Feature fusion ceramic product three-dimensional visual design method and system

Abstract

The invention belongs to the technical field of ceramic product visual design, and particularly discloses a feature fusion ceramic product three-dimensional visual design method and system. Line feature and surface feature parameters of successful cases in historical manufacturing records are used as multi-dimensional detail constraint conditions of current design; meanwhile, dynamic simulation verification is conducted on the constraint conditions, the constraint conditions which are successfully verified are screened out for design, it is ensured that the design scheme is not only based on verified actual process data, but also potential design defects can be recognized and eliminated in advance, and the design efficiency is improved. Therefore, the current product design can be designed based on actual comprehensive process data, the disjunction of design and manufacturing is greatly reduced, the reliability and success rate of the design scheme are improved, and the problems of repeated trial-manufacture and correction caused by neglecting the manufacturing process are effectively avoided.

Description

Technical Field

[0001] The present invention belongs to the technical field of ceramic product visualization design, and specifically discloses a feature-fused three-dimensional visualization design method and system for ceramic products. Background Art

[0002] Ceramic products are widely used in daily life and art due to their aesthetics, functionality, and cultural value. As consumers' demand for personalization and customization increases, ceramic design must achieve innovative integration of complex shapes and patterns while ensuring technological feasibility.

[0003] Computer-based 3D visualization design technology is currently widely used in ceramic design, aiming to improve design efficiency, accuracy, and user experience through digital means. For example, Chinese invention patent publication number CN114781146A proposes a computer-based 3D ceramic product design system. This system inputs basic ceramic information on a central server and uses computer simulation to design the type, pattern, and appearance of the ceramic, thereby generating a design solution that better meets user expectations. This method has the advantages of high automation, high design accuracy, simple operation, and wide applicability, significantly improving the overall efficiency of ceramic design.

[0004] However, this approach relies heavily on basic ceramic information for simulation design, failing to fully integrate manufacturing constraints. This results in a lack of necessary restrictions and specifications, leading to an overly open design. This design approach often requires multiple adjustments and revisions during actual trial production, inevitably increasing material waste and time costs.

[0005] For example, Chinese invention patent publication number CN114004054B proposes a 3D-assisted design and visualization system and method for ceramic products. This method decomposes the product connectivity graph into multiple subgraphs and applies geometric constraints to each of these subgraphs to establish corresponding geometric feature models. Next, the system extracts the product's shape and decorative features, and constructs a fusion model based on the geometric feature model to integrate these features. Combining the geometric feature model and the fusion model, the system creates a data model and displays the product in a 3D visualization.

[0006] Although this approach uses geometric constraints for 3D model design, its process constraints focus solely on the decomposition of the product's connectivity graph and are primarily limited to macro-geometric constraints. On the one hand, this approach fails to consider line and surface features, failing to capture surface details and resulting in poor adaptability of detailed design. On the other hand, it also fails to fully utilize the design constraints of similar historical ceramic products, depriving the design process of valuable historical experience and successful cases, potentially leading to repeated errors or missed optimization opportunities.

[0007] In summary, although existing 3D visualization design technology has greatly improved the efficiency and flexibility of ceramic design, process constraints are not considered or are not fully considered during the design stage, which can easily lead to repeated trials and revisions, affecting not only the product development cycle but also easily causing product quality problems. Summary of the Invention

[0008] To this end, one purpose of the embodiments of the present application is to provide a feature-fused three-dimensional visualization design method and system for ceramic products, which effectively solves the problems existing in the existing technology by introducing a historical data-driven multi-constraint fusion method in the ceramic design process.

[0009] The purpose of the present invention can be achieved by the following technical solutions: In the first aspect, the present invention proposes a feature-fused three-dimensional visualization design method for ceramic products, comprising the following steps: (1) selecting qualified finished products that match the current design requirements from the historical ceramic manufacturing records according to the error matching principle of preset vessel size and pattern alignment, and extracting line feature parameters and surface feature parameters from the manufacturing data of the qualified finished products as design constraints for the current product; (2) Construct a 3D virtual device profile baseline of the current product based on line feature constraints, and construct a surface model of the current product based on surface feature constraints. Apply dynamic load simulation to the 3D virtual device profile baseline and thermal expansion simulation to the surface model. The constraint effect is verified by combining the simulation results, and successful design constraint conditions are screened and verified. (3) Generate the effective device profile baseline and surface model of the current product through parametric modeling based on the successfully verified design constraints; (4) Based on the generated effective vessel outline baseline and surface model, a geometric continuity constraint algorithm is used to perform curvature gradient fusion on the vessel body, or a free deformation algorithm is used for unconstrained fusion; (5) Adaptively mesh the fused device model and generate visual metadata.

[0010] In the second aspect, the present invention proposes a feature-fused three-dimensional visualization design system for ceramic products, including the following modules: a design constraint determination module: used to screen line features and surface features of finished products that meet design requirements from historical ceramic manufacturing records as design constraints for the current product.

[0011] Constraint Verification Module: Contains a virtual modeling unit and a constraint screening unit, which are used to build a 3D verification model and screen valid constraint conditions respectively; Model building module: used to generate baseline and surface models based on valid constraints; Fusion design module: Integrates geometric constraint fusion unit and free fusion unit to support dual-mode fusion design of device body; Visualization module: used to mesh the fused device model and render mesh metadata.

[0012] Combining all the above technical solutions, the present invention has the following positive effects: 1. This invention utilizes the line and surface feature parameters of successful cases in historical manufacturing records as multi-dimensional detail constraints for the current design, enabling current product designs to be based on actual comprehensive process data. This significantly reduces the disconnect between design and manufacturing, improving the reliability and success rate of design solutions while effectively avoiding repeated trials and revisions caused by neglecting manufacturing processes. 2. While utilizing the line and surface feature parameters of successful cases in historical manufacturing records as multi-dimensional detailed constraints for the current design, this invention also dynamically simulates and verifies these constraints. By selecting only those constraints that have been successfully verified, the design is not only based on verified actual process data, but also enables the early identification and elimination of potential design flaws. This makes products designed based on these selected constraints more reliable and robust, capable of withstanding the challenges of actual production and use. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The present invention is further described with reference to the accompanying drawings. However, the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative effort.

[0014] Figure 1 This is a flow chart for implementing the method of Example 1 of the present invention.

[0015] Figure 2 This is a schematic diagram of the implementation of verification of the constraint effect of design constraint conditions under comprehensive simulation in the present invention.

[0016] Figure 3 This is a schematic diagram of the system module structure of Example 2 of the present invention. DETAILED DESCRIPTION

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0018] Example 1 See also Figure 1As shown, the present invention proposes a feature-fused three-dimensional visualization design method for ceramic products, which includes the following steps: (1) selecting qualified finished products that match the current design requirements from the historical ceramic manufacturing records according to the error matching principle of preset vessel size and pattern alignment, and extracting line feature parameters and surface feature parameters from the manufacturing data of the qualified finished products as design constraints for the current product.

[0019] As a preferred implementation of the above solution, the following process is used to screen qualified finished products that match the current design requirements: extract manufacturing raw materials and manufacturing process environment from the historical manufacturing records of ceramics, and screen out consistent historical manufacturing records based on the manufacturing raw materials and manufacturing process environment specified by the current product design and mark them as similar manufacturing records.

[0020] In one example, the manufacturing raw materials mentioned above refer to various materials and their properties used in the production process of ceramic products, including but not limited to the following: Basic materials: such as kaolin, quartz sand, feldspar and other main components.

[0021] Additives: such as plasticizers, reinforcing agents, colorants, etc., used to improve the processability of materials or impart specific properties.

[0022] Glaze: The composition of the surface covering that affects the product's appearance (e.g., gloss, color) and functionality (e.g., wear resistance, corrosion resistance).

[0023] In another example, the aforementioned manufacturing process environment encompasses the various conditions and parameters throughout the entire process, from raw material preparation to finished product. This primarily encompasses the following aspects: Molding process: The choice of methods, such as slip casting, dry pressing, and extrusion, and their process parameters (e.g., pressure, temperature, and time).

[0024] Drying process: the process of controlling the evaporation of moisture from the green body, involving the type of drying equipment (such as hot air drying, microwave drying), drying rate, humidity control, etc.

[0025] Firing process: This includes key parameters such as firing temperature, heating rate, holding time, and cooling rate. Different firing processes will affect the density, strength, and microstructure of the final product.

[0026] Post-processing process: such as polishing, grinding, decoration (printing, decals) and other steps and their corresponding process conditions.

[0027] By extracting manufacturing materials and manufacturing process environments from historical manufacturing records and screening out historical records that are consistent with the manufacturing materials and manufacturing process environments of the current product design, it can be ensured that the new design can be based on similar historical cases, providing solid actual data support for subsequent designs.

[0028] For each similar manufacturing record, the actual shape and size of the corresponding finished product and the pattern type data are extracted and compared with the shape and size of the current product design requirements, and the deviation value between the two is calculated.

[0029] The above-mentioned vessel dimensions include but are not limited to height, width, diameter, etc., and the pattern type data include but are not limited to pattern type, position, proportion, etc.

[0030] In the specific calculation of the above deviations, the size deviation of the device can be determined by calculating the difference between the historical actual values of height, width and diameter and the design target values.

[0031] The specific calculation of the pattern deviation is as follows: For the position of the pattern, the position deviation can be determined by calculating the Euclidean distance between the historical actual position coordinates and the designed position coordinates. For the proportion of the pattern, the proportion deviation can be determined by comparing the difference between the historical actual proportion and the designed proportion. For example, .

[0032] The above provides a quantitative criterion to evaluate the similarity between historical products and new designs, thus providing a basis for subsequent selection.

[0033] Under the guidance of the preset error matching principle of vessel size and pattern alignment, it is evaluated whether the vessel size deviation and pattern type deviation in each similar manufacturing record are within the acceptable range. Therefore, similar manufacturing records whose vessel size deviation and pattern type deviation meet the preset error matching standards are selected and defined as matching manufacturing records.

[0034] For example, the error matching principle for vessel size and pattern alignment is that the error of each vessel size parameter is controlled within ±2mm, the error of pattern position is controlled within ±1mm, and the error of pattern proportion is controlled within ±5%.

[0035] The preset error matching principle proposed in this invention ensures that the accuracy of the selected historical records on key parameters meets the required standards. This method not only improves the objectivity and accuracy of the screening process, but also ensures that the final selected design reference has high feasibility.

[0036] For all relevant finished products identified as matching manufacturing records, their associated finished product inspection records are reviewed, and the quality inspection results (such as strength, heat resistance, surface finish, etc.) of each finished product are extracted. Finished products whose quality inspection items meet the inspection standards are then identified as qualified finished products.

[0037] By reviewing the quality test results of finished products, we can ensure that the selected historical records represent successful cases. This method is directly linked to actual production results, reducing design risks and increasing the success rate of new products.

[0038] By utilizing historical data to screen qualified finished products, this method avoids all steps of designing from scratch and significantly shortens the design cycle. Furthermore, with reliable data support, trial and error times are reduced. Furthermore, by fully utilizing the company's accumulated internal data resources, knowledge can be effectively reused, reducing R&D costs.

[0039] The line feature parameters mentioned above mainly refer to the geometric features involving lines or edges in ceramic products. Specifically, they include but are not limited to the following: Contour line: The outer contour shape of the product, such as the boundaries of a circle, square, or other complex shapes.

[0040] Seam Line: The joining line between different parts or materials that ensures precise alignment when the parts are joined.

[0041] Decorative lines: lines used to decorate the surface of products, such as lines formed by processes such as engraving and embossing.

[0042] Axis of symmetry: The axis of symmetry in product design ensures the symmetry and balance of the design (such as the position and length of the contour baseline, etc.), and surface feature parameters (such as the curvature and smoothness of the surface, etc.).

[0043] Surface feature parameters mainly refer to various characteristics of the surface of ceramic products, including but not limited to the following: Surface curvature: Changes in the surface curvature of the product affect the product's aesthetics and functionality (such as anti-slip properties).

[0044] Surface texture: The texture type and distribution of the product surface, such as smooth, frosted, embossed, etc.

[0045] Surface flatness: The flatness of the product surface, ensuring there are no obvious bumps.

[0046] Glaze thickness: The thickness and uniformity of the surface glaze layer affect the gloss and durability of the product.

[0047] Line feature and surface feature parameters have a direct impact on the appearance and functionality of the product. If they are not used as design constraints during the design phase, the design scheme may be too divergent and lack an effective constraint mechanism, making it difficult to ensure the consistency, accuracy and manufacturability of the design.

[0048] See also Figure 2 As shown, (2) a three-dimensional virtual device contour baseline of the current product is constructed based on line feature constraints, and a surface model of the current product is constructed based on surface feature constraints. Dynamic load simulation is applied to the three-dimensional virtual device contour baseline, and thermal expansion simulation is applied to the surface model. The constraint effect is verified by combining the simulation results, and the successful design constraint conditions are screened and verified.

[0049] It should be added that the above-mentioned construction of the three-dimensional virtual device contour baseline can be achieved by using professional computer-aided design software to draw a preliminary three-dimensional contour baseline of the product based on the above-mentioned line feature constraints.

[0050] In the manner in which the above scheme can be implemented, applying a dynamic load to the three-dimensional virtual device profile baseline simulates the following implementation process: determining the physical properties of the material (such as elastic modulus, Poisson's ratio, etc.) based on the manufacturing raw materials specified by the current product design.

[0051] Define the support points of the device outline baseline based on the actual application scenarios of the ceramic product.

[0052] It's important to understand that defining the support points of the ceramic product's contour baseline is a crucial step in ensuring structural stability and functionality. The process of defining support points based on actual application scenarios typically involves the following: a. Functional Requirements Analysis: a1. Usage Environment: First, analyze the environmental conditions in which the ceramic product will be used, such as whether it needs to withstand external loads (such as pressure and tension) and whether it requires specific stability (to prevent tipping).

[0053] a2 Operation method: Consider how users interact with the product, such as the design of the handheld part, the choice of placement, etc.

[0054] b. Mechanical Analysis: b1 Stress Analysis: Mechanical analysis is used to determine the main stress distribution that the product may be subjected to during use. For example, for a vase, the bottom and center of gravity are usually the main stress points.

[0055] b2 Support point selection: Based on the results of the stress analysis, support points are set in key stress areas to ensure the structural stability and durability of the product. These support points can be physical contact points or structural reinforcement points.

[0056] c. Geometric feature analysis: c1 shape analysis: Analyze the geometric shape of the product, identify key parts that are prone to deformation or damage, and set support points in these parts to enhance their strength.

[0057] C2 Symmetry and balance: Ensure that the product has good symmetry and balance. Especially in asymmetrical designs, reasonable setting of support points helps maintain overall stability.

[0058] The determined material physical properties and defined support points are used to set the boundary conditions for the simulation.

[0059] The physical properties of these materials (such as elastic modulus, Poisson's ratio, and density) determine their response behavior under different stress conditions. Accurately inputting these properties allows the simulation model to more realistically reflect the material's actual performance, thereby improving simulation accuracy.

[0060] The aforementioned support points, as key structural connection points, determine the product's overall stability and load-bearing capacity. Properly placing support points effectively disperses stress and prevents damage caused by localized overload. In finite element analysis, support points define boundary conditions, specifically the location and type of fixed or constrained points. This directly impacts the reliability of simulation results, as different support point configurations lead to varying stress distributions and deformation patterns.

[0061] Therefore, by inputting accurate material physical properties and reasonable support point configuration, the simulation model can be closer to the actual working conditions and predict the performance of the product more accurately.

[0062] Select the load type (such as mechanical stress) according to the expected use of the product, and set different load levels and their simulation order for the load type.

[0063] For example, the load range can be determined by analyzing the product's expected usage environment and functional requirements. The load levels can be set to low, medium, and high, with low corresponding to the lower third of the load range; medium to the middle third; and high to the upper third. The simulation sequence should begin with low, progress to medium, and finally to high, to ensure that the product's performance under different stress conditions is gradually verified.

[0064] Under the set boundary conditions, finite element analysis software is used to apply dynamic loads to the support points of the three-dimensional virtual device contour baseline according to the preset load type and the simulation sequence of the corresponding load gear.

[0065] During the simulation process, the response data of the support points of the three-dimensional virtual device contour baseline under different load levels corresponding to the load type are output, including deformation, stress, and vibration data.

[0066] The response data of the above support points provides deep insights into the structural stability and durability of the product.

[0067] It should be added that the above-mentioned surface model can be constructed by using professional computer-aided design to construct a three-dimensional surface model of the product based on the above-mentioned surface feature constraints.

[0068] In another possible implementation of the above solution, thermal expansion simulation is applied to the surface model as follows: the temperature range and temperature gradient during simulation are set according to the actual application environment of the ceramic product, thereby generating a series of temperature nodes.

[0069] The above settings are intended to simulate all thermal environments that the product may experience during its life cycle.

[0070] In the example of the above embodiment, it is assumed that the simulated temperature range is 25°C to 1200°C.

[0071] To accurately capture the thermal expansion behavior of ceramic products at different temperature stages, it is necessary to set a reasonable temperature gradient. For example, if you choose 100°C as the temperature gradient, you will set a temperature node every time the temperature increases by 100°C.

[0072] Based on the above temperature range and temperature gradient, a series of temperature nodes are generated: 25℃, 125℃, 225℃, 325℃, 425℃, 525℃, 625℃, 725℃, 825℃, 925℃, 1025℃, 1125℃, and 1200℃.

[0073] The material physical properties of the ceramic product are input into the simulation software, and the thermal expansion simulation program is run at each temperature node.

[0074] The accurate material properties mentioned above are crucial to ensure the authenticity and reliability of simulation results.

[0075] During the simulation process, the deformation distribution diagram and stress distribution diagram of the surface model at different temperature nodes are output visually.

[0076] These plots provide intuitive visual feedback on how temperature changes affect the shape and structural integrity of the model.

[0077] In a further implementation of the above scheme, the constraint effect is verified by comprehensive simulation results, and the design constraint conditions that are successfully screened and verified are referred to the following process: the support point response data under different load levels in the online feature simulation of each qualified product selected from historical manufacturing are used to quantify the response fluctuations of adjacent support points to obtain the response fluctuation amounts of adjacent support points under different load levels.

[0078] In the specific example of the above operation, the response fluctuation quantification of adjacent support points can calculate the standard deviation of the response data of each pair of adjacent support points, then take the average of these standard deviations, and compare it with the overall mean of the response data of all support points to obtain the response variation coefficient as the response fluctuation amount.

[0079] In another example, the response fluctuation quantification of adjacent support points can calculate the response difference of each pair of adjacent support points, select the maximum response difference and the minimum response difference, and then subtract the maximum response difference from the minimum response difference and divide it by the maximum response difference to obtain the response fluctuation amount.

[0080] It should be understood that the response fluctuation can reflect the stability of the baseline support of the three-dimensional virtual device profile under the action of load. When the response fluctuation is larger, it indicates that the response change between the support points is more significant, which implies that the stability of the structure is worse.

[0081] The support point response data under different load levels in the online characteristic simulation of each qualified product is compared with the set limit response amount to quantify the response excess.

[0082] In the specific example of the above operation, the response excess quantification can compare the response data of each support point with the limited response amount to obtain the response excess difference, and then compare it with the limited response amount to obtain the response excess coefficient of each support point, and take the average of the response excess coefficients of all support points to obtain the overall response excess.

[0083] It's important to understand that the response exceedance reflects the extent to which the actual response value of each support point exceeds the preset limit response value. Specifically, it is a key indicator of whether the design operates within safety limits. A higher response exceedance indicates that more support points or larger response values exceed the set safety threshold, indicating a possible design flaw.

[0084] The load response defect is defined as the fusion value of the response fluctuation and the response excess. The load response defect at different load levels is calculated using the response fluctuation and response excess at different load levels.

[0085] As an example of the above operation, the geometric mean is used to fuse the response fluctuation and response excess, thereby emphasizing the synergistic effect between the two.

[0086] In another example, different weight coefficients are assigned to the response fluctuation amount and the response excess amount, and then the weight coefficients are added together to obtain the load response defect degree.

[0087] In practical applications, different fusion methods can be selected according to specific application scenarios and design requirements.

[0088] The present invention evaluates the support defects of the three-dimensional virtual device profile baseline under load by fusing the response fluctuation and the response excess, which comprehensively reflects the overall performance of the device profile baseline under specific load conditions.

[0089] Weights are assigned to different load levels, and the load response defects of different load levels are combined with the weights to obtain the overall load response defect of each qualified product under online characteristic simulation.

[0090] Specifically, the weight assignment for different load gears mentioned above can assign higher weights to higher load gears according to the level of the load gear. For example, assuming that the weight range is 0 to 1, the weights of low load gear, medium load gear, and high load gear can be 0.2, 0.3, and 0.5 respectively. The weight assignment is made in this way considering that in actual applications, the high load gear is usually closer to the product's extreme working conditions or extreme environments, and the product is more likely to malfunction or fail under these conditions. Therefore, the high load gear has a greater impact on product performance and safety, and thus the impact of the high load gear is often more significant in multi-level load assessments. Therefore, assigning a higher weight to the high load gear is consistent with engineering experience and practice.

[0091] In a further implementation of the above scheme, the deformation distribution map and stress distribution map of each qualified product selected from historical manufacturing at different temperature nodes in the surface feature simulation are marked with deformation distribution areas and stress concentration areas.

[0092] The deformation distribution area mentioned above refers to the distribution area of displacement or deformation on the product surface. The stress concentration area refers to the area on the product surface where local stress increases significantly.

[0093] As an example of the above solution, consider a ceramic vase design. Using surface features, we simulate deformation and stress distribution at different temperature nodes and mark key areas. For example, the deformation distribution area shows that at 25°C, the deformation of the entire vase is relatively uniform and small. However, at 600°C, the deformation at the bottom and neck of the vase increases significantly, with a significant concentrated deformation area forming at the bottom edge.

[0094] Stress Concentration Area Marking: At 25°C, the stress distribution is relatively uniform, with no obvious stress concentration areas. At 800°C, significant stress concentration is observed at the junction of the neck and body of the carafe. This area appears darkest on the stress distribution diagram, indicating the highest stress there.

[0095] The thermal expansion defect is defined as the fusion value of the deformation area ratio and the stress concentration area ratio. For each temperature node, the thermal expansion defect at that node is calculated based on the corresponding deformation distribution area ratio and stress concentration area ratio.

[0096] In an example of the above operation, the thermal expansion defect degree may be a weighted sum of the area ratio of the deformation region and the area ratio of the stress concentration region.

[0097] In another example, the thermal expansion defect degree may be a geometric mean of the area ratio of the deformation region and the area ratio of the stress concentration region.

[0098] Weights are assigned to different temperature nodes, and the thermal expansion defectivity of different temperature nodes is combined with the weights to obtain the overall thermal expansion defectivity of each qualified product under surface feature simulation.

[0099] The above-mentioned weight distribution of different temperature nodes can be similarly referred to the weight assignment of load gears.

[0100] In a further implementation of the above scheme, the overall load response defect and overall thermal expansion defect of each qualified product under online feature simulation and surface feature simulation are compared with the configured defect thresholds respectively. If the overall load response defect and overall thermal expansion defect of a qualified product under online feature simulation and surface feature simulation both meet the defect thresholds, the line feature parameters and surface feature parameters corresponding to the qualified product are used as design constraints for successful verification.

[0101] As an example of the above implementation, assuming that the configuration thresholds of the overall load response defect and the overall thermal expansion defect are 0.3 and 0.2 respectively, the constraint verification of some qualified products is shown in Table 1.

[0102] Table 1: Constraint verification data for some qualified products

[0103] While utilizing the line and surface feature parameters of successful cases in historical manufacturing records as multi-dimensional detailed constraints for the current design, this method also dynamically simulates and verifies these constraints. By selecting only those constraints that have been successfully verified, the design is not only based on verified actual process data but also enables the early identification and elimination of potential design flaws. This makes products designed based on these selected constraints more reliable and robust, capable of withstanding the challenges of actual production and use.

[0104] (3) Generate the effective device contour baseline and surface model of the current product through parametric modeling based on the successfully verified design constraints.

[0105] The above steps are specifically implemented as follows: define the parameter variables corresponding to the design constraints. For example, for the baseline of the vessel contour, it may be necessary to define parameters such as length, angle, curve radius, etc.; for the surface model, it may involve parameters such as curvature, thickness, and surface smoothness.

[0106] Create basic geometry (such as lines, arcs, etc.) in parametric modeling software based on preliminary design concepts as the basis for the builder's outline baseline.

[0107] Apply the verified successful line feature constraint conditions to the basic geometry, and control the shape and size of the contour baseline by adjusting the parameter variables.

[0108] Use the tools provided by the parametric modeling software to generate an initial surface model based on the constructed vessel contour baseline.

[0109] Apply the verified surface feature constraints to the surface model and adjust the relevant parameters to ensure that the surface smoothness, curvature continuity and other performance requirements are met.

[0110] In one improved implementation, after successfully performing parametric modeling based on validated design constraints, further validation can be performed, such as by running a finite element analysis or thermal expansion simulation, to verify that the newly generated device contour baseline and surface model still meet all pre-defined design constraints. If any non-compliance is found, the model can be re-implemented and adjusted accordingly.

[0111] In further improvements and implementations, firing shrinkage compensation parameters can be incorporated into ceramic product designs to primarily address the dimensional changes that occur during high-temperature firing. Physical and chemical reactions during firing cause changes in volume and size, a phenomenon known as firing shrinkage. Without proper compensation, the final product's dimensions may deviate significantly from the designed dimensions. Therefore, accounting for firing shrinkage during the design phase and making appropriate adjustments through parametric modeling can ensure that fired ceramic products meet the intended design dimensions.

[0112] This systematic process effectively translates validated design constraints into concrete 3D models, ensuring that new products not only meet the original design intent but also possess excellent physical properties and visual appeal. This approach significantly improves design efficiency, reduces trial-and-error costs, and promotes the development of innovative designs.

[0113] Based on the generated effective vessel contour baseline and surface model, a geometric continuity constraint algorithm is used to perform curvature gradient fusion on the vessel body, or a free deformation algorithm is used for unconstrained fusion.

[0114] It's important to understand that the geometric continuity constraint algorithm is a technique used to ensure smooth transitions between different parts of a surface model. It enforces specific geometric continuity conditions (such as positional continuity, tangent continuity, and curvature continuity) to ensure that there are no abrupt changes at the connections between surfaces, thereby achieving both visual and physical smoothness.

[0115] The specific implementation steps are: Define boundary conditions: determine the different surface parts that need to be fused and their boundary conditions (such as starting point, end point, tangent direction, etc.).

[0116] Apply continuity constraints: Select an appropriate continuity level (such as C0, C1, or C2) based on design requirements and apply corresponding constraints.

[0117] Optimize surface: Use optimization algorithms to adjust surface parameters so that the transition between parts is as smooth as possible and meets preset continuity conditions.

[0118] The free deformation algorithm is a deformation technology based on the control grid. It allows designers to flexibly modify the shape of the 3D model without destroying the original geometric structure. It affects the overall form of the model by changing the position of the control points in the control grid, providing great flexibility and creativity.

[0119] The specific implementation steps are: Construct a control grid: Create a suitable control grid for the surface model to be deformed.

[0120] Select control points: Select the control points that need to be adjusted according to the design intention.

[0121] Adjust the position of the control point: Adjust the position of the control point by dragging or entering coordinates, and observe the real-time changes of the model.

[0122] Apply deformation: Confirm the adjusted control point positions and complete the deformation operation of the model.

[0123] The aforementioned geometric continuity constraint algorithm is more suitable for applications that require smooth transitions, while the free-form deformation algorithm provides designers with greater creative freedom. Both methods can effectively achieve the integration of ceramic product features, but the specific choice depends on the specific needs and design goals of the project.

[0124] The above solution ensures smooth transitions between different curved surfaces by blending curvatures, avoiding abrupt changes. This is crucial for enhancing the overall aesthetics and visual consistency of a product. For example, in the design of a ceramic vase, if there is no smooth transition between the neck and the body, it may appear inconsistent and even affect the user experience. In addition, by ensuring a gradual blending of curvatures, stress concentration can be reduced, especially in high-stress areas such as corners. This helps to improve the structural strength and durability of the product, extending its service life. For example, for ceramic products used in high-temperature environments, smooth curvature transitions can effectively disperse thermal stress and prevent cracks.

[0125] (5) Adaptively mesh the fused device model and generate visual metadata.

[0126] The specific implementation of the above steps is as follows: import the device model completed by fusion of geometric continuity constraint algorithm or free deformation algorithm into software that supports mesh generation.

[0127] Define the target meshing accuracy based on design requirements. For example, a denser mesh is required in stress concentration areas, while a coarser mesh can be used in smooth areas.

[0128] This ensures that critical areas have sufficient resolution to capture detail.

[0129] Furthermore, you can select the mesh type such as triangular / quadrilateral surface mesh or volume mesh (tetrahedral / hexahedral).

[0130] According to the curvature distribution characteristics of the model surface and the preset curvature change threshold, the geometric area is divided into high curvature areas and low curvature areas. The adaptive mesh generation algorithm is used to automatically increase the mesh resolution in the high curvature area and reduce the network density in the low curvature area to generate multi-scale mesh areas.

[0131] It should be added that the curvature change threshold is used to quantify the degree of significant change in local curvature, thereby distinguishing different geometric feature areas on the model surface. Specifically, this threshold can be determined by clustering analysis of the curvature of each point on the model surface. First, the curvature values of all points on the model surface are calculated, and the corresponding curvature distribution map is generated. Then, these curvature data points are classified using a clustering algorithm. In the clustering process, each cluster represents a specific curvature characteristic or range. In order to set the curvature change threshold, it is necessary to evaluate the range of change of the curvature values within each cluster and the differences between clusters. The curvature change threshold is set by determining the difference between clusters.

[0132] For example, suppose that after cluster analysis, it is found that the surface of the vessel can be clearly divided into two main clusters: the curvature values of one cluster are concentrated in a lower range, indicating relatively flat or smoothly transitioned areas; the other cluster contains higher curvature values, corresponding to edges, sharp corners, or other parts with rich geometric details. If the analysis determines that when the curvature value reaches 0.03 or above, the geometric details of the component begin to become complex and have a significant impact on the simulation results, the curvature change threshold can be set to 0.03. In this way, in the subsequent mesh generation process, all areas with curvature exceeding this threshold will be assigned a higher density mesh to ensure the accuracy and efficiency of the numerical simulation.

[0133] Geometric information (such as vertex coordinates, normal vectors, and unit connection relationships) and physical field data (such as stress and temperature) are extracted from the generated mesh area as metadata, and functional attributes (such as decorative areas, support areas, etc.) are marked.

[0134] Furthermore, if the model contains multiple parts or features (such as base, body, and decoration), a clear hierarchical structure needs to be defined so that the display effects of different parts can be controlled separately in the visualization.

[0135] Use the visualization tool to load metadata for a mesh region.

[0136] High-quality rendering techniques and advanced animation methods can be used when visually loading mesh metadata, thereby enhancing intuitiveness and significantly improving visual expression.

[0137] In the optimized implementation of the above solution, the visual display also provides interactive functions such as rotation, zooming, and click query, which makes it convenient for designers to view model details in real time.

[0138] This adaptive meshing of the fused device model and the generation of visual metadata effectively support the evaluation and optimization of ceramic product designs. This approach not only improves design transparency and controllability but also provides reliable foundational data for subsequent manufacturing and analysis. Whether used for simulation analysis by engineers or presentations to customers, this technology can significantly improve design quality and communication efficiency.

[0139] Example 2 See also Figure 3 As shown, the present invention proposes a feature-fused three-dimensional visualization design system for ceramic products, including the following modules: a design constraint determination module: used to screen line features and surface features of finished products that meet design requirements from historical ceramic manufacturing records as design constraints for the current product.

[0140] Constraint verification module: includes a virtual modeling unit and a constraint screening unit, which are used to build a three-dimensional verification model and screen valid constraint conditions respectively.

[0141] Model building module: used to generate baseline and surface models based on valid constraints.

[0142] Fusion design module: Integrates geometric constraint fusion unit and free fusion unit to support dual-mode fusion design of the device body.

[0143] Visualization module: used to mesh the fused device model and render mesh metadata.

[0144] The above content is merely an example and explanation of the structure of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the present invention, they should all fall within the scope of protection of the present invention.

Claims

1. A feature-fusion three-dimensional visualization design method for ceramic products, characterized in that: The following steps are involved: (1) Screening qualified finished products that match the current design requirements from the historical ceramic manufacturing records according to the preset error matching principle of vessel size and pattern alignment, and extracting line feature parameters and surface feature parameters from the manufacturing data of the qualified finished products as the design constraints of the current product; (2) Construct a 3D virtual device profile baseline of the current product based on line feature constraints, and construct a surface model of the current product based on surface feature constraints. Apply dynamic load simulation to the 3D virtual device profile baseline and thermal expansion simulation to the surface model. The constraint effect is verified by combining the simulation results, and successful design constraint conditions are screened and verified. (3) Generate the effective device profile baseline and surface model of the current product through parametric modeling based on the successfully verified design constraints; (4) Based on the generated effective vessel outline baseline and surface model, a geometric continuity constraint algorithm is used to perform curvature gradient fusion on the vessel body, or a free deformation algorithm is used for unconstrained fusion; (5) Adaptively mesh the fused device model and generate visual metadata.

2. The feature-fused 3D visualization design method for ceramic products according to claim 1, wherein: The screening of qualified finished products that match the current design requirements is described in the following process: Extracting manufacturing materials and manufacturing process environment from historical ceramic manufacturing records, and screening out consistent historical manufacturing records based on the manufacturing materials and manufacturing process environment specified by the current product design and marking them as similar manufacturing records; For each similar manufacturing record, extract the actual shape, size and decoration type data of the corresponding finished product, compare and analyze the shape, size and decoration type required by the current product design, and calculate the deviation value between the two; Under the guidance of the preset error matching principle of vessel size and pattern alignment, evaluate whether the vessel size deviation and pattern type deviation in each similar manufacturing record are within the acceptable range, and thus select similar manufacturing records whose vessel size deviation and pattern type deviation both meet the preset error matching standards and define them as matching manufacturing records; For all relevant finished products identified as matching manufacturing records, their associated finished product inspection records are reviewed, and the quality inspection results of each finished product are extracted. Finished products whose quality inspection items meet the inspection standards are then identified as qualified finished products.

3. The feature-integrated 3D visualization design method for ceramic products according to claim 1, wherein: The dynamic load applied to the three-dimensional virtual device profile baseline simulates the following implementation process: Determine the physical properties of the material based on the manufacturing raw materials specified by the current product design; Define the support points of the contour baseline according to the actual application scenarios of ceramic products; Set the boundary conditions of the simulation using the determined material physical properties and defined support points; Select the load type according to the expected use of the product, and set different load levels and simulation sequences for the load type; Under the set boundary conditions, finite element analysis software is used to apply dynamic loads to the support points of the three-dimensional virtual device contour baseline according to the preset load type and the simulation sequence of the corresponding load gear; During the simulation process, the response data of the support points of the three-dimensional virtual device contour baseline under different load levels corresponding to the load type are output, including deformation, stress, and vibration data.

4. The feature-fused 3D visualization design method for ceramic products according to claim 3, wherein: The thermal expansion simulation process of the surface model is as follows: Set the temperature range and temperature gradient during simulation according to the actual application environment of the ceramic product, thereby generating a series of temperature nodes; Input the physical properties of the ceramic product into the simulation software and run the thermal expansion simulation program at each temperature node; During the simulation process, the deformation distribution diagram and stress distribution diagram of the surface model at different temperature nodes are output visually.

5. The feature-fused 3D visualization design method for ceramic products according to claim 4, characterized in that: The comprehensive simulation results are used to verify the constraint effect, and the design constraint conditions that are successfully screened and verified are referred to the following process: The response fluctuation of adjacent support points is quantified by the support point response data under different load levels in the online feature simulation of each qualified product selected from historical manufacturing to obtain the response fluctuation amount of adjacent support points under different load levels; Compare the support point response data under different load levels in the online characteristic simulation of each qualified product with the set limit response to quantify the response excess; The load response defect is defined as the fusion value of the response fluctuation and the response excess. The load response defect at different load levels is calculated using the response fluctuation and response excess at different load levels. Weights are assigned to different load levels, and the load response defects of different load levels are combined with the weights to obtain the overall load response defect of each qualified product under online characteristic simulation.

6. The feature-fused 3D visualization design method for ceramic products according to claim 5, characterized in that: The comprehensive simulation results are used to verify the constraint effect, and the successful design constraint conditions are screened and verified, which also includes the following process: Mark the deformation distribution area and stress concentration area of each qualified product selected from historical manufacturing at different temperature nodes in the surface feature simulation; The thermal expansion defect is defined as the fusion value of the deformation area ratio and the stress concentration area ratio. For each temperature node, the thermal expansion defect at that node is calculated based on the corresponding deformation distribution area ratio and stress concentration area ratio. Weights are assigned to different temperature nodes, and the thermal expansion defectivity of different temperature nodes is combined with the weights to obtain the overall thermal expansion defectivity of each qualified product under surface feature simulation.

7. The feature-fused 3D visualization design method for ceramic products according to claim 6, wherein: The comprehensive simulation results are used to verify the constraint effect, and the successful design constraint conditions are screened and verified, which further includes the following process: The overall load response defect and overall thermal expansion defect of each qualified product under online feature simulation and surface feature simulation are compared with the configured defect thresholds respectively. If the overall load response defect and overall thermal expansion defect of a qualified product under online feature simulation and surface feature simulation both meet the defect thresholds, the corresponding line feature parameters and surface feature parameters of the qualified product are used as design constraints for successful verification.

8. The feature-fused 3D visualization design method for ceramic products according to claim 1, wherein: The specific implementation process of step (3) is as follows: Define parameter variables corresponding to design constraints; Create basic geometry based on preliminary design concepts in parametric modeling software as the basis for builder profile baselines; Apply the verified successful line feature constraint conditions to the basic geometry, and control the shape and size of the contour baseline by adjusting the parameter variables; Use the tools provided by the parametric modeling software to generate an initial surface model based on the constructed vessel contour baseline; Apply the verified surface feature constraints to the surface model and adjust the relevant parameters to ensure that the surface smoothness, curvature continuity and other performance requirements are met.

9. The feature-fused 3D visualization design method for ceramic products according to claim 1, wherein: The specific content of step (5) is as follows: Import the device model completed by fusion of geometric continuity constraint algorithm or free deformation algorithm into software that supports mesh generation; Define the target accuracy of mesh generation according to design requirements; Based on the curvature distribution characteristics of the model surface and the preset curvature change threshold, the geometric area is divided into high curvature areas and low curvature areas. An adaptive mesh generation algorithm is used to automatically increase the mesh resolution in the high curvature area and reduce the network density in the low curvature area to generate multi-scale mesh areas. Extract geometric information and physical field data from the generated mesh area as metadata and perform functional attribute tagging; Use the visualization tool to load metadata for a mesh region.

10. Feature-integrated 3D visualization design system for ceramic products, characterized by: Includes the following modules: Design constraint determination module: used to select line features and surface features that meet the design requirements and meet the standards of finished products from the historical ceramic manufacturing records as design constraints for the current product; Constraint Verification Module: Contains a virtual modeling unit and a constraint screening unit, which are used to build a 3D verification model and screen valid constraint conditions respectively; Model building module: used to generate baseline and surface models based on valid constraints; Fusion design module: Integrates geometric constraint fusion unit and free fusion unit to support dual-mode fusion design of device body; Visualization module: used to mesh the fused device model and render mesh metadata.

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