961 results about "Direction vector" patented technology

The invention relates to the technical field of light source controllers, and discloses a simulation light source controller parameter adaptive adjustment method and device, and the method comprises the steps: collecting an input voltage signal, an output current signal, an environment temperature signal and a channel power signal of a simulation light source controller, and inputting a neural network model for parameter mapping, obtaining a light source parameter dynamic response matrix; carrying out feature dimension reduction, and constructing a target optimization model; grid division is carried out on the parameter space, a steepest descent direction vector and a vertical search direction vector are respectively generated on divided grid points, and a parameter optimization direction set is obtained; iteratively updating each control parameter to obtain a parameter iteration sequence set; performing a voltage stabilization output test to obtain a plurality of candidate control parameter combinations; and the parallel verification test is carried out, and the optimal control parameter combination is determined, so that the inter-channel crosstalk of the simulation light source controller is effectively inhibited, and the problem of mutual interference when multiple channels work in parallel is solved.

The invention relates to the technical field of industrial component detection, in particular to a transformer iron core detection method based on computer vision, which comprises the following steps of: acquiring an iron core image, extracting key pixel characteristics, screening a directional scattering abnormal region to generate an interference map, extracting a consistent gradient region correction image to generate a reconstruction map, and positioning a symmetric disturbance generation structure map by integral gray difference. And analyzing an overlapping relation by a superposition structure graph to generate an abnormal component graph, and evaluating a risk level by matching a reference index to generate an early warning graph layer. Interference reflection and structural features can be distinguished through linkage analysis of the pixel direction vector and the brightness change frequency, correction of a distorted area in an image is realized based on a gray statistical stable value, and the distortion of the image is corrected by constructing a symmetric point map and analyzing the change trend of a gradient difference value sequence. And the structural overlapping relation is quantitatively judged by combining a component mapping profile diagram, so that the relevance between an abnormal region and a key component is clearly expressed, and the grading evaluation capability of various fault risks in the iron core is improved.

The disclosure provides a communication delay compensation method and a communication delay compensation system based on an autonomous robot, where the method includes the following steps: establishing a state equation based on a system model of an AUV positioning system; acquiring an included angle between a direction vector of AUV to an observation station and a velocity vector of AUV based on the system model; establishing an observation equation according to the state equation and the included angle; establishing an extended Kalman filter equation based on the system model, the included angle and the observation equation; and calculating a position information predicted value at the current time by using the extended Kalman filter equation to complete communication delay compensation.

The invention provides a moving target capturing method and system based on AI multi-view vision, and relates to the technical field of data processing.The method comprises the steps that camera parameters in all vision systems are calibrated, and the camera parameters comprise a camera internal parameter matrix and a camera external parameter matrix; extracting 2D feature points of the moving target through each calibrated visual system; reconstructing each 2D feature point by combining a multi-view geometric reconstruction algorithm and a least square method according to the calibrated camera parameters to obtain 3D feature points; constraints are added to the 3D feature points, and the constraints comprise spatial constraints, direction vector constraints and time sequence constraints; reconstructing the 3D feature points added with the constraints through a multi-view geometric analysis algorithm to obtain three-dimensional motion information of the moving target; and outputting the three-dimensional motion information of the moving target to complete the capture of the moving target. And non-contact high-precision capture of the moving target can be realized.

The invention provides an equipment fatigue crack intelligent detection method and system based on deep learning, and the method comprises the steps: firstly obtaining an equipment surface detection image set, generating a first crack detection thermodynamic diagram through a pre-trained deep learning model, and constructing a crack physical expansion constraint model according to equipment design material parameters and real-time operation condition parameters, then performing crack area iterative optimization based on the first crack detection thermodynamic diagram and the crack physical expansion constraint model to obtain a second crack detection thermodynamic diagram, and analyzing the second crack detection thermodynamic diagram to determine equipment surface crack state parameters such as crack area boundary coordinates, crack expansion direction vectors and crack depth gradient values; and finally, generating an equipment fatigue crack intelligent detection report containing a crack space distribution schematic diagram and a crack propagation risk grade identifier, thereby integrating image data and physical constraints, and improving the accuracy and reliability of crack detection.

The invention relates to the technical field of medical image processing, in particular to a neurosurgery image diagnosis method and system based on image processing, and the method comprises the following steps: obtaining gray matter edge nodes of a triaxial section, constructing a symmetric path unit, collecting an edge direction vector, and generating a direction trajectory diagram; and extracting continuous slices, constructing a rotation track sequence, identifying an abnormal region, filling gaps, combining path voxels, and dividing spatial levels to generate an image structure chart. According to the method, the grey matter edge nodes in the three-axis tangent plane are obtained, and the node paths with the symmetrical characteristics are screened out according to the space projection trend, so that the continuous region of the structure can be accurately recognized, the direction vectors in the continuous slices are extracted, the direction mutation region in the track is recognized, and the jump and fracture performance of the structure can be timely captured; and the abnormal region is accurately labeled, so that higher-dimensional expression and finer-grained recognition of the neural structure are realized, and spatial modeling and visual analysis of complex neuropathy are effectively supported.

The invention relates to the technical field of partial discharge detection, in particular to a leak detection and partial discharge detection method and system based on artificial intelligence, and the method comprises the following steps: obtaining a partial discharge pulse signal, extracting a phase mutation coordinate, analyzing an incremental feature, reconstructing a propagation waveform, constructing an amplitude gradient matrix, and screening a direction vector; and a backtracking path calculates a change rate to generate a time track, and track mapping and space positioning are completed in combination with image data. According to the method, the accuracy and the response speed of partial discharge detection are improved through multi-stage signal processing, extreme points and phase abrupt change are analyzed, more accurate discharge feature capture and equipment defect positioning are achieved, phase and amplitude data are combined, the discharge mode is recognized, a signal propagation path is reconstructed, the fault source positioning accuracy is improved, and the fault source positioning accuracy is improved. Through dynamic rendering, the intuition of a detection result is enhanced, real-time decision is supported, the method is more intelligent and efficient, the equipment fault risk is greatly reduced, and the safe operation level of power equipment is improved.

The invention provides a game model penetration prevention method and device, equipment and a storage medium. The method comprises the steps that a moving direction vector of a hand model is calculated according to current frame position data and previous frame position data of the hand model in a virtual environment; predicting the next frame of position data of the hand model according to the moving direction vector and the current frame of position data, and emitting rays based on the next frame of position data and the moving direction vector; and judging whether the ray has a collision event in the virtual environment or not, and performing position adjustment and model rendering on the hand model when the ray has the collision event. According to the method, through vector calculation and ray detection, the calculation complexity is reduced, and the real-time performance is improved. The introduction of model prediction enables the system to cope with the potential mold-penetrating situation in advance, and further improves the efficiency of mold-penetrating prevention. A direct position adjustment strategy is adopted for collision processing, complex physical simulation calculation is avoided, and therefore the problems that in the prior art, calculation complexity is high, and real-time performance is insufficient are solved.

The invention provides an oral surgery positioning and navigation method and system and a storage medium, and the method comprises the steps: calibrating an implanted mobile phone to obtain a unit vector of a rotating shaft of a drill bit and a three-dimensional coordinate value of the tip of the drill bit under an optical three-dimensional coordinate system, scanning to obtain a CT three-dimensional model of a patient, and segmenting to obtain a tooth CT model and an alveolar bone CT model; generating a tooth three-dimensional point cloud according to the real-time pattern of the speckle structured light on the teeth of the patient, acquiring a matrix transformation relation between a CT three-dimensional coordinate system and an optical three-dimensional coordinate system, and performing real-time navigation on the implanted mobile phone according to the real-time point position deviation and the real-time angle deviation of the drill bit. According to the technical scheme, the matrix transformation relation between the CT three-dimensional coordinate system and the optical three-dimensional coordinate system is calculated through the tooth CT feature points and the tooth point cloud feature points, and auxiliary navigation is carried out by comparing the target position of the implant with the real-time pose of the tip of the drill bit, the direction vector of the planting path and the unit vector of the rotating shaft of the drill bit. Operation is convenient and positioning precision is high.

The invention relates to a method for measuring the spatial pointing precision of a panoramic camera turntable, which comprises the following steps of: firstly, establishing an initial coordinate system for an azimuth axis and a pitch axis, performing data measurement on the two axes during rotary motion through a laser tracker, and calculating circle center coordinates and circular surface direction vectors of the two rotary axes through a spatial circle fitting method of sphere fitting and plane fitting; the actual position relation of the two coordinate systems can be obtained, then the offset and the angular deviation between the two coordinate systems can be calculated through the actual position relation of the two coordinate systems, and calibration parameters are obtained; and solving a transformation matrix between the reference coordinate system and the measurement coordinate system by using the actual position relation of the two coordinate systems, obtaining a coordinate vector of a measured point in the reference coordinate system, and solving a space included angle between the two vectors according to the coordinate vector and a theoretical position coordinate vector of the measured point to obtain a space pointing error. The method adopts a space coordinate calculation mode of a robotization method, not only has universal significance, but also can be popularized to precision measurement of other two-axis universal two-dimensional space pointing mechanisms.

The invention relates to the technical field of space measurement and calibration, and discloses a laser ranging-fused vision measurement system calibration method, which comprises the following steps of: S1, establishing a system coordinate model of a vision measurement system and a laser range finder, and defining a laser ranging coordinate system, a camera coordinate system and a world coordinate system; s2, calibrating a camera, and obtaining an internal parameter matrix and an external parameter matrix of the camera; s3, acquiring image pixel coordinates of the laser points on the calibration plate; s4, converting the pixel coordinates of the laser points into three-dimensional coordinates under a camera coordinate system based on the internal reference matrix and the external reference matrix of the camera; s5, fitting a direction vector of a laser beam through the three-dimensional space distribution data of the laser points; and S6, based on the laser beam direction vector and the laser ranging value. A direction vector of a laser beam is extracted through principal component analysis, abnormal points are eliminated in combination with a random sampling consistency algorithm, a fitting result is optimized, and the calibration robustness and precision are remarkably improved.

The invention relates to the technical field of laser pipe cutting machining, and discloses a laser pipe cutting machine machining optimization method for small pipes. The method comprises the following steps: acquiring three-dimensional point cloud data of a to-be-processed pipe, and extracting a pipe axis direction vector and pipe wall thickness distribution data through geometric topology analysis; a dynamic machining coordinate system is established based on the axis direction vector, and the theoretical projection position of the laser focus in the coordinate system is calculated; material absorption characteristic parameters are matched according to the pipe wall thickness distribution data, and a laser power density gradient adjusting instruction is generated; monitoring the radial run-out amount in the rotating process of the pipe in real time, and generating a laser focus track compensation parameter in combination with a theoretical projection position; and finally, the laser power density gradient adjusting instruction and the focus track compensation parameters are fused to generate a cutting path control signal, and a laser cutting head is driven to complete machining. According to the method, the problems of insufficient precision and unstable quality in the machining process of small pipes are effectively solved, and the machining adaptability is improved.

The invention provides an automatic identification method and system for a linear structural plane in a complex rock mass outcrop, and belongs to the field of rock mass engineering, and the method comprises the steps: obtaining a DeepLabV3 + model of a rock mass outcrop image, carrying out the semantic segmentation of an input image, outputting a binary mask image of the trace pixel of the structural plane, and carrying out the topology reconstruction; establishing a mapping relation between the image coordinate system and the three-dimensional point cloud; calculating a space included angle between the direction vector of the trace and the average occurrence of the structural plane groups, classifying the three-dimensional point cloud data according to the structural plane groups according to an angle threshold value, and performing three-dimensional line segment extraction by adopting an improved iterative Hough transform algorithm; and realizing global multi-segment connection and trace length calculation of discrete segments based on a greedy algorithm. The method breaks through the limitation of a topographic region when the rock mass structural plane data is obtained through manual measurement, and improves the precision and efficiency of structural plane extraction in the complex rock mass.

The invention relates to the technical field of target detection, in particular to a search and rescue task-oriented unmanned aerial vehicle thermal imaging visual target detection method, which comprises the following steps of: acquiring multiple frames of thermal imaging images of an unmanned aerial vehicle, extracting regional thermal difference characteristics according to a window, marking a non-background region to generate a candidate set, and fitting and reconstructing a suspected thermal target contour. And analyzing the track and the thermal change rate, screening background interference, identifying jump abnormity, positioning the gravity center, and generating a target repositioning signal. According to the method, the heat value range and variance index sequence in the image area is constructed, the thermal anomaly area is judged in combination with the temperature baseline difference, background disturbance comparison is executed in combination with the direction vector of the coordinate trajectory in the multi-frame image and the thermal change parameter, the false detection probability caused by background noise is reduced, and the detection accuracy is improved. The target jump identification is carried out according to the inter-frame heat value and area change rate in linkage with the thermal isoline closure degree, the target discrimination accuracy in a shielding scene is improved, and the robustness of thermal target extraction in a complex search and rescue environment is integrally improved.

The invention discloses a displacement auxiliary measuring mechanism and a reservoir dam monitoring and early warning system thereof, and belongs to the technical field of dam monitoring. The reservoir dam monitoring and early warning system comprises a data acquisition module, an attitude calibration module, a data fusion judgment module, a risk grading analysis module and a remote early warning trigger module. The distance measurement precision under the complex field condition is remarkably improved, the current mechanical direction and the reference direction are fused, a correction vector pointing to a target reflection point is generated, the direction drift error is effectively eliminated, and the distance measurement accuracy is improved by constructing a double-path model of main path fusion and auxiliary path comparison. According to the method, non-structural anomalies caused by sensor body interference or environmental disturbance are eliminated, data offset is corrected in real time, a stable trend curve is output, when a main path has a drift or error trend, the main path is automatically guided to converge to an auxiliary path, and the abnormal data recognition and restoration capability is enhanced.

The invention relates to the technical field of logistics collaborative optimization, in particular to an urban logistics distribution range collaborative optimization method and system, and the method comprises the following steps: obtaining a path network node and order coordinate time sequence, constructing a path mapping number, extracting a direction vector and an included angle difference value, and recognizing a path sudden change node and a density change node. Dividing boundaries, calculating density ratio differences, screening unbalanced sections, extracting direction and distance abrupt change nodes, reconstructing a path structure and outputting a boundary graph. According to the method, the corresponding relation between the order and the path node is enhanced by constructing the path mapping number sequence, the adaptive capacity of the boundary to the path trend is improved, the density ratio analysis is combined with the spatial distribution difference to identify the non-uniform region, the responsiveness of the boundary to the order aggregation situation is enhanced, and the boundary node is jointly judged through the included angle and the centroid distance. And target judgment and structural stability control of boundary adjustment are realized, connection coherence is kept in path structure reconstruction, and a boundary path shape with dynamic adaptation capability is output.

The invention discloses a method for realizing multi-stage solid-liquid separation by using graded filter pipes, which relates to the technical field of solid-liquid separation, and comprises the following steps: under the condition that the particle size between adjacent filter pipes is at a critical boundary, collecting a continuous motion track of particles in a particle size interval in a filter transition area, extracting a direction vector change sequence and a flow velocity disturbance amplitude, and judging whether particles of which the direction reversal frequency exceeds a preset threshold and the flow velocity disturbance amplitude is lower than a stable fluctuation limit exist or not so as to determine whether a particle repeated movement state occurs or not; a drift factor and a disturbance sensitivity factor are constructed according to a particle repeated movement state and are introduced into an affiliation path identification model as input variables, and affiliation judgment operation is executed through an affiliation probability calculation network. According to the invention, the problem that the path attribution of particles with critical particle sizes in the filtering transition area is unknown is solved, and the dynamic identification and accurate guide control of the particle attribution path are realized.

The invention relates to the technical field of artificial intelligence, in particular to a big data information analysis method and system based on artificial intelligence, and the method comprises the following steps: obtaining a jump segment direction vector, classifying label nodes with consistent directions, splitting a path lacking a mapping relation to form an interruption segment, recognizing a node with continuous directions as a bridge segment entrance, and obtaining a bridge segment direction vector; according to the method, by means of classification according to the node sequence and the channel number in the segment hopping direction, direction aggregation boundary determination and semantic field combination path position interruption recognition, the node sequence structure positioning precision and the paragraph division reasonability are improved, and the focus analysis set is generated by combining the path segments. Bridge segment connection is screened based on direction consistency, path continuation logic, behavior tracks and aggregation numbers are kept in sequence and hierarchy regularization, a behavior aggregation sequence of a semantic chain is constructed, and the continuity of path recognition in a channel aggregation area and the stability of node attribution are enhanced.

The invention provides an intelligent warehouse goods posture recognition and automatic sorting method and system, and the method comprises the steps: S2, extracting the edge contour and surface features of goods from point cloud data for a preliminary value set, calculating the direction vector and shape distribution characteristics of the goods through a principal component analysis method, and obtaining a quantitative result of shape feature extraction; s6, historical sorting data and real-time sensor data are extracted from the warehousing system database according to the classification basis adapted to the complex scene, the dynamic posture change trend of the goods is predicted through a time sequence analysis method, and optimization parameters of real-time processing are obtained; and S7, the movement track and the grabbing angle of the sorting mechanical arm are adjusted through the optimization parameters subjected to real-time processing, a deep reinforcement learning algorithm is adopted to conduct iterative optimization on the sorting action sequence, and an execution scheme of sorting accuracy is determined. According to the method, the accuracy of goods posture recognition and the automatic sorting efficiency in the complex storage environment are remarkably improved.

The invention discloses a road scene space rapid investigation system combining RTK and image reconstruction, relates to the technical field of road scene space investigation, and is used for solving the problem of poor road mapping splicing effect. According to the method, an RTK track in road inspection is collected and synchronized with an image frame, after abnormal points are removed, continuous control points are extracted to construct a road topology skeleton, a space is divided into a plurality of mapping units based on the control points and direction vectors, redundant overlapping areas are set, and a mapping task package with structural continuity is generated; a road structure area in an image is extracted through semantic segmentation and edge detection, a structure mask is constructed and projected to a three-dimensional space, and point cloud density enhancement and reconstruction optimization are guided, so that block boundary structure anchor points are further identified, local rigid body registration is completed, and a global error minimization model is constructed. The posture consistency and the space continuous splicing of all the image blocks are realized, and the exploration efficiency of the road scene space is improved.

The invention discloses a distribution network fault positioning method, system and device based on variational mode decomposition and a medium, and relates to the technical field of power system fault positioning, and the method comprises the steps: collecting a traveling wave signal of a power distribution network, and carrying out the preprocessing of the collected traveling wave signal; performing modal decomposition on the preprocessed traveling wave signal, and outputting a plurality of modal components; based on the mode component obtained through decomposition, wave head arrival time is extracted; performing correction compensation based on the wave head arrival time difference, the phase difference and the propagation characteristics, and calculating the relative distance between the fault point and the known node; calculating the position coordinates of the fault point in the distribution network according to the geographic coordinates and the direction vectors of the nodes in combination with the relative distance; and constructing a visual interface, displaying the position of a fault point, and storing the traveling wave signal data and a fault positioning result into a database. According to the method, the adaptive correction function and the time difference compensation model are constructed, so that time difference errors caused by factors such as frequency change and phase nonlinearity can be corrected, and the accuracy of fault positioning is improved.

The invention relates to the technical field of reflected waves, in particular to a coal mine disaster comprehensive evaluation system based on three-component micro-motion detection, which comprises a frequency direction extraction module, a propagation included angle calculation module, a sensitive path identification module, a critical turning identification module and a structural disturbance mapping module. According to the method, the continuous sequence is formed in the space through the direction vector constructed through the main frequency value of the measuring point, an included angle screening strategy is used for eliminating incoherent direction sections, it is ensured that the path has trend consistency, the frequency amplitude difference value and symbol inversion are used for detecting a mutation point, and the response recognition capacity for directional changes is enhanced; the normalized frequency ratio is combined with a standard deviation and a difference value to carry out joint calculation so as to quantify a structure jump degree and improve the accuracy of reflex position expression, disaster boundary points form an image set, and a structure identification channel is established by taking a frequency direction as a principal line; and the spatial expression definition and precision are improved in the aspects of path aggregation, boundary precision, disaster recognition and partition and continuous structure drawing.

The invention relates to the technical field of design service, in particular to a roof waterproof structure intelligent design optimization system which comprises a node contour extraction module, a contact segment recognition module, a close boundary evaluation module, a disturbance area labeling module and a waterproof configuration reconstruction module. According to the invention, by extracting the direction vector change of the boundary point cloud sequence, the continuity and stability of the turning trend in the contour structure can be accurately obtained, the boundary of the roof structure can be identified, and the contact type of the boundary joint can be determined in combination with the direction change rate distribution of the contact surface, so that the boundary sealing state has quantitative index output; in addition, local positioning information of a fitting path and a structure defect can be provided, a node contour reconstruction path with an adjustment space is provided based on a pressing path continuity judgment and simulation edge shift strategy, and the adaptability of a node structure under the action of complex stress and the configuration optimization capability of the overall waterproof performance of a roof are improved.

The invention relates to the technical field of gesture recognition, in particular to an air gesture action intelligent capture and interactive data processing method and system.According to the air gesture action intelligent capture and interactive data processing method and system, significant jumps are marked through timestamps, time sequence deconstruction of action streams is achieved, nonlinear alignment processing of time structures between paragraphs is introduced, and the time sequence deconstruction efficiency is improved. The fragment consistency recognition capability under the conditions of unequal action durations and different rhythms is remarkably improved, spatial topology among three points is modeled by adopting a graph structure, a graph convolutional network is introduced to process dynamic changes of connection relations among different nodes, the continuity and stability of structure judgment can be kept under a shielding or structure deformation scene, and the recognition efficiency is improved. Through a triple constraint mechanism of direction vector included angle amplitude, length ratio and slope fluctuation, the action is subjected to modeling support in three aspects of time dimension, space structure and direction continuity at the same time, and the dynamic stability of gesture recognition and the resolution precision of paragraph judgment are enhanced.

The invention discloses a path planning method and system for corner optimization. The method and system are used for cutter radius compensation and machining instruction smooth transition of a three-dimensional path of a numerical control machine tool. The method comprises the steps that a machining instruction is pre-read, and a path point location is analyzed; calculating a path direction vector and a normal vector, and determining a path plane equation; calculating a plane included angle and an intersection direction vector through a normal vector; generating a compensation curve by translating along the perpendicular direction of the intersecting line by taking the radius of the cutter as a constraint; and generating a smooth control instruction through curve subdivision and inserting the instruction into an instruction queue. The problem that three-dimensional path corner transition is not smooth is solved, the machining precision and efficiency are remarkably improved, and the method is suitable for a numerical control machine tool for complex curved surface machining.

The invention provides a method and a system for transmitting a photographic image of a security camera, relates to the technical field of image transmission, and effectively divides an image frame into a differential image block and a background image block by introducing a partition mechanism based on inter-frame pixel difference, thereby remarkably improving the detection efficiency of a moving target and the pertinence of data processing. Through embedding marks such as a direction vector and a motion timestamp in a differential image block set, priority coding of a dynamic target image area is realized, and further in combination with a periodic compression strategy of a background image frame, redundant data is compressed to the greatest extent, and the overall data transmission load is effectively reduced. Meanwhile, an image fragment priority model is jointly constructed through brightness saliency and texture complexity, and structure entropy and direction gradient analysis is assisted, so that redundant backup generation of key content is realized, and data integrity under a weak network condition is greatly improved.

The invention discloses a calibration method, device and equipment for an external actuator of a robot, and the method comprises the steps: enabling the tail end of a mechanical arm with a calibration plate to be in contact with the actuator in different poses, and obtaining two different circular mark points and a preset transformation matrix; calculating a three-dimensional point cloud coordinate of the circular mark point based on a mapping relation between a pixel coordinate and a point cloud coordinate in the structured light system; calculating a pose transformation matrix between two poses at the tail end of the mechanical arm according to a preset transformation matrix; according to the three-dimensional point cloud coordinates, the pose transformation matrix and a preset hand-eye matrix, the actuator coordinates of the tail end of the actuator under the mechanical arm base coordinate system are calculated; direction vectors of the tail ends of the actuators are calculated through the coordinates of the two different actuators; and calculating a homogeneous transformation matrix calibrated and aligned at the tail end of the actuator according to the direction vector to obtain a calibration result. The technical problem that the actual calibration scene requirement is difficult to meet due to the problems of low precision, complex measurement process, high cost and the like in the prior art can be solved.

The invention discloses a frequency offset compensation method and electronic equipment, relates to the field of communication, and is used for respectively compensating crystal oscillator frequency offset and Doppler frequency offset when the electronic equipment performs satellite communication. The frequency offset compensation method comprises the following steps: obtaining a direction vector of an electronic device pointing to a satellite in an electronic device coordinate system according to a phase difference of downlink signals from the satellite received by a plurality of antennas; obtaining a direction vector of the electronic equipment pointing to the satellite in the earth coordinate system according to the direction vector of the electronic equipment pointing to the satellite in the electronic equipment coordinate system and the attitude information of the electronic equipment; obtaining the coordinates of the satellite in the earth coordinate system according to the direction vector of the electronic equipment pointing to the satellite in the earth coordinate system; according to the carrier frequency of the downlink signal emitted by the satellite and the coordinates of the satellite in the earth coordinate system at multiple moments, Doppler frequency offset and crystal oscillator frequency offset of the downlink signal are obtained; and compensating the carrier frequency of the uplink signal sent by the electronic equipment.

The invention discloses an aero-engine part fatigue crack propagation identification method based on machine vision. The method comprises the following steps: S1, obtaining an image block sequence; s2, inputting each image block into a pseudo stress estimation network to generate an image block pseudo stress diagram; s3, inputting the image block and the image block pseudo-stress diagram into an image feature decoupling coding module, and outputting a fusion feature vector; s4, inputting the fusion feature vector into an improved fox algorithm, and generating a crack path guide map and a direction vector field; s5, inputting the image block pseudo-stress diagram, the crack path guide diagram, the direction vector field and the fusion feature vector into a crack mask generation module, and outputting an image block crack mask; s6, splicing the image block crack masks according to the positions of the image blocks in the surface image to generate a complete crack structure diagram; and S7, outputting a crack propagation result based on the complete crack structure chart. According to the method, machine vision and an evolutionary path optimization method are fused, and accurate recognition of aero-engine crack propagation is achieved.

The invention provides a multi-dimensional Hash acceleration-based grid ray intersection method, which comprises the following steps of: acquiring original model data, and carrying out standardized preprocessing on the original model data to obtain standardized scene data; self-adaptive space grid division is carried out based on the preprocessed standardized scene data, space coordinates of three-dimensional grid units are mapped to a hash table to construct a one-dimensional index of a space grid, and triangular patches of the scene data are associated with the space grid; performing direction parameter decomposition on rays to be intersected, discretizing direction vectors of the rays, and constructing a ray direction composite hash key; and executing mixed intersection calculation in a mode of combining multi-level cache query construction, direction pruning and invalid intersection filtering and space hash traversal intersection, and determining intersection point information of the ray and the geometry. According to the method, the space grids and the ray direction data are converted into the hash values to be stored, the occupied memory is small, and the ray intersection efficiency is improved.