66 results about "Mesh optimization" patented technology

The invention discloses a deep learning-based middle-deep layer geothermal pipe group multi-field coupling simulation method, which comprises the following steps: carrying out numerical simulation cross mutual verification to obtain a middle-deep layer buried pipe heat pump system model, and carrying out system configuration by adopting a Monte Carlo method to obtain a first parameter environment set; screening the first parameter environment set according to a parameter environment function to obtain a second parameter environment set, performing data augmentation to obtain mid-deep layer geothermal pipe group simulation data, constructing a mid-deep layer geothermal pipe group multi-field coupling deep learning model, and obtaining simulation heat exchange data and prediction coupling heat exchange data; and adaptive grid optimization is carried out to obtain an optimized grid size, and the optimized grid size is adopted to adjust the mid-deep layer buried pipe heat pump system model to output the mid-deep layer buried pipe multi-field coupling model. According to the method, accurate and rapid simulation of the multi-field coupling process of the medium-deep geothermal pipe group can be realized under complex geological conditions, and the method has important practical significance for promoting large-scale development and utilization of medium-deep geothermal resources.

The invention provides a thermal imaging automatic calibration and key region segmentation method. The method comprises the steps of obtaining a thermal imaging image, and then performing preliminary denoising processing on the image to obtain a denoised image; constructing a high-density grid in an image pixel dot matrix by adopting a dense sampling method according to the de-noised image so as to determine an initial pixel coordinate of each grid point; obtaining neighborhood feature vectors through an abnormal point set, and grouping the vectors by adopting K-means clustering so as to determine a temperature change mode, and fusing a temperature gradient to extract a boundary extraction basis as grid optimization input; and extracting a boundary extraction basis of the key part from the temperature change mode, adjusting the high-density grid according to the boundary extraction basis to obtain an optimized grid, and starting relocation iteration adjustment through coordinate deviation calculation. According to the method, a closed-loop optimization process of high-density grid construction, abnormal point identification, clustering analysis, grid dynamic optimization and iterative relocation is constructed, so that refinement and adaptive segmentation of a thermal anomaly region are realized.

The invention discloses a topological network global optimization method based on graph reinforcement learning, and relates to the field of computational geometry and grid optimizing.The method comprises the steps that a topological optimization process is modeled into a Markov decision process, a topological network containing singular points and angular points is converted into heterogeneous graph representation, and a graph state is constructed; selecting a topology editing action by a reinforcement learning agent fused with the graph neural network based on the current graph state; after executing the action, updating a topological structure and a graph state, and calculating an instant reward based on the global grid quality index change; training intelligent agents in batches through experience playback and time sequence differential learning, so that the intelligent agents learn a mapping strategy from a graph state to an optimal action; and applying the trained policy network deployment to automatic optimization of the new topology. According to the method, full-process automation of topological optimization is achieved, non-local negative effects of local modification are effectively avoided, a global optimal optimization strategy is learned, the grid quality and optimization efficiency are remarkably improved, and the method is suitable for simulation grid generation of aircrafts.

This invention discloses a fully automated, high-speed, and highly accurate three-dimensional reconstruction method and system, relating to the field of three-dimensional dynamic reconstruction. The invention introduces the construction of a spectral-point cloud fusion model and the calculation of a dynamic reflectance field by Monte Carlo ray tracing. By combining this with Fresnel's equation and dynamic ray tracing techniques, the reflectance calculation conforms to physical laws, thereby improving the accuracy of spectral mapping. Furthermore, the invention optimizes spectral data based on an error correction matrix using a spectral error compensation network, reducing the accumulation of errors caused by factors such as measurement angle and surface roughness. Moreover, in the three-dimensional reconstruction process, the invention improves the continuity and spectral consistency of the three-dimensional model by using Poisson surface reconstruction and a spectral reflectance-driven mesh optimization method based on spectrally enhanced point cloud data.

The invention provides a hyperbolic variable cross-section construction process optimization method, and belongs to the technical field of building construction.The method includes the steps that precise geometric data of a hyperbolic variable cross-section structure is obtained to establish a geometric parameter matrix, and a high-precision finite element analysis model is established through a self-adaptive mesh refinement algorithm; establishing a double-layer game grid optimization model to realize coordination and balance of calculation precision and efficiency, establishing a prestressed tendon three-dimensional path planning model, optimizing a spatial arrangement path of the prestressed tendon in a hyperboloid by adopting a genetic algorithm, accurately calculating a curvature radius and a friction loss coefficient of the prestressed tendon, and adjusting arrangement parameters according to a prestress loss rate. And a real-time monitoring system is established to dynamically adjust construction parameters, and the technical problem of low prestress transmission efficiency caused by complex spatial path planning of the prestressed tendons in the construction process of the hyperbolic variable cross-section structure is solved.

The invention discloses a vehicle body grid parameter dynamic optimization method and system based on model simulation, and belongs to the crossing field of computer-aided engineering and artificial intelligence technology. According to an existing vehicle body grid optimization scheme, deep mining and analysis of grid data cannot be achieved, and consequently the accuracy and reliability of a grid optimization result are not high. According to the vehicle body grid parameter dynamic optimization method based on model simulation, a vehicle body historical database module, a vehicle body grid optimization module and a domain knowledge base module are utilized to match vehicle body grid data to be optimized with vehicle body historical data to obtain the most similar vehicle body historical data; the information is used as experience information and verification basis of vehicle body grid parameter optimization; and then experience information and a verification basis are reused, the to-be-optimized grid data of the vehicle body are analyzed and processed, and optimization suggestion information is generated, so that historical data can be deeply mined and analyzed, and the accuracy and reliability of a grid optimization result can be effectively improved.

The invention relates to the technical field of finite element optimization, in particular to a performance optimization method and system based on finite elements, and the method comprises the steps: obtaining a finite element model of a gear in a transplanting mechanism of a rice transplanter, and dividing the finite element model into a plurality of grids; corresponding loads are applied to the finite element model according to simulation data of gears when the rice transplanter works, simulation indexes of all the grids are obtained, the grid sizes of all the grids are optimized based on the simulation indexes, and optimized target grids are output; determining a performance index of each target grid, optimizing design parameters of the target grids according to the performance indexes, and updating the finite element model based on the optimized design parameters to serve as a final finite element model of the gear; according to the method, through deep coupling of grid optimization and parameter optimization, the analysis precision and optimization efficiency of the gear can be improved.

The invention discloses a multi-model collaborative two-dimensional Gaussian splash three-dimensional reconstruction method, which comprises the following steps: acquiring a multi-view RGB image, outputting camera parameters and sparse point clouds by using a VGGT model, and generating a depth image and a mask image through a monocular depth estimation network and an image segmentation network; carrying out densification processing by utilizing a visual shell algorithm; initializing a two-dimensional Gaussian primitive by using the dense point cloud; carrying out training on the initialized two-dimensional Gaussian primitives; re-rendering depth maps of all visual angles, and generating a three-dimensional grid through a truncated symbol distance function and a contour surface extraction algorithm; performing grid optimization based on local bilateral filtering on the three-dimensional grid to obtain a smooth grid; and carrying out scale correction and smoothing the grid to obtain a three-dimensional model with a real scale. According to the method, an omnibearing three-dimensional model with high-fidelity geometry, real scale and new view rendering capability is generated through a multi-model collaborative initialization and optimization strategy.

The application discloses a fluid simulation method and system based on adaptive grid optimization, and belongs to the technical field of computational fluid dynamics, and comprises the following contents: receiving fluid state data at a current moment, state data at a historical moment and global physical parameters, performing scale alignment and normalization processing on the data and encapsulating the data as structured input; performing initial blocking on the whole calculation domain, converting original regular grid expression into a candidate unit set with hierarchical relationship; calculating physical indexes of each candidate unit based on fluid physical properties, judging whether each candidate unit needs to be refined, reserved or discarded; performing word tokenization and position coding on a multi-scale unit sequence, inputting the sequence into a neural solver to establish a long-range dependence relationship across regions, and outputting state word tokens at a next moment; and mapping the state word tokens back to an original regular grid space to generate a flow field simulation result. By using the method, accurate identification of a key region of a flow field and efficient modeling of multi-scale flow characteristics are realized.

The application relates to the technical field of CAD model processing, in particular to a triangular mesh quality optimization method and system based on local reconstruction, which comprises the following steps: acquiring a triangular mesh, and screening a first triangular mesh to be optimized based on a preset regularity; performing basic topological adjustment on the first triangular mesh to be optimized, and obtaining a second triangular mesh to be optimized; acquiring a first local neighborhood mesh of the second triangular mesh to be optimized, moving the vertexes of the triangular mesh in the first local neighborhood mesh, and obtaining a third triangular mesh to be optimized; acquiring a second local neighborhood mesh of the third triangular mesh to be optimized and a projection plane of the second local neighborhood mesh, determining a layout triangle according to the area of the projection plane and a target side length, and mapping the layout triangle to the second local neighborhood mesh. The application can optimize the quality of the triangular mesh on the basis of retaining the original geometric characteristics of the triangular mesh, and greatly improve the calculation efficiency of the triangular mesh optimization.

The invention provides an unstructured parallel grid quality optimization method based on grid unit merging. According to the method, when it is detected that a negative volume unit exists in a computational grid, the negative volume unit and an adjacent unit are combined, and optimized grid geometric information, topological information, boundary condition information and butt joint surface information are reconstructed. And through loop iteration until no negative volume unit exists in the optimized grid, the quality of the computational grid is remarkably improved, and the efficiency and precision of CFD numerical simulation are improved. The method can be applied in a multi-block parallel grid environment, supports grid optimization of a large-scale complex geometric model, and is suitable for two-dimensional and three-dimensional unstructured grids.

The application discloses a kind of complex tide river network's multi-source compound disaster inundation risk simulation method, contains the construction method of astronomic tide-storm surge-flood-salinity-falling multi-scale dynamic process full coupling model, can analyze complex river network in climate change scenario mountain torrent, storm surge, salinity and rainstorm etc. extreme compound disaster's inundation and salinity upstream risk.Through potential inundation area determination, model grid optimization, numerical format setting and parallel acceleration etc. technical means, on the basis of guaranteeing momentum and material flux conservation in river network, maximum degree optimizes calculation efficiency, can realize in estuary-coastal cross-scale spatial region high-precision simulation of the purpose of giving priority to multi-source disaster inundation and saltwater stratification.Based on the application, the problem that water dynamics, salinity, relatively isolated nearshore complex topography cannot interact in traditional simulation can be solved, technical support is provided for scientific evaluation of estuary area multi-source disaster risk and return period, with outstanding social benefits and disaster prevention and mitigation economic benefits.

The invention relates to the field of radiator design analysis, in particular to a radiator flow channel three-dimensional reconstruction and fluid performance prediction system and a method thereof.The method comprises the steps that a parameter input module receives a radiator three-dimensional model and boundary information and calculates parameters of a flow channel section and an inlet section; the streamline drawing module receives the parameters and calculates and determines starting coordinates and boundary points of a streamline; and the streamline smoothing module is used for smoothing the streamline. The flow channel curved surface gridding module receives the smoothed streamline coordinates, generates a three-dimensional curved surface based on spatial structure points, and performs adaptive non-uniform mesh generation and boundary constraint intelligent mesh optimization; the fluid performance prediction module receives the flow channel curved surface grid, inputs fluid performance analysis parameters and predicts fluid performance; the calculation result output module receives the prediction result, arranges and summarizes the prediction result and outputs the result; and through streamline tracking and smoothing processing, accurate reconstruction of the complex flow channel of the radiator is realized, the modeling precision is improved by more than 40%, and the design accuracy and efficiency of the radiator are improved.

A method and apparatus that renders a mesh from one or more virtual camera views of an object, the one or more virtual camera views being projections of the mesh onto a plurality of 2D planes; inputs the one or more virtual camera views into a fully-convolutional model for real-time segmentation; generates one or more 2D pixel-wise masks based on the fully-convolutional model, the 2D pixel-wise masks being associated with one or more segmented elements; performs remeshing and mesh optimization using the one or more 2D pixel-wise masks; and generates an output mesh based on the remeshing and mesh optimization.

The application discloses an intelligent identification and modeling method for an aviation composite special-shaped component inner preform, and belongs to the technical field of aviation composite material microstructure digitization reconstruction and modeling. The method comprises the following steps: S1, data acquisition; S2, data preprocessing; S3, model training preparation; S4, intelligent segmentation; S5, three-dimensional reconstruction; S6, grid optimization; S7, topology processing; and S8, model output. The aviation composite special-shaped component inner preform intelligent identification and modeling method is adopted, topology errors and grid conforming problems that are prone to occur in explicit modeling are combined with grid Boolean operation and post-processing repair algorithms, grid intersections and discontinuous regions are accurately processed, grid gaps, missing surfaces and other closed defects introduced by the Boolean operation are repaired, the node conformality, topology connectivity and spatial closedness of the preform substructure grid are ensured, manual participation is reduced, and the modeling efficiency and stability are improved.

The invention relates to the technical field of parameter design of a double-exponential pulse current source, and particularly discloses a pulse current source parameter prediction and optimization method based on artificial intelligence, which comprises the following steps of: constructing a two-stage parameter reverse framework of artificial intelligence prediction and local grid optimization, and taking target rise time, pulse width and load internal resistance as input; rough prediction of the capacitance C and the inductance L is given by using a regression neural network; then, a two-dimensional local parameter grid is constructed by taking the prediction as a center, a double-index analysis model is called to carry out rapid feature calculation and error evaluation, and a parameter group enabling the relative error of each feature to be minimum is selected as a final solution. The method aims at obtaining engineering balance between precision within 1% and second-level response.

The invention provides a coal mine vertical shaft model construction method and device and electronic equipment, and the method comprises the steps: obtaining a coal mine three-dimensional geologic model, and determining a model boundary of a to-be-constructed vertical shaft model based on vertical shaft model construction parameters; determining a to-be-cut area based on the model boundary and the coal mine three-dimensional geologic model; in response to the situation that the vertical shaft cutting condition is not met, optimizing the distorted triangular mesh area; determining a windowing boundary, and performing vertical shaft model cutting in the windowing boundary to generate candidate vertical shaft models; and the steps are repeated until the candidate vertical shaft model meets the cutting end condition, and the candidate vertical shaft model and the coal mine three-dimensional geologic model are fused to generate a target vertical shaft model. By triggering a local grid optimization + dynamic windowing retry mechanism, global model defects can be effectively avoided, an effective vertical shaft model can still be stably generated under severe geological conditions, dependence on professional modeling personnel is greatly reduced, modeling efficiency is improved, and the method is suitable for large-scale mine group batch processing scenes.

The application discloses a pipe type filter core structure with high water purification capacity based on grid optimization, which comprises threaded rotary interfaces arranged at two ends of a filter core body, and a plurality of filter core bodies arranged in the filter core body; the filter core bodies sequentially comprise third filter core bodies, second filter core bodies and first filter core bodies from inside to outside; first filter openings are arranged between adjacent first rotary plates and are arranged on the first filter core bodies; second filter openings are arranged between adjacent second rotary plates and are arranged on the second filter core bodies; and third filter openings are arranged between adjacent third rotary plates and are arranged on the third filter core bodies. The device is simple in structure, novel in design, and is assembled and connected through rotation, so that the internal structure and position of the device can be conveniently adjusted, replaced and disassembled by workers, the device is convenient for workers to install and use, the use and installation efficiency is effectively improved, the disassembly difficulty in the prior art is solved, and the service life of the water purifier is prolonged.

The application discloses a two-dimensional Gaussian splash three-dimensional reconstruction method based on multi-model cooperation, and comprises the following steps: acquiring multi-view RGB images, outputting camera parameters and sparse point clouds by using a VGGT model, generating a depth map and a mask map by using a monocular depth estimation network and an image segmentation network, performing dense processing by using a visual shell algorithm, initializing a two-dimensional Gaussian primitive by using the dense point cloud, training the initialized two-dimensional Gaussian primitive, re-rendering depth maps of all views, generating a three-dimensional grid by using a truncated signed distance function and an isosurface extraction algorithm, performing grid optimization on the three-dimensional grid based on local bilateral filtering to obtain a smooth grid, performing scale correction on the smooth grid to obtain a three-dimensional model with a real scale, and generating a comprehensive three-dimensional model with high-fidelity geometry, a real scale and new-view rendering capability through the initialization and optimization strategy based on multi-model cooperation.

The invention belongs to the technical field of gear transmission systems, and particularly discloses a gear meshing optimization method and system based on random progressive iteration and regularization, and the method comprises the following steps: carrying out the data sampling and preliminary fitting based on a gear tooth surface curve model; aiming at the preliminary fitting, setting an adaptive double-layer optimization framework which comprises a first layer of control point updating strategy optimization and a second layer of parameter distribution optimization, constructing an objective function, and realizing adaptive fusion optimization in the same iterative loop to obtain an optimized involute curve and a curved surface; and for the meshing region, introducing second-order difference smoothing, carrying out multi-objective optimization, and outputting a finally fitted NURBS control point P and an optimized parameter mapping weight w. By adopting the technical scheme, on the basis of least square approximation (LSPIA), the adaptive double-layer optimization technology is integrated, and the fitting precision, the fairness and the convergence speed are remarkably improved by jointly optimizing a control point updating strategy and parameter distribution.

The invention discloses an intelligent identification and modeling method for a prefabricated body in an aviation composite material special-shaped component, and belongs to the technical field of aviation composite material microstructure digital reconstruction and modeling, and the method comprises the following steps: S1, data acquisition; s2, data preprocessing; s3, model training preparation; s4, performing intelligent segmentation; s5, performing three-dimensional reconstruction; s6, carrying out grid optimization; s7, carrying out topology processing; and S8, outputting the model. According to the intelligent identification and modeling method for the prefabricated body in the aviation composite material special-shaped component, aiming at the problems of topological errors and grid conformality which are likely to occur in explicit modeling, grid intersection and discontinuous areas are accurately processed in combination with a grid Boolean operation and post-processing repair algorithm, and the modeling accuracy is improved. Sealing defects such as grid gaps and missing surfaces introduced by Boolean operation are repaired, and node conformality, topological connectivity and space sealing performance of substructure grids of the prefabricated body are guaranteed; and meanwhile, manual participation is reduced, and the modeling efficiency and stability are improved.

The embodiment of the invention discloses a grid optimization method and equipment based on rotation parameters. The method comprises the following steps: inputting an initial grid, and calculating a local slope value of each grid point in the initial grid; judging a flat region and a steep region in the initial grid according to the local gradient value; optimizing a grid density function of the steep region based on a grid density rotation parameter to generate an optimized grid density function; and generating a grid in the steep region according to the optimized grid density function, thereby realizing collaborative optimization of the grid in the steep terrain region while maintaining the grid quality of the flat or simple terrain region, realizing targeted grid encryption, more accurately depicting the terrain forcing effect, and improving the terrain forcing effect. The simulation capability of key weather processes such as mountain circulation and terrain rainfall is improved; meanwhile, through reasonable grid transition distribution, computing resources are saved, and ideal technical support is provided for high-resolution region simulation.

This invention proposes a method, apparatus, equipment, and storage medium for simulation training of ship section construction. It achieves the construction of a high-performance virtual reality simulation environment, supporting collaborative interaction across multiple terminals such as VR, PC, and CAVE, significantly improving the system's adaptability and interactive immersion. Through a multi-user network synchronization architecture and workstation-level dynamic simulation scene construction, it realizes the realistic restoration of section construction process logic and operational synchronization, improving collaboration and training realism. Employing a multi-level detail model and dynamic mesh optimization technology based on view distance and bounding box overlap rate effectively reduces the rendering load of complex scenes and improves the system's real-time response performance. By establishing a multi-projection plane world coordinate system and real-time viewpoint matrix calculation, it achieves consistent rendering across multiple terminals. Combined with workstation cycle data synchronization and an operation scoring mechanism, it forms a quantifiable training evaluation system, thereby comprehensively improving the efficiency, safety, and scientific rigor of ship section construction training.

The application provides a surface flaw analysis method combined with metal material fatigue life prediction, comprising: performing mesh optimization and refinement processing on an initial three-dimensional model, performing fine reconstruction on a local area, and obtaining a three-dimensional geometric model of a metal material surface, the three-dimensional geometric model containing surface flaw information of a microscale; performing regional division on the three-dimensional geometric model, identifying and extracting a surface flaw region, performing edge detection on the surface flaw region, and determining accurate geometric contours and spatial position information of the flaw; using finite element analysis software, importing the three-dimensional geometric model of the metal material and a flaw mathematical description model, setting material properties, boundary conditions and load working conditions, and establishing a finite element analysis model containing micro flaws; performing stress and strain analysis on the finite element analysis model of the micro flaw, calculating stress distribution and stress concentration coefficients around the flaw, and using fracture mechanics theory to evaluate the influence of the flaw on fatigue crack initiation and propagation.

The present disclosure proposes a coal mine shaft model construction method and device, and an electronic device, comprising: obtaining a coal mine three-dimensional geological model, and determining a model boundary of a to-be-constructed shaft model based on shaft model construction parameters; determining a to-be-cut region based on the model boundary and the coal mine three-dimensional geological model; in response to not meeting a shaft cutting condition, optimizing a distorted triangular mesh region; determining a windowing boundary, and performing shaft model cutting within the windowing boundary to generate a candidate shaft model; repeating the above steps until the candidate shaft model meets a cutting end condition, and fusing the candidate shaft model with the coal mine three-dimensional geological model to generate a target shaft model. By triggering a local grid optimization + dynamic windowing retry mechanism, global model defects can be effectively bypassed, and under severe geological conditions, an effective shaft model can still be stably generated, greatly reducing the dependence on professional modeling personnel, improving modeling efficiency, and being suitable for large-scale mine group batch processing scenarios.

The application discloses a kind of based on industrial CT sequence image direct generation hexahedral grid method, comprising the following steps: 1) reading the CT sequence image of workpiece;2) the CT sequence image is preprocessed, to obtain target area with workpiece information;3) based on octree, target area is divided into several hexahedral grid;4) extracting core grid and its outer surface in hexahedral grid;5) fitting is carried out to core grid, and boundary grid is obtained;6) boundary grid unit is optimized in quality, and then the hexahedral grid corresponding to workpiece is obtained.This method uses the CT sequence image of workpiece as input, first image pre-processing, secondly, using octree divides grid, extracts core grid and outer surface, then boundary fitting is carried out, finally, grid optimization is carried out, realizes that CT image directly generates hexahedral grid, does not need third party commercial software to reconstruct the CAD model of workpiece, can improve automation degree, efficiency is promoted.

The invention discloses a neutron transport unstructured grid calculation result three-dimensional visualization system and method, and the system comprises a reading module which is used for reading the original data of the unstructured grid calculation result; the data preprocessing module is used for carrying out data partitioning on the original data, establishing a thread pool and executing multi-thread analysis in parallel to obtain analysis data; the data merging module is used for performing data merging on the analysis data to obtain complete unstructured grid calculation result analysis data; the data structure construction module is used for constructing a data structure according to the unstructured grid calculation result analysis data to obtain grid optimization data; the color mapping module is used for performing color mapping on the grid optimization data; and the rendering module is used for rendering the model passing through the color mapping module to obtain a three-dimensional visualization result of the neutron transport unstructured grid calculation result. The technical problems that in the prior art, the visualization rendering efficiency of an unstructured grid calculation result is low, and the model precision is low are solved.

The application discloses a rigid multi-geometry outer surface reconstruction method based on rotation imaging and belongs to the technical field of three-dimensional reconstruction. The method comprises the following steps: center of rotation calibration; collecting three-dimensional point cloud data of the surface of an object to be reconstructed; performing pretreatment work such as removing stray points and repairing holes on the collected three-dimensional point cloud data; reconstructing a point cloud model of a measured object by using a surface reconstruction algorithm based on the pretreated three-dimensional point cloud data; and performing mesh optimization on the constructed point cloud model to complete outer surface reconstruction. The application supports an arbitrary internal rotation axis and is suitable for complex geometrical shapes such as annular and prism. A self-calibration method based on a standard part reduces the influence of equipment installation errors. A dynamic algorithm optimizes point cloud reconstruction and can realize micron-level three-dimensional reconstruction requirements.

The application provides a capacitor identification and mesh optimization method and system for integrated passive device simulation. The method comprises the steps of determining a target dielectric layer in an integrated passive device model; determining a projection overlapping area of each pair of upper and lower metal contact surfaces having a projection overlapping relationship on the plane to which the target dielectric layer belongs and an area of a bounding box thereof; marking the projection overlapping area with a ratio of its own area to the area of the bounding box greater than a ratio threshold value as a target projection overlapping area; identifying the related entity structure of the target projection overlapping area as a capacitor; and performing mesh encryption setting on the related area of the capacitor. The system comprises various functional modules corresponding to the above steps. According to the application, the IPD capacitor encryption area can be automatically found through physical characteristics, the capacitor identification and mesh setting are integrated, the simulation stage adaptive process is accelerated, and the calculation efficiency is significantly improved while the simulation accuracy is ensured.

The application relates to the technical field of finite element optimization, in particular to a performance optimization method and system based on finite elements, which comprises the following steps: obtaining a finite element model of a gear in a rice transplanter dividing mechanism, dividing the finite element model into multiple grids; applying corresponding loads to the finite element model according to simulation data of the gear of the rice transplanter during operation, obtaining simulation indexes of each grid, optimizing the grid size of each grid based on the simulation indexes, and outputting an optimized target grid; determining performance indexes of each target grid, optimizing design parameters of the target grid according to the performance indexes, updating the finite element model based on the optimized design parameters, and taking the finite element model as the final finite element model of the gear; and the application can improve the analysis accuracy and optimization efficiency of the gear through deep coupling of grid optimization and parameter optimization.