73 results about "Level set" patented technology

The invention belongs to the technical field of structure optimization, and particularly discloses a geometric nonlinearity-considered parameterized level set porous structure topological optimization method, which comprises the following steps of: constructing a level set function to implicitly describe a structure boundary, and performing spline interpolation by adopting a tightly-supported radial basis function to obtain a parameterized level set function; establishing an equilibrium equation of geometric nonlinear topological optimization, and solving structural response under the condition of large deformation through geometric nonlinear finite element analysis; approximating and simplifying local volume constraint through a local constraint domain and a p norm function; establishing a topological optimization model based on geometric nonlinear porous filling rigidity maximization; performing sensitivity analysis through an adjoint method, and calculating a partial derivative of an objective function of the topological optimization model to an expansion coefficient so as to determine an optimization direction of each finite element in geometric nonlinear porous filling stiffness maximization; and carrying out iterative optimization to obtain an optimized topological structure. According to the method and the device, porous filling topological optimization under geometric nonlinear conditions can be realized.

The invention provides a theoretical spectral data optimization method and a measurement method wherein the theoretical spectral data optimization method can obtain an optimized level pair set by obtaining the sensitivity corresponding to each convergence level pair under the condition of obtaining convergence level pair sets and screening the convergence level pair sets according to the sensitivity pairs. And obtaining corresponding theoretical spectral data according to the optimization level pair set. According to the method, the influence of the change quantity of the Fourier coefficient of the order pair on the change quantity of the theoretical spectral data is represented through the sensitivity, and the smaller the value of the sensitivity is, the smaller the influence of the change quantity of the Fourier coefficient of the corresponding order pair on the theoretical spectral data is; the corresponding level is more indispensable in the calculation process of theoretical spectral data. Due to the fact that the number of the order pairs in the optimization order pair set is smaller than that in the convergence order pair set, the calculation efficiency of theoretical spectrum data can be improved through the optimization order pair set.

The invention relates to the technical field of volume measurement, and provides a test pit volume measurement device and a measurement method thereof in roadbed compactness detection. A laser scanning module scans to obtain point cloud data in a test pit and transmits the point cloud data to a data preprocessing module; the data preprocessing module receives the point cloud data and then performs denoising according to a radius outlier filtering algorithm; the data calculation module receives the preprocessed data, calculates point cloud data information, iteratively calculates a zero contour surface of a level set function representing the surface of the test pit, and then performs volume calculation by using the Gaussian-Green theorem; the data display module displays a test pit region boundary image and a volume and point cloud data image according to a calculation result; point cloud data are obtained through the laser scanning module, after filtering and noise reduction are conducted through the data preprocessing module, a level set function is constructed through the data calculation module, the boundary of the test pit is determined by means of partial differential equation evolution, then the size is calculated through the Gaussian-Green theorem, and the accurate size of the irregular test pit is measured.

The invention discloses a self-adaptive point cloud implicit curved surface reconstruction method based on a truncation level B spline, and the method comprises the steps: constructing a first-layer truncation level B spline primary function space, and obtaining an initial implicit function through solving an optimization model; evaluating the fitting error of each point of the input point cloud, and determining the fitting error as a region which needs to be further refined; establishing a new truncation hierarchy B-spline primary function set, and expanding a current function space; performing truncation operation on the THB spline primary function which is completely positioned in the refined region; combining the truncated primary function with the primary function set generated by the new layer, and updating the whole primary function library; re-optimizing the model, and solving the updated implicit function; refining and optimizing layer by layer, and outputting a final implicit function and a zero level set thereof; and performing triangular meshing on the final zero level set to finish curved surface reconstruction. According to the method, an extra training process is not needed, excellent point-to-surface distance and curvature indexes can be kept at the noise level up to 10%, and the memory and calculation overhead can be greatly reduced.

The invention belongs to the related technical field of dual-scale structure design, and discloses a dual-scale structure optimization design method and system based on substructure data driving, and the method comprises the steps: an offline stage: for cell elements of a dual-scale structure, carrying out the cutting operation of a level set function, obtaining a virtual microstructure, and carrying out the cutting operation of the level set function; determining the density of the actual microstructure according to the density of the virtual microstructure; performing static condensation through a substructure method to obtain a stiffness matrix of the super-unit, and constructing a mapping model of the cutting height parameter, the stiffness matrix of the super-unit and the density of the actual microstructure; in the online stage, a data driving model with the cutting height parameter as the input quantity and the stiffness matrix of the super-unit and the density of the actual microstructure as the output quantity is obtained; and applying the data driving model to a finite element optimization process of the dual-scale structure, and finally obtaining an optimized dual-scale structure. According to the invention, an off-line data driving method is adopted to carry out dual-scale structure optimization, and the efficiency can be greatly improved under the condition that the precision is ensured.

The invention provides a shell-based mechanical metamaterial design strategy based on level set function weighted combination. The framework is inspired by a three-period minimal curved surface, and a shell-based mechanical metamaterial database is constructed by adopting a level set function weighted combination strategy. The effective elastic performance of the metamaterial is evaluated through the homogenization theory of voxel modeling. A back propagation neural network model is developed, and the model can realize reverse mapping between geometric parameters and material attributes of a shell base unit. In addition, the reliability of the homogenization theory is verified by adopting a quasi-static compression test, and the effective elastic characteristic and the compression response of the shell-based structure are evaluated. Research results show that the shell-based mechanical metamaterial not only shows isotropic elasticity and high rigidity exceeding the upper limit of the Hashin-Shtrikman theory, but also has significantly improved yield strength and energy absorption ability under compression. According to the design, a series of light-weight and high-rigidity-strength structures are finally formed, and 3D printing forming is conducted through the PolyJet technology.

The invention discloses a deep strike-slip fracture fracture zone identification method, and the method comprises the steps: converting original seismic data into a frequency-wavenumber domain through Fourier transform, carrying out the multi-scale decomposition and downsampling through a radial filter cascade architecture, converting the data into a time-space domain through a directional basis filter, and carrying out the filtering. And acquiring an optimal direction by adopting an optimization strategy, and constructing characterization attributes based on neighborhood attribute differences to extract multi-scale fracture attributes. And introducing a plurality of level set functions to construct an energy functional model, and solving through a dynamic weight adjustment algorithm to realize internal and external band identification. And constructing a model by means of a topological relation based on distance-angle constraint to analyze the three-dimensional space topology. The problems that traditional data processing is not fine and model analysis is insufficient are solved, accurate recognition of the deep strike-slip fracture fracture zone is achieved, and the method has important application value in the fields of oil and gas exploration and development and the like.

The invention discloses a multi-objective topological optimization method for aircraft design, and belongs to the technical field of aerospace. The method comprises the steps that a three-dimensional geometric model is established, and an optimization area and an aerodynamic reservation area are delimited; describing a structural boundary by adopting a level set function; with rigidity maximization and inherent frequency maximization as targets, volume and manufacturing constraints are applied; utilizing a compromise planning method to construct a comprehensive objective function for minimizing the ideal point distance; transforming the constraint problem through an augmented Lagrangian method; calculating shape sensitivity and exporting a normal velocity field; updating a level set function to drive topology evolution; iterating until convergence, and generating a Pareto frontier solution set; and selecting an optimal scheme and reconstructing the optimal scheme into a three-dimensional model capable of being manufactured. On the premise of keeping the aerodynamic configuration, the problem of multi-target collaborative optimization is solved, the boundary is clear, the manufacturability is high, and the structural performance and the engineering applicability are remarkably improved.

The embodiment of the invention discloses a bill key field identification method and device. The method comprises the following steps: acquiring a bill image; defining the key field, wherein the key field comprises at least one of an invoice number, an amount and a date; fractional order differential calculation is carried out on the bill image, an enhanced image and fractional order differential features are generated, and the fractional order differential features comprise a fractional order gradient field and a multi-scale feature vector; semantic features of the bill image are extracted according to a predefined bill semantic template, semantic priori is generated, and the semantic priori represents the relative position and expected content of the key field; a level set function is initialized based on the fractional order differential features and the semantic priori, an energy function is constructed, the energy function is minimized to drive the level set function to evolve, and a segmentation result is generated; and performing feature extraction on the segmentation result to generate structured data. According to the invention, the accuracy and efficiency of key field identification are improved.

Systems, devices, methods and computer program products are described herein for a convolutional approach to highly efficient single parameter radial basis function level set structural optimization and inverse homogenization.

The invention discloses a level set field reconstruction method and system based on a three-dimensional finite element grid and a medium. Relates to the technical field of geometric reconstruction. Positioning a space Cartesian grid area intersected with the boundary surface grid based on a separation axis theory; calculating a geometric space point-surface position relation, calculating a directed projection distance from a space Cartesian grid center to a two-dimensional boundary surface grid, and correcting the positive and negative characteristics of a Cartesian grid level set value based on a three-dimensional eight-direction rapid scanning method, so that the grid level set value is consistent with a region boundary value; according to the method, the geometric reconstruction problem of the deformable body which is complex in appearance and free of explicit analytic expression can be efficiently and accurately solved, a coupling approach between a finite element grid and a Cartesian grid is established under a non-conformal grid system, and the flexibility and universality of explicit calculation of a level set function under the Cartesian grid are improved.

The application belongs to the technical field of image segmentation, and particularly relates to a complex scene target segmentation method and system based on image recognition, which comprises the following steps: performing superpixel adaptive division on an input image, fusing gray scale and texture features to determine a superpixel boundary, mapping the superpixel boundary into a graph node and calculating an edge weight, and constructing an undirected weighted graph; adaptively encoding a graph signal, utilizing a hybrid graph wavelet-Fourier joint transform to optimize and separate features, and obtaining purified graph frequency domain features; sparsely reconstructing features through adaptive super-complete dictionary learning, and obtaining target enhanced features; extracting topological parameters based on an improved persistent homology, constructing a topological constraint feature graph, mapping the topological constraint feature graph into an initial contour field, iteratively optimizing a level set and a contour through an adaptive partial differential equation, and obtaining a high-fidelity coarse segmentation result; extracting geometric features to construct a joint constraint model to repair an occluded area, and outputting a precise segmentation result. In the application, sparse topological modeling is adopted, weak features are strengthened, and target discrimination accuracy is improved.

The present application belongs to the technical field of wind power generation, and specifically relates to a wind power tower material crack propagation prediction method and system, which is suitable for fatigue life evaluation of large supporting structures in the wind energy industry. The method comprises: deploying a multi-source heterogeneous sensor network to collect strain, acoustic emission and environmental load data; constructing a digital twin high-fidelity finite element submodel to obtain a dynamic stress intensity factor; constructing a deep neural network, embedding the Paris law of fracture mechanics in the form of residual into the loss function to form a physical information neural network, and realizing crack propagation rate prediction; using the extended finite element method combined with the level set function and the maximum circumferential stress criterion to dynamically track the three-dimensional space expansion path of the crack; combining Monte Carlo simulation and recursive Bayesian update to evaluate the remaining life and trigger graded early warning. The present application solves the problems of insufficient fusion of physical mechanisms and data-driven in the prior art, low prediction accuracy under small samples, and lack of crack space path tracking.

The present invention belongs to the field of image detection technology and is a SAR image coastline detection method based on level sets. The level set function is initialized as a signed distance function, the grayscale means of the foreground and background are calculated according to the initialized level set function, and each point of the level set function is evolved using the grayscale means of the foreground and background estimated previously. The iterative step size of the level set function in the evolution process is adaptively changed by a step size control function. If the level set function value of the current point is greater than 100 or less than -100, the step size is changed from the original 0.1 to 1, otherwise it remains unchanged. The level set function is then continuously evolved. According to the definition, foreground>0 and background<0, if the grayscale value of the current point is close to the foreground valuation, the value of the level set is correspondingly increased, otherwise it is decreased. The level set function is reinitialized according to the penalty term to make it conform to the signed distance function. Finally, it is checked whether the level set function converges, and if not, it is re-evolved.

The present invention relates to an image processing method based on morphology and non-linear Poisson equation, which includes: fitting an intensity differential fitting function of the contours on both sides of the input image according to gray-scale morphological erosion and dilation operations, and defining an energy function containing the image contour line; obtaining a new energy function according to the level set function and taking the derivative to obtain a gradient descent flow equation; decomposing the data term therein and introducing a non-linear Poisson equation for representation; constructing a canonical function for non-linearly stretching the value range of the data term function; continuously updating the level set function, and after regularization and neighborhood average filtering processing, obtaining the final level set function; outputting the same and the image segmentation result; adopting mathematical morphology to increase the anti-noise ability, effectively eliminating the influence of noise on image segmentation, reducing the amount of computation and the image segmentation time; constructing a non-linear Poisson equation to weaken disturbances such as non-uniformity, introducing a level set model to complete image segmentation, and increasing the accuracy of image segmentation; constructing a canonical function to improve the robustness.

This invention discloses a multi-objective topology optimization method for aircraft design, belonging to the field of aerospace technology. The method includes: establishing a three-dimensional geometric model and defining the optimization region and aerodynamic preservation region; describing the structural boundary using level set functions; applying volume and manufacturing constraints with the objectives of maximizing stiffness and natural frequency; constructing a comprehensive objective function that minimizes the distance between ideal points using a compromise programming method; transforming the constraint problem using the augmented Lagrangian method; calculating shape sensitivity and deriving the normal velocity field; updating the level set functions to drive topology evolution; iterating until convergence to generate a Pareto front solution set; selecting the optimal solution and reconstructing it into a manufacturable three-dimensional model. This invention solves the multi-objective collaborative optimization problem while preserving the aerodynamic shape, resulting in clear boundaries, strong manufacturability, and significantly improved structural performance and engineering applicability.

The present application relates to the field of additive manufacturing, and specifically discloses a kind of generation method of manufacturing three-dimensional Chinese character cup model based on energy driving.The present application constructs the smooth time evolution path from multiple outline initial region to single target outline, adopts level set function to describe the outline evolution process, and establishes energy functional including curve length regularization term, adaptive inflation term and shape prior term;Through introducing the dynamic coupling control mechanism based on area difference of region, shape error and boundary length, the adaptive adjustment of inflation coefficient is realized;Then the level set evolution equation is obtained by variational derivation, and after numerical discrete solution, two-dimensional evolution sequence is added to three-dimensional volume field along time axis;Finally, through isosurface extraction and thick shell processing, the 3D printable three-dimensional Chinese character cup model with complete structure and uniform wall thickness is generated.

This application belongs to the field of structural optimization technology and specifically discloses a parameterized level set topology optimization method for porous structures that takes geometric nonlinearity into account. The method comprises: constructing a level set function to implicitly describe the structural boundary, and using compactly supported radial basis function spline interpolation to obtain the parameterized level set function; establishing an equilibrium equation for geometric nonlinear topology optimization, and performing geometric nonlinear finite element analysis to solve the structural response under large deformation conditions; approximating and simplifying local volume constraints through local constraint domains and p-norm functions; establishing a topology optimization model based on maximizing the geometric nonlinear porous filling stiffness; performing sensitivity analysis through the adjoint method, and calculating the partial derivatives of the objective function of the topology optimization model with respect to the expansion coefficient to determine the optimization direction of each finite element in maximizing the geometric nonlinear porous filling stiffness; and performing iterative optimization to obtain the optimized topology structure. This application can realize the topology optimization of porous fillings under geometric nonlinear conditions.

The invention belongs to the technical field related to structure optimization design, and discloses a lattice structure optimization design method and device combining a multivariable cutting level set and progressive optimization, and the method comprises the steps: (1) building a lattice structure optimization model by taking structure flexibility as a target function and cutting height as a design variable; (2) performing finite element analysis based on the lattice structure optimization model to obtain a structure volume fraction; (3) if the current number of iterations is an odd number or the structural volume fraction is lower than the set threshold value, calculating the sensitivity of the target function and the constraint function to the design variable, and updating the design variable by adopting a moving asymptote algorithm based on the obtained sensitivity; if the number of iterations is an even number and the volume fraction of the structure exceeds a set threshold value, calculating a unit sensitivity degree so as to obtain a sensitivity degree of the virtual microstructure, and removing a part of the virtual microstructure based on the sensitivity degree of the virtual microstructure; and a final lattice structure is further obtained. According to the invention, the optimization efficiency is improved.

The application provides a kind of marine structure flow field simulation method, the method comprises: generating calculation grid and object surface grid for flow field simulation;Initialize object surface grid level set function field;According to flow field information, calculate the force condition of object surface, calculate object translation vector and rotation vector;Complete data mapping of object surface grid to calculation grid, obtain the level set function field of calculation grid;According to the obtained calculation grid level set function field, divide cell type;Carry out geometric calculation to cut cell, based on cut cell flow field reconstruction strategy, complete fluid cell, cut cell estimated speed update;Solve pressure Poisson equation, obtain pressure field, pressure gradient, update velocity field according to the obtained pressure gradient, obtain the final velocity field satisfying continuity condition.The marine structure flow field simulation method of the application greatly improves the numerical simulation efficiency of complex structure flow field, and reduces the implementation difficulty.

The present application belongs to the technical field of structure optimization design, and discloses a structure topology optimization design method and device, steps are as follows: (1) dividing a physical design domain into a background grid, based on coordinate information of background nodes of the background grid, a sparse filtering matrix is constructed by using a Gaussian kernel function with row normalization; (2) using the sparse filtering matrix to perform front filtering on design variables on the background nodes to obtain a smooth density field, and then obtaining a level set function field; (3) using an adaptive grid subdivision algorithm to cut and locally adaptively reconstruct the level set function field to obtain an analysis grid; (4) interpolating the level set function field to the analysis grid through a sparse global interpolation matrix from the background grid to the analysis grid to obtain a level set function field; (5) projecting the level set function field to obtain a pseudo-density field on the analysis grid nodes, and then obtaining an optimal topology configuration. The present application realizes good boundary smoothness while improving optimization efficiency.

The present application provides a training method for a mask pattern correction model and a mask pattern correction method. The method includes: obtaining a pre-OPC mask pattern and a post-OPC mask pattern; calculating a first level set function and a second level set function based on the pre-OPC mask pattern and the post-OPC mask pattern, respectively; and training the first level set function as the input of a neural network model and the second level set function as the output of the neural network model to obtain a mask pattern correction model. The method provided in the present application utilizes the first level set function and the second level set function to represent the images of the pre-OPC mask pattern and the post-OPC mask pattern on a discrete grid, eliminating the need to use a large number of feature vectors to encode the mask pattern's proximity, thereby improving the efficiency of OPC.

The invention relates to a high-order interface capturing method for a coupling level set and a fluid volume based on mixing precision, which comprises the following steps of: firstly, dividing a calculation area into a grid comprising a plurality of control body units, initializing, then identifying interface units, and reconstructing a THINC interface function by adopting a high-order polynomial based on an LS value; thirdly, introducing a mixed precision iterative algorithm to solve an interface position nonlinear equation, and adaptively switching to multi-precision operation to obtain a robust solution when double precision cannot converge; then, flux is calculated through an accurate interface, a VOF transport equation is solved, and mass conservation is guaranteed; and finally, on the basis of the predicted interface geometry, an LS field which does not need to be reinitialized is directly reconstructed through pure geometric methods such as interface point cloud generation through projection and nearest point searching in a narrow band. According to the method, the capture precision and geometric fidelity of complex interfaces with high curvature, sharp corners and the like on the unstructured grids are remarkably improved, and the method has high precision and strong robustness.

The invention belongs to the technical field of aero-engine cooling design and flow heat exchange optimization, and provides a turbine blade cooling turbulence rib construction method, system and configuration based on level set topological optimization and a blade. The method comprises the steps that a fluid-solid coupling calculation model containing a cooling channel fluid domain and a blade wall surface solid domain is constructed, defining a level set function to implicitly represent the two-phase region; establishing a unified control equation set covering a full computational domain based on the function, and introducing a flow velocity suppression mechanism into a solid domain to carry out single-domain coupling solution of fluid flow and solid heat conduction; according to the physical field solution, constructing an optimization model taking the cooling performance as a target function and the volume fraction of the turbulent flow rib as a constraint, and calculating the sensitivity of the target function to a level set function; using the sensitivity to drive a level set function update to evolve a spoiler rib boundary; iterating until convergence and outputting the final geometric configuration of the turbulent flow rib. According to the invention, the irregular turbulent flow structure with high heat exchange efficiency and low flow resistance can be automatically generated without presetting a rib type.

The present invention relates to an active contour model image segmentation method based on K-medoids clustering, comprising: using a K-medoids clustering algorithm to perform binarization processing on an image to be segmented to obtain a fitting result, and acquiring a foreground image and a background image; constructing a pre-segment fitting function based on the binarization fitting result; using a zero level set that meets the Lipschitz condition to replace the contour curve of the pre-segment fitting function to obtain a KM pre-segment fitting function; using a gradient descent method to minimize the energy functional of the KM pre-segment fitting function to obtain a gradient flow equation; using an adaptive regularization function to regularize a data-driven term of the gradient flow equation; using a rulesig function to regularize the zero level set function, using a kernel function to smooth and shorten the curve of the regularized zero level set function, and outputting a level set function as a segmentation result of the image to be segmented.

The invention relates to the field of medical image processing, and discloses a random field variational optimization medical image segmentation method and device and a storage medium, and the method comprises the steps: obtaining a medical image, and carrying out the solving operation of an initialization model; a solving model is constructed, the target of the model is given image gray Y, and the corresponding optimal segmentation X is solved; changing the model solution into the maximum value of the product of the likelihood probability and the prior probability by adopting a Bayesian formula; a simplified Potts model is adopted to solve a prior probability; the likelihood probability is equivalent to # imgabs0 #, a level set function phi (s) is introduced into the prior probability and the likelihood probability, a regular term is added to ensure the stability of the level set function in the evolution process, and finally a numerical calculation method is adopted for calculation to obtain a segmentation result. The method has the beneficial effects that the gray information and the spatial information of the image are considered at the same time, so that the segmentation result is more accurate.

The invention relates to the field of machine vision, and provides a corrosion diagnosis method, device and equipment based on machine vision, and the method comprises the steps: obtaining an input image, and carrying out the preprocessing of the image; selecting an initial contour in the preprocessed image as an initial range of a corrosion area; defining a level set function according to the initial contour; iteratively updating the level set function based on the selected energy functional model; after iterative optimization is completed, a final contour is extracted as a segmentation result, and a final corrosion area is obtained; and performing corrosion diagnosis according to the final corrosion area to obtain a corrosion report. According to the invention, the problem of poor accuracy of the traditional machine vision technology in corrosion diagnosis in the prior art is solved, and high-accuracy judgment of the corrosion image is realized.

The invention provides a reactive infiltration process numerical simulation method based on COMSOL multi-physics field coupling, which comprises the following steps: constructing a simplified liquid silicon infiltration model, and simulating a pore structure of a porous body by adopting a two-dimensional single capillary equivalent model; based on the liquid silicon infiltration model, coupling a laminar flow-level set two-phase flow field, a chemical reaction field, a dilute substance transfer field and a fluid heat transfer field to form a multi-physical field numerical model; and a liquid silicon permeation height curve, concentration distribution and pore structure evolution data are obtained through transient solution. According to the method, the time cost required by calculation is saved by simplifying the model, meanwhile, the accuracy of the model can be ensured, and the pore structure change in the reaction infiltration process is predicted according to the reaction layer change rule obtained through simulation; the problem that in the prior art, pore closing critical conditions and a reaction-permeation dynamic coupling mechanism are lack of systematic revelation is effectively solved, theoretical support is provided for directional regulation and control of prefabricated body pore parameters and optimization of process parameters, and the method has remarkable innovativeness and practicability.

The present invention discloses a three-dimensional structure interactive topology optimization method based on level set, which relates to the technical fields of computer-aided design, topology optimization, and interactive design. The method includes establishing a three-dimensional structure topology optimization design region; importing the level set field of the initial structure or a three-dimensional model file and generating an initial level set field; extracting a geometric structure from the level set field by using the Marching Cubes method, rendering and displaying the initial model; performing level set topology optimization on the structure, updating and real-time rendering and displaying the structure form; during the optimization process, the process can be paused at any time for interactive modification, and forced or non-forced intervention methods are adopted to increase or decrease the structure or refine the form through an interactive sphere, and the level set field is updated in real time to continue the optimization. Therefore, by adopting the above method, the topology optimization of complex initial models can be efficiently realized, the structure form can be dynamically adjusted, the cumbersome post-processing steps of traditional methods can be effectively reduced, and the structure design efficiency, accuracy, and flexibility are improved.

The invention discloses a shot peening forming process planning method based on a level set algorithm, and the method comprises the steps: S1, obtaining the features of a target wallboard, and selecting the type and number of level set functions according to the features of the target wallboard, so as to describe the boundary between a shot peening region and a non-shot peening region of the target wallboard; s2, establishing a shot peening forming process optimization mathematical model based on the level set function; s3, calculating the sensitivity of an objective function of the optimization model, and deducing an iterative formula of the level set movement velocity field; s4, the optimization model is initialized, the level set function is solved, the shot blasting area boundary is updated, if the boundary is not convergent, the step S3 is executed, and if the boundary is convergent, the step S5 is executed; and S5, discretely generating a shot blasting impact point set based on the converged shot blasting area boundary. According to the method, the problems existing in shot peening forming of complex wallboards in an existing shot peening process are solved, the process planning cost is remarkably reduced, and the forming precision is improved.