight weighting processing on the difference feature atlas, calculate to obtain the comprehensive defect score reflecting the overall defect degree of workpiece. Comprehensive defect score can reflect the influence degree of different area structure difference on overall quality, improve the adaptability of quality inspection result and actual production process demand.

The invention relates to an anti-money laundering detection method and system based on community and loop joint detection. The method comprises the following steps: acquiring transaction data among a plurality of accounts, and constructing a transaction network diagram; dividing the transaction network diagram into a plurality of communities by using a community division algorithm; filtering communities based on a first preset rule to obtain a target community; detecting transaction data in the target community by adopting a directed loop detection algorithm, and identifying a fund loop path with a loop mode; filtering the fund circulation path based on a second preset rule; and carrying out risk scoring and grade marking on the suspicious transaction chain in the suspicious fund circulation path. By adopting the method, the money laundering behavior lower than the supervision threshold can be effectively identified, the missing report rate and the false report rate are reduced, and the accuracy and efficiency of anti-money laundering detection are improved.

The invention discloses a motor fault state monitoring method and system based on deep learning, a computer program product and a storage medium. The method comprises the following steps: collecting a vibration signal and a rotating speed signal in a motor operation process in real time; according to the rotating speed signal, identifying a current working condition section of motor operation by using an interval division algorithm; in the current working condition section, a section of vibration signal and a section of rotation speed signal in a first duration and a second duration are intercepted according to a preset time rule to form a first signal section and a second signal section; performing equal-angle resampling on the first signal segment and the second signal segment, and generating respective corresponding order spectrograms through Fourier transform; splicing the two order spectrograms according to a time axis to form a spliced spectrogram as a data sample, forming a data set, and training a model; the spliced spectrogram data samples are input into a pre-trained neural network model for reasoning, the neural network model is used for recognizing whether the spliced spectrogram data samples have differences or not, a result is output, and whether the motor breaks down or not is judged.

The application provides a kind of wide-area charging facility-oriented operation and maintenance resource dynamic scheduling method, medium and system, belongs to wide-area charging facility operation and maintenance technical field, the present application is by receiving charging facility fault information and carrying out edge preprocessing, based on manifold learning driven multi-scale district adaptive fractal division algorithm dynamically generates operation and maintenance responsibility partition, match fault information to corresponding operation and maintenance responsibility district, start fault cascade propagation prediction model to deduce and calculate operation and maintenance resource pre-deployment location, execute multi-objective optimization operation and maintenance personnel scheduling decision, generate electronic work order and execute spare parts intelligent linkage, implement whole-process dynamic tracking and closed-loop management, through artificial intelligence prediction fault cascade propagation path and combine dynamic partition division and resource pre-deployment mechanism, solve the technical problems that wide-area charging facility operation and maintenance resource scheduling response lag and difficult to adapt to the dynamic change of fault space-time distribution.

The invention discloses an intelligent bus timetable dynamic generation method and system based on multi-source data, and belongs to the technical field of intelligent city buses, and the method comprises the following steps: 1, analyzing a city bus multi-line data file, and obtaining a data set of line station names, longitudes and latitudes, historical passenger flow data, initial departure time and legal departure frequency; 2, time periods are dynamically divided based on a dynamic time period division algorithm and passenger flow, an optimization model is constructed by adopting three timetable generation principles and four departure frequency calculation methods, and an optimized departure time sequence of each station is generated based on the initial departure time and the dynamic optimization model; 3, adjusting the departure-arrival time of multiple routes at the transfer station through a transfer cooperation algorithm; and step 4, outputting the optimized departure time table and a visual output result. The problem of low efficiency of traditional scheduling can be solved, the operation cost is reduced, and the satisfaction degree of passengers is improved.

The application discloses a RCS recovery and compensation calculation method based on flexible metal mesh equivalent surface reconstruction, which comprises the following steps: collecting the structure of the metal mesh, the test scene, the fitting state parameters and the measured RCS original data, and forming a standardized parameter database after preprocessing; adopting an adaptive density triangular division algorithm to disassemble the complex curved surface into triangular facets, constructing an electromagnetic reflection model for each triangular facet, correcting the electromagnetic coupling effect of adjacent facets, and integrating the complete equivalent reflection surface; dividing the system error and random error of the RCS measurement, establishing an error calculation model through electromagnetic theory derivation and experimental data fitting, and determining the weight through the entropy weight method; adopting a hybrid compensation strategy to compensate the system error, the random error and the curved surface reconstruction error, and verifying the recovery accuracy and the curved surface adaptability after outputting the accurate RCS data. The method greatly improves the RCS recovery accuracy, can well adapt to the complex curved surface of equipment, and meets the high-precision engineering test demand.

The invention provides a relay fragment dynamic capacity expansion method and a block chain system for realizing the method. The method comprises the following steps of: responding to a relay fragment expansion scheme collection by nodes voluntarily participating in operation of a relay fragment division algorithm, and respectively operating the relay fragment division algorithm under a chain to generate respective preferred relay fragment division schemes; the consensus node votes from the optimal relay fragmentation division schemes to select an optimal relay fragmentation division scheme; and carrying out capacity expansion on the relay fragments according to the optimal relay fragment division scheme. The system comprises at least one relay fragment which is used for managing cross-fragment transaction forwarding between service fragments and guaranteeing the safety of the service fragments; the governance fragment is used for being responsible for all on-chain governance functions, configuring a proposal consensus for other global systems, monitoring the load of each relay fragment and initiating a relay fragment capacity expansion scheme collection; and the multiple groups of service fragments are responsible for specific transactions.

The invention discloses a method for generating a war game deduction map based on a GIS (Geographic Information System). The method comprises the following steps: acquiring a GIS data set, and performing coordinate unification and data clipping processing on the GIS data set to obtain processed standardized geographic data; based on the standardized geographic data, establishing a hexagonal grid on the two-dimensional projection plane by using a grid division algorithm, and adjusting the side length of a hexagonal grid unit of the hexagonal grid according to the elevation variance of each region to obtain a hexagonal grid division result; for each hexagonal grid unit, calculating an area proportion of each ground feature type in the hexagonal grid unit, and calculating fuzzy probability distribution of the ground feature types based on the area proportion; obtaining feature entropy distribution data according to the fuzzy probability distribution; and based on the feature entropy distribution data, performing adaptive symbol generation and rendering processing on each hexagonal grid unit. The technical problem that a map generated by existing war chess deduction is inaccurate is solved.

The invention discloses a resource benefit evaluation method and device, electronic equipment and a storage medium, and relates to the technical field of resource benefit evaluation, and the method comprises the steps: building a three-dimensional feature space containing a business type, coverage quality and user density based on multi-dimensional feature data, and outputting the prediction results of resource benefits in different business scenes through a dynamic mapping model. And benefit grading is carried out through a preset grading algorithm, so that the problems that a mapping relation between flow and physical resource block utilization rate is distorted and a 5G network complex environment is difficult to adapt due to the fact that a service classification mode based on 4G experience is adopted and a static threshold value is depended in an existing 5G cell resource benefit evaluation method can be solved; the technical effect of improving the accuracy, adaptability and flexibility of resource benefit evaluation is achieved.

The invention discloses an electric power 5G network slice deterministic service guarantee method, and belongs to the technical field of electric power communication. The method comprises the following steps: firstly, classifying and grouping power services according to guarantee demands such as service bandwidth, time delay and bit error rate, and establishing an LSTM neural network model to predict a resource demand trend of packet services; and dynamically evaluating the slice resource state through a comprehensive utilization rate calculation model fusing PRB, bandwidth, CPU and other multi-factor weights. And identifying a resource overrun time period based on a preset threshold value and a buffer period strategy, and carrying out capacity expansion / reduction adjustment on the network slice under the condition that a preset stable proportion condition is met in combination with an overrun region division algorithm. According to the method, through prediction driving, multi-dimensional evaluation and stability optimization, the power 5G network resource utilization efficiency is remarkably improved, the service quality of deterministic services is ensured, meanwhile, the operation and maintenance complexity is reduced, and an effective guarantee is provided for high-reliability and low-delay communication requirements of a power system.

The invention discloses an emergency evacuation supervision method and device based on an emergency broadcast system, and relates to the technical field of emergency broadcast supervision, and the method comprises the steps: dividing a target village into a plurality of management grids through a spatial clustering and graph division algorithm based on the residence position of each villager, the safety collection region position and a village road network, and carrying out the management of the village. The method comprises the following steps: analyzing a monitoring video stream returned by monitoring equipment located in an exit area of each management grid in real time in each management grid; determining the state of the non-evacuated villagers and executing a supervision strategy; distributing patrol personnel to the management grid nearby or inserting targeted reminding information to the nearest emergency broadcasting equipment which is playing the evacuation information according to the residence position information of the non-evacuated villagers. Through monitoring the evacuation completion condition of villagers in each management grid, non-evacuated villagers can be quickly found, point-to-point assistance and reminding of patrol personnel can be accurately scheduled, and the supervision closed loop of the evacuation state of the villagers in the emergency evacuation process can be completed.

The application discloses a kind of based on target k-coverage multi-unmanned plane auxiliary charging and data acquisition method, comprising: obtaining and defining wireless chargeable sensor network area and related parameter set;Formalization based on target k-coverage unmanned plane minimization deployment problem;Using the clustering division algorithm based on coalition formation game, obtain disjoint sensor set family;Using restricted Prim algorithm, obtain candidate charging sensor set;Using the unmanned plane minimization deployment algorithm without neighborhood based on edge weight threshold, obtain the flight trajectory of all unmanned planes, supply power for the sensor of insufficient power, and collect the perception data of data concentrator.Greatly reduce the deployment cost of unmanned plane, ensure the long-term operation of wireless chargeable sensor network, while collecting important perception data for professional data analysis.

The invention discloses a privacy track fuzzy matching method for collision early warning of an unmanned aerial vehicle. The method comprises the following steps that S1, an initiator and a responder set and share public parameters related to collision early warning; s2, the initiator and the responder respectively execute a super-dimensional cube division algorithm based on the common parameters, and track point coordinate information of the initiator and the responder is converted into a tetrad identifier based on a division result; s3, the initiator carries out OKVS coding on the three-dimensional positions of the own track points and the neighborhood points and the corresponding timestamps to obtain a message of an OKVS structure and sends the message to the responder; step S4, the responder performs linear decoding on the request message by using a Gaussian elimination method to generate a DDH re-randomized tuple, and further constructs a mask message and feeds back the mask message to the initiator; and S5, the initiator carries out decryption and comparison based on the feedback message to obtain a collision early warning judgment result. The method has the advantages of being high in early warning real-time performance, high in precision and high in safety.