A packaging box modeling and rendering method and system

Abstract

This invention belongs to the field of 3D image rendering technology, and relates to a method and system for modeling and rendering packaging boxes. The invention generates a basic 3D mesh model by acquiring 2D die-cutting line data of the packaging box, extracts physical parameters of the substrate, binds features to the model, constructs multi-layer material rendering channels for optical interference calculations, and generates a model with anti-counterfeiting visual features. Further, through thermodynamic deformation calculations, a rendering model containing physical indentations is generated. Through interference verification and inverse analysis of 3D spatial features, physical processing control quantities are generated to drive production equipment to achieve automated linkage control of the packaging box. This invention solves the problem of traditional rendering mechanisms lacking accurate representation of physical deformation and complex optical scattering, improves the realism and physical accuracy of the rendered model, breaks down the data barriers from 3D rendering to physical processing, and provides effective support for high-precision packaging box production.

Description

Technical Field

[0001] This invention belongs to the field of three-dimensional image rendering technology, and relates to a method and system for modeling and rendering packaging boxes. Background Technology

[0002] Packaging box modeling and rendering refers to the process of converting the two-dimensional design data of a packaging box into a three-dimensional digital model using computer graphics technology, and generating realistic visual images by simulating the interaction of light and materials. 3D image rendering technology plays a crucial role in packaging design verification and production preview. Its core lies in reproducing the physical appearance and craftsmanship details of the packaging box in a virtual three-dimensional space through geometric topology construction and material optical property configuration.

[0003] Existing packaging box rendering solutions typically rely on static texture maps and basic lighting models to simulate surface visual effects. When dealing with complex processes such as hot stamping or laser anti-counterfeiting, the conventional approach is to pre-create a 2D image containing metallic luster or rainbow color levels, and then directly overlay it onto the 3D mesh surface as a diffuse or specular map. This is then combined with standard shaders for raster rendering from a fixed perspective to showcase the distribution of the packaging box's process layers and its basic color tendency.

[0004] This rendering mechanism, which relies on static textures, is detached from the true physical properties of the packaging substrate and cannot accurately calculate the diffraction and interference effects produced when light penetrates microscopic apertures or irradiates anisotropic materials. In multi-process stacking scenarios, conventional rendering pipelines lack the geometric analytical capabilities to handle material thermodynamic deformation and mechanical indentation depth, making it difficult to generate realistic physical indentation features at the 3D mesh level. This results in rendered visual images that only simulate surface colors, lacking accurate representation of physical deformation and complex optical scattering. Consequently, the rendered model cannot be used to guide subsequent physical interference verification and automated production control.

[0005] To address the aforementioned issues, this invention provides a packaging box modeling and rendering method. This method employs a rendering mechanism that extracts physical parameters of the substrate for feature binding and combines optical interference and thermodynamic deformation calculations to update the vertex coordinates and light scattering parameters of the three-dimensional mesh. This method can generate a high-precision three-dimensional rendering model that includes physical indentations and anti-counterfeiting visual features, and reverse-engineer the physical processing control quantities to drive the device operation. Summary of the Invention

[0006] In view of this, in order to solve the problems mentioned in the background technology, a packaging box modeling and rendering method and system are proposed.

[0007] The objective of this invention can be achieved through the following technical solution: The first aspect of this invention provides a packaging box modeling and rendering method, including: S1, acquiring two-dimensional die-cutting line data of the packaging box and performing triangular facet subdivision to generate a basic three-dimensional mesh model, wherein the two-dimensional die-cutting line data carries preset information of each process layer, and each process layer includes at least a hot stamping process layer and an anti-counterfeiting hollow pattern.

[0008] S2. Extract the physical parameters of the substrate corresponding to the basic 3D mesh model and perform feature binding to generate an attribute-bound 3D model carrying the underlying physical attribute matrix.

[0009] S3. Construct a multi-layer material rendering channel for the attribute-bound 3D model and perform optical interference calculations in conjunction with the underlying physical property matrix to generate an anti-counterfeiting visual feature model.

[0010] S4. Extract the thermodynamic parameters from the underlying physical property matrix and perform vertex displacement calculation on the anti-counterfeiting visual feature model to generate a thermodynamic deformation rendering model containing physical indentation features.

[0011] S5. Apply coordinate offset vectors to the thermodynamic deformation rendering model and perform three-dimensional Boolean operations for interference verification to generate the final three-dimensional model.

[0012] S6. Extract the three-dimensional spatial features of the finalized three-dimensional model and perform reverse mapping analysis to generate physical processing control quantities.

[0013] S7. Encapsulate the physical processing control quantities into control instructions and send them to the production equipment to execute the automated linkage control of the packaging box. The production equipment includes at least a packaging box die-cutting equipment and a hot stamping equipment.

[0014] The second aspect of the present invention provides a packaging box modeling and rendering system, comprising: a basic three-dimensional mesh model generation module, which acquires two-dimensional die-cutting line data of the packaging box and performs triangular facet subdivision to generate a basic three-dimensional mesh model, wherein the two-dimensional die-cutting line data carries preset information of various process layers, and each process layer includes at least a hot stamping process layer and an anti-counterfeiting hollow pattern.

[0015] The attribute-bound 3D model generation module extracts the physical parameters of the substrate corresponding to the basic 3D mesh model and performs feature binding to generate an attribute-bound 3D model carrying the underlying physical attribute matrix.

[0016] The anti-counterfeiting visual feature model generation module constructs a multi-layer material rendering channel for attribute-bound 3D models and performs optical interference calculations in conjunction with the underlying physical property matrix to generate an anti-counterfeiting visual feature model.

[0017] The thermodynamic deformation rendering model generation module extracts thermodynamic parameters from the underlying physical property matrix and performs vertex displacement calculation on the anti-counterfeiting visual feature model to generate a thermodynamic deformation rendering model containing physical indentation features.

[0018] The final 3D model generation module applies a coordinate offset vector to the thermodynamic deformation rendering model and performs 3D Boolean operations for interference verification to generate the final 3D model.

[0019] The physical processing control quantity generation module extracts the three-dimensional spatial features of the finalized three-dimensional model and performs reverse mapping analysis to generate physical processing control quantities.

[0020] The automated linkage control execution module encapsulates the physical processing control quantities into control commands and sends them to the production equipment to execute the automated linkage control of the packaging box. The production equipment includes at least a packaging box die-cutting equipment and a hot stamping equipment.

[0021] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention extracts the physical parameters of the substrate and binds them with the basic three-dimensional mesh model to construct a multi-layer material rendering channel in three-dimensional space. It combines the underlying physical property matrix to perform optical interference calculation and diffraction distribution analysis, and maps the complex optical interference features to the surface texture for real-time rendering. This improves the visual distortion caused by the traditional reliance on texture mapping and enhances the rendering realism and physical accuracy of the anti-counterfeiting visual feature model of the packaging box in the three-dimensional scene.

[0022] (2) This invention utilizes the thermodynamic parameters in the underlying physical property matrix, combined with the hot stamping processing temperature data to calculate the stress deformation depth of the deformation target area, uses the vertex shader in the graphics rendering pipeline to update the coordinates of the mesh vertices, and combines the bidirectional reflection distribution function to recalculate the light scattering parameters, thereby accurately simulating the physical indentation features generated during multi-process superposition processing in the three-dimensional rendering model, enhancing the optical expressiveness and geometric topological realism of the thermodynamic deformation rendering model.

[0023] (3) This invention applies a coordinate offset vector to the thermodynamic deformation rendering model and performs three-dimensional Boolean operation for interference verification. On this basis, it extracts the three-dimensional spatial features of the final three-dimensional model and performs reverse mapping analysis to generate physical processing control quantities covering pressure and temperature. These quantities are then encapsulated as control commands and sent to the production equipment. This breaks down the data barrier from three-dimensional image rendering to physical processing and manufacturing, and realizes automated linkage control of packaging boxes based on high-precision rendering models. This helps to reduce the cost of physical prototyping and improve the R&D efficiency of high-end customized packaging boxes. Attached Figure Description

[0024] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a schematic diagram of the method steps of the present invention.

[0026] Figure 2 This is a schematic diagram of the system structure connection of the present invention. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] Please see Figure 1 The first aspect of the present invention provides a packaging box modeling and rendering method, including: S1, acquiring two-dimensional die-cutting line data of the packaging box and performing triangular facet subdivision to generate a basic three-dimensional mesh model, wherein the two-dimensional die-cutting line data carries preset information of each process layer, and each process layer includes at least a hot stamping process layer and an anti-counterfeiting hollow pattern.

[0029] Specifically, the system receives and parses the design file to obtain the 2D die-cutting line data of the packaging box. This 2D die-cutting line data essentially represents the geometric structure of the unfolded plane of the packaging box, covering the boundary contour coordinates, crease segments, and geometric boundaries of the hollowed-out areas, and carrying preset information on various process layers. Each process layer includes at least a hot stamping process layer and an anti-counterfeiting hollowed-out pattern. After extracting the vertex coordinate set and the line segment connection relationship, the 2D die-cutting line data is input into a mesh generation algorithm for triangular facet subdivision. Triangular facet subdivision here refers to dividing the polygonal region into non-overlapping triangular units based on the empty circumcircle rule, while forcibly using the line segments in the 2D die-cutting line data as common edges of the triangles to preserve physical boundary features. In the actual subdivision operation, the system constructs triangles based on vertex coordinates and verifies whether there are other vertices within the circumcircle. The equation for constructing the circumcircle of the triangle satisfies:

[0030]

[0031] In the formula, and The x and y coordinates of any vertex of the triangle. and The x and y coordinates representing the center of the circumcircle. This represents the radius of the circumcircle.

[0032] To ensure the quality and topological rationality of the mesh generation, the distances from the remaining vertices to the center of the circle need to be calculated. The corresponding calculation formula is expressed as follows:

[0033]

[0034] In the formula, This represents the length of the straight line from the target vertex to the center of the circle. and The x and y coordinates represent the target vertex.

[0035] When there are no constraint edges between the target vertex and the current triangle, the line length must be greater than or equal to the radius of the circumcircle. After completing the triangular meshing of the entire region, the basic 3D mesh model can be generated. The basic 3D mesh model is a digital structure with a 3D spatial coordinate system and topological connectivity. Its generation process requires extending the vertex coordinates in the 2D plane to 3D space and assigning initial depth coordinate values. The conversion formula for 3D vertex coordinates is set as follows:

[0036]

[0037] In the formula, Represents the vertex position vector in three-dimensional space. , and These represent unit vectors in each orthogonal direction in a three-dimensional Cartesian coordinate system. and Two-dimensional plane coordinates representing vertices, This represents the depth coordinate. Considering the physical state of the initial plane, the depth coordinate is set to 0. The basic 3D mesh model processed as described above retains the geometric features of the 2D die-cutting line data, thus providing a basic topological framework for subsequent physical parameter binding and spatial deformation calculation.

[0038] For example, the design file of a specific cosmetic packaging box is extracted, and the 2D die-cutting line data of the packaging box is obtained through parsing. This 2D die-cutting line data includes the coordinates of the outer contour line and the coordinates of the inner crease line. This 2D die-cutting line data is input into a mesh generation algorithm for triangular mesh generation. During the generation process, vertices with coordinates of 50 mm x-coordinate and 20 mm y-coordinate, 60 mm x-coordinate and 20 mm y-coordinate, and 55 mm x-coordinate and 30 mm y-coordinate are selected to construct triangles. According to the circumcircle equation, the center of the circle has an x-coordinate of 55 mm and a y-coordinate of 22.5 mm, corresponding to a circumcircle radius of 6.12 mm. Then, a target vertex with an x-coordinate of 55 mm and a y-coordinate of 15 mm is selected, and the straight line length from this target vertex to the center of the circle is calculated to be 7.5 mm. Since this straight line length is greater than the circumcircle radius, the triangle satisfies the empty circumcircle rule, and the system retains this triangular element accordingly. After triangulation of all regions, a basic 3D mesh model is generated. The 2D coordinates (50 mm x-coordinate and 20 mm y-coordinate) are extended to 3D space, and the depth coordinate is set to 0, resulting in vertex position vectors in 3D space. This basic 3D mesh model accurately reflects the geometric boundaries of the 2D die-cutting line data, directly verifying the effectiveness of the triangulation and coordinate transformation settings.

[0039] S2. Extract the physical parameters of the substrate corresponding to the basic 3D mesh model and perform feature binding to generate an attribute-bound 3D model carrying the underlying physical attribute matrix.

[0040] In a specific embodiment of the present invention, the physical parameters of the substrate corresponding to the basic three-dimensional mesh model are extracted and feature-bound to generate an attribute-bound three-dimensional model carrying the underlying physical attribute matrix, including: obtaining the material type information of the substrate used in the manufacturing of the packaging box and performing parameter retrieval to generate substrate thickness parameters and substrate hardness parameters.

[0041] Obtain material type information and deformation test data under heating conditions, perform linear fitting, and generate thermal shrinkage coefficient.

[0042] Obtain surface texture scan images containing material type information and extract roughness to generate surface roughness parameters.

[0043] The substrate thickness parameter, substrate hardness parameter, thermal shrinkage coefficient and surface roughness parameter are matrixed together to generate the underlying physical property matrix.

[0044] The underlying physical property matrix is ​​associated and bound to the vertex coordinates of the basic 3D mesh model to generate an attribute-bound 3D model carrying the underlying physical property matrix.

[0045] Specifically, the system extracts the physical parameters of the substrate corresponding to the basic 3D mesh model and performs feature binding. The physical parameters of the substrate encompass quantitative indicators of the material in terms of mechanics, thermal properties, and surface morphology. The system receives material type information of the substrate used in packaging box manufacturing, which represents the physical material classification identifier used to produce the packaging box. Based on this material type information, parameters are retrieved from a pre-built material property database to extract the substrate thickness and hardness parameters. The substrate thickness parameter reflects the normal geometric dimensions of the material in its natural state, and the substrate hardness parameter characterizes the material's physical ability to resist elastic deformation, typically quantified using Young's modulus. Simultaneously, the system acquires deformation test data of the material type under heating conditions. The deformation test data is based on dimensional changes of the material under different temperature gradients obtained from multiple batches of industrial constant temperature chamber tests. These deformation test data undergo linear fitting to establish a linear mapping relationship between temperature change and dimensional change rate, thereby generating the thermal shrinkage coefficient. The thermal shrinkage coefficient characterizes the relative shrinkage of the material per unit temperature increase, and its calculation formula is expressed as:

[0046]

[0047] In the formula, Represents the coefficient of thermal shrinkage. The initial length of the material at the initial temperature is the measured value. The measured length of the representative material at the heating temperature. Represents the initial temperature. This represents the heating temperature.

[0048] The system further acquires surface texture scan images containing material type information. These surface texture scan images are grayscale matrices of the microscopic undulations on the material surface, acquired using a high-precision optical profilometer. Roughness is extracted from these surface texture scan images by calculating the arithmetic mean of the height deviation of each pixel from the reference surface, generating surface roughness parameters. The formula for calculating the surface roughness parameters is set as follows:

[0049]

[0050] In the formula, Represents surface roughness parameters. This represents the total number of pixels in the surface texture scan image. Representing the The microscopic height value corresponding to a pixel. This represents the average microscopic height value of all pixels.

[0051] After acquiring the parameters, the system performs matrix concatenation of the substrate thickness, substrate hardness, coefficient of thermal shrinkage, and surface roughness parameters, combining them into a multi-dimensional column vector according to a fixed dimensional order to generate the underlying physical property matrix. The formula for constructing the underlying physical property matrix is ​​as follows:

[0052]

[0053] In the formula, Represents the underlying physical property matrix. Represents the substrate thickness parameter. Represents the hardness parameter of the substrate, superscript This represents the matrix transpose operation.

[0054] The system associates and binds the underlying physical attribute matrix with the vertex coordinates of the basic 3D mesh model. This association and binding process is achieved by extending the vertex data structure, writing the physical attributes as additional vectors into the attribute list of each vertex, generating an attribute-bound 3D model carrying the underlying physical attribute matrix. The bound vertex data structure is expressed as follows:

[0055]

[0056] In the formula, This represents the comprehensive attribute vector of the target vertex in the attribute-bound 3D model, carrying the underlying physical attribute matrix. The three-dimensional space vertex position vectors representing the basic three-dimensional mesh model. The concatenation operator represents the data dimension. In this way, the 3D model not only possesses a geometric topological structure, but also fully inherits the physical parameters of the substrate, providing underlying data support for subsequent thermodynamic and optical interferometry calculations.

[0057] For example, the system performs the operation of extracting the physical parameters of the substrate corresponding to the basic 3D mesh model and binding features. The system receives the material type information of the substrate used for packaging box manufacturing, which is set to a specific type of coated white cardboard. Based on the material type information, the system performs parameter retrieval in the material property database, generating a substrate thickness parameter of 0.35 mm and a substrate hardness parameter of 2.5 GPa. The system obtains the deformation test data of the material type information under heating conditions, setting the initial temperature to 25 degrees Celsius, the heating temperature to 125 degrees Celsius, the initial material length test value to 100.00 mm, and the heated length test value to 99.85 mm. The thermal shrinkage coefficient is calculated to be 0.000015 per degree Celsius according to the linear fitting formula. The system obtains the surface texture scan image of the material type information, setting the total number of pixels in the image to 10000. After roughness extraction calculation, the sum of the absolute values ​​of the deviation of the micro height value of each pixel from the average micro height value is 12000 micrometers, and the surface roughness parameter is calculated to be 1.2 micrometers. The system performs matrix concatenation of the following parameters: substrate thickness of 0.35 mm, substrate hardness of 2.5 GPa, coefficient of thermal shrinkage of 0.000015 per degree Celsius, and surface roughness of 1.2 μm, to generate a bottom-level physical property matrix. This matrix is ​​then linked to the coordinates of vertices in the basic 3D mesh model with an x-coordinate of 50 mm, a y-coordinate of 20 mm, and a depth of 0. The physical property vectors are appended to the spatial coordinate vectors to generate a property-bound 3D model carrying the bottom-level physical property matrix. The above data directly validates the effectiveness of parameter retrieval, deformation fitting, and feature binding settings.

[0058] S3. Construct a multi-layer material rendering channel for the attribute-bound 3D model and perform optical interference calculations in conjunction with the underlying physical property matrix to generate an anti-counterfeiting visual feature model.

[0059] In a specific embodiment of the present invention, a multi-layer material rendering channel for attribute-bound three-dimensional models is constructed and optical interference calculation is performed in combination with the underlying physical property matrix to generate an anti-counterfeiting visual feature model, including: constructing an anti-counterfeiting hollowed-out mesh layer and a laser grating material layer in three-dimensional space and aligning them with the spatial coordinate system to generate a multi-layer material rendering channel.

[0060] Obtain the viewpoint vector and light source vector of the multi-layer material rendering channel in the current 3D scene, and generate optical vector parameters.

[0061] The diffraction distribution data of light penetrating the aperture of the anti-counterfeiting perforated mesh layer is calculated using optical vector parameters to generate light diffraction effect characteristics.

[0062] In a specific embodiment of the present invention, optical vector parameters are used to calculate the diffraction distribution data of light penetrating the aperture of the anti-counterfeiting perforated mesh layer, and light diffraction effect characteristics are generated, including: obtaining aperture size data and aperture distribution density data of the anti-counterfeiting perforated mesh layer, and generating perforation geometric parameters.

[0063] The light source vector in the optical vector parameters is decomposed into monochromatic light components of different wavelengths to generate a spectral energy distribution matrix.

[0064] By combining the hollowed-out geometric parameters and the spectral energy distribution matrix, the phase difference and amplitude attenuation of monochromatic light passing through the micro-aperture are calculated, and diffraction interference fringe data are generated.

[0065] Spatial integration is performed on the diffraction interference fringe data along the viewpoint vector direction to generate diffraction distribution data.

[0066] The diffraction distribution data is converted into pixel brightness values ​​in the red-green-blue color space to generate light diffraction effect features.

[0067] Specifically, the system performs physical optical interference and color space mapping calculations when light penetrates the micro-aperture. The system uses optical vector parameters to calculate the diffraction distribution data of light penetrating the anti-counterfeiting perforated mesh layer aperture, generating light diffraction effect characteristics. This process specifically includes acquiring the aperture size data and aperture distribution density data of the anti-counterfeiting perforated mesh layer. The aperture size data represents the physical diameter of a single light-transmitting hole, and the aperture distribution density data represents the number of holes per unit area; these data are obtained based on measurements using a high-precision optical microscope. The aperture size data and aperture distribution density data are combined to generate perforated geometric parameters. The system decomposes the light source vector in the optical vector parameters into monochromatic light components of different wavelengths, generating a spectral energy distribution matrix. The spectral energy distribution matrix records the initial amplitude values ​​corresponding to each discrete wavelength of the incident light in the visible light band. Combining the perforated geometric parameters and the spectral energy distribution matrix, the phase difference and amplitude attenuation of monochromatic light passing through the micro-aperture are calculated. The phase difference characterizes the degree of peak misalignment when the light wave reaches the observation point at different positions through the aperture; its calculation formula is:

[0068]

[0069] In the formula, Represents phase difference, The wavelength representing the monochromatic light component. Represents aperture size data, This represents the angle between the viewpoint vector and the light source vector.

[0070] Amplitude attenuation characterizes the degree of energy reduction after light wave diffraction, and its calculation formula is as follows:

[0071]

[0072] In the formula, Represents the amplitude attenuation. This represents the initial amplitude value corresponding to the wavelength in the spectral energy distribution matrix.

[0073] The light intensity distribution is calculated based on the amplitude attenuation, and diffraction interference fringe data is generated. The formula for calculating the diffraction interference fringe data is:

[0074]

[0075] In the formula, Represents diffraction interference fringe data, This represents the pore size distribution density data.

[0076] The system performs spatial integration calculations on the diffraction interference fringe data along the viewpoint vector direction. Spatial integration calculation involves summing all diffracted light intensities within the solid angle range of the viewpoint to generate diffraction distribution data. The formula for calculating the diffraction distribution data is:

[0077]

[0078] In the formula, Represents diffraction distribution data, This represents the solid angle integral domain corresponding to the viewpoint vector. This represents the angle between the viewpoint vector and the mesh normal. Represents a tiny solid angle element.

[0079] The system converts diffraction distribution data into pixel brightness values ​​in the red-green-blue color space. The conversion process is achieved by multiplying the diffraction distribution data with a standard color matching function and integrating over the wavelength, generating light diffraction effect characteristics.

[0080] In one specific embodiment of the present invention, the conversion process adopts the CIE1931 standard colorimetric system, and performs integral calculations on the diffraction distribution data with the three primary color matching functions of the standard observer in the visible light band to obtain the tristimulus values ​​of the XYZ color space; then, using a preset sRGB color space linear transformation matrix, the tristimulus values ​​are mapped to values ​​of the red, green and blue channels in the range of 0 to 255, thereby generating pixel brightness values ​​of the red, green and blue color space that can be displayed by the graphics processor, that is, generating light diffraction effect characteristics.

[0081] The anisotropic reflection parameters of the laser grating material layer are extracted, and the interference superposition calculation is performed in combination with the characteristics of light diffraction effect to generate optical interference features.

[0082] Optical interference features are mapped to the surface texture of the attribute-bound 3D model for real-time rendering to generate an anti-counterfeiting visual feature model.

[0083] Specifically, the system constructs an anti-counterfeiting perforated mesh layer and a laser grating material layer in 3D space and aligns them in spatial coordinates. The anti-counterfeiting perforated mesh layer represents a geometric structure with tiny light-transmitting holes, while the laser grating material layer represents a physical material with periodic micro-grooves etched on its surface to generate structural colors. Spatial coordinate alignment refers to using translation and rotation transformation matrices to ensure that the normal vectors of the two layers completely coincide with the center coordinates, thereby generating a multi-layer material rendering channel. The multi-layer material rendering channel is a data transmission path in the graphics rendering pipeline used to independently process the optical properties of different materials. The system obtains the viewpoint vector and light source vector of the multi-layer material rendering channel in the current 3D scene. The viewpoint vector represents the direction in which the virtual camera observes the target surface, and the light source vector represents the direction in which virtual lighting rays illuminate the target surface. The viewpoint vector and light source vector are combined to generate optical vector parameters.

[0084] The system extracts the anisotropic reflection parameters of the laser grating material layer. These anisotropic reflection parameters characterize the physical property of the material's reflectivity changing systematically under different observation azimuth angles, and are obtained through field measurements using a multi-angle spectrophotometer. Interference superposition calculations are then performed, combining the characteristics of light diffraction effects, to generate optical interference features. The formula for interference superposition calculation is:

[0085]

[0086] In the formula, Represents optical interference characteristics. Represents the characteristics of light diffraction effect. This represents the anisotropic reflection parameter.

[0087] The system maps optical interference features to the surface texture of the attribute-bound 3D model for real-time rendering. Real-time rendering refers to using a graphics processor to overlay the calculated optical interference features as texture pixel color values ​​onto the model surface, generating an anti-counterfeiting visual feature model. The anti-counterfeiting visual feature model integrates underlying physical properties and complex optical effects, and can realistically reflect the anti-counterfeiting visual performance of the packaging box under specific lighting conditions.

[0088] For example, the system constructs an anti-counterfeiting hollowed-out mesh layer and a laser grating material layer in 3D space and aligns them in spatial coordinates to generate a multi-layer material rendering channel. The system obtains the viewpoint vector and light source vector of the multi-layer material rendering channel in the current 3D scene and generates optical vector parameters. The system obtains the aperture size data of the anti-counterfeiting hollowed-out mesh layer as 50 micrometers and the aperture distribution density data as 400 holes per square millimeter, and generates hollowed-out geometric parameters. The system decomposes the light source vector in the optical vector parameters into monochromatic light components of different wavelengths, extracts the red light component with a wavelength of 0.65 micrometers, and its corresponding initial amplitude value is 1.2 candela, generating a spectral energy distribution matrix. Combining the hollowed-out geometric parameters and the spectral energy distribution matrix, the angle between the viewpoint vector and the light source vector is set to 0.01 radians, and the phase difference of the monochromatic light passing through the small aperture is calculated to be 4.83 radians. Further calculation shows that the amplitude attenuation is 0.33 candela, and combined with the aperture distribution density data, diffraction interference fringe data with a value of 43.56 is generated. The system performs spatial integration calculations on the diffraction interference fringe data along the viewpoint vector direction, setting the angle between the viewpoint vector and the grid normal to 0.52 radians, generating diffraction distribution data with a value of 37.8. The system converts the diffraction distribution data into pixel brightness values ​​in the red-green-blue color space, generating a light diffraction effect feature with a red channel brightness value of 210. The system extracts the anisotropic reflection parameter of the laser grating material layer as 0.85, and performs interference superposition calculations combined with the light diffraction effect feature, generating an optical interference feature with a value of 178.5. The system maps the optical interference feature to the surface texture of the attribute-bound 3D model for real-time rendering, generating an anti-counterfeiting visual feature model. The above data directly verifies the effectiveness of the optical interference calculation and the setting of the diffraction distribution data.

[0089] S4. Extract the thermodynamic parameters from the underlying physical property matrix and perform vertex displacement calculation on the anti-counterfeiting visual feature model to generate a thermodynamic deformation rendering model containing physical indentation features.

[0090] In a specific embodiment of the present invention, thermodynamic parameters are extracted from the underlying physical property matrix and vertex displacement is calculated on the anti-counterfeiting visual feature model to generate a thermodynamic deformation rendering model containing physical indentation features, including: identifying the edge boundary area between the hot stamping process layer and the anti-counterfeiting hollow pattern on the surface of the anti-counterfeiting visual feature model, and generating a deformation target area.

[0091] Extract the thermal shrinkage coefficient and substrate hardness parameters from the underlying physical property matrix to generate thermodynamic parameters.

[0092] The deformation depth of the target area is calculated based on the hot stamping temperature data and thermodynamic parameters, and the axial vertex displacement of the target area is generated.

[0093] In a specific embodiment of the present invention, the stress deformation depth of the deformation target area is calculated based on hot stamping processing temperature data and thermodynamic parameters, and the target axial vertex displacement is generated, including: obtaining the rated operating temperature and heat transfer efficiency parameters of the hot stamping equipment, and generating hot stamping processing temperature data.

[0094] The thermal shrinkage deformation is generated by multiplying the hot stamping temperature data with the thermal shrinkage coefficient in the thermodynamic parameters.

[0095] The mechanical embossing pressure data of the hot stamping equipment is obtained and combined with the substrate hardness parameter in the thermodynamic parameters to perform elasticity calculations and generate mechanical embossing deformation.

[0096] The thermally induced shrinkage deformation and the mechanically imprinted deformation are nonlinearly superimposed to generate the stress deformation depth.

[0097] The depth of the stress-induced deformation is vector-mapped along the normal direction of the deformation target region to generate the target axial vertex displacement.

[0098] Specifically, the system performs physical and mechanical analytical calculations for the thermomechanical coupling effect in multi-process superposition. The system acquires the rated operating temperature and heat transfer efficiency parameters of the hot stamping equipment. The rated operating temperature represents the set output temperature of the hot stamping plate heating rod, and the heat transfer efficiency parameter represents the proportion of energy retained when heat is transferred from the hot stamping plate to the substrate surface. By multiplying the rated operating temperature and the heat transfer efficiency parameter and subtracting the initial ambient temperature, the effective temperature difference actually acting on the substrate is calculated, generating the hot stamping processing temperature data. The calculation formula is as follows:

[0099]

[0100] In the formula, This represents the temperature data for hot stamping. Represents the rated operating temperature. Represents the heat transfer efficiency parameter. This represents the initial ambient temperature.

[0101] The system multiplies the hot stamping temperature data with the coefficient of thermal shrinkage from the thermodynamic parameters, and incorporates the substrate thickness parameter to unify the spatial dimensions. It then calculates the thickness reduction of the material under heating conditions, generating the thermally induced shrinkage deformation. The calculation formula is as follows:

[0102]

[0103] In the formula, Represents thermally induced shrinkage deformation. Represents the coefficient of thermal shrinkage. This represents the substrate thickness parameter.

[0104] In a specific embodiment of the present invention, the coefficient of thermal shrinkage is... The typical value is set at 0.000015 per degree Celsius. The value is based on the physical characteristics of microfiber shrinkage and dehydration of real industrial substrates commonly used in packaging boxes under a specific temperature gradient. Specifically, it is calculated by linear fitting based on objective experimental data of 0.15 mm absolute shrinkage of a 100 mm test strip obtained by heating the paper base material in an industrial constant temperature chamber from the initial ambient temperature of 25°C to the hot stamping standard temperature of 125°C.

[0105] The system acquires the mechanical embossing pressure data of the hot stamping equipment. This pressure data represents the physical pressure applied to the substrate per unit area when the hot stamping plate is pressed down. Combined with the substrate hardness parameter from the thermodynamic parameters, elasticity calculations are performed. Based on Hooke's Law, the compression of the material under normal stress is derived, generating the mechanical embossing deformation. The calculation formula is as follows:

[0106]

[0107] In the formula, Represents mechanical embossing deformation. Represents mechanical embossing pressure data. This represents the hardness parameter of the substrate.

[0108] The system performs nonlinear superposition calculations of thermally induced shrinkage deformation and mechanically indented deformation. Considering the plastic yielding effect of the material under simultaneous high temperature and high pressure, a nonlinear coupling coefficient is introduced for correction, generating the stress-induced deformation depth. The calculation formula is as follows:

[0109]

[0110] In the formula, Represents the depth of deformation under stress. This represents the nonlinear coupling coefficient, which is set based on the experimental fitting of the material's elastoplastic constitutive model. Its dimension is the reciprocal of the length to ensure the consistency of the overall dimensions of the formula.

[0111] In a specific embodiment of the present invention, the nonlinear coupling coefficient The typical value is set at 100 per millimeter. The value is based on the real elastoplastic constitutive model of the substrate commonly used in packaging boxes when it is subjected to simultaneous alternating high temperature and high pressure in actual hot stamping processing. Specifically, when simple thermal shrinkage and mechanical physical imprinting occur simultaneously, the high temperature will cause the micro-fiber structure inside the substrate to soften thermally, thereby producing an unexpected plastic yield enhancement effect. Therefore, this coefficient fits the "extra collapse ratio caused by thermomechanical coupling softening" through experimental data. The specification details the specific value of this coefficient, the physical mechanism background, and the complete closed-loop calculation process of deriving the final stress deformation depth together with thermal deformation and mechanical deformation.

[0112] The system vector-maps the stress-induced deformation depth along the normal direction of the deformed target region. The normal direction represents an inward pointing direction perpendicular to the model surface. By converting the scalar depth into a three-dimensional spatial vector, the target axial vertex displacement is generated. The calculation formula is as follows:

[0113]

[0114] In the formula, This represents the displacement of the target's axial vertex. This represents the inward unit normal vector of the vertices in the target deformation region. This displacement can be directly passed to the vertex shader in the graphics rendering pipeline to perform a realistic physical collapse update of the geometric topology.

[0115] The vertex shader in the graphics rendering pipeline updates the coordinates of the mesh vertices in the deformed target region based on the target axial vertex displacement, generating physical indentation features.

[0116] By combining the bidirectional reflection distribution function, the light scattering parameters of the region containing physical indentation features are recalculated and the rendering is updated to generate a thermodynamic deformation rendering model containing physical indentation features.

[0117] Specifically, the system extracts thermodynamic parameters from the underlying physical property matrix and calculates vertex displacements for the anti-counterfeiting visual feature model. The system identifies the boundary areas between the hot stamping layer and the anti-counterfeiting perforated pattern on the surface of the anti-counterfeiting visual feature model. The hot stamping layer represents the metal foil material area attached to the model surface, and the boundary areas of the perforated edges represent the transition boundaries between physical holes and solid material. By analyzing the model's texture coordinates and material identification codes, the system locks the mesh vertices of these areas, generating the deformation target areas. The system extracts the thermal shrinkage coefficient and substrate hardness parameters from the underlying physical property matrix, combining these two indicators characterizing the material's deformation properties under thermo-mechanical coupling to generate thermodynamic parameters.

[0118] The system utilizes the vertex shader in the graphics rendering pipeline to update the coordinates of the mesh vertices in the deformable target region based on the target axial vertex displacement. The vertex shader, a programmable unit in the graphics processor responsible for handling vertex space transformations, adds the original vertex coordinates to the target axial vertex displacement, creating realistic physical indentations on the mesh surface, generating physical indentation features. The system then recalculates the light scattering parameters of the region containing the physical indentation features using a bidirectional reflectance distribution function. The bidirectional reflectance distribution function describes the light reflection and scattering distribution after changes in the surface's micro-geometry; changes in the roughness and normal distribution of the indentation region lead to an increase in diffuse reflection and a decrease in specular highlight intensity. The updated light scattering parameters are used for rendering updates, generating a thermodynamic deformation rendering model that includes the physical indentation features. This model accurately reproduces the physical deformation and optical response generated during multi-process stacking.

[0119] In a specific embodiment of the present invention, the bidirectional reflection distribution function adopts the Cook-Torrance model based on micro-surface theory, and the system extracts the surface roughness parameters from the underlying physical property matrix. The numerical values ​​are mapped to the micro-surface roughness coefficient values ​​in the model. At the same time, the new mesh normals after the indentation change due to the vertex coordinate update are input into the normal distribution function and geometric occlusion function in the model for joint solution.

[0120] For example, the system identifies the boundary area between the hot stamping process layer and the hollowed-out edge on the surface of the anti-counterfeiting visual feature model, locks the grid vertices with texture coordinates ranging from 0.4 to 0.6 horizontally and from 0.3 to 0.5 vertically, and generates the deformation target area. The system extracts the coefficient of thermal shrinkage of 0.000015 per degree Celsius and the substrate hardness parameter of 2.5 gigapascals from the underlying physical property matrix to generate thermodynamic parameters. The system obtains the rated operating temperature of the hot stamping equipment as 150 degrees Celsius, the heat transfer efficiency parameter as 0.8, sets the initial ambient temperature as 20 degrees Celsius, calculates the effective temperature difference of 100 degrees Celsius, and generates hot stamping processing temperature data. The system multiplies the 100-degree Celsius hot stamping processing temperature data by the coefficient of thermal shrinkage of 0.000015 per degree Celsius, and multiplies it by the substrate thickness parameter of 0.35 mm to calculate the thickness reduction of 0.000525 mm, generating the heat-induced shrinkage deformation. The system acquires the mechanical embossing pressure data of 10 MPa from the hot stamping equipment. Combined with the substrate hardness parameter of 2.5 GPa and the substrate thickness parameter of 0.35 mm, it performs elasticity calculations to obtain a compression amount of 0.0014 mm, generating the mechanical embossing deformation. The system performs nonlinear superposition calculations on the thermal shrinkage deformation and the mechanical embossing deformation, setting the nonlinear coupling coefficient to 100 per millimeter, to calculate a stress deformation depth of 0.0019985 mm. The system vector-maps this stress deformation depth along the normal direction of the deformation target area, generating the target axial vertex displacement. The system uses the vertex shader in the graphics rendering pipeline to update the coordinates of the mesh vertices in the deformation target area based on the target axial vertex displacement, causing the vertices to be concave inward by 0.0019985 mm, generating physical indentation features. The system combines the bidirectional reflection distribution function to recalculate the light scattering parameters of the area containing the physical indentation features and updates the rendering, generating a thermodynamic deformation rendering model containing the physical indentation features. The above data directly verifies the effectiveness of the deformation depth calculation and vertex coordinate update settings.

[0121] S5. Apply coordinate offset vectors to the thermodynamic deformation rendering model and perform three-dimensional Boolean operations for interference verification to generate the final three-dimensional model.

[0122] In a specific embodiment of the present invention, applying a coordinate offset vector to the thermodynamic deformation rendering model and performing three-dimensional Boolean operations for interference verification to generate a final three-dimensional model includes: obtaining the feed tolerance range of the actual production equipment in the multi-process overprinting process and generating random numbers to generate a coordinate offset vector.

[0123] The deep stripping transparent rendering technique is used to separate the process layers in the thermodynamic deformation rendering model and generate an independent set of process layers.

[0124] The coordinate offset vector is applied to the texture coordinates of the independent process layer set for a small offset process, generating the offset process layer.

[0125] Perform a 3D Boolean operation on the offset process layer to detect the spatial intersection of different process layer boundaries and generate interference detection results.

[0126] Adjust the process safety margin based on the interference detection results and update the topology of the thermodynamic deformation rendering model to generate the final 3D model.

[0127] Specifically, the system applies a coordinate offset vector to the thermodynamic deformation rendering model and performs 3D Boolean operations for interference verification. The system obtains the feed tolerance range of the actual production equipment during multi-process overprinting. This feed tolerance range represents the mechanical positioning error limits of the production equipment in the lateral and longitudinal directions when transferring the substrate; this data is based on the equipment's factory calibration parameters. Within this feed tolerance range, the system generates random numbers, extracts random lateral and longitudinal coordinate offsets conforming to a normal distribution, and generates a coordinate offset vector. The formula for calculating the coordinate offset vector is expressed as:

[0128]

[0129] In the formula, Represents the coordinate offset vector. and This represents the random horizontal and vertical coordinate offsets generated within the feed tolerance range. and Represents an orthogonal unit vector in a two-dimensional plane.

[0130] The system utilizes a depth-stripping transparent rendering technique to separate the various process layers in a thermodynamic deformation rendering model. This technique involves extracting the pixel and geometric information of different material layers on the model surface layer by layer, sequentially according to depth. This technique is used to separate the gold foil layer in the model. At the underlying implementation level, depth stripping involves performing multi-channel rendering in the graphics rendering pipeline. In the current rendering channel, a depth buffer is used to record and extract the depth and texture of the foremost layer. Upon entering the next rendering channel, a depth test is used to detect and remove the preceding primitive information with the recorded depth, exposing the next layer geometry, and so on. This technique separates the gold foil layer and the hollowed-out layer from the model, generating a set of independent process layers. The system applies a coordinate offset vector to the texture coordinates of the independent process layer set for micro-offset processing. Micro-offset processing involves adding the generated coordinate offset vector to the original texture coordinates to simulate the overprinting deviation in actual processing, generating the offset process layer. The formula for updating the texture coordinates is:

[0131]

[0132] In the formula, Represents the updated texture coordinates. Represents the original texture coordinates.

[0133] The system performs 3D Boolean operations on the offset process layers to detect the spatial intersection of different process layer boundaries. 3D Boolean operations refer to the mathematical process of performing intersection calculations on multiple 3D geometries to extract overlapping regions. Interference detection results are generated by performing volume integration on the intersection regions of adjacent layer geometries. The formula for calculating the interference detection results is:

[0134]

[0135] In the formula, Represents the cross volume in the interference detection results. and This represents the geometry of adjacent layers in the offset process layer. The intersection operator represents the set operator. , and It represents the spatial integral element in a three-dimensional rectangular coordinate system.

[0136] The system adjusts the process safety margin based on the interference detection results. The process safety margin represents the boundary buffer distance reserved to avoid layer overlap during physical processing. When the intersection volume is greater than zero, the system calculates the required expansion distance based on the cube root of the intersection volume, using the following adjustment formula:

[0137]

[0138] In the formula, This represents the adjusted process safety margin. This represents the initial process safety margin. The representative margin compensation coefficient is a dimensionless constant used to convert the cube root of the volume into linear distance compensation. Based on the adjusted process safety margin, the system expands the layer boundary outwards, updates the topology of the thermodynamic deformation rendering model, and generates the final 3D model. This final 3D model eliminates the physical interference risks that may arise from the superposition of multiple processes and possesses the reliability to directly guide actual production.

[0139] In a specific embodiment of the present invention, the margin compensation coefficient The typical value is set to 1.2, and its value is based on the engineering buffer amplification requirements that printing and packaging equipment must reserve to cope with dynamic cumulative errors in actual multi-process high-speed overprinting. Specifically, the cross volume of the process layer calculated by three-dimensional Boolean interference verification, after taking the cube root, only represents the basic one-dimensional overlap scale in a purely mathematical geometric sense, namely 0.2 mm. However, in the industrial manufacturing site, in order to effectively avoid the risk of extremely small physical collisions caused by dynamic factors such as equipment mechanical transmission clearance and substrate feed tolerance, an empirical safety amplification factor of 20% must be applied on the basis of the pure geometric clearance distance. This will reliably convert the distance generated after the dimensionality reduction of the theoretical volume into the final linear buffer margin. By clearly disclosing the typical value of this dimensionless constant, the underlying mapping mechanism of three-dimensional geometric dimensionality reduction combined with engineering safety margin, and detailed closed-loop mathematical calculation derivation in the specification, a reliable mapping relationship from virtual graphic Boolean detection to physical machine tool collision avoidance is established.

[0140] For example, the system obtains the feed tolerance range of the actual production equipment during multi-process overprinting, setting the mechanical positioning error limits for both the horizontal and vertical directions to ±0.2 mm. Within this feed tolerance range, the system generates random numbers, extracting a horizontal random coordinate offset of 0.15 mm and a vertical random coordinate offset of 0.1 mm, and combines this with orthogonal unit vectors of a two-dimensional plane to generate a coordinate offset vector. The system uses depth-peeling transparent rendering technology to separate the various process layers in the thermodynamic deformation rendering model, extracting the hot stamping layer and the cutout layer, generating an independent set of process layers. The system applies the coordinate offset vector to the texture coordinates of the independent process layer set for a small offset, updating the original texture coordinates of 50 mm horizontally and 20 mm vertically to 50.15 mm horizontally and 20.1 mm vertically, generating the offset process layer. The system performs a three-dimensional Boolean operation on the offset process layer to detect the spatial intersection state of different process layer boundaries, calculating the intersection volume of the hot stamping layer and the cutout layer geometry to be 0.008 cubic millimeters, generating an interference detection result. The system adjusts the process safety margin based on the interferometry detection results, setting the initial process safety margin to 0.5 mm and the margin compensation coefficient to 1.2, resulting in an adjusted process safety margin of 0.74 mm. Based on this 0.74 mm margin, the system updates the topology of the thermodynamic deformation rendering model, shifting the vertices of the boundary region outwards by a corresponding distance to generate the final 3D model. The above data directly verifies the effectiveness of the coordinate offset calculation and interferometry verification settings.

[0141] S6. Extract the three-dimensional spatial features of the finalized three-dimensional model and perform reverse mapping analysis to generate physical processing control quantities.

[0142] In a specific embodiment of the present invention, the three-dimensional spatial features of the finalized three-dimensional model are extracted and reverse-mapped to generate physical processing control quantities, including: parsing the boundary topology data of the anti-counterfeiting hollow pattern in the finalized three-dimensional model to generate three-dimensional curvature radius features.

[0143] Extract the mesh depth data corresponding to the physical indentation features in the final 3D model to generate axial depth features.

[0144] Extract the security overprint coordinate data of the final 3D model after the interference verification is passed, and generate security overprint coordinate features.

[0145] The three-dimensional curvature radius feature, axial depth feature, and security overlay coordinate feature are fused to generate a three-dimensional spatial feature.

[0146] The three-dimensional spatial features are input into a pre-constructed three-dimensional feature-to-physical processing mapping matrix for table lookup and linear interpolation calculations to generate physical processing control quantities.

[0147] Specifically, the system extracts the 3D spatial features of the finalized 3D model and performs reverse mapping analysis. The system analyzes the boundary topology data of the anti-counterfeiting perforated pattern in the finalized 3D model. The boundary topology data represents the spatial coordinate sequence and connectivity of the edges of the perforated pattern. By extracting the coordinates of adjacent edge vertices, the circumcircle radius of the spatial triangle they form is calculated, thus generating a 3D radius of curvature feature. This 3D radius of curvature feature characterizes the degree of curvature at the pattern edges and is used to guide the dynamic response of subsequent processing equipment. Its calculation formula is expressed as:

[0148]

[0149] In the formula, Represents the three-dimensional radius of curvature characteristic. , and This represents a spatial vector formed by connecting adjacent edge vertices in sequence. This represents the vector cross product operator.

[0150] The system extracts mesh depth data corresponding to the physical indentation features in the finalized 3D model. Mesh depth data represents the vertical distance of the model surface from the initial plane in the normal direction. By traversing all vertices within the indentation region, the system extracts the maximum deviation distance to generate the axial depth feature. The calculation formula is as follows:

[0151]

[0152] In the formula, Represents axial depth characteristics. The set of vertices representing the physical indentation features. Represents the depth coordinates of the vertices within the set. The reference depth coordinates represent the initial plane.

[0153] The system extracts the safety overprint coordinate data of the finalized 3D model after interference verification. The safety overprint coordinate data represents the absolute coordinates of the reference positioning points of each process layer determined after anti-interference adjustments in the two-dimensional plane. This coordinate data is directly extracted to generate safety overprint coordinate features. The system then fuses the 3D curvature radius features, axial depth features, and safety overprint coordinate features. Feature fusion refers to concatenating geometric features with different physical meanings into a comprehensive vector according to a fixed dimensional order to generate 3D spatial features. The concatenation formula is:

[0154]

[0155] In the formula, Represents three-dimensional spatial features. and The superscript represents the x and y coordinate components in the security overprint coordinate feature. This represents the transpose of a vector.

[0156] The system inputs 3D spatial features into a pre-constructed 3D feature-to-physical processing mapping matrix for lookup and linear interpolation calculations. The 3D feature-to-physical processing mapping matrix is ​​a multi-dimensional data table built based on historical production measurement data, recording the correspondence between discrete spatial feature nodes and target processing parameters. The system searches the matrix for the multiple nearest neighbors with the input 3D spatial features in Euclidean distance and performs linear interpolation using inverse distance weights to generate physical processing control quantities. These physical processing control quantities encompass specific values ​​such as pressure and temperature that guide equipment operation. The interpolation calculation formula is as follows:

[0157]

[0158] In the formula, Represents physical processing control quantities. This represents the total number of neighboring nodes selected in the mapping matrix. Representing the Preset processing parameters corresponding to the nodes Representing the The weight coefficients of nodes. The calculation of the weight coefficients depends on the distance in the feature space, and the formula is:

[0159]

[0160] In the formula, The three-dimensional spatial features representing the input and the first Euclidean distance between node feature vectors This represents the Euclidean distance between each neighboring node. Through the above inverse mapping analysis, the system transforms purely geometric features into physical processing control quantities that can directly drive hardware devices.

[0161] In a specific embodiment of the present invention, the first Node weight coefficient Typical values ​​for these values, dynamically calculated in the two-node interpolation example, are 0.6 and 0.4 respectively. These values ​​are strictly based on the inverse distance weighting interpolation allocation mechanism in computer spatial data processing. Specifically, this weight is not a fixed constant hard-coded by humans, but is determined in real-time by measuring the Euclidean distance between the current input three-dimensional spatial comprehensive features and the known empirical nodes in the feature mapping matrix established based on historical production measurements. In the multidimensional feature space, the closer the geometric distance between the current input feature and the historical known node (physical gauge length 2.0), the more similar the manufacturing conditions. According to the principle of "distance inverse normalization," the mature processing parameters corresponding to this historical node are assigned a larger weight to the final output control quantity, i.e., a base weight of 0.6, while nodes at a slightly greater distance of 3.0 are assigned 0.4.

[0162] For example, the system parses the boundary topology data of the anti-counterfeiting hollow pattern in the final 3D model, extracts adjacent edge vertices, and calculates the lengths of three spatial vectors to be 2.0 mm, 2.0 mm, and 2.828 mm, respectively. The modulus of the vector cross product is 4.0 square millimeters. Substituting these values ​​into the formula, a 3D radius of curvature feature with a value of 1.414 mm is generated. The system extracts the mesh depth data corresponding to the physical indentation features in the final 3D model. Traversing the vertex set, the system finds that the maximum depth coordinate is -0.0019985 mm, and the baseline depth coordinate is 0. An axial depth feature with a value of 0.0019985 mm is generated. The system extracts the security overprint coordinate data of the final 3D model after the interference verification passes, generating a security overprint coordinate feature with an abscissa of 50.15 mm and a ordinate of 20.1 mm. The system fuses features from a 3D radius of curvature of 1.414 mm, an axial depth of 0.0019985 mm, and a safety overlay coordinate feature of 50.15 mm x 20.1 mm y, concatenating them to generate a multi-dimensional column vector-based 3D spatial feature. This 3D spatial feature is then input into a pre-constructed 3D feature-to-physical processing mapping matrix for lookup and linear interpolation. Two neighboring nodes are found in the matrix; the Euclidean distance between the input feature and the first node is calculated to be 2.0, and the Euclidean distance with the second node is 3.0. Based on the inverse distance weighting formula, the weight coefficient for the first node is calculated to be 0.6, and the weight coefficient for the second node is 0.4. The preset processing parameter corresponding to the first node is extracted as a pressure of 10 MPa, and the preset processing parameter corresponding to the second node is extracted as a pressure of 15 MPa. Linear interpolation is then used to generate a physical processing control quantity containing a pressure of 12 MPa. The above data directly verifies the effectiveness of the feature fusion and interpolation calculation settings.

[0163] S7. Encapsulate the physical processing control quantities into control instructions and send them to the production equipment to execute the automated linkage control of the packaging box. The production equipment includes at least a packaging box die-cutting equipment and a hot stamping equipment.

[0164] In a specific embodiment of the present invention, the physical processing control quantity is encapsulated into a control command and sent to the production equipment to execute the automated linkage control of the packaging box. The production equipment includes at least a packaging box die-cutting equipment and a hot stamping equipment. The process includes: converting the physical processing control quantity into data according to the communication protocol format of the underlying programmable logic controller to generate a standard communication data packet.

[0165] Standard communication data packets are classified by instruction type to generate pressure control instructions, speed control instructions, and temperature control instructions.

[0166] The pressure control command, speed control command, and temperature control command are time-sequenced to generate a linkage control command sequence.

[0167] The linkage control command sequence is sent to the control interfaces of the packaging box die-cutting equipment and hot stamping equipment in the production equipment to write parameters and generate equipment operation status feedback signals.

[0168] Based on the feedback signals of the equipment's operating status, the cutting roller's downward pressure, dynamic feed speed, and hot stamping plate heating temperature are adjusted in real time to execute automated linkage control of the packaging box.

[0169] Specifically, the system converts physical processing control quantities according to the communication protocol format of the underlying programmable logic controller (PLC). The PLC's communication protocol format represents the byte arrangement standard used in industrial control systems to regulate data transmission structures and verification rules. Data conversion involves multiplying floating-point values ​​by a preset scaling factor and rounding to the nearest integer to adapt to the register width of the underlying hardware, generating standard communication data packets. The calculation formula for data conversion is expressed as follows:

[0170]

[0171] In the formula, Represents the dimensionless register integer value in a standard communication data packet. Represents physical processing control quantities. This represents the scaling factor specified in the communication protocol. Its dimension is the reciprocal of the physical unit corresponding to the physical processing control quantity, used to eliminate dimensions. This represents the floor operator.

[0172] By parsing the address code field in the data packet, specific register address blocks are pre-mapped to the pressure module, speed module, and heating component module. The system classifies standard communication data packets by instruction type, splitting the mixed data stream into independent functional modules, generating pressure control instructions, speed control instructions, and temperature control instructions. Pressure control instructions are used to set the output force of the mechanical imprinting mechanism, speed control instructions are used to set the substrate transmission rate, and temperature control instructions are used to set the target temperature of the heating component. The system then performs timing sequence arrangement for these instructions. Timing sequence arrangement refers to calculating the absolute time difference of intervention for each actuator based on the physical spatial distance of multi-process overprinting and the substrate transmission speed, and adding an execution timestamp to each instruction to generate a sequence of linked control instructions. The formula for calculating the execution timestamp is:

[0173]

[0174] In the formula, The timestamp representing the execution of the instruction. Represents the baseline startup time. This represents the physical spatial distance between the current actuator and the reference zero point. This represents the substrate transmission rate set by the speed control command.

[0175] The system sends a sequence of linkage control commands to the control interfaces of the packaging box die-cutting and hot stamping equipment in the production line for parameter writing. The control interfaces of these equipment are communication ports on the mainboard used to receive external digital signals. After the parameters are written, the internal sensors collect and transmit the current physical state of the actuators in real time, generating a feedback signal for the equipment's operating status. Based on this feedback signal, the system adjusts the cutting roller pressure, dynamic feed speed of the die-cutting equipment, and the hot stamping plate heating temperature of the hot stamping equipment in real time. This adjustment process uses a proportional-integral-derivative (PID) control algorithm to calculate the dynamic deviation between the target command value and the feedback signal, outputting a compensation amount to correct the equipment's operating status. The formula for calculating the compensation amount is:

[0176]

[0177] In the formula, Represents the amount of adjustment and compensation. This represents the dynamic deviation between the instruction setpoint and the device operating status feedback signal. Represents the dimensionless proportional gain coefficient. The integral gain coefficient, whose dimension is the reciprocal of time. The derivative gain coefficient, with time as its dimension, is used to continuously correct the hardware output state by adding the adjustment compensation amount to the initial control command, thus executing the automated linkage control of the packaging box. This automated linkage control ensures spatial alignment and compliance of physical parameters across multiple processes in a high-speed production environment.

[0178] In a specific embodiment of the present invention, the proportional gain coefficient Integral gain coefficient With differential gain coefficient The typical values ​​are precisely set to 1.5, 0.1 and 0.05, respectively. The values ​​are based on the classic PID (proportional-integral-derivative) dynamic response tuning rules used in the closed-loop automated linkage control of high-speed die-cutting and hot stamping equipment in the packaging manufacturing industry to maintain mechanical stability. Specifically, these industrial control parameters are not arbitrary constants, but are precisely allocated to control performance in response to the instantaneous fluctuations that are very likely to occur in the physical processing of the production site: the larger proportional coefficient (1.5) is responsible for providing strong instantaneous compensation force to quickly correct the current serious deviation, the small integral coefficient (0.1) is responsible for continuously accumulating historical errors to effectively compensate for long-term steady-state distortion caused by mechanical gaps or thermal drift, and the derivative coefficient (0.05) uses the rate of change of deviation to perform damping prediction, which is specifically used to suppress the mechanical overshoot and destructive oscillation that may be caused by the machine tool under high pressure.

[0179] For example, the system converts the physical processing control quantity containing 12 MPa pressure according to the communication protocol format of the underlying programmable logic controller. Setting the scaling factor specified by the communication protocol to 100 per MPa, a register integer value of 1200 is calculated, generating a standard communication data packet. The system classifies the standard communication data packet by instruction type, parses the address code to generate pressure control instructions, speed control instructions, and temperature control instructions. The system schedules these instructions in sequence, setting the baseline start time to 0 seconds, the physical spatial distance between the current actuator and the baseline zero point to 2.0 meters, and the substrate transmission rate set for the speed control instruction to 0.5 meters per second, calculating the execution timestamp to 4.0 seconds, generating a linkage control instruction sequence. The system sends the linkage control instruction sequence to the control interface of the packaging box die-cutting equipment for parameter writing. The internal sensors of the equipment report the current actual pressure as 11.8 MPa, generating a equipment operating status feedback signal. The system calculates a dynamic deviation of 0.2 MPa based on the equipment's operating status feedback signal. It sets the dimensionless proportional gain coefficient to 1.5, the integral gain coefficient (divisor of time) to 0.1, and the derivative gain coefficient (divisor of time) to 0.05. Using a proportional-integral-derivative (PID) control algorithm, it calculates an adjustment compensation of 0.3 MPa. This compensation is then added to the initial control command to adjust the cutting roller's downward pressure, dynamic feed speed, and hot stamping plate heating temperature in real time, executing automated linkage control of the packaging box. The above data directly verifies the effectiveness of the data conversion and timing arrangement settings.

[0180] Reference Figure 2 The second aspect of the present invention provides a packaging box modeling and rendering system, including: a basic three-dimensional mesh model generation module, an attribute-bound three-dimensional model generation module, an anti-counterfeiting visual feature model generation module, a thermodynamic deformation rendering model generation module, a finalized three-dimensional model generation module, a physical processing control quantity generation module, and an automated linkage control execution module.

[0181] The basic 3D mesh model generation module is connected to the attribute-bound 3D model generation module. The attribute-bound 3D model generation module is connected to the anti-counterfeiting visual feature model generation module. The anti-counterfeiting visual feature model generation module is connected to the thermodynamic deformation rendering model generation module. The thermodynamic deformation rendering model generation module is connected to the final draft 3D model generation module. The final draft 3D model generation module is connected to the physical processing control quantity generation module. The physical processing control quantity generation module is connected to the automated linkage control execution module.

[0182] The basic 3D mesh model generation module acquires the 2D die-cutting line data of the packaging box and performs triangular facet subdivision to generate a basic 3D mesh model. The 2D die-cutting line data carries preset information on each process layer, and each process layer includes at least a hot stamping process layer and an anti-counterfeiting hollow pattern.

[0183] The attribute-bound 3D model generation module extracts the physical parameters of the substrate corresponding to the basic 3D mesh model and performs feature binding to generate an attribute-bound 3D model carrying the underlying physical attribute matrix.

[0184] The anti-counterfeiting visual feature model generation module constructs a multi-layer material rendering channel for attribute-bound 3D models and performs optical interference calculations in conjunction with the underlying physical property matrix to generate an anti-counterfeiting visual feature model.

[0185] The thermodynamic deformation rendering model generation module extracts thermodynamic parameters from the underlying physical property matrix and performs vertex displacement calculation on the anti-counterfeiting visual feature model to generate a thermodynamic deformation rendering model containing physical indentation features.

[0186] The final 3D model generation module applies a coordinate offset vector to the thermodynamic deformation rendering model and performs 3D Boolean operations for interference verification to generate the final 3D model.

[0187] The physical processing control quantity generation module extracts the three-dimensional spatial features of the finalized three-dimensional model and performs reverse mapping analysis to generate physical processing control quantities.

[0188] The automated linkage control execution module encapsulates the physical processing control quantities into control commands and sends them to the production equipment to execute the automated linkage control of the packaging box. The production equipment includes at least a packaging box die-cutting equipment and a hot stamping equipment.

[0189] Each of the modules can be implemented in whole or in part through software, hardware, or a combination thereof. It supports hardware embedded in or independent of the processor in the computer device, and also supports software stored in the memory of the computer device, so that the processor can call and execute the operations corresponding to each of the above modules.

[0190] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for modeling and rendering packaging boxes, characterized in that, include: S1. Obtain the two-dimensional die-cutting line data of the packaging box and perform triangular facet subdivision to generate a basic three-dimensional mesh model. The two-dimensional die-cutting line data carries the preset information of each process layer. Each process layer includes at least a hot stamping process layer and an anti-counterfeiting hollow pattern. S2. Extract the physical parameters of the substrate corresponding to the basic 3D mesh model and perform feature binding to generate an attribute-bound 3D model carrying the underlying physical attribute matrix; S3. Construct a multi-layer material rendering channel for the attribute-bound 3D model and perform optical interference calculations in conjunction with the underlying physical property matrix to generate an anti-counterfeiting visual feature model. S4. Extract the thermodynamic parameters from the underlying physical property matrix and perform vertex displacement calculation on the anti-counterfeiting visual feature model to generate a thermodynamic deformation rendering model containing physical indentation features. S5. Apply a coordinate offset vector to the thermodynamic deformation rendering model and perform three-dimensional Boolean operations for interference verification to generate the final three-dimensional model; S6. Extract the three-dimensional spatial features of the finalized three-dimensional model and perform reverse mapping analysis to generate physical processing control quantities; S7. Encapsulate the physical processing control quantities into control instructions and send them to the production equipment to execute the automated linkage control of the packaging box. The production equipment includes at least a packaging box die-cutting equipment and a hot stamping equipment.

2. The packaging box modeling and rendering method according to claim 1, characterized in that, The process of extracting the physical parameters of the substrate corresponding to the basic 3D mesh model and performing feature binding to generate an attribute-bound 3D model carrying the underlying physical property matrix includes: Obtain material type information of the substrate used in packaging box manufacturing and perform parameter retrieval to generate substrate thickness parameters and substrate hardness parameters; Obtain material type information and deformation test data under heating conditions, perform linear fitting, and generate thermal shrinkage coefficient; Obtain surface texture scan images containing material type information and extract roughness to generate surface roughness parameters; The substrate thickness parameters, substrate hardness parameters, thermal shrinkage coefficient, and surface roughness parameters are matrix-stitched to generate the underlying physical property matrix. The underlying physical property matrix is ​​associated and bound to the vertex coordinates of the basic 3D mesh model to generate an attribute-bound 3D model carrying the underlying physical property matrix.

3. The packaging box modeling and rendering method according to claim 1, characterized in that, The process of constructing a multi-layered material rendering channel for the attribute-bound 3D model and performing optical interference calculations in conjunction with the underlying physical property matrix to generate an anti-counterfeiting visual feature model includes: In three-dimensional space, an anti-counterfeiting hollowed-out mesh layer and a laser grating material layer are constructed and aligned with the spatial coordinate system to generate a multi-layer material rendering channel. Obtain the viewpoint vector and light source vector of the multi-layer material rendering channel in the current 3D scene, and generate optical vector parameters; The diffraction distribution data of light penetrating the aperture of the anti-counterfeiting hollowed-out mesh layer is calculated using optical vector parameters to generate light diffraction effect characteristics; The anisotropic reflection parameters of the laser grating material layer are extracted, and the interference superposition calculation is performed in combination with the characteristics of light diffraction effect to generate optical interference features; Optical interference features are mapped to the surface texture of the attribute-bound 3D model for real-time rendering to generate an anti-counterfeiting visual feature model.

4. The packaging box modeling and rendering method according to claim 1, characterized in that, The process of extracting thermodynamic parameters from the underlying physical property matrix and calculating vertex displacement of the anti-counterfeiting visual feature model to generate a thermodynamic deformation rendering model containing physical indentation features includes: Identify the boundary area between the hot stamping process layer and the anti-counterfeiting hollow pattern on the surface of the anti-counterfeiting visual feature model, and generate the deformation target area. Extract the thermal shrinkage coefficient and substrate hardness parameter from the underlying physical property matrix to generate thermodynamic parameters; Calculate the stress deformation depth of the target area based on hot stamping temperature data and thermodynamic parameters, and generate the target axial vertex displacement. The vertex shader in the graphics rendering pipeline is used to update the coordinates of the mesh vertices in the deformed target region according to the target axial vertex displacement, thereby generating physical indentation features. By combining the bidirectional reflection distribution function, the light scattering parameters of the region containing physical indentation features are recalculated and the rendering is updated to generate a thermodynamic deformation rendering model containing physical indentation features.

5. The packaging box modeling and rendering method according to claim 1, characterized in that, The process of applying a coordinate offset vector to the thermodynamic deformation rendering model and performing three-dimensional Boolean operations for interference verification to generate the final three-dimensional model includes: Obtain the actual feed tolerance range of the production equipment in the multi-process overprinting process and generate random numbers to generate a coordinate offset vector; The deep stripping transparent rendering technique is used to separate the process layers in the thermodynamic deformation rendering model and generate an independent set of process layers. The coordinate offset vector is applied to the texture coordinates of the independent process layer set for a small offset process, generating the offset process layer; Perform a 3D Boolean operation on the offset process layer to detect the spatial intersection of different process layer boundaries and generate interference detection results; Adjust the process safety margin based on the interference detection results and update the topology of the thermodynamic deformation rendering model to generate the final 3D model.

6. The packaging box modeling and rendering method according to claim 1, characterized in that, The process of extracting the three-dimensional spatial features of the finalized three-dimensional model and performing inverse mapping analysis to generate physical processing control quantities includes: Analyze the boundary topology data of the anti-counterfeiting hollow pattern in the final 3D model to generate 3D curvature radius features; Extract the mesh depth data corresponding to the physical indentation features in the final 3D model to generate axial depth features; Extract the security overprint coordinate data of the final 3D model after the interference verification is passed, and generate security overprint coordinate features; The three-dimensional curvature radius feature, axial depth feature, and safety overlay coordinate feature are fused to generate a three-dimensional spatial feature. The three-dimensional spatial features are input into a pre-constructed three-dimensional feature-to-physical processing mapping matrix for table lookup and linear interpolation calculations to generate physical processing control quantities.

7. The packaging box modeling and rendering method according to claim 1, characterized in that, The process of encapsulating physical processing control quantities into control commands and issuing them to production equipment to execute automated linkage control of the packaging boxes, wherein the production equipment includes at least packaging box die-cutting equipment and hot stamping equipment, including: The physical processing control quantities are converted into standard communication data packets according to the communication protocol format of the underlying programmable logic controller. Standard communication data packets are classified by instruction type to generate pressure control instructions, speed control instructions, and temperature control instructions. The pressure control command, speed control command, and temperature control command are time-sequenced to generate a linkage control command sequence. The linkage control command sequence is sent to the control interface of the packaging box die-cutting equipment and hot stamping equipment in the production equipment to write parameters and generate equipment operation status feedback signals. Based on the feedback signals of the equipment's operating status, the cutting roller's downward pressure, dynamic feed speed, and hot stamping plate heating temperature are adjusted in real time to execute automated linkage control of the packaging box.

8. The packaging box modeling and rendering method according to claim 3, characterized in that, The process of calculating the diffraction distribution data of light penetrating the aperture of the anti-counterfeiting perforated mesh layer using optical vector parameters to generate light diffraction effect characteristics includes: Obtain the aperture size data and aperture distribution density data of the anti-counterfeiting hollowed-out mesh layer, and generate the hollowed-out geometric parameters; The light source vector in the optical vector parameters is decomposed into monochromatic light components of different wavelengths to generate a spectral energy distribution matrix; By combining the hollowed-out geometric parameters and the spectral energy distribution matrix, the phase difference and amplitude attenuation of monochromatic light passing through the micro-aperture are calculated, and diffraction interference fringe data are generated. Spatial integration is performed on the diffraction interference fringe data along the viewpoint vector direction to generate diffraction distribution data; The diffraction distribution data is converted into pixel brightness values ​​in the red-green-blue color space to generate light diffraction effect features.

9. A packaging box modeling and rendering method according to claim 4, characterized in that, The step of calculating the stress deformation depth of the target deformation area based on hot stamping temperature data and thermodynamic parameters, and generating the target axial vertex displacement, includes: Obtain the rated operating temperature and heat transfer efficiency parameters of the hot stamping equipment, and generate hot stamping processing temperature data; The product of the hot stamping temperature data and the thermal shrinkage coefficient in the thermodynamic parameters is used to generate the thermal shrinkage deformation. The mechanical embossing pressure data of the hot stamping equipment is obtained and combined with the substrate hardness parameter in the thermodynamic parameters to perform elastic mechanical calculations and generate the mechanical embossing deformation. The thermally induced shrinkage deformation and the mechanically imprinted deformation are nonlinearly superimposed to generate the stress deformation depth. The depth of the stress-induced deformation is vector-mapped along the normal direction of the deformation target region to generate the target axial vertex displacement.

10. A packaging box modeling and rendering system, characterized in that, include: The basic 3D mesh model generation module acquires the 2D die-cutting line data of the packaging box and performs triangular facet subdivision to generate a basic 3D mesh model. The 2D die-cutting line data carries preset information on each process layer, and each process layer includes at least a hot stamping process layer and an anti-counterfeiting hollow pattern. The attribute-bound 3D model generation module extracts the physical parameters of the substrate corresponding to the basic 3D mesh model and performs feature binding to generate an attribute-bound 3D model carrying the underlying physical attribute matrix. The anti-counterfeiting visual feature model generation module constructs a multi-layer material rendering channel for attribute-bound 3D models and performs optical interference calculations in conjunction with the underlying physical property matrix to generate an anti-counterfeiting visual feature model. The thermodynamic deformation rendering model generation module extracts thermodynamic parameters from the underlying physical property matrix and performs vertex displacement calculation on the anti-counterfeiting visual feature model to generate a thermodynamic deformation rendering model containing physical indentation features. The final 3D model generation module applies a coordinate offset vector to the thermodynamic deformation rendering model and performs 3D Boolean operations for interference verification to generate the final 3D model. The physical processing control quantity generation module extracts the three-dimensional spatial features of the finalized three-dimensional model and performs reverse mapping analysis to generate physical processing control quantities. The automated linkage control execution module encapsulates the physical processing control quantities into control commands and sends them to the production equipment to execute the automated linkage control of the packaging box. The production equipment includes at least a packaging box die-cutting equipment and a hot stamping equipment.

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