98 results about "Vector field" patented technology

The invention provides a shield tunnel longitudinal seam joint recessive damage diagnosis method based on multi-mode ultrasonic guided waves, and the method comprises the steps: applying orthogonal polarization in a specific region of a longitudinal seam joint, and forming a space-time coupled guided wave interference pattern in the whole region of the longitudinal seam joint; the acquired guided wave interference map is utilized to separate baseline interference characteristics and abnormal disturbance components caused by hidden damage through multi-physics field reverse decoupling, and the abnormal disturbance components are represented as energy abnormal attenuation and phase distortion in a specific polarization direction; constructing a three-dimensional damage sensitive vector field in the longitudinal seam joint; and carrying out dynamic manifold topology analysis by utilizing the generated three-dimensional damage sensitive vector field, identifying topological characteristics in the three-dimensional damage sensitive vector field, and tracking a migration path and an intensity evolution trajectory of the topological characteristics along with the change of the detection condition. According to the method, full-dimension diagnosis and evolution prediction of the hidden damage of the longitudinal joint connector of the shield tunnel are realized.

The invention discloses an airspace engine 3D printing deformation compensation method. The method comprises the following steps that S1, a three-dimensional CAD model is constructed, and a printing layer set is generated; s2, obtaining residual stress tensor fields of the current printing layer and the historical printing layer; s3, constructing a stress shadow mapping tensor; s4, inputting the stress shadow mapping tensor and the current printing layer parameter into the reverse stress propagation neural network model, and outputting a deformation prediction vector field; s5, performing geometric compensation processing on the geometric area of the printing layer according to the deformation prediction vector field; s6, generating a printing code according to the compensated geometric model; and S7, carrying out error comparison on the actual deformation vector field and the overall prediction deformation vector field, if the error is greater than a preset tolerance threshold value, feeding back error information to the step S5, and repeatedly executing the steps S5 to S7 until the error vector field does not exceed the tolerance threshold value. According to the method, residual stress modeling and the reverse stress propagation neural network are fused, and 3D printing deformation compensation of the airspace engine is achieved.

The invention relates to the technical field of shoe body detection, in particular to a shoe body quality detection method based on image visual analysis, which comprises the following steps: synchronously acquiring three-dimensional contour and surface spectral information of a to-be-detected shoe body through three-dimensional scanning and spectral imaging equipment to obtain original point cloud spectral data; performing registration and fusion processing on the original point cloud spectral data to construct a registered hyperspectral three-dimensional grid model containing space coordinates and hyperspectral reflectivity values; and calculating a normal vector field and a curvature distribution diagram of the surface based on the hyperspectral three-dimensional grid model so as to quantify geometric features of the surface of the shoe body. According to the invention, through registration and fusion processing, surface spectral information collected by a spectral imaging device is reversely projected and interpolated to each space coordinate vertex of an initial three-dimensional point cloud constructed by a three-dimensional scanning device, so that a registered hyperspectral three-dimensional grid model is constructed, and a surface chemical characteristic spectrum is endowed with three-dimensional space geometric coordinates. And the detection capability is improved.

The invention relates to a nondestructive flaw detection method and system, and the method comprises the steps: carrying out the dynamic coupling wave mode decomposition of a response signal, and obtaining a basic wave mode component and an energy ratio; aiming at a plurality of discrete time-frequency scale units, constructing a multi-scale time-frequency energy flow graph cluster based on the basic wave mode component and the energy ratio; calculating the direction gradient of each energy flow graph in the energy flow graph cluster by taking the energy amplitude as the weight to obtain a gradient vector field; determining a suspicious region according to topological structure characteristics of the gradient vector field and an abnormal threshold value of a wave mode energy ratio in the energy flow graph cluster; determining the boundary of the suspicious region based on the trajectory of the gradient vector field; performing depth distribution inversion calculation on the suspicious region according to the energy attenuation gradient of the multi-scale energy flow diagram and the attenuation of each basic wave mode energy in the depth direction; and performing regularization tomography by using the energy ratio and spatial distribution of each fundamental wave mode as multi-channel input, and reconstructing the three-dimensional geometrical morphology of the suspicious region.

The invention relates to a welding seam point cloud extraction method and a welding seam track generation method based on a normal vector field, and solves the technical problem of how to improve the accuracy of identifying a welding seam from point cloud information of a workpiece. The method comprises the following steps: carrying out operations such as preprocessing and splicing on multi-view point clouds to obtain complete and pure workpiece point clouds, carrying out normal vector and divergence estimation on the workpiece point clouds to segment a plurality of welding seam point clouds of a workpiece, and separating the plurality of welding seam point clouds into independent welding seam point clouds based on a region growing method; and fitting of various geometric configurations is carried out on the welding seams, so that the fitting degree of the fitted welding seam track and the real welding seam track is improved. The complete acquisition of the workpiece point cloud and the accurate generation of the welding seam track are realized, so that the subsequent welding track planning use is realized.

The invention discloses an energy consumption management system and method for a data center, and relates to the technical field of data center thermal management, and the method comprises the steps: carrying out the noise reduction of a structured data set through quantum harmonic oscillator coupling wavelet transform, and generating a real-time three-dimensional thermal distribution diagram through a Kriging spatial interpolation algorithm, solving a Navier-Stokes equation by combining the magneto-rheological grid wind resistance value, and extracting a heat flow vector; injecting pulse voltage into the microcapsule phase-change material layer according to the dual-channel execution instruction set to trigger phase-change heat absorption, reducing the viscosity of a target path by using a space gradient magnetic field, and generating a three-dimensional wind speed vector field; the real-time three-dimensional thermal distribution diagram is generated through the Kriging space interpolation algorithm, high-precision monitoring and analysis of the complex thermal environment of the data center are achieved, the accuracy of local hot spot recognition is improved, and therefore the energy utilization efficiency and the cooling effect are remarkably improved, and the purposes of reducing energy consumption and improving the operation stability and energy efficiency of the data center are achieved.

The invention relates to the technical field of motion control, in particular to a motion trail real-time optimization analysis method and system based on multi-modal perception, and the method comprises the following steps: a multi-sensor array obtains position and speed visual features, carries out the coordinate transformation, extracts a direction amplitude, and builds a multi-modal perception data set; the method comprises the following steps: inputting Kalman filtering prediction trajectory comparison deviation to generate a trajectory deviation vector field, calculating a deviation gradient, screening an over-threshold point marking time sequence, generating a dynamic weight correction parameter through weighted least square distribution normalization, and outputting a real-time optimization trajectory scheme through weighted correction fusion coordinates. The position information and the velocity vector of a moving target are obtained in real time by fusing multi-modal sensing data, a state estimation model is combined to predict a trajectory, a trajectory deviation vector field is generated, and a deviation point is subjected to weighted correction, so that the trajectory optimization precision is effectively improved, the weight is dynamically allocated to optimize the priority, and the trajectory optimization precision and the system stability are improved. And the self-adaption and robustness in a complex environment are enhanced.

The invention relates to the technical field of magnetic material injection molding, and discloses an injection molding magnetic powder orientation optimization method and system based on rheology-magnetic field coupling. The method comprises the following steps: deploying a distributed sensing network at key positions of a mold runner and a mold cavity, and synchronously capturing dynamic viscosity change gradient and magnetic field intensity space distribution of a melt in real time in a filling process. The captured data are input into a multi-physics field coupling simulation engine based on micromechanics, an instantaneous orientation vector field of the magnetic powder in the cavity is obtained through calculation, then an orientation order degree topological graph is constructed through tensor analysis and an image algorithm, and a weak orientation area and the boundary of the weak orientation area are accurately recognized. And finally generating a composite regulation and control instruction of the magnetic field and the injection parameters according to an identification result. According to the method, online diagnosis and active compensation regulation and control of the orientation state of the magnetic powder can be realized, and the orientation uniformity and consistency of the injection molding magnet are improved.

The invention provides a monitoring method and system for the conveying state of grain capable of being washed based on multi-mode sensing. Multi-axis laser speed measurement probes with dust covers are arranged on the two sides of the conveying belt, so that interference of dust to a light path is eliminated. Laser Doppler frequency shift signals of surface particles and echo intensity data of deep particles are synchronously collected, and a hierarchical control volume model is established; and utilizing the echo intensity to compensate the scattering signal, and generating a flow velocity distribution profile map through self-correlation processing. A particle motion vector field is further constructed by adopting an optical flow method, and a collision energy value is calculated through vector field energy distribution. When the energy value exceeds a preset threshold value, a positioning early warning signal is generated, and real-time monitoring and accurate positioning of particle collision abnormity are achieved. According to the technical scheme, full-dimension monitoring of the particle motion state in the grain conveying process can be achieved in the high-dust environment, collision abnormity is effectively recognized, the fault area is accurately positioned, and the grain conveying quality is guaranteed.

The invention discloses a multi-dimensional metering system and metering method based on an FPGA, and belongs to the technical field of electronic data processing, and the system comprises a data collection module which is used for obtaining and preprocessing multi-source sensing data; the simulator construction module is used for constructing a multi-physics field interference simulator and loading a geometric model and a physical response coefficient of a reference shadow workpiece, the reference shadow workpiece is digital representation of an actual measured workpiece, and the geometric model and the physical response coefficient of the reference shadow workpiece are mutually decoupled data sets; the vector field generation module is used for generating a pre-distortion vector field based on the output of the interference simulator and the reference shadow workpiece; and the interference identification module is used for extracting primary features from the multi-source sensing data. Through constructing a multi-physical field interference simulator and generating a pre-distortion vector field, physical state drift of a cross-sensing channel is accurately modeled, a multi-sensor data fusion error is reduced, and data consistency and reliability in a high-speed dynamic measurement scene are improved.

The invention relates to the technical field of visual inspection, and discloses a piston rod surface defect detection method and system based on visual inspection. According to the method, firstly, a depth-of-field image data set containing color saturation features of each depth-of-field level is obtained, and a detection process is triggered by calculating the overall color vision offset of the color saturation features and reference features. When the offset exceeds a threshold value, point cloud data are extracted, an oxidation area three-dimensional model is constructed through surface contour fitting, and first space contour data are output; after the oxidation depth is divided into grid units, a depth gradient vector field and local curvature features are calculated, and oxidation depth distribution data are obtained; and grading and generating an oxidation degree distribution diagram based on the data, and finally correcting the boundary of the three-dimensional model in combination with an original image data set to generate accurate second space contour data. According to the method, color features and depth information are fused, accurate positioning, quantitative grading and boundary correction of the oxidation corrosion area are achieved, and reliable support is provided for automatic detection of piston rod surface defects.

The invention provides an automatic scanning and measuring method for a blade margin plate gap, and belongs to the technical field of industrial machining.The automatic scanning and measuring method comprises the steps that a corresponding relation between a workpiece and a machine coordinate system is established by constructing a three-dimensional measuring coordinate system, and a laser scanning measuring head is adopted for conducting full-circumferential automatic scanning to obtain high-density point cloud data; fitting a gap curved surface by using a least square method, calculating geometric deviation, constructing a multi-dimensional error compensation vector field of a spatial position, an optical system, material thermal expansion and the like, establishing an airflow model based on fluid mechanics, and analyzing airflow characteristics through a numerical solution and analytical solution method. A measurement problem is converted into a traveling salesman problem, an improved ant colony algorithm is applied to optimize a scanning path, gap uniformity analysis is carried out, a gap curve is decomposed through Fourier series expansion to recognize an abnormal rule, a comprehensive evaluation report is finally generated, and the core problem that the measurement precision is affected by multi-dimensional errors is solved.

The invention relates to the technical field of image recognition, in particular to a petrochemical pipeline leakage recognition method based on an unmanned aerial vehicle inspection image, which comprises the following steps: generating a pixel-level surface normal vector field according to an unmanned aerial vehicle inspection image sequence, and calculating an angle variation between adjacent vectors in the pixel-level surface normal vector field, and generating a surface normal vector gradient map in combination with luminosity change information of the multiple frames of images. According to the method, the analysis range is focused in the determined geometric deformation candidate area, the unique gloss and color change characteristics of liquid leakage are captured, and finally, the wet abnormal coordinate set and the geometric deformation area are subjected to space alignment and overlapping judgment, so that the high credibility of an identification result is ensured, and the identification accuracy is improved. False report and missing report caused by interference of environmental factors such as illumination change and surface stains of a single feature source are avoided.

The embodiment of the invention provides an aviation gravity and magnetic vector dynamic measurement method based on multi-source data synchronous fusion, and relates to the technical field of data acquisition, after sensor array data on a driving flight platform is acquired, a specific force measurement value, a carrier pitch angle, a carrier roll angle and a carrier motion parameter are calculated and output; calculating three output gravity disturbance components by adopting carrier motion parameters and specific force measurement values; fusing total field data of the optical pumping magnetometer to carry out magnetic vector calculation on three-component data of the fluxgate and outputting geomagnetic total elements; and taking a carrier pitch angle, a carrier roll angle, a carrier position, a carrier speed and a carrier course angle as carrier pose data, combining the geomagnetic total elements and the carrier pose data, and outputting a dynamic measurement result of the gravity-magnetic vector field. The problems that in the prior art, gravity measurement and magnetic measurement are separated, equipment redundancy is low in efficiency, collection time is asynchronous, and data precision is reduced are solved. The effect of high-precision, high-dynamic and high-efficiency synchronous acquisition of the gravity and magnetic vector data under the single platform is achieved.

The present application relates to the technical field of additive manufacturing online monitoring and closed-loop control, in particular to a 3D printing workpiece defect identification system based on image detection; containing coaxial acquisition, potential mapping, diffusion analysis, singular point extraction and bidirectional feedback module; the system converts the collected image stream into a virtual flow velocity vector field; the core is to simulate the evolution of the physical field by using the virtual viscosity diffusion algorithm, calculate the difference of the vector field before and after diffusion to extract the topological mutation, and generate a defect potential thermal map; based on the potential value of the thermal map, the system performs bidirectional feedback of generating G code intervention instructions and adjusting the virtual viscosity coefficient; the present application reduces the pattern recognition to local physical field simulation, without sample training, and realizes millisecond-level real-time response.

An embodiment of the present application discloses a method for simulating motion artifacts. The method may include determining a segmented motion vector field of a target object based on an artifact simulation model. The method may include determining a segmented reconstructed image by segmentally reconstructing a target image, and the method may further include generating a motion artifact simulation image based on the segmented motion vector field and the segmented reconstructed image.

The invention discloses a variable-scale multispectral remote sensing image segmentation method using a spectral index, which belongs to the technical field of remote sensing image processing, and comprises the following steps: firstly, determining the gradient of a multispectral remote sensing image by using a vector field model, generating a mark according to the gradient, selecting a proper spectral index, and carrying out image segmentation according to the spectral index; and carrying out image segmentation by using watershed transformation. According to the variable-scale multispectral remote sensing image segmentation method using the spectral index, optimization is carried out by using the spectral index, the capability of distinguishing different ground feature types is enhanced, and the segmentation precision is improved; according to the method, watershed transformation is adopted for segmentation, so that the image segmentation result is more stable and efficient, the method can adapt to remote sensing images of different scales, the quality and effect of remote sensing data processing are improved, and mathematical morphology-based variational scale watershed segmentation is optimized.

The invention discloses a rapid calculation method and device for the sensitivity of a linear periodic time-varying system based on a matrix sparse technology, and belongs to the technical field of modeling analysis of the linear periodic time-varying system.The rapid calculation method comprises the steps that an LTP system is converted into an equivalent LTI system, and the eigenvalue, the left eigenvector and the right eigenvector of the LTP system are obtained; based on a functional derivative method, obtaining a sensitivity analytical expression of the LTP system characteristic value to the parameter; according to the influence mechanism of the parameters on the system matrix, obtaining an analysis form of the influence of the parameters on the LTP system matrix in the sensitivity analysis expression; and converting a partial derivative of a system matrix to a steady-state trajectory into sparse calculation of a vector field Hessian matrix by using a matrix sparse technology, thereby obtaining a calculation result of the characteristic value sensitivity of the LTP system. According to the method, the sparse characteristic of the system matrix in the PEPS is utilized, the calculated amount and the storage requirement of the system matrix on trajectory partial derivative solving are reduced, and therefore calculation of the LTP characteristic value sensitivity is accelerated.

The present invention discloses a near-term extrapolation forecasting method for fast-moving quasi-linear convection. The method comprises the following steps: within half an hour of the onset of the forecast, the echo is extrapolated using the semi-Lagrangian extrapolation method based on the mixed extrapolation vector field of the convective monomer; and half an hour after the onset of the forecast, the echo is extrapolated using the semi-Lagrangian extrapolation method based on the extrapolation vector field of the convective organization propagation characteristics. This method can improve the short-term extrapolation forecast accuracy of fast-moving quasi-linear convection and significantly enhance the early warning capability of fast-moving quasi-linear convection, representing a technological breakthrough for meteorological disaster prevention and mitigation of severe convection.

The invention relates to the technical field of permanent magnet magnetizing, and discloses a complex curved surface permanent magnet multi-pole magnetizing method and system. The method comprises the following steps: preparing a permanent magnet to be magnetized and importing magnetization vector field data; carrying out adaptive grid division on the permanent magnet to be magnetized, determining a magnetizing sequence from strong to weak, and planning a magnetizing path; pre-magnetizing each magnetizing unit according to a path sequence, and generating a pulsed magnetic field meeting parameter requirements to complete magnetizing; magnetic field distribution measurement and deviation calculation are carried out, an actual magnetization vector field is reconstructed, the deviation between an actual magnetization vector and a target magnetization vector is calculated, and standard exceeding units exceeding a precision threshold value are identified; and establishing a magnetizing response model, obtaining coupling interference of adjacent units, calculating compensation parameters of standard-exceeding units, and performing iteration until the whole magnetic field distribution meets the precision requirement. Omnibearing and high-precision multi-pole magnetizing of the complex curved surface permanent magnet is achieved, the magnetizing direction can be continuously changed in a three-dimensional space, and interference of adjacent areas is effectively restrained.

The invention discloses a distributed intelligent door lock control system and method for executing separation, and relates to the technical field of intelligent equipment control, and the method comprises the following steps: based on acquired multi-band electromagnetic field intensity data of a guest room area, reconstructing discrete electromagnetic field intensity data into a two-dimensional gridding interference intensity distribution diagram by using a spatial interpolation algorithm; gradient field calculation is carried out based on the interference intensity distribution diagram, the gradient amplitude of each grid point is obtained, a space gradient vector field is generated according to the gradient amplitude, and an interference propagation flow path diagram is generated based on the space gradient vector field; all interference frequency bands in the interference intensity distribution diagram are extracted, the overlapping coefficient of the interference frequency bands and the main working frequency band of the intelligent door lock is calculated, and when the overlapping coefficient exceeds a preset threshold value, dangerous overlapping is judged; the pain point caused when the legal user is rejected outside the door is avoided; accurate monitoring, efficient response, reliable unlocking and comprehensive adaptation of the intelligent door lock in an interference scene are integrally guaranteed.

This specification discloses a method and system for correcting scanned data. The method includes: acquiring multiple motion vector fields corresponding to multiple motion time points of a target object based on reference time points; acquiring image motion deviations corresponding to each motion time point based on the motion vector fields corresponding to each motion time point and the motion reconstruction images corresponding to each motion time point; acquiring raw data deviations corresponding to each motion time point based on each image motion deviation; and correcting the scanned data based on the raw data deviations corresponding to at least one of the motion time points to obtain corrected data.

The application belongs to the technical field of building structure health monitoring, and discloses a visual perception driven building structure damage intelligent monitoring and evaluation system and method. The method acquires a structure surface image with rolling shutter distortion and motion blur and a transient kinematics state sequence, and constructs a transient motion state space model. A two-dimensional pixel offset vector field coupled with platform displacement and exposure time difference is deduced in combination with structure depth information. An apparent relative displacement of adjacent image frames is extracted, a pure pixel displacement is obtained by using the vector field to strip non-structure deformation, and a real second-order physical strain tensor field is calculated by back-projection to a three-dimensional physical surface. Based on the tensor field and a preset material mechanics threshold, a spatial integral evolution model containing a non-negative truncation operator is constructed to solve a global structure damage intelligent evaluation index, and a monitoring and early warning result is output. The application can effectively eliminate the space-time distortion error of dynamic visual inspection.

The application provides an industrial character image data enhancement method and related equipment, decodes an obtained industrial character normal line image to be processed to obtain a normal line vector field of each pixel, performs mirror inversion and / or an angle measurement-based morphological operation on the normal line vector field to obtain an updated normal line vector field, encodes the updated normal line vector field to obtain an RGB image, stores the RGB image in an image matrix, and obtains an enhanced industrial character normal line image; compared with the prior art, the application directly performs vector field operation on the normal line image to realize controllable deformation of the character surface geometry, thereby generating an industrial character sample with rich morphological diversity, and solving the problems of fixed character geometry morphology, difficulty in simulating changes in concave-convex depth caused by process differences, edge blunting and other deformations in the prior art industrial character data generation method.

The present application relates to the technical field of athlete trajectory and posture analysis, and particularly relates to an AI fusion analysis method and system for athlete trajectory and posture, which encodes and models global trajectory coordinate sequences, local posture joint node coordinate sequences and motion speed vector field data to obtain features and map them to a unified Riemann manifold space, calculates the correlation measure of the trajectory and the posture, and constructs cross-modal fusion features by using dynamic consistency correction, establishes a trajectory-driven posture evolution causal chain based on the features, performs topological analysis on the causal chain to extract abnormal nodes, generates fusion analysis results by using causal interpolation compensation of causal paths unaffected by the abnormality, so as to improve the accuracy and reliability of trajectory and posture fusion analysis.

The application discloses a G1 continuity curved surface reconstruction and generation method based on boundary constraint, and belongs to the technical field of computer aided design and computer graphics technology. Step 1: taking a three-dimensional industrial model to be repaired as input, a unified normalized parameter mapping is established to obtain a standard boundary data set; step 2: taking the standard boundary data set as input, a basic cross-border tangent vector field is obtained; step 3: taking the basic cross-border tangent vector field as input, an original modified cross-border tangent vector field is obtained; step 4: taking the original modified cross-border tangent vector field as input, a tangent plane geometric constraint mechanism is established, and a final cross-border tangent vector field is obtained; step 5: taking the final cross-border tangent vector field as input, a rational harmonic formula is introduced, and four corner point torsion vectors after rational harmonic are obtained; step 6: a high-order B-spline geometric entity meeting an industrial tolerance is generated through a reverse approximation algorithm, and a B-spline curved surface is obtained. The application can automatically generate a high-quality transition curved surface without high-light tearing under complex and disordered boundary constraints.

The application discloses an image efficient generation method and device based on a diffusion model, which realizes efficient high-quality image synthesis through a vector field estimation generation result and a discriminator cooperative optimization mechanism. In the method, Euler discretization is performed in the training process, and a prediction model generation result is generated through single forward propagation, which is used for subsequent model training; a multi-dimensional feature extractor discriminator is used to learn the difference between the prediction generation data manifold and the real data manifold; and the gradient information provided by the discriminator is used to guide the vector field to directly point to the real data manifold while learning the vector field. The application first combines the adversarial training and the vector field learning by efficiently predicting the generation result in the training process, greatly accelerates the generation process, guarantees the high-quality generation of the image, is superior to the prior art, and has the advantages of high generation quality and strong universality.

This invention discloses an AUV obstacle avoidance method, system, computer device, and storage medium based on vector fields and fuzzy rules. By acquiring a sonar dataset, an obstacle recognition model is constructed using a YOLOv4 network and trained on the sonar dataset. The trained obstacle recognition model identifies obstacles and constructs an obstacle environment. A vector field algorithm and fuzzy rules are used to calculate the AUV's desired heading, guiding the AUV to avoid detected obstacles and move towards its destination. In addition to using the vector field algorithm for obstacle avoidance path planning, fuzzy rules for safety distance, unit momentum vector, and roll-up torque are introduced to ensure the safety and effectiveness of local obstacle avoidance, preventing the AUV from getting stuck in local terrain. Compared to traditional obstacle avoidance methods, this invention not only enables AUVs to effectively avoid unknown obstacles but also demonstrates good adaptability and obstacle avoidance capabilities for complex terrains such as parallel obstacles and square well obstacles.

This invention provides an aerial docking method for unmanned aerial vehicles (UAVs) based on magnetic vector fields. The method includes establishing a dynamic model of the UAV; measuring and fitting a mathematical model of the magnetic vector field using a magnetic vector field measurement and simulation device; designing a docking process; calculating new expected torque and force based on the initial expected force and torque and the magnetic vector field mathematical model; compensating for the expected difference using QP compensation to obtain the final expected thrust of the UAV; and controlling the UAV motors based on the final expected thrust of the UAV using a throttle-thrust relationship identification model. This invention achieves high-precision docking and long-term aerial loiter without the need for high-precision sensors or complex mechanical structures. By deploying the fitted magnetic vector field mathematical model into the UAV docking system, this invention achieves UAV docking through electromagnetic force. Furthermore, it effectively integrates the relevant factors introduced by the magnetic vector field, resulting in a more robust docking system.

The embodiment of the application provides a dynamic measurement method for aviation gravity and magnetic vector based on multi-source data synchronous fusion, relates to the technical field of data acquisition, and outputs the specific force measurement value, the carrier pitch angle, the carrier roll angle and the carrier motion parameter after driving the flight platform to collect the sensing array data; adopts the carrier motion parameter and the specific force measurement value to output the gravity disturbance three components; fuses the total field data of the optical pumping magnetometer to perform the magnetic vector calculation and output of the geomagnetic full element of the flux gate three component data; takes the carrier pitch angle, the carrier roll angle, the carrier position, the carrier speed and the carrier heading angle as the carrier pose data, combines the geomagnetic full element and the carrier pose data, and outputs the dynamic measurement result of the gravity and magnetic vector field. The problems that the gravity and magnetic force measurement are separated in the prior art, the equipment is redundant and inefficient, the acquisition time is asynchronous, and the data precision is reduced are solved. The effect of high-precision, high-dynamic and high-efficiency synchronous acquisition of the gravity and magnetic vector data under a single platform is achieved.