129 results about "Geometric mapping" patented technology

The invention discloses a building engineering progress automatic identification early warning system based on computer vision, which relates to the field of building engineering informatization and comprises a synchronous calibration module, a joint calibration module, a pose generation module, a mapping construction module, a resampling module, a mapping registration module and a comparison early warning module. Clock synchronization and rolling readout calibration are carried out on a camera and an inertial measurement unit, a continuous time pose is established in a frame, sampling is carried out according to rows, and an equivalent global shutter frame is generated in combination with plane and pixel-level geometric mapping; outputting a camera pose track and a local measurement map by adopting back-end optimization containing a rolling mechanism, and registering with the building information model; component detection, instance segmentation and state discrimination are completed on an equivalent global shutter frame, pixel domain measurement is unified into engineering quantity under pose and registration constraints, the engineering quantity is mapped to a work decomposition structure and a progress plan, deviation is calculated, and graded early warning is output according to a multi-threshold rule. Long-term stable and reliable operation and evidence traceability of the system are guaranteed through whole-course quality monitoring and threshold grading.

The invention discloses a method for optimizing micro-crack segmentation based on deep learning and super-resolution reconstruction, and the method comprises the steps: cutting an image in real time, obtaining an image block which takes a component as a target main body, and synchronously recording a homography matrix for geometric mapping; selecting an amplification strategy to improve the resolution, and recording a scale mapping relation; inputting the enhanced image block into a double-flow network; adaptive fusion and reconstruction are carried out on the two branch features, and a high-resolution texture image is output; generating a geometrically corrected ortho-image, fusing the geometrically corrected ortho-image with original illumination information, and outputting a corrected image with a known pixel size; identifying cracks, spalling and honeycomb diseases in parallel; generating a unified defect confidence map; calculating real geometric parameters of the BIM in a BIM global coordinate system through coordinate back projection; and generating quantitative defect reports and maintenance suggestions. The method has the advantage that seamless connection between the detection result and the BIM global coordinates is realized.

The invention provides a coal face mining auxiliary method based on visual and point cloud data fusion modeling, and the method comprises the steps: collecting the visual image data of a coal face, collecting the three-dimensional point cloud data through a point cloud sensor, and obtaining the motion state information through an inertial sensor; based on internal and external parameters and IMU data of joint calibration, mapping point cloud data to an image plane, establishing a geometric mapping relationship between three-dimensional points and pixels, generating an attribute point cloud model containing geometry, color and semantics, and generating a high-precision global three-dimensional digital twinning model; and identifying and tracking equipment instances in the digital twinborn model, and resolving motion parameters of key components based on a URDF kinematics model and a principal component analysis algorithm to support remote control decisions. According to the invention, high-precision real-time sensing and three-dimensional visualization of the working space size, the equipment connection relation and the movement position of the coal face can be realized, and the remote control precision and the response efficiency of unmanned mining are remarkably improved.

The invention discloses a cross-view multi-target collaborative perception and global tracking method. The method comprises the following steps: receiving original video streams of different views in parallel; carrying out feature extraction and content perception feature recombination processing; establishing a homography transformation matrix representing the mapping relation between the visual angles; performing forward geometric mapping by using the homography transformation matrix, and performing reverse mapping, secondary confirmation and state updating; a joint cost model based on space-time-appearance fusion is constructed, the potential association degree of unassociated residual targets is quantified, and missing targets are recalled; performing duplicate removal and optimization on the targets in the association set; and training and optimizing the network. According to the embodiment of the invention, the method achieves the capturing of a pixel-level target, and improves the texture and edge expression capability of a tiny target in a deep feature map. Efficient fusion of multi-dimensional spatio-temporal information among visual angles is realized; higher robustness and tracking continuity are achieved, and the integrity and fineness of a final trajectory result are improved; and the recall is ensured, and the generation of redundant tracks is avoided at the same time.

The invention relates to the technical field of airborne wind power measurement, and discloses an airborne wind measurement laser radar method and system. The method comprises the following steps: generating a scanning time sequence identifier and a path correction mark structure through scanning beat synchronization and stray light shielding processing; executing time-frequency demodulation and quality gating based on the back scattering signal to generate an observation wind speed initial value sequence; performing time alignment and motion compensation in combination with inertial navigation data, and generating a wind speed vector grid fragment through spatial interpolation and scanning geometric mapping; and finally, generating a configuration updating instruction structure through coordinate alignment and grid splicing. According to the invention, the precision and the anti-interference capability of wind field measurement in an airborne environment are effectively improved, and the data reliability and the system stability under a complex meteorological condition are remarkably enhanced through multi-source data fusion and a self-adaptive compensation mechanism.

The invention discloses a tunnel cross-sectional image analysis method based on image processing, and aims to solve the problems that a surface image is not clear in correspondence with a transient seismic wave method, a geological radar and a resistivity imaging section space, and anomalies at a certain distance in front are difficult to map to a tunnel face. According to the method, anisotropic reforming is carried out by adopting a Fourier neural operator, cross-modal Transform registration of a micro attention mask based on sector geometry, curve mileage and section polar coordinate position coding is combined, analytic geometry mapping and uncertainty propagation are matched, tunnel face structure traces and water seepage texture evidences are fused, and the tunnel face structure traces and the water seepage texture evidences are combined. The technical effects of accurate positioning of abnormity on the tunnel face, position confidence range estimation, risk grading early warning, stripe artifact suppression, abnormal boundary reservation and output of structured results of mileage stake numbers, azimuth angles, distance intervals and the like are achieved.

The invention discloses an automatic texture color mapping method for large-scale point cloud data. The automatic texture color mapping method comprises the following steps: firstly, realizing geometric alignment of geographic texture data and point cloud data; then realizing release of intra-core buffer by means of a mass point cloud space segmentation and retrieval management technology, and segmenting the mass point cloud into a plurality of regional point cloud blocks; carrying out filtering processing on the regional point cloud blocks to filter out discrete flying spots; secondly, considering correction constraints of different texture source information to realize seamless generation of geographic texture data; secondly, efficient point cloud preliminary color assignment is achieved by means of the spatial relation between geometric mapping and local aggregation of regional point cloud blocks and geographic texture data; secondly, eliminating the texture information (color) of the wrong coloring point cloud by using the self-shielding judgment result of the point cloud; and finally, realizing spatial merging of regional point cloud block data sets by using an efficient out-of-core file merging technology. According to the method, the dependence on hardware equipment (such as a large memory and a high graphics card) is avoided, and the block processing of massive point clouds is efficiently realized.

The invention belongs to the field of image processing, and provides a projection image automatic correction method and system based on deep learning, and the method comprises the steps: controlling a projector to output a preset test image; acquiring a first image of a user at a viewing angle by the mobile terminal; acquiring a second image at a projection angle by a shooting device of the projector; extracting features and predicting adjustment parameters for projection correction based on a projection image correction model of deep learning; the adjustment parameters are issued to the projector through a network; and performing pre-distortion processing on an image signal to be projected based on the geometric mapping parameter, and performing pixel-level adjustment of brightness and color based on the compensation parameter to generate a corrected projection output image. According to the method, the usability and accuracy of projection image correction can be improved.

The invention discloses an intelligent human body modeling method and system based on a three-dimensional dot matrix, and relates to the field of intelligent modeling, and the method comprises the steps: carrying out the structural analysis of the semantic level of an original three-dimensional point cloud, and predicting a space displacement field pointing from the surface of observed clothes to the surface of an internal real human body under the semantic guidance. By applying the displacement field, double transformation of point cloud stripping and standardization is carried out on the point cloud, so that repeated fine tuning and optimization are carried out on the body type and posture parameters of the human body model in a standardized space, and finally a high-fidelity human body three-dimensional model is generated through driving. In this way, the complex clothes interference problem is deconstructed into a staged geometric mapping and parameter optimization process, and therefore the robustness and accuracy of human body three-dimensional reconstruction under the real wearing condition are effectively improved.

The invention discloses a geometric analytic expression three-dimensional reconstruction method, and relates to the technical field of computer vision and three-dimensional environment perception. According to the method, for an application scene with a target area located in a known space attitude plane, an accurate geometric mapping relation among a navigation coordinate system, a camera coordinate system and an imaging plane is constructed by fusing a visible light image, a single-point distance measurement value and attitude information output by an attitude sensor (such as an IMU); and pixel-level depth estimation is realized by adopting an analytic expression calculation strategy, so that high-precision and low-complexity three-dimensional reconstruction of a coplanar region is completed.

The invention relates to the technical field of video collection, in particular to a video synchronous collection method and device based on an optical far image, and provides the following scheme: obtaining a calibration image of to-be-synchronized content and a user posture parameter; calculating a geometric mapping matrix and a point spread function through the calibration image and a preset calibration sequence, and performing geometric predistortion and frequency domain compensation on the to-be-synchronized content to obtain a compensation frame; and combining with the rotation range predicted by the attitude parameters, generating a sub-frame sequence by adopting multi-view rendering of time multiplexing, and outputting the sub-frame sequence by a display end, so as to realize stable far-image watching experience under the condition of small desktop size. According to the scheme, visual fatigue caused by close gaze can be relieved, and the intelligent level of learning interaction is improved.

The invention discloses a determination method for an injection orifice of an enhanced vapor injection compressor, the opening angle theta open and the closing angle theta close of the injection orifice in an enhanced vapor injection loop in the compressor are determined, accurate determination of the position of the injection orifice is realized by combining a three-circle positioning geometric mapping method, and the injection orifice can be accurately determined through geometric constraints of a base circle, an auxiliary circle and a rotor inner circle trajectory circle. The settable area of the jet orifice on the partition plate is precisely defined, the maximum allowable outline of the jet orifice is determined through the inscribed circle, it is ensured that the jet orifice can be reliably opened and sealed within the calculated ideal angle range in the rotor movement process, gas backflow and mechanical interference are prevented, the timing precision of enhanced vapor injection and the control accuracy of the gas injection amount are improved, and the service life of the jet orifice is prolonged. The adaptability and the operation stability of the compressor under different working conditions are improved, and the injection efficiency is improved.

The invention relates to the technical field of medical auxiliary diagnosis, and discloses a hypospadias penis curvature measuring method based on physical simulation inversion. The invention aims to solve the technical pain point that the penile erection curvature and the internal fibrosis focus distribution are difficult to quantify noninvasively and accurately before the operation in the existing hypospadias diagnosis and treatment. According to the method, a standard white mold containing fine anatomical partitions is constructed, personalized geometric mapping is realized by using a static look-around image, and constraint physical parameter inversion is performed in combination with a multi-attitude dynamic stress image, so that the digital twin with real biomechanical properties is reconstructed in a virtual environment. According to the method, the erection bending form can be accurately predicted in the non-erection state, the mechanical property abnormal area range is positioned, operation planning is assisted, experience medical treatment is spanned to accurate digital medical treatment, and the wound diagnosis and treatment and operation risks are remarkably reduced.

The invention provides an organ three-dimensional reconstruction method and system based on a sparse ultrasonic section and a medium, and the method comprises the steps: obtaining a CT image sequence and an ultrasonic image sequence of an organ, and generating a complete point cloud and a sparse point cloud through processing; the point cloud is converted to a unified coordinate system through a registration technology, and position matching is carried out; inputting the matched sparse point cloud and complete point cloud into a point cloud reconstruction network for training, and learning a geometric mapping relation from the sparse point cloud to the complete point cloud; and obtaining a to-be-reconstructed organ sparse point cloud, inputting the to-be-reconstructed organ sparse point cloud into the trained point cloud reconstruction network to generate a complete point cloud, and drawing a three-dimensional contour surface of the organ. According to the invention, intelligent reconstruction of a complete three-dimensional organ contour can be realized through organ contour information obtained by a limited number of two-dimensional ultrasonic sections; the reconstruction precision and the surface integrity of sparse ultrasonic data are remarkably improved, an efficient and accurate three-dimensional reconstruction solution is provided for medical image analysis, and clinical diagnosis and treatment planning are assisted.

The invention discloses a virtual reality roaming method and system based on a multi-view panoramic image model, and belongs to the technical field of computer vision and virtual reality. Through a multi-viewpoint panoramic image set, real-time generation of a high-quality panoramic image from a known viewpoint to any unknown viewpoint is realized based on a spherical projection viewpoint transformation algorithm. Modeling generation methods for a road scene and a region scene are respectively designed according to scene feature differences, so that scene representation with complete coverage is constructed. According to the system, adjacent viewpoints are quickly positioned through a spatial index mechanism, geometric mapping and multi-viewpoint weighted fusion are performed by using the spherical projection algorithm, and a smooth and continuous free viewpoint roaming picture is rendered in a virtual reality environment. According to the method, on the premise of ensuring high fidelity of the scene, real-time rendering is realized on common consumption-level hardware, and the coherence and the degree of freedom of immersive interactive experience are improved.

The invention provides a deployable flexible GMR eddy current testing method and system for a complex curved surface component, and relates to the technical field of nondestructive testing. The method comprises the following steps: establishing a curved surface coordinate system and an expansion domain coordinate system, constructing a geometric mapping relation of a flexible sensing array, and performing clearance compensation, attitude correction and temperature drift correction on multi-frequency response data in an expansion domain to form a unified response data set; defect response distribution is generated through robust reconstruction and reprojected to the curved surface coordinate system, and space positioning and size and orientation recognition of defects are achieved; and adaptively updating the attitude, the path and the excitation scheme in combination with the fitting state parameters until the detection coverage and the confidence meet the requirements. According to the method, high-precision detection and process traceability of the defects of the complex curved surface component are realized.

The invention discloses a formation control method for an unmanned aerial vehicle cluster, and relates to the technical field of intelligent formation of unmanned aerial vehicles, and the method comprises the following steps: S1, obtaining an initial space state of the unmanned aerial vehicle cluster; s2, performing adjacent constraint construction by using the initial state vector; s3, performing geometric mapping by using the local adjacency relation graph; s4, performing global formation generation by using the relative geometric position matrix; and S5, performing dynamic formation control calculation by using the relative geometric position matrix and the target formation reference model. By setting multi-dimensional measurement calculation based on an initial state vector and combining a combined constraint set of a spatial distance, a speed difference and an angular speed difference, a weighted local adjacency relation graph is formed, and according to the scheme, spatial proximity and dynamic consistency can be considered while the adjacency relation is constructed; the generated graph structure not only reflects the geometric closeness degree between the unmanned aerial vehicles, but also quantifies the compatibility of the unmanned aerial vehicles in motion and attitude changes.

The invention provides a semantic scene reconstruction and interaction method and system based on a visual language model, and relates to the technical field of artificial intelligence and robots. The method comprises the following steps: acquiring image data shot by a camera; estimating a world pose of the camera; inputting the image data to a Visual Language Model (VLM) to generate a structured description containing an object semantic tag and quantitative spatial information thereof relative to the camera; calculating the world pose of the object according to the camera pose and the quantitative space information; a node representative of the object is created or updated in a hierarchical scene graph. The invention further provides a corresponding interaction system. According to the method, a rich and visual three-dimensional semantic map facing natural language interaction is constructed by deeply fusing the semantic understanding ability of the VLM and the geometric mapping ability of the SLAM, and the intelligent level of robot environment perception and man-machine interaction is greatly improved.

The invention discloses an integrated circuit electrical characteristic simulation method and device, a terminal and a storage medium, and the method comprises the steps: obtaining a to-be-simulated integrated circuit model, carrying out the mesh generation of the to-be-simulated integrated circuit model, so as to obtain an integrated circuit mesh data set composed of a plurality of mesh units, constructing a corresponding charge basis function and a current basis function based on the grid units; step-by-step fusion updating of the charge primary function is realized by taking the charge primary function as a fusion object, and meanwhile, corresponding fusion updating is performed on the current primary function in a geometric mapping mode; and after all fusion updating is completed, obtaining an integrated circuit primary function data set, and performing electrical characteristic simulation on the to-be-simulated integrated circuit based on the integrated circuit primary function data set. According to the method, fast updating and low-order representation of a complex coupling capacitance matrix are achieved, compared with a traditional post-order reduction method, the theoretical complexity is reduced from O (n3) to O (n), and meanwhile the model order reduction efficiency is greatly improved while the model precision and the order reduction effect are guaranteed.

The invention relates to the technical field of mode recognition, in particular to a switch cabinet drawer early warning system based on multi-mode perception, and the system comprises the steps: obtaining a visible light video, an infrared thermal image, a mechanical waveform, an electrical time sequence signal and asynchronous event stream data in the operation process of a switch cabinet through a data collection module; a tensor construction module is used for executing geometric mapping correction and timestamp synchronization by taking the visible light video as a space reference, and constructing a multi-modal spatial-temporal feature tensor containing texture, temperature and electromechanical response; the state variable calculation module projects the electrical time sequence signal to an orthogonal feature space, decouples and extracts an active component feature vector, and calculates a dynamic resistance state variable; and the abnormity identification module further constructs a physical information neural network which introduces a physical equation residual error as a constraint term, the tribological parameters are solved through online iteration, and through virtual trajectory comparison and parameter time-varying trend analysis, classified judgment of lubrication failure, mechanical jamming and contact faults is realized.

The present application relates to the technical field of fusion design, in particular to a three-period minimal surface spatial positioning fusion structure design method based on the inverse distance weighting method, in the present application, by setting the implicit function equation of the three-period minimal surface and screening the control points according to the spatial distribution and geometric constraints, the accurate selection and positioning of the structure unit in the design target area are realized, the accuracy of geometric mapping is improved, the inverse distance weighting calculation is carried out through the convolutional neural network, the difference of the geometric region in the space can be effectively identified, the response ability of structure fusion is improved, the weight is calculated combined with the spatial distribution of the control points, and the weight distribution mechanism is formed by using the actual geometric distance between the control points, the continuity and smoothness of the geometric response in the interpolation region are guaranteed, the graph neural network is introduced to process the surface continuity problem, the local geometric mutation area is identified and corrected through the edge weight and topological structure between nodes, and the geometric smoothness and boundary consistency of the whole structure are improved.

The invention provides a data closed-loop method and system, and the method comprises the following steps: importing a model format file, and obtaining the unstructured data of the model format file; packaging the unstructured data to form standard data, wherein the standard data comprises a geometric mapping relationship; a configuration file is imported, the configuration file comprises configuration parameter information, and a parameter mapping relation between the configuration parameter information and the standard data is obtained; and constructing a closed-loop data set according to the geometric mapping relationship and the parameter mapping relationship, wherein the closed-loop data set is suitable for feeding back the hierarchical relationship of the model format file. According to the data closed-loop method and system provided by the invention, the transparency of a data closed-loop process can be improved.

The application relates to the technical field of indoor positioning, in particular to an indoor personnel positioning method and system based on multi-modal perception. The application proposes the following scheme: by acquiring the ultra-wideband channel impulse response, millimeter wave radar data and thermal imaging data of each layer, combining building information for double-base geometric mapping, reconstructing an indoor ray path and generating an occupancy grid map. Further, the water mist distribution intensity generated by a spraying device is collected, phase correction and beam domain purification are performed on the millimeter wave data, and flow direction filtering and flicker suppression are performed on the thermal imaging data to obtain pretreatment data. On this basis, motion prior information and boundary constraint information are extracted, and fusion is realized through mass conservation update and normalization synthesis in the occupancy grid map, and finally the position information and motion direction of the object to be positioned are output. The application can maintain positioning stability and accuracy under the interference of fire smoke, water mist and multipath effect, and is suitable for high-risk scenes such as fire rescue.

The invention discloses a barrier regularization method for a nonlinear grid distortion problem. The analysis steps of grid distortion suppression based on unit geometric mapping specifically comprise: obtaining input data of an analysis model, and initializing nonlinear analysis parameters; obtaining a Jacobian determinant based on the deformation gradient, and constructing a barrier regularization function; constructing a correction potential energy functional containing a barrier regular term, assembling the material stiffness matrix, the geometric stiffness matrix and the barrier stiffness matrix to obtain a tangent stiffness matrix, and solving a nonlinear equation to update a displacement field; if the displacement field is not convergent, updating the load step length and iteratively returning to calculate the deformation gradient, and if the displacement field is convergent, outputting the displacement; and constructing a topological optimization mathematical model, calculating an objective function value and sensitivity according to a displacement field obtained by convergence, updating unit density, adjusting material distribution or topological form, and outputting a final optimization structure. According to the method, unit distortion is directly suppressed in the analysis process, the numerical stability is enhanced, and the topological optimization convergence performance is improved.

A tracking system for tracking an expansion state of an object is provided. The tracking system includes at least one processor and a memory having stored therein instructions that, when executed by the at least one processor, cause the tracking system to perform a probabilistic filter that iteratively tracks a confidence of the expansion state of the object, wherein the confidence is predicted using a motion model of the object and further updated using a composite measurement model of the object. The composite measurement model includes a plurality of probability distributions constrained to lie on a contour of the object and has a predetermined relative geometric mapping to a center of the object. Further, the tracking system tracks the expansion state of the object based on the updated confidence of the expansion state.

The invention provides an indoor 3D scene semantic segmentation method and system based on multi-view solid geometry guidance, and relates to the technical field of indoor 3D scene understanding, and the method comprises the following steps: constructing a multi-view geometric mapping relation model; establishing a 2D-3D feature combined 3D scene semantic segmentation network based on a multi-view geometric mapping relation; constructing a cross-view 2D feature fusion device, and performing conversion and adaptive fusion on the multi-view 2D features to obtain multi-view complementary information enhanced 2D features; further constructing a cross-modal 2D-3D feature fusion device, and performing adaptive fusion on the 2D features and the 3D features after multi-view information enhancement to obtain 3D features with rich information representation; and finally, inputting the fused 3D features into a simple classifier to obtain a semantic segmentation result of the 3D point cloud model. According to the method, the semantic segmentation precision of the 3D point cloud model in the indoor complex scene is improved.

The application provides an unmanned aerial vehicle optimal track planning method and system fusing image recognition and M-RRT and APF algorithms. Wind power generator point cloud and visual data are acquired in real time through a multi-modal sensor, key components of blades are recognized based on deep learning, a geometric mapping model is constructed, tip point is corrected in combination with DBSCAN clustering, and a shutdown posture is predicted. A global path adopts an M-RRT algorithm improved by a direction heuristic factor, and a key area of the blade is guided to search; a local track is optimized through a dynamic weight APF algorithm, and a repulsive force field is adjusted in real time to cope with posture changes. An online replanning mechanism is introduced, NSGA-III multi-objective optimization is triggered when an environment mutates or a tracking error exceeds a threshold, and optimal tracks are generated by comprehensively considering energy consumption, time and safety. The system integrates high-precision perception, adaptive planning and dynamic optimization, and significantly improves inspection coverage and track safety under a complex shutdown posture.

The invention relates to the technical field of data processing, in particular to a code disc concentricity adjusting method for a DD motor, and the method comprises the steps: obtaining a rotor absolute angle, a pulse error and a rotor angular velocity of each sampling point, and calculating the credibility weight of each sampling point according to the rotor angular velocity; a weighted vector integral model is introduced, the mode length of an eccentric main vector and an eccentric phase angle are obtained through the combined operation of orthogonal decomposition and full-period accumulation, and the physical adjustment distance of the code disc is calculated based on the mode length of the eccentric main vector in combination with a geometric mapping coefficient and a friction compensation amount. According to the eccentric phase angle and the physical adjustment distance, visual guide information is generated, an operator is instructed to conduct concentricity adjustment on the coded disc, noise and deformation interference are effectively filtered out, pulse errors are converted into specific physical displacement instructions, and standardization and high efficiency of debugging operation are achieved.

The invention discloses a robust visual servo control method and verification system based on interference estimation. The method comprises the following steps: acquiring an environment RGB image and depth information; constructing a state transition equation and a pseudo-linear measurement equation, and performing joint estimation on the target position and speed by adopting a Kalman filter; according to the estimated target space position, establishing a geometric mapping relation between a rotary table coordinate system and a target coordinate system, and calculating an attitude angle required by the rotary table; and designing a time-varying disturbance observer, estimating unmodeled dynamics and external disturbance of the system in real time, performing feed-forward compensation based on a disturbance estimation value, and generating an anti-disturbance control instruction in combination with an expected attitude angle. The system is applied to the servo control method and comprises the two-degree-of-freedom rotary table, the depth camera, the target, the connecting firmware, the laser director, the balancing weight and the ground station. According to the invention, the precision of servo control can be improved. The method can be widely applied to the field of sensing control.

This application relates to the field of cloud storage technology and discloses a file management system and method based on cloud storage, including: a data encryption module for homomorphically encrypting user-uploaded files and storing the encrypted files in the cloud; an algebraic geometry mapping module for mapping the encrypted files to an algebraic variety and optimizing the storage path according to the algebraic geometry structure; a query processing module for receiving user query requests, performing geometric measurement calculations on the encrypted files, and returning matching results while in an encrypted state; and an adaptive storage management module for dynamically adjusting the file storage location according to the file access frequency, enabling fast retrieval of frequently accessed files. This invention uses homomorphic encryption technology to encrypt user-uploaded files, achieving the technical effect of effectively protecting data privacy during cloud storage and computation.