Rendering method of 3D design model based on precision hardware mold

Abstract

The present invention relates to the technical field of three-dimensional model rendering, and in particular to a three-dimensional design model rendering method based on precision hardware molds. The method comprises the following steps: obtaining the surface topology data of the precision hardware mold; performing three-dimensional mesh conversion on the surface topology data of the precision hardware mold to generate the three-dimensional mesh conversion data of the precision hardware mold; performing feature repair compensation on the three-dimensional mesh conversion data of the precision hardware mold to generate the precision hardware mold repair data; performing precision hardware mold model structure decomposition on the precision hardware mold repair data to generate the precision hardware mold model structure data; performing hierarchical three-dimensional modeling based on the precision hardware mold model structure data to generate a precision hardware hierarchical three-dimensional model; formulating model material conversion rules for the precision hardware hierarchical three-dimensional model to generate material conversion rules. The present invention improves the loadability and flexibility of rendering through precise data processing, model structure decomposition, dynamic rendering and performance evaluation.

Description

Technical Field

[0001] The present invention relates to the technical field of three-dimensional model rendering, and in particular to a three-dimensional design model rendering method based on precision hardware molds. Background Art

[0002] As computer performance improves, 3D modeling technology has gradually matured. Designers began to use 3D CAD software to create more complex and sophisticated mold designs. These software allow designers to rotate, scale, and view molds in virtual space, but rendering is still relatively simple. Computer graphics have made great progress, especially in real-time rendering and ray tracing. This provides mold designers with more realistic rendering capabilities, allowing them to see the true appearance of the mold on the screen, including light reflections, shadows, and materials. As virtual reality and augmented reality technologies begin to penetrate the field of industrial design, these technologies enable mold designers to experience molds immersively and even interact with molds in a virtual environment. This greatly improves the accuracy and efficiency of the design. At present, the application of artificial intelligence in mold design is becoming more and more extensive. AI can help designers with mold optimization, material selection, and cost estimation, and can also assist in generating more realistic rendering effects. However, the current traditional rendering methods are difficult to handle the dynamic rendering requirements of complex molds, and the modeling of hardware molds cannot be well adjusted according to the operating status of the mold, resulting in low load and flexibility of rendering. Summary of the invention

[0003] Based on this, it is necessary to provide a three-dimensional design model rendering method based on precision hardware molds to solve at least one of the above technical problems.

[0004] To achieve the above purpose, a 3D design model rendering method based on precision hardware molds is provided, the method comprising the following steps:

[0005] Step S1: acquiring the surface topology data of the precision hardware mold; performing three-dimensional mesh conversion on the surface topology data of the precision hardware mold to generate three-dimensional mesh conversion data of the precision hardware mold; performing feature repair compensation on the three-dimensional mesh conversion data of the precision hardware mold to generate repair data of the precision hardware mold;

[0006] Step S2: Decomposing the precision hardware mold repair data into a precision hardware mold model structure to generate precision hardware mold model structure data; performing hierarchical three-dimensional modeling based on the precision hardware mold model structure data to generate a precision hardware hierarchical three-dimensional model;

[0007] Step S3: Formulate model material conversion rules for the precision hardware hierarchical three-dimensional model to generate material conversion rules; dynamically render the precision hardware hierarchical three-dimensional model through the material conversion rules to generate a dynamic rendering model of a precision hardware mold;

[0008] Step S4: Perform rendering degree analysis on the hierarchical rendering model of the precision hardware mold to generate rendering degree analysis data; perform rendering performance evaluation on the rendering degree analysis data to generate mold rendering performance evaluation data; perform rendering adjustment on the comprehensive rendering model of the precision hardware mold based on the mold rendering performance evaluation data to achieve real-time dynamic adjustment of the rendering of the three-dimensional design model of the precision hardware mold.

[0009] The present invention can help convert mold data in the real world into a computer-recognizable three-dimensional model by acquiring the surface topology data of precision hardware molds and performing three-dimensional grid conversion and feature repair compensation, thereby reducing defects and errors in the model. Structural decomposition and hierarchical three-dimensional modeling of the repaired mold data can help decompose complex mold structures into parts that are easier to manage and design, thereby improving the efficiency and flexibility of mold design. Model material conversion rules are formulated and dynamic rendering is performed. According to the requirements of mold design and material properties, the rendering effect of the mold under different materials is achieved, so that designers and customers can intuitively preview the appearance of the mold, which can improve the efficiency of design communication. Customers and designers can see the mold design effect more intuitively, reducing design and production errors. Rendering degree analysis and performance evaluation of the rendering model: analyzing the rendering effect and evaluating the rendering performance can help optimize the mold design, ensure that the rendering effect meets the design requirements, and optimize the mold design at the same time, ensure that the rendering effect and performance are in the best state, and improve the design quality and customer satisfaction. Rendering adjustment of the comprehensive rendering model of the mold based on performance evaluation data can realize real-time dynamic adjustment of the mold. Designers can modify the appearance and material of the mold in real time as needed, quickly optimize the design, improve the flexibility and response speed of the design, reduce the time cost of design adjustment, and speed up product iteration and market launch. Through automated processing and dynamic rendering, the time and errors of manual processing are reduced, and the design efficiency and accuracy are improved. The optimized design and rendering process can reduce errors and adjustments in production, reduce production costs and cycles, and can more intuitively understand the mold design effect, make comments and adjustments in time, and increase customer satisfaction and trust. Therefore, the present invention improves the loadability and flexibility of rendering through precise data processing, model structure decomposition, dynamic rendering and performance evaluation.

[0010] The beneficial effect of the present invention is that the repair data generated by acquiring the surface topology data of the precision hardware mold, and after three-dimensional mesh conversion and feature repair compensation, ensures the integrity and accuracy of the mold data, and provides a reliable basis for subsequent work. The repair data is decomposed into the structure of the precision hardware mold model, and the generated model structure data helps to clearly understand the composition structure of the mold, which facilitates the subsequent modeling work. Through the material conversion rule formulation and dynamic rendering of step S3, the material conversion rule is applied to the precision hardware hierarchical three-dimensional model, and dynamic rendering is realized, so that the design and rendering of the mold are more integrated, and the design efficiency is improved. Rendering degree analysis and rendering performance evaluation, as well as rendering adjustment based on evaluation data, help to optimize the rendering effect of the mold, improve the visual presentation quality, and enable designers to more accurately evaluate the appearance and performance of the mold. Therefore, the present invention improves the loadability and flexibility of rendering through precise data processing, model structure decomposition, dynamic rendering and performance evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 A schematic diagram of the steps of a 3D design model rendering method based on precision hardware molds;

[0012] Figure 2 for Figure 1 Detailed implementation steps of step S3 in FIG.

[0013] Figure 3 for Figure 2 Detailed implementation steps of step S33;

[0014] Figure 4 for Figure 3 Detailed implementation steps of step S335;

[0015] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0016] The following is a clear and complete description of the technical method of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are 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 technicians in this field without creative work are within the scope of protection of the present invention.

[0017] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0018] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0019] To achieve this, please refer to Figures 1 to 4 , provides a 3D design model rendering method based on precision hardware molds, comprising the following steps:

[0020] Step S1: acquiring the surface topology data of the precision hardware mold; performing three-dimensional mesh conversion on the surface topology data of the precision hardware mold to generate three-dimensional mesh conversion data of the precision hardware mold; performing feature repair compensation on the three-dimensional mesh conversion data of the precision hardware mold to generate repair data of the precision hardware mold;

[0021] Step S2: Decomposing the precision hardware mold repair data into a precision hardware mold model structure to generate precision hardware mold model structure data; performing hierarchical three-dimensional modeling based on the precision hardware mold model structure data to generate a precision hardware hierarchical three-dimensional model;

[0022] Step S3: Formulate model material conversion rules for the precision hardware hierarchical three-dimensional model to generate material conversion rules; dynamically render the precision hardware hierarchical three-dimensional model through the material conversion rules to generate a dynamic rendering model of a precision hardware mold;

[0023] Step S4: Perform rendering degree analysis on the hierarchical rendering model of the precision hardware mold to generate rendering degree analysis data; perform rendering performance evaluation on the rendering degree analysis data to generate mold rendering performance evaluation data; perform rendering adjustment on the comprehensive rendering model of the precision hardware mold based on the mold rendering performance evaluation data to achieve real-time dynamic adjustment of the rendering of the three-dimensional design model of the precision hardware mold.

[0024] The present invention can help convert mold data in the real world into a computer-recognizable three-dimensional model by acquiring the surface topology data of precision hardware molds and performing three-dimensional grid conversion and feature repair compensation, thereby reducing defects and errors in the model. Structural decomposition and hierarchical three-dimensional modeling of the repaired mold data can help decompose complex mold structures into parts that are easier to manage and design, thereby improving the efficiency and flexibility of mold design. Model material conversion rules are formulated and dynamic rendering is performed. According to the requirements of mold design and material properties, the rendering effect of the mold under different materials is achieved, so that designers and customers can intuitively preview the appearance of the mold, which can improve the efficiency of design communication. Customers and designers can see the mold design effect more intuitively, reducing design and production errors. Rendering degree analysis and performance evaluation of the rendering model: analyzing the rendering effect and evaluating the rendering performance can help optimize the mold design, ensure that the rendering effect meets the design requirements, and optimize the mold design at the same time, ensure that the rendering effect and performance are in the best state, and improve the design quality and customer satisfaction. Rendering adjustment of the comprehensive rendering model of the mold based on performance evaluation data can realize real-time dynamic adjustment of the mold. Designers can modify the appearance and material of the mold in real time as needed, quickly optimize the design, improve the flexibility and response speed of the design, reduce the time cost of design adjustment, and speed up product iteration and market launch. Through automated processing and dynamic rendering, the time and errors of manual processing are reduced, and the design efficiency and accuracy are improved. The optimized design and rendering process can reduce errors and adjustments in production, reduce production costs and cycles, and can more intuitively understand the mold design effect, make comments and adjustments in time, and increase customer satisfaction and trust. Therefore, the present invention improves the loadability and flexibility of rendering through precise data processing, model structure decomposition, dynamic rendering and performance evaluation.

[0025] In the embodiment of the present invention, reference Figure 1 The above is a schematic diagram of the steps of a method for rendering a three-dimensional design model based on a precision hardware mold according to the present invention. In this example, the method for rendering a three-dimensional design model based on a precision hardware mold includes the following steps:

[0026] Step S1: acquiring the surface topology data of the precision hardware mold; performing three-dimensional mesh conversion on the surface topology data of the precision hardware mold to generate three-dimensional mesh conversion data of the precision hardware mold; performing feature repair compensation on the three-dimensional mesh conversion data of the precision hardware mold to generate repair data of the precision hardware mold;

[0027] In an embodiment of the present invention, surface topological data of a precision hardware mold is collected by using a suitable device (such as a three-dimensional scanner). This can be done by scanning the entire mold surface to obtain the geometry and topological structure of the mold. The collected surface topological data is converted into three-dimensional mesh data. This can be done through computer-aided design (CAD) software or a specialized three-dimensional modeling tool to convert the topological data into a three-dimensional mesh composed of many small cubes or polygons. Feature repair compensation is performed on the converted three-dimensional mesh data to repair possible defects or incomplete features. This may involve operations such as filling holes, repairing fractures, and smoothing surfaces to ensure that the geometry of the mold is complete and meets the design requirements. After feature repair compensation, the repaired precision hardware mold data, i.e., repair data, is generated. These data will be used as input for subsequent steps.

[0028] Step S2: Decomposing the precision hardware mold repair data into a precision hardware mold model structure to generate precision hardware mold model structure data; performing hierarchical three-dimensional modeling based on the precision hardware mold model structure data to generate a precision hardware hierarchical three-dimensional model;

[0029] In an embodiment of the present invention, by using computer-aided design (CAD) software or special mold design software, the repaired precision hardware mold data is imported. The mold is structurally decomposed into different parts or components. This can be done by analyzing the function, structure and assembly relationship of the mold, and dividing the mold into parts that are easy to manage and manufacture. In the CAD software, appropriate attributes and identifications are added to each part or component to describe its material, size, processing technology and other information. A data file containing the mold model structure is generated, and these data files will be used for subsequent hierarchical three-dimensional modeling. Using CAD software or professional three-dimensional modeling tools, hierarchical three-dimensional modeling is performed on the basis of the model structure data. Starting from the component level of the mold, the various parts of the mold are gradually assembled to ensure accurate matching and assembly relationship between them. Details, features and decorations can be added as needed to make the model more realistic and visual. The generated hierarchical three-dimensional model is verified to ensure that its geometry and structure meet the design requirements and manufacturing standards. The model is optimized to improve its performance, manufacturability and maintainability. The model generated by hierarchical three-dimensional modeling is saved in a standard model file format, such as STL, STEP, etc., for subsequent manufacturing and use.

[0030] Step S3: Formulate model material conversion rules for the precision hardware hierarchical three-dimensional model to generate material conversion rules; dynamically render the precision hardware hierarchical three-dimensional model through the material conversion rules to generate a dynamic rendering model of a precision hardware mold;

[0031] In an embodiment of the present invention, by determining the needs and goals of model material conversion, such as which materials need to be used in the rendering process, how to adjust the material's glossiness, color, transparency and other parameters. Analyze the material characteristics and surface treatment methods of the precision hardware mold, and formulate corresponding material conversion rules. These rules can be based on different parts of the mold, material properties and appearance requirements, such as metal parts, plastic parts, coating surfaces, etc. In the rendering software or tool, create or edit a material library containing various common material types and properties. According to the formulated rules, specify appropriate materials and parameters for different parts or components to achieve model material conversion and adjustment. Use the rendering software or engine to import the precision hardware hierarchical three-dimensional model. According to the previously formulated material conversion rules, dynamically render the model. This includes combining the model's geometry with the specified material, adjusting parameters such as lighting, shadows and reflections to produce realistic rendering effects. Multiple renderings can be performed as needed, adjusting the material and rendering parameters until a satisfactory effect is achieved. After the rendering is completed, the rendering result is saved as a dynamic rendering model file. This is usually an image or video file that shows the appearance of the mold at different angles and lighting conditions. Dynamically rendered models can be integrated into mold design and manufacturing processes for product display, communication, and review.

[0032] Step S4: Perform rendering degree analysis on the hierarchical rendering model of the precision hardware mold to generate rendering degree analysis data; perform rendering performance evaluation on the rendering degree analysis data to generate mold rendering performance evaluation data; perform rendering adjustment on the comprehensive rendering model of the precision hardware mold based on the mold rendering performance evaluation data to achieve real-time dynamic adjustment of the rendering of the three-dimensional design model of the precision hardware mold.

[0033] In an embodiment of the present invention, a rendering software or tool is used to render a hierarchical rendering model of a precision metal mold to generate a rendering image or animation. The rendering results are visually analyzed to evaluate the quality and realism of the rendering effect. This may include checking details such as lighting, shadows, reflections, and material performance. Based on the analysis results, rendering degree analysis data is generated to record various indicators and evaluation criteria of the rendering effect. The rendering degree analysis data is quantitatively evaluated, including performance indicators such as rendering time, memory usage, and frame rate. A performance evaluation tool or script is used to perform a performance test on the rendering process and collect rendering performance data. The rendering performance data is analyzed to evaluate the efficiency and stability of the rendering process and determine the quality of the rendering performance. Based on the mold rendering performance evaluation data, the comprehensive rendering model of the precision metal mold is adjusted in a targeted manner. Adjust the rendering parameters, such as reducing the number of polygons of the model, simplifying the material mapping, optimizing the lighting and shadow settings, etc., to improve the rendering performance. A real-time feedback method can be used to instantly view the adjusted rendering effect, and further adjustments can be made as needed until the ideal rendering effect and performance requirements are achieved. Integrate the rendering adjustment process into the mold design software or tools to achieve real-time dynamic adjustment of the 3D design model of precision hardware molds. During the design process, designers can adjust the rendering parameters of the mold at any time, preview the rendering effect in real time, and modify and optimize as needed to meet design requirements and performance requirements.

[0034] Preferably, step S1 comprises the following steps:

[0035] Step S11: Scan the surface of the precision hardware mold using an optical scanner to obtain surface topology data of the precision hardware mold;

[0036] Step S12: preprocessing the surface topology data of the precision hardware mold to generate standard surface topology data of the precision hardware mold, wherein the data preprocessing includes data cleaning, data outlier removal, data integration and data standardization;

[0037] Step S13: reconstructing the surface topology data of the standard precision hardware mold to generate precision hardware mold reconstruction data; performing three-dimensional mesh conversion on the precision hardware mold reconstruction data to generate precision hardware mold three-dimensional mesh conversion data; performing surface fitting on the precision hardware mold three-dimensional mesh conversion data to generate precision hardware mold three-dimensional mesh surface fitting data;

[0038] Step S14: extract local features of the three-dimensional mesh surface fitting data of the precision hardware mold to generate local feature data of the precision hardware mold, wherein the local feature data of the precision hardware mold includes the edge data of the hardware mold and the curvature data of the hardware mold; perform feature repair and compensation on the surface topology data of the precision hardware mold based on the edge data of the hardware mold and the curvature data of the hardware mold to generate precision hardware mold repair data.

[0039] The present invention uses an optical scanner to scan the surface of a precision hardware mold to obtain its surface topology data, which helps to obtain accurate mold surface shape information. The acquired surface topology data is preprocessed, including data cleaning, outlier removal, data integration and data standardization operations to generate standard surface topology data, which helps to improve data quality and consistency. The standard surface topology data is reconstructed to generate reconstructed data of the mold. Then, the reconstructed data is converted into a three-dimensional grid to generate three-dimensional grid conversion data, which helps to convert the mold surface data into a form more suitable for subsequent processing. Local feature extraction is performed on the three-dimensional grid surface fitting data to generate local feature data of the mold, including angular data and curvature data. Then, based on these local feature data, feature repair compensation is performed on the surface topology data to generate repair data, which is intended to repair defects and incompleteness on the mold surface to improve its quality and usability.

[0040] In an embodiment of the present invention, the surface of a precision hardware mold is scanned by using an optical scanner. During the scanning process, it is ensured that the scanner can accurately capture the details and shape of the mold surface and convert them into digital surface topological data. The surface topological data obtained from the scanner is preprocessed. This includes data cleaning, removing possible noise or incomplete data points; outlier removal, excluding data points inconsistent with the mold surface shape; data integration, integrating the data of different scanned parts into a complete data set; data standardization, ensuring that the data is consistent in scale and format for subsequent processing. The standard surface topological data is reconstructed using an appropriate algorithm to fill in possible vacancies or missing parts and generate reconstructed data. Then, the reconstructed data is converted into three-dimensional mesh data, and various mesh generation algorithms and tools can be used to implement this step, such as triangulation, quadrilateralization, etc. Local feature extraction is performed on the three-dimensional mesh surface fitting data, such as detecting local features such as edges and curvatures. Then, based on the extracted local feature data, feature repair compensation is performed on the surface topological data to repair possible defects or errors and generate repaired data.

[0041] Preferably, step S2 comprises the following steps:

[0042] Step S21: extracting geometric features from the precision hardware mold repair data to generate geometric feature data of the precision hardware mold, wherein the geometric feature data of the precision hardware mold includes normal data of the hardware mold and area data of the hardware mold;

[0043] Step S22: performing feature classification description on the precision hardware mold according to the hardware mold normal data and the hardware mold area data, and generating precision hardware mold classification feature data, wherein the precision hardware mold classification feature data includes precision hardware mold boundary feature data and precision hardware mold concave-convex feature data;

[0044] Step S23: Decomposing the precision hardware mold model structure through the precision hardware mold boundary feature data and the precision hardware mold concave-convex feature data to generate precision hardware mold model structure data, wherein the precision hardware mold model structure data includes mold base plate structure data, mold molding structure data and mold operation control structure data;

[0045] Step S24: Perform hierarchical three-dimensional modeling on the mold base plate structure data, mold forming structure data and mold operation control structure data to generate a precision hardware hierarchical three-dimensional model, wherein the hierarchical three-dimensional modeling includes the mold base plate module modeling process, the mold forming module modeling process and the mold operation control module modeling process.

[0046] The present invention extracts geometric features from the repaired mold data, including extracting normal data and area data. Normal data can describe the direction information of the mold surface, while area data can reflect the size and shape of the mold surface. These geometric feature data are helpful for further analyzing the shape and features of the mold. Based on the normal data and area data, the mold is classified and described, including boundary features and concave-convex features. Boundary features describe the edges and contours of the mold, while concave-convex features describe the concave and convex parts of the mold surface. Through this classification description, the structure and characteristics of the mold can be better understood. The mold is modeled using boundary feature data and concave-convex feature data. This step decomposes the mold into parts such as base plate structure, molding structure and operation control structure, so as to better understand the composition and function of the mold. Based on the base plate structure, molding structure and operation control structure data of the mold, hierarchical three-dimensional modeling is performed. This includes modeling different parts of the mold separately to ensure that the structure and function of the model are fully considered and expressed. Hierarchical three-dimensional modeling helps to better understand the complex structure and function of the mold.

[0047] In an embodiment of the present invention, the precision hardware mold repair data is loaded by using computer-aided design (CAD) software or similar tools. The normal data and area data of the mold are extracted by the geometric analysis tool provided by the CAD software. The normal data can be obtained by calculating the normal vector at each point on the mold surface, and the area data can be obtained by calculating the polygonal area of ​​the mold surface. Based on the extracted normal data and area data, a classification algorithm is used to perform feature classification description on the mold. Machine learning algorithms such as support vector machines (SVM), decision trees or neural networks can be used for classification, or rule-based methods can be used. The classification of boundary features and concave-convex features can be performed based on features such as the curvature and edge shape of the mold surface. The extracted boundary feature data and concave-convex feature data are used to decompose the model structure of the mold. A geometric analysis method or a topological analysis method can be used to identify different structural parts of the mold. The mold is decomposed into sub-parts such as a base plate structure, a molding structure, and an operation control structure, and their mutual relationships are recorded. Hierarchical three-dimensional modeling is performed based on the mold base plate structure data, the molding structure data, and the operation control structure data. CAD software or three-dimensional modeling software can be used to gradually build a model according to different structural parts of the mold. The modeling process of each structural part should take into account its function and the way it connects with other parts to ensure the integrity and accuracy of the overall model.

[0048] Preferably, the mold base module modeling process in step S24 includes the following steps:

[0049] Perform mold base plate structure analysis on the mold base plate structure data to generate mold base plate structure analysis data; perform geometric modeling on the mold base plate structure analysis data to generate a base plate geometric model;

[0050] Performing a mechanical characteristic analysis of the base plate material on the base plate geometric model to generate base plate mechanical characteristic data, wherein the base plate mechanical characteristic analysis includes base plate strength mechanical analysis and base plate stiffness mechanical analysis; performing a base plate force analysis on the base plate geometric model according to the base plate mechanical characteristic data to generate base plate force analysis data;

[0051] Perform force uniformity analysis on the force analysis data of the bottom plate to generate the force area uniformity analysis data of the bottom plate; optimize the layout of the bottom plate positioning holes based on the force area uniformity analysis data of the bottom plate to generate the optimization data of the layout of the bottom plate positioning holes; perform bolt hole fixation through the optimization data of the layout of the bottom plate positioning holes to generate the position data of the bolt holes for fixing the bottom plate;

[0052] The thermal stability of the base plate is analyzed on the base plate geometric model through the base plate fixing bolt hole position data and the base plate positioning hole layout optimization data, and the base plate thermal stability analysis data is generated; based on the base plate thermal stability analysis data and the base plate force analysis data, the model structure heat dissipation adjustment is performed on the base plate geometric model to generate the mold base plate module.

[0053] By analyzing the structure of the mold base plate, the present invention can understand its internal structure and characteristics, and provide basic data for subsequent modeling. Through geometric modeling, a three-dimensional model of the base plate is generated, which provides a basis for further analysis and design. Through mechanical property analysis, the strength and rigidity of the base plate can be evaluated to ensure that it can withstand the mechanical load under working conditions. By analyzing the force on the base plate, the force condition can be determined, and then the design and structure of the base plate can be optimized. By analyzing the uniformity of the force on the base plate, the stability and reliability of the base plate under the force condition can be ensured. Optimizing the arrangement of the base plate positioning holes can improve the assembly accuracy and stability of the mold and reduce assembly errors. Determining the position of the base plate fixing bolt hole helps to ensure the stability and safety of the mold during use. Analyzing the thermal stability of the base plate can evaluate the performance of the mold in a high temperature environment, providing a basis for improvement and optimization. Based on the thermal stability analysis and force analysis data, the base plate model is structurally adjusted to improve the heat dissipation effect of the mold and ensure its stability and durability during long-term operation.

[0054] In the embodiment of the present invention, the structure of the mold base plate is analyzed in detail by using professional engineering software (such as finite element analysis software) to obtain structural analysis data. Based on the structural analysis data, computer-aided design (CAD) software is used for geometric modeling to generate a three-dimensional model of the base plate. The strength and stiffness of the base plate material are analyzed using engineering mechanics principles and professional software to generate corresponding mechanical property data. Based on the geometric model and mechanical property data of the base plate, a force analysis is performed, considering the various load conditions that the mold bears during operation. The uniformity of the force on the base plate is evaluated using numerical analysis methods or engineering experience to determine whether the force distribution is reasonable. Combined with the force analysis and uniformity analysis data, the arrangement of the base plate positioning holes is optimized to ensure the accuracy and stability during mold assembly. According to the optimization data of the positioning hole arrangement, the position and number of the bolt holes are determined to ensure that the base plate can be firmly fixed in the mold. Using heat conduction theory and thermodynamic analysis methods, the stability of the base plate in a high temperature environment is evaluated to generate thermal stability analysis data. Combined with the thermal stability analysis and force analysis data, the structure of the base plate model is adjusted to optimize the heat dissipation performance to ensure that the mold will not be affected by overheating during long-term operation.

[0055] Preferably, the mold forming module modeling process in step S24 includes the following steps:

[0056] Performing mold cavity geometry analysis on the mold molding structure data to generate mold cavity geometry analysis data; performing mold cavity geometry modeling on the mold cavity geometry analysis data to generate a mold cavity geometry model;

[0057] Calculate the volume of the internal cavity space of the mold according to the mold base plate module of the mold cavity geometry model to obtain the internal space volume data of the mold cavity; design the mold core model based on the internal space volume data of the mold cavity to generate the mold core geometry model;

[0058] Based on the mold cavity geometry model and the mold core geometry model, the mold internal cooling channel layout is performed to generate the mold internal cooling channel data; the mold internal cooling channel data is subjected to channel intersection analysis to generate the mold internal cooling channel intersection data; the mold internal cooling channel intersection data is compared with the preset standard channel intersection threshold, and when the mold internal cooling channel intersection data is greater than or equal to the preset standard channel intersection threshold, the corresponding mold internal cooling channel is segmented to generate a high-load cooling channel; when the mold internal cooling channel intersection data is less than the preset standard channel intersection threshold, the corresponding mold internal cooling channel is marked to generate a low-load cooling channel;

[0059] Perform heat conduction simulation based on high-load cooling channels and low-load cooling channels to generate high-load channel heat conduction simulation data and low-load area heat conduction simulation data; arrange feed ports and exhaust ports based on high-load channel heat conduction simulation data and low-load area heat conduction simulation data to generate feed port quantity data and exhaust port quantity data;

[0060] The cavity filling bubble area of ​​the high-load cooling channel and the low-load cooling channel is divided by the feed port number data and the exhaust port number data to generate a high-bubble area and a low-bubble area; the bubble hot melt analysis is performed on the high-load channel heat conduction simulation data and the low-load area heat conduction simulation data using the high-bubble area and the low-bubble area. When the high-load cooling channel is in the high-bubble area, the feed port number data and the exhaust port number data are adjusted by the first air port so that the exhaust port number data is always greater than the feed port number data, and the first feed and exhaust adjustment data is generated; when the low-load cooling channel is in the high-bubble area, the feed port number data and the exhaust port number data are adjusted by the second air port so that the exhaust port number data is greater than or equal to the feed port number data, and the second feed and exhaust adjustment data is generated;

[0061] When the high-load cooling channel is in the low-bubble area or the low-load cooling channel is in the low-bubble area, the third air port adjustment is performed on the feed port quantity data and the exhaust port quantity data, so that the feed port quantity data is greater than the exhaust port quantity data, and the feed and exhaust third adjustment data is generated; the working filling simulation is performed according to the feed and exhaust first adjustment data, the feed and exhaust second adjustment data, and the feed and exhaust third adjustment data to generate the mold forming module.

[0062] The present invention can ensure that the geometric shape of the mold cavity meets the design requirements and improve the molding accuracy and efficiency of the mold by performing geometric structure analysis and modeling on the mold molding structure data. Calculating the internal space volume of the mold cavity helps to optimize the mold design, ensure that the material is filled evenly during the molding process, and avoid the generation of cavities and bubbles. By designing the mold core model, the product can be effectively supported and molded during the mold molding process to ensure that the shape and size of the product are accurate. Reasonable layout of the cooling channel inside the mold can effectively control the temperature during the molding process, speed up the product cooling time, improve production efficiency and reduce deformation and defects during the molding process. By simulating the heat conduction process and analyzing the hot melting of bubbles, the temperature distribution and material flow during the molding process can be better understood, and the optimization of mold design and molding parameter settings can be guided. Reasonable arrangement and adjustment of the feed port and exhaust port can effectively control the flow of gas inside the mold, avoid the occurrence of bubbles and insufficient melt glue, and improve product quality and molding efficiency. Through the working filling simulation, the molding effect of the mold in actual production can be evaluated, potential problems can be discovered and solved, and the rationality and feasibility of the mold design and parameter settings can be ensured.

[0063] In an embodiment of the present invention, the mold molding structure data is analyzed, including considerations of shape, size, etc. The mold cavity geometry analysis data is generated, which may include geometric parameters, surface data, etc. Based on the mold cavity geometry analysis data, geometric modeling is performed to generate a mold cavity geometry model. This may involve CAD software or similar tools for creating geometric bodies, surfaces, etc. According to the mold base plate module, the spatial volume data inside the mold cavity is calculated. This helps to determine the volume inside the mold cavity, which affects the flow and filling of the material during the molding process. The geometric model of the mold core is designed using the internal spatial volume data of the mold cavity. The mold core model is used to form the internal cavity structure of the material. Based on the mold cavity geometry model and the mold core geometry model, the layout of the cooling channel inside the mold is designed. The layout of the cooling channel affects the temperature distribution and cooling effect during the molding process. The cooling channel inside the mold is intersected by analysis to detect whether there is a channel intersection. The intersection analysis helps to determine which channels need to be segmented or marked. Heat conduction simulation is performed on high-load cooling channels and low-load cooling channels to evaluate the cooling effect and temperature distribution. This can be performed using numerical simulation software, taking into account factors such as the thermal conductivity properties of the material. Based on the results of the heat transfer simulation, the location and number of feed and exhaust ports are determined. This helps optimize material flow and gas exhaust during the molding process. By analyzing the data on the number of feed ports and the number of exhaust ports, the mold cavity is divided into filling bubble areas. This helps predict and optimize the location and number of bubble formation. The heat transfer simulation data is analyzed using bubble areas to evaluate the impact of bubbles on the molding process. This may involve considering the hot melt characteristics and flow behavior of bubbles. Based on the results of the bubble hot melt analysis, the location and number of feed and exhaust ports are adjusted to optimize the molding process. Adjustments may include adding, reducing or rearranging feed and exhaust ports. Based on the feed and exhaust adjustment data, a working filling simulation is performed to verify and optimize the design of the mold molding module. This helps predict material flow and filling during the molding process.

[0064] Preferably, the mold operation control module modeling process in step S24 includes the following steps:

[0065] The mold forming module and the mold base module are used to model the guide element of the mold operation control structure data to generate the guide positioning element geometric model; the mold motion space analysis is performed on the guide positioning element geometric model to generate the mold X-axis motion data, the mold Y-axis motion data and the mold Z-axis motion data;

[0066] According to the X-axis motion data, Y-axis motion data and Z-axis motion data of the mold, the driving force analysis of the geometric model of the guide positioning element is performed to generate the mold motion driving force data; based on the mold motion driving force data, the ejector mechanism of the guide positioning element geometric model is designed to generate the mold ejector mechanism data;

[0067] The mold ejector mechanism data is parameterized by the spring fastener to generate the mold ejector spring fastener parameterized data; the mold ejector mechanism data is evaluated for mold residual material by using the mold ejector spring fastener parameterized data to generate the mold residual material evaluation data;

[0068] Design the cutting blade based on the mold residual material evaluation data to generate the mold cutting blade; use the mold cutting blade to perform space cutting of the mold model on the geometric model of the guide positioning element based on the mold ejector mechanism data to generate the mold manipulation control geometric model; perform kinematic simulation analysis on the mold manipulation control geometric model to generate the mold manipulation control module, where the kinematic simulation analysis includes ejector motion analysis and spring rebound analysis;

[0069] The mold manipulation control module, mold forming module and mold base module are integrated to generate a precise hardware hierarchical three-dimensional model.

[0070] The present invention uses a mold forming module and a mold bottom plate module to model the guide element of the mold operation control structure data, and generates a guide positioning element geometric model. This step ensures that the structure of the mold is stable and the material can be accurately positioned and guided. By analyzing the motion space of the mold, the range and mode of movement of the mold in different directions can be determined. According to the mold X-axis motion data, the mold Y-axis motion data and the mold Z-axis motion data, the guiding and positioning element geometric model is analyzed for driving force, and mold motion driving force data is generated. This step can help designers understand the force required to be applied during the mold movement process, thereby optimizing the design and operation of the mold. Based on the mold motion driving force data, the guiding and positioning element geometric model is designed for an ejector mechanism, and mold ejector mechanism data is generated. The ejector mechanism is designed to ensure that the mold can accurately apply pressure to the material or perform other necessary actions during operation. The mold ejector mechanism data is parameterized by a spring fastener, and the mold ejector spring fastener parameterized data is generated. The parameterized design of the spring fastener can ensure that the ejector mechanism has the required elasticity and stability when working. The mold ejector spring fastener parameterized data is used to evaluate the mold residual material of the mold ejector mechanism data, and the mold residual material evaluation data is generated. The purpose of mold residual material assessment is to determine the waste or residual material that may be generated during the operation process, so as to make reasonable design and planning. Based on the mold residual material assessment data, the cutting blade design is carried out to generate the mold cutting blade. The design of the cutting blade can ensure that the mold has good cutting effect and accuracy when cutting materials. The mold model space cutting is performed on the guide positioning component geometry model based on the mold ejector mechanism data by using the mold cutting blade to generate the mold control geometry model. The design of the mold model space cutting can ensure that the mold has good control and control performance during operation. The mold control geometry model is subjected to kinematic simulation analysis to generate the mold control module, in which the kinematic simulation analysis includes ejector motion analysis and spring rebound analysis. Kinematic simulation analysis can help designers verify whether the movement and action of the mold meet the design requirements, and make necessary adjustments and optimizations. The mold control module, mold forming module and mold base plate module are modularly integrated to generate a precision hardware hierarchical three-dimensional model. Module integration can ensure that the various parts of the mold can work in coordination to meet the requirements of the overall design.

[0071] In an embodiment of the present invention, the mold operation control structure data is modeled by using a mold forming module and a mold base module to generate a geometric model of a guide positioning element. The guide positioning element geometric model is analyzed to determine the range of motion of the mold on the X-axis, Y-axis and Z-axis, and to generate mold motion data. The driving force analysis is performed based on the motion data of the mold on each axis to determine the driving force required for the mold motion, and the corresponding driving force data is generated. Based on the mold motion driving force data, the mold ejector mechanism is designed to ensure that it can effectively control the movement of the mold, and the corresponding mechanism data is generated. The spring fasteners in the mold ejector mechanism data are parameterized for subsequent evaluation and design processes. The mold ejector mechanism is evaluated for residual material using the mold ejector spring fastener parameterized data to ensure the accuracy and efficiency of the mold design, and to generate corresponding evaluation data. The cutting blade is designed based on the residual material evaluation data to achieve the precise cutting function of the mold. The guide positioning element geometric model is spatially cut using the cutting blade to generate a mold manipulation control geometric model to ensure the manipulation accuracy and stability of the mold. Perform kinematic simulation analysis on the mold manipulation control geometry model, including ejector motion analysis and spring rebound analysis, to verify the effectiveness and reliability of the mold design. Integrate the mold manipulation control module, mold forming module and mold base module to generate a three-dimensional model of the precision hardware level to ensure the coordination and overall performance of each module.

[0072] Preferably, step S3 comprises the following steps:

[0073] Step S31: performing mold material analysis on the precision hardware hierarchical three-dimensional model to generate precision hardware hierarchical material analysis data; collecting material attributes on the precision hardware hierarchical three-dimensional model to generate precision hardware hierarchical material attribute analysis data;

[0074] Step S32: Based on the material allocation algorithm, material allocation is performed through the precision hardware level material attribute analysis data and the precision hardware level material analysis data to generate precision hardware level material allocation data; the precision hardware level material allocation data is mapped to the precision hardware level three-dimensional model to perform model material association to generate material attribute mapping data;

[0075] Step S33: Formulate model material conversion rules according to the material attribute mapping data to generate material conversion rules; dynamically render the precision hardware hierarchical three-dimensional model through the material conversion rules to generate a precision hardware mold dynamic rendering model.

[0076] The present invention can ensure accurate basic data for the allocation and conversion of mold materials in subsequent steps by performing material analysis and property collection on the precision hardware hierarchical three-dimensional model, thereby improving the accuracy and reliability of mold design. The material allocation algorithm can intelligently allocate suitable materials based on the precision hardware hierarchical material attribute analysis data and material analysis data to meet the requirements of mold design and improve the performance and durability of the mold. Mapping the material allocation data to the precision hardware hierarchical three-dimensional model for model material association can ensure that the mold design is more visually intuitive and help designers to accurately evaluate the appearance and material properties of the mold. By formulating material conversion rules, dynamic rendering of the precision hardware hierarchical three-dimensional model is achieved, allowing designers to intuitively observe the appearance and performance of the mold under different materials, thereby better making design decisions and optimizations.

[0077] As an example of the present invention, refer to Figure 2 As shown, in this example, step S3 includes:

[0078] Step S31: performing mold material analysis on the precision hardware hierarchical three-dimensional model to generate precision hardware hierarchical material analysis data; collecting material attributes on the precision hardware hierarchical three-dimensional model to generate precision hardware hierarchical material attribute analysis data;

[0079] In an embodiment of the present invention, a precision hardware hierarchical three-dimensional model is loaded by using computer-aided design (CAD) software. The model is geometrically analyzed to identify the various components and elements that constitute the mold. According to the structure, function and application scenario of the mold, a suitable material analysis method is selected. This may involve physical testing, computer simulation or reference to existing material data tables. Material analysis is performed on each component or element of the mold, including the physical properties (such as hardness, strength, thermal conductivity, etc.) and chemical properties (such as corrosion resistance, etc.) of the material. In the CAD software, for each component or element, its relevant material attribute information is collected. This attribute information may include visual attributes such as color, texture, gloss, transparency, and physical attributes such as hardness, elastic modulus, and thermal expansion coefficient. If there is an existing material attribute database, the corresponding attribute information can be directly obtained from it. For specific application requirements, it may be necessary to collect some special material attribute information, such as high temperature resistance, corrosion resistance, etc. The data obtained in the process of mold material analysis and material attribute collection is recorded and sorted. This may include establishing a database, making data tables or documents, etc. Ensure the accuracy and completeness of the data for use in subsequent steps.

[0080] Step S32: Based on the material allocation algorithm, material allocation is performed through the precision hardware level material attribute analysis data and the precision hardware level material analysis data to generate precision hardware level material allocation data; the precision hardware level material allocation data is mapped to the precision hardware level three-dimensional model to perform model material association to generate material attribute mapping data;

[0081] In the embodiment of the present invention, a material allocation algorithm is designed, and the algorithm should take into account the precision hardware level material attribute analysis data and the precision hardware level material analysis data. The key to the algorithm design is to determine how to combine the material attribute analysis data with the material analysis data to achieve appropriate material allocation. This may involve methods such as attribute matching and weight adjustment. According to the designed algorithm, the precision hardware level material attribute analysis data and the material analysis data are processed to perform material allocation. Each component or element is matched with a suitable material, and the corresponding precision hardware level material allocation data is generated. The material allocation data is mapped to the precision hardware level three-dimensional model to associate the model material. In CAD software or similar tools, the corresponding material attributes are applied to the model according to the material allocation data of each component or element. This process will generate material attribute mapping data, that is, information that associates the material attributes of each component or element with the actual model. The generated precision hardware level material allocation data and material attribute mapping data are verified to ensure that the allocated material meets the actual requirements.

[0082] Step S33: Formulate model material conversion rules according to the material attribute mapping data to generate material conversion rules; dynamically render the precision hardware hierarchical three-dimensional model through the material conversion rules to generate a precision hardware mold dynamic rendering model.

[0083] In an embodiment of the present invention, by analyzing the material attribute mapping data, the performance and influence of each material attribute on the model are understood. According to the analyzed material attribute mapping data, model material conversion rules are formulated. These rules will guide how to convert the original material attribute data into material attributes suitable for dynamic rendering. This may involve conversion rules in terms of color, glossiness, reflectivity, etc. Based on the formulated conversion rules, an algorithm or script is written to realize the dynamic conversion of the material. This may require the use of a computer graphics library or software tool for coding and testing. The written algorithm or script is tested and debugged to ensure that it can correctly convert the material attributes of the model according to the rules and generate the expected dynamic rendering effect. The written material conversion algorithm is applied to the precision hardware hierarchical three-dimensional model. This may require integration with existing modeling software or rendering engines to ensure smooth conversion and dynamic rendering of material attributes. By applying the material conversion rules, the precision hardware hierarchical three-dimensional model is dynamically rendered to generate a dynamic rendering model of a precision hardware mold. The generated dynamic rendering model is evaluated and optimized to ensure that its quality and performance meet the requirements. This may involve adjusting the parameters of the material conversion rules or algorithms to improve the rendering effect or reduce the rendering time.

[0084] Preferably, step S33 includes the following steps:

[0085] Step S331: dividing the mold model operation process of the precision hardware hierarchical three-dimensional model according to the material attribute mapping data to generate model operation process division data;

[0086] Step S332: collecting model operation environment data on the model operation process division data to obtain model operation environment collection data; performing operation part environment impact identification on the model operation process division data based on the model operation environment collection data to generate model operation part environment change identification data, wherein the model operation part environment change identification data includes high temperature impact data and impact impact data;

[0087] Step S333: adding initial material to the precision hardware hierarchical three-dimensional model to generate initial model material data; monitoring the data change of the model operation part environment change identification data based on the initial model material data, when high temperature impact data is monitored, the corresponding model operation part of the precision hardware hierarchical three-dimensional model is converted to a high temperature resistant alloy material to generate a high temperature conversion material rule; when impact impact data is monitored, the corresponding model operation part of the precision hardware hierarchical three-dimensional model is converted to a high-strength alloy steel material to generate an impact conversion material rule;

[0088] Step S334: Integrate the high temperature conversion material rule and the impact conversion material rule to generate a material conversion rule; perform a model field of view distance analysis on the precision hardware hierarchical three-dimensional model through the material conversion rule to generate model field of view distance data;

[0089] Step S335: Rendering the precision hardware hierarchical three-dimensional model by field of view distance segment based on the model field of view distance data, thereby generating a precision hardware mold hierarchical rendering model.

[0090] By dividing the mold model operation process, the present invention can better understand the characteristics and requirements of the model at different operation stages, and provide a clear data basis for subsequent steps. By collecting model operation environment data and identifying environmental changes, the impact on the model can be timely understood, providing a basis for selecting appropriate material conversion. According to the model operation environment change identification data, high temperature and impact conversion material rules are formulated, which can ensure that the mold has appropriate material properties under different environmental conditions and improve the durability and stability of the mold. Through the analysis and data generation of the model's field of view distance, the display effect and visible range of the model can be better understood, providing an important reference basis for the subsequent rendering process. Field of view distance segment rendering based on the model field of view distance data can ensure that the mold presents a more realistic and accurate effect during the rendering process, and improve the visualization and display effects of the mold.

[0091] As an example of the present invention, refer to Figure 3 As shown, in this example, step S33 includes:

[0092] Step S331: dividing the mold model operation process of the precision hardware hierarchical three-dimensional model according to the material attribute mapping data to generate model operation process division data;

[0093] In an embodiment of the present invention, material attribute mapping data related to the three-dimensional model of the precision hardware hierarchy is collected. These data may include information on mechanical properties, thermal properties, chemical properties, etc. of different materials. The operation process of the three-dimensional model of the precision hardware hierarchy is analyzed. This may involve the operation process of the mold at different stages such as design, processing, and assembly. The collected material attribute mapping data is applied to the model operation process, and the mold model operation process is divided according to the requirements of different material attributes. For example, according to the use requirements of the mold in a high temperature environment, the operation process is divided into a high temperature operation stage and a normal temperature operation stage. According to the division of the model operation process, the corresponding model operation process division data is generated. These data may include information such as the stage division of the operation process, the material requirements of each stage, and the operation steps. The generated model operation process division data is verified and adjusted to ensure that it is consistent with the actual operation process, and further corrections and improvements are made as needed.

[0094] Step S332: collecting model operation environment data on the model operation process division data to obtain model operation environment collection data; performing operation part environment impact identification on the model operation process division data based on the model operation environment collection data to generate model operation part environment change identification data, wherein the model operation part environment change identification data includes high temperature impact data and impact impact data;

[0095] In an embodiment of the present invention, environmental data is collected when the model is operated in an actual operating environment. This may involve installing sensors or monitoring equipment to collect data on environmental parameters such as temperature, pressure, and humidity, and ensure the accuracy and integrity of the data. The collected model operating environment data is analyzed, including analysis of environmental parameters such as temperature changes, pressure changes, and humidity changes. This can help identify the environmental changes faced by the model at different operating locations. Based on the model operating environment data, the model operation process division data is used to identify the environmental impact of the operating location. This includes identifying the high temperature impact and impact impact that may occur at different operating locations. The high temperature impact data may include information such as the stability of the model in a high temperature environment and changes in material properties, while the impact impact data may involve the model's bearing capacity and deformation when subjected to external impact. After identifying the environmental changes at different operating locations, model operating location environmental change identification data is generated. These data may include information such as the changes in each operating location under different environmental conditions, the impact on model performance and stability, etc. The generated model operating location environmental change identification data is integrated, and a corresponding report or data document is generated. These data can provide important references for subsequent model optimization, improvement, and design.

[0096] Step S333: adding initial material to the precision hardware hierarchical three-dimensional model to generate initial model material data; monitoring the data change of the model operation part environment change identification data based on the initial model material data, when high temperature impact data is monitored, the corresponding model operation part of the precision hardware hierarchical three-dimensional model is converted to a high temperature resistant alloy material to generate a high temperature conversion material rule; when impact impact data is monitored, the corresponding model operation part of the precision hardware hierarchical three-dimensional model is converted to a high-strength alloy steel material to generate an impact conversion material rule;

[0097] In the embodiment of the present invention, by targeting the precision hardware hierarchical three-dimensional model, it is first necessary to add the initial material to it. This can be achieved by assigning material properties to various parts of the model to ensure that each part has corresponding initial material properties. The environmental change identification data of the model operation part generated in step S332 is used to monitor the environmental changes of different operation parts of the model. When high temperature impact data or impact impact data is monitored, the corresponding processing rules are triggered. When high temperature impact data is monitored, according to the pre-set rules, the affected model operation parts are converted to high temperature resistant alloy materials. This may involve selecting materials suitable for high temperature environments from a known alloy material library and applying them to the corresponding parts of the model. When impact impact data is monitored, according to the pre-set rules, the affected model operation parts are converted to high-strength alloy steel materials. This also requires selecting suitable materials from the alloy steel material library and applying them to the corresponding parts of the model. The generated high temperature conversion material rules and impact conversion material rules are applied to the corresponding parts of the precision hardware hierarchical three-dimensional model to ensure that the model can have better performance and stability in a high temperature environment or when impacted.

[0098] Step S334: Integrate the high temperature conversion material rule and the impact conversion material rule to generate a material conversion rule; perform a model field of view distance analysis on the precision hardware hierarchical three-dimensional model through the material conversion rule to generate model field of view distance data;

[0099] In an embodiment of the present invention, the high temperature conversion material rule and the impact conversion material rule generated in step S333 are integrated. This may involve fusing or integrating the two rules into a complete material conversion rule set so that multiple environmental factors such as high temperature and impact can be considered simultaneously when necessary. Based on the rule integration, a comprehensive material conversion rule is generated. These rules may include automatically selecting a suitable material conversion scheme according to environmental changes to ensure that the model can have appropriate material properties under different environmental conditions. Using the generated material conversion rules, a model field of view distance analysis is performed on the precision hardware hierarchical three-dimensional model. This may involve evaluating the distance and relative position of different parts in the model to determine which parts may need to be converted according to the rules. Based on the results of the model field of view distance analysis, model field of view distance data is generated. These data can be used to guide subsequent material conversion operations to ensure that the positions and relationships of different parts in the model are taken into account when performing material conversion.

[0100] Step S335: Rendering the precision hardware hierarchical three-dimensional model by field of view distance segment based on the model field of view distance data, thereby generating a precision hardware mold hierarchical rendering model.

[0101] In an embodiment of the present invention, the accuracy and completeness of the data are ensured by using the model field of view distance data generated in step S334. According to the model field of view distance data, the precision hardware hierarchical three-dimensional model is rendered by field of view distance segmentation. This may involve dividing the model into different parts or areas and rendering them according to their distance in the field of view. Generally, the closer parts will be clearer, while the farther parts will appear blurred. Combined with the results of the field of view distance segment rendering, a precision hardware mold hierarchical rendering model is generated. This model will dynamically adjust the rendering effect of the model according to the observer's perspective and distance, so that the model can present a realistic effect at different viewing angles and distances. Adjust the rendering effect as needed to ensure that all parts of the model can be clearly seen at different field of view distances, and can accurately reflect the hierarchical structure and detail features of the model. The generated precision hardware mold hierarchical rendering model is verified and optimized to ensure that it meets the design requirements and can meet the user's visual needs.

[0102] Preferably, step S335 includes the following steps:

[0103] Step S3351: confirming the initial point position of the view of the precision hardware layered three-dimensional model based on the model view distance data, and generating the model observation initial view position; analyzing the view range of the precision hardware layered three-dimensional model according to the model observation initial view position, and generating the model observation view range data;

[0104] Step S3352: Perform model corner point analysis on the model observation field of view range data to generate model corner point data; use the model corner point data to connect the corner points of the model observation initial field of view position to generate field of view corner point connection lines; perform line dimension reduction projection on the field of view corner point connection lines to generate model field of view corner point dimension reduction connection lines;

[0105] Step S3353: performing projection distance analysis on the dimension reduction connection lines of the model view corner points based on the model view distance data to generate model view corner point projection distance data; dividing the model view corner point projection distance data into distance segments to generate high-distance observation segments, medium-distance observation segments, and low-distance observation segments;

[0106] Step S3354: performing hierarchical precision rendering on the precision hardware hierarchical three-dimensional model according to the high-distance observation segment, the medium-distance observation segment, and the low-distance observation segment to generate a precision hardware mold hierarchical rendering model;

[0107] The specific steps of layered precision rendering include:

[0108] When the initial viewing angle of the model observation is in the high-distance observation segment, the precision hardware level three-dimensional model is rendered with low precision; when the initial viewing angle of the model observation is in the medium-distance observation segment, the precision hardware level three-dimensional model is rendered with medium precision; when the initial viewing angle of the model observation is in the low-distance observation segment, the precision hardware level three-dimensional model is rendered with high precision.

[0109] The present invention determines the initial viewing angle position of the model observation by analyzing the model field of view distance data, and generates the model observation field of view range data. At the same time, by analyzing and connecting the corner points of the model, the field of view corner point connection line is generated, which helps to determine the position and shape of the model in the field of view. The model field of view distance data is used to perform distance analysis and division, and the model field of view corner point projection distance data is divided into a high-distance observation segment, a medium-distance observation segment and a low-distance observation segment. This helps to determine the accuracy and rendering effect of the model observed in different distance ranges. According to the distance data of different observation segments, the precision hardware hierarchical three-dimensional model is rendered with hierarchical accuracy. According to the situation of the initial viewing angle position of the model observation in different observation segments, low, medium and high precision rendering processing is performed. In this way, the rendering accuracy of the model can be adjusted according to the distance and viewing angle of the observer to achieve the best visual effect and performance requirements. Through hierarchical accuracy rendering, a precision hardware mold hierarchical rendering model is generated. This model takes into account the observation requirements within different distance ranges, and provides a more accurate reference and visual display for subsequent mold design and manufacturing.

[0110] As an example of the present invention, refer to Figure 4 As shown, in this example, step S335 includes:

[0111] Step S3351: confirming the initial point position of the view of the precision hardware layered three-dimensional model based on the model view distance data, and generating the model observation initial view position; analyzing the view range of the precision hardware layered three-dimensional model according to the model observation initial view position, and generating the model observation view range data;

[0112] In an embodiment of the present invention, it is necessary to obtain the visual field distance data related to the model. This can be obtained by a sensor, a camera or other measuring equipment, or virtual distance data can be generated in a computer simulation environment. The obtained model visual field distance data is used to determine the initial point position of the observer's visual field. This can select a suitable position as the observer's initial point according to the distribution of the distance data to ensure that the model can be fully displayed within the visual field. According to the confirmed initial point position of the visual field, the initial visual field position of the model observation is generated. This can be a three-dimensional coordinate point, indicating the position of the observer relative to the model. Using the model observation initial visual field position, the precision hardware hierarchical three-dimensional model is analyzed for the visual field range. This may involve determining the width, height and depth of the visual field, as well as the visual field angle related to the observer's position. According to the results of the visual field analysis, the visual field range data of the model observation is generated. This may be a set of parameters describing the visual field range, such as the visual field angle, the visual field distance, etc.

[0113] Step S3352: Perform model corner point analysis on the model observation field of view range data to generate model corner point data; use the model corner point data to connect the corner points of the model observation initial field of view position to generate field of view corner point connection lines; perform line dimension reduction projection on the field of view corner point connection lines to generate model field of view corner point dimension reduction connection lines;

[0114] In an embodiment of the present invention, corner point analysis is performed on the model observation field of view data. This means that the corner point positions at the edge or key parts of the model can be determined by calculating geometric features, boundary detection algorithms or feature extraction techniques. Model corner point data is generated, and the position coordinates and other relevant information of each corner point are recorded. Using the model corner point data, the initial viewing angle position of the model observation is connected with each corner point to form a field of view corner point connection line. This can be achieved through simple geometric calculations, such as calculating a straight line segment between two points. The field of view corner point connection line is subjected to a line dimensionality reduction projection. This means projecting the three-dimensional connection line onto a two-dimensional plane for better display or analysis. The projection can be performed using methods such as perspective projection or orthogonal projection. Generate a model field of view corner point dimensionality reduction connection line, and record the projected connection line information, such as the starting point, the end point, the length, etc.

[0115] Step S3353: performing projection distance analysis on the dimension reduction connection lines of the model view corner points based on the model view distance data to generate model view corner point projection distance data; dividing the model view corner point projection distance data into distance segments to generate high-distance observation segments, medium-distance observation segments, and low-distance observation segments;

[0116] In an embodiment of the present invention, the projection distance of the dimensionality reduction connection lines of the model field of view corner points is analyzed based on the model field of view distance data. This can be achieved by calculating the distance from each point on each connection line to the viewing angle position. Generate the projection distance data of the model field of view corner points, and record the projection distance from each corner point to the viewing angle. Divide the projection distance data of the model field of view corner points into distance segments. According to the distribution of distance data and actual needs, the distance can be divided into three observation segments: high, medium and low. High-distance observation segment: areas with longer distances may require a larger scale or a different processing method. Medium-distance observation segment: areas with moderate distances, which are the main observation range. Low-distance observation segment: areas with shorter distances may require higher precision or special processing.

[0117] Step S3354: performing hierarchical precision rendering on the precision hardware hierarchical three-dimensional model according to the high-distance observation segment, the medium-distance observation segment, and the low-distance observation segment to generate a precision hardware mold hierarchical rendering model, wherein the hierarchical precision rendering specific steps include:

[0118] When the initial viewing angle of the model observation is in the high-distance observation segment, the precision hardware level three-dimensional model is rendered with low precision; when the initial viewing angle of the model observation is in the medium-distance observation segment, the precision hardware level three-dimensional model is rendered with medium precision; when the initial viewing angle of the model observation is in the low-distance observation segment, the precision hardware level three-dimensional model is rendered with high precision.

[0119] In an embodiment of the present invention, the model field of view corner projection distance data generated according to the aforementioned steps is divided into a high-distance observation segment, a medium-distance observation segment, and a low-distance observation segment. When the initial viewing angle position of the model observation is in the high-distance observation segment, low-precision rendering is selected. When the initial viewing angle position of the model observation is in the medium-distance observation segment, medium-precision rendering is selected. When the initial viewing angle position of the model observation is in the low-distance observation segment, high-precision rendering is selected. Low-precision rendering: Use a simpler model representation to reduce details to improve performance and rendering speed. This may include using low-polygon models or simplified texture mapping. Medium-precision rendering: Rendering using a medium level of model and texture quality while maintaining a certain degree of detail to balance performance and visual quality. High-precision rendering: Maintain the highest level of model and texture quality to show the richest details and realism.

[0120] Preferably, step S4 comprises the following steps:

[0121] Step S41: performing ray tracing simulation on the hierarchical rendering model of the precision hardware mold to generate ray tracing simulation data; performing texture mapping on the hierarchical rendering model of the precision hardware mold according to the ray tracing simulation data to generate a comprehensive rendering model of the precision hardware mold;

[0122] Step S42: Perform rendering degree analysis on the comprehensive rendering model of precision hardware molds to generate rendering degree analysis data; divide the rendering degree analysis data into data sets to generate a model training set and a model test set; perform model training on the model training set using a support vector machine algorithm to generate a mold rendering performance training model; perform model testing on the mold rendering performance training model using a model test set to generate a mold rendering performance prediction model;

[0123] Step S43: Import the rendering degree analysis data into the mold rendering performance prediction model to perform rendering performance evaluation and generate mold rendering performance evaluation data; perform rendering adjustment on the precision hardware mold comprehensive rendering model based on the mold rendering performance evaluation data to achieve real-time dynamic adjustment of the rendering of the precision hardware mold three-dimensional design model.

[0124] The present invention generates simulation data through ray tracing simulation, and uses these data to perform texture mapping on the hierarchical rendering model of precision hardware molds. This helps improve the visual quality and sense of reality of the model, making it more realistic and attractive. The rendering degree analysis is performed on the comprehensive rendering model of precision hardware molds to generate rendering degree analysis data. Then, these data are divided into a training set and a test set, and the training set is trained with a support vector machine algorithm to generate a mold rendering performance training model. The model is tested with a model test set to generate a mold rendering performance prediction model. The generation and training of these models help to improve the efficiency and accuracy of mold rendering. The rendering degree analysis data is imported into the mold rendering performance prediction model for rendering performance evaluation, and mold rendering performance evaluation data is generated. Based on these evaluation data, the rendering adjustment is performed on the comprehensive rendering model of precision hardware molds to achieve real-time dynamic adjustment of rendering. In this way, the rendering effect can be optimized according to actual needs and performance evaluation, thereby achieving better visual effects and user experience.

[0125] In an embodiment of the present invention, the rendering degree analysis is performed on the comprehensive rendering model of precision hardware molds to evaluate its rendering quality and efficiency. This may include checking the clarity, light and shadow effects, color accuracy and other aspects of the rendering results. The rendering degree analysis data is divided into a model training set and a model test set, usually by cross-validation or random sampling. The model training set is trained using a support vector machine algorithm to construct a mold rendering performance training model. Support vector machine is a supervised learning algorithm suitable for classification and regression tasks. The rendering degree analysis data is imported into the mold rendering performance prediction model for rendering performance evaluation to generate mold rendering performance evaluation data. This can help evaluate the prediction accuracy and performance of the model. Based on the mold rendering performance evaluation data, the comprehensive rendering model of precision hardware molds is adjusted. This may involve adjusting the parameters of the model, optimizing the rendering algorithm, or improving the data processing process to improve the rendering effect and performance.

[0126] The beneficial effect of the present invention is that the repair data generated by acquiring the surface topology data of the precision hardware mold, and after three-dimensional mesh conversion and feature repair compensation, ensures the integrity and accuracy of the mold data, and provides a reliable basis for subsequent work. The repair data is decomposed into the structure of the precision hardware mold model, and the generated model structure data helps to clearly understand the composition structure of the mold, which facilitates the subsequent modeling work. Through the material conversion rule formulation and dynamic rendering of step S3, the material conversion rule is applied to the precision hardware hierarchical three-dimensional model, and dynamic rendering is realized, so that the design and rendering of the mold are more integrated, and the design efficiency is improved. Rendering degree analysis and rendering performance evaluation, as well as rendering adjustment based on evaluation data, help to optimize the rendering effect of the mold, improve the visual presentation quality, and enable designers to more accurately evaluate the appearance and performance of the mold. Therefore, the present invention improves the loadability and flexibility of rendering through precise data processing, model structure decomposition, dynamic rendering and performance evaluation.

[0127] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0128] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A 3D design model rendering method based on precision hardware molds, characterized in that: The following steps are involved: Step S1: Acquire the surface topology data of precision hardware molds; Perform 3D mesh conversion on the surface topology data of precision hardware molds to generate 3D mesh conversion data of precision hardware molds; perform feature repair compensation on the 3D mesh conversion data of precision hardware molds to generate repair data of precision hardware molds; Step S2: Decomposing the precision hardware mold repair data into a precision hardware mold model structure to generate precision hardware mold model structure data; performing hierarchical three-dimensional modeling based on the precision hardware mold model structure data to generate a precision hardware hierarchical three-dimensional model; Step S3: Formulate model material conversion rules for the precision hardware hierarchical three-dimensional model to generate material conversion rules; dynamically render the precision hardware hierarchical three-dimensional model through the material conversion rules to generate a dynamic rendering model of a precision hardware mold; Step S4: performing rendering degree analysis on the hierarchical rendering model of the precision hardware mold to generate rendering degree analysis data; Perform rendering performance evaluation on the rendering degree analysis data to generate mold rendering performance evaluation data; Based on the mold rendering performance evaluation data, the comprehensive rendering model of the precision hardware mold is rendered and adjusted to achieve real-time dynamic adjustment of the rendering of the precision hardware mold three-dimensional design model.

2. The method for rendering a three-dimensional design model based on a precision hardware mold according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: Scan the surface of the precision hardware mold using an optical scanner to obtain surface topology data of the precision hardware mold; Step S12: preprocessing the surface topology data of the precision hardware mold to generate standard surface topology data of the precision hardware mold, wherein the data preprocessing includes data cleaning, data outlier removal, data integration and data standardization; Step S13: reconstructing the surface topology data of the standard precision hardware mold to generate precision hardware mold reconstruction data; performing three-dimensional mesh conversion on the precision hardware mold reconstruction data to generate precision hardware mold three-dimensional mesh conversion data; performing surface fitting on the precision hardware mold three-dimensional mesh conversion data to generate precision hardware mold three-dimensional mesh surface fitting data; Step S14: extract local features of the three-dimensional mesh surface fitting data of the precision hardware mold to generate local feature data of the precision hardware mold, wherein the local feature data of the precision hardware mold includes the edge data of the hardware mold and the curvature data of the hardware mold; perform feature repair and compensation on the surface topology data of the precision hardware mold based on the edge data of the hardware mold and the curvature data of the hardware mold to generate precision hardware mold repair data.

3. The method for rendering a three-dimensional design model based on a precision hardware mold according to claim 1, characterized in that: Step S2 includes the following steps: Step S21: extracting geometric features from the precision hardware mold repair data to generate geometric feature data of the precision hardware mold, wherein the geometric feature data of the precision hardware mold includes normal data of the hardware mold and area data of the hardware mold; Step S22: performing feature classification description on the precision hardware mold according to the hardware mold normal data and the hardware mold area data, and generating precision hardware mold classification feature data, wherein the precision hardware mold classification feature data includes precision hardware mold boundary feature data and precision hardware mold concave-convex feature data; Step S23: Decomposing the precision hardware mold model structure through the precision hardware mold boundary feature data and the precision hardware mold concave-convex feature data to generate precision hardware mold model structure data, wherein the precision hardware mold model structure data includes mold base plate structure data, mold molding structure data and mold operation control structure data; Step S24: Perform hierarchical three-dimensional modeling on the mold base plate structure data, mold forming structure data and mold operation control structure data to generate a precision hardware hierarchical three-dimensional model, wherein the hierarchical three-dimensional modeling includes the mold base plate module modeling process, the mold forming module modeling process and the mold operation control module modeling process.

4. The method for rendering a three-dimensional design model based on a precision hardware mold according to claim 3 is characterized in that: The mold base module modeling process in step S24 includes the following steps: Perform mold base plate structure analysis on the mold base plate structure data to generate mold base plate structure analysis data; perform geometric modeling on the mold base plate structure analysis data to generate a base plate geometric model; Performing a mechanical characteristic analysis of the base plate material on the base plate geometric model to generate base plate mechanical characteristic data, wherein the base plate mechanical characteristic analysis includes base plate strength mechanical analysis and base plate stiffness mechanical analysis; performing a base plate force analysis on the base plate geometric model according to the base plate mechanical characteristic data to generate base plate force analysis data; Perform force uniformity analysis on the force analysis data of the bottom plate to generate the force area uniformity analysis data of the bottom plate; optimize the layout of the bottom plate positioning holes based on the force area uniformity analysis data of the bottom plate to generate the optimization data of the layout of the bottom plate positioning holes; perform bolt hole fixation through the optimization data of the layout of the bottom plate positioning holes to generate the position data of the bolt holes for fixing the bottom plate; The thermal stability of the base plate is analyzed on the base plate geometric model through the base plate fixing bolt hole position data and the base plate positioning hole layout optimization data, and the base plate thermal stability analysis data is generated; based on the base plate thermal stability analysis data and the base plate force analysis data, the model structure heat dissipation adjustment is performed on the base plate geometric model to generate the mold base plate module.

5. The method for rendering a three-dimensional design model based on a precision hardware mold according to claim 3 is characterized in that: The mold forming module modeling process in step S24 includes the following steps: Performing mold cavity geometry analysis on the mold molding structure data to generate mold cavity geometry analysis data; performing mold cavity geometry modeling on the mold cavity geometry analysis data to generate a mold cavity geometry model; Calculate the volume of the internal cavity space of the mold according to the mold base plate module of the mold cavity geometry model to obtain the internal space volume data of the mold cavity; design the mold core model based on the internal space volume data of the mold cavity to generate the mold core geometry model; Based on the mold cavity geometry model and the mold core geometry model, the mold internal cooling channel layout is performed to generate the mold internal cooling channel data; the mold internal cooling channel data is subjected to channel intersection analysis to generate the mold internal cooling channel intersection data; the mold internal cooling channel intersection data is compared with the preset standard channel intersection threshold, and when the mold internal cooling channel intersection data is greater than or equal to the preset standard channel intersection threshold, the corresponding mold internal cooling channel is segmented to generate a high-load cooling channel; when the mold internal cooling channel intersection data is less than the preset standard channel intersection threshold, the corresponding mold internal cooling channel is marked to generate a low-load cooling channel; Perform heat conduction simulation based on high-load cooling channels and low-load cooling channels to generate high-load channel heat conduction simulation data and low-load area heat conduction simulation data; arrange feed ports and exhaust ports based on high-load channel heat conduction simulation data and low-load area heat conduction simulation data to generate feed port quantity data and exhaust port quantity data; The cavity filling bubble area of ​​the high-load cooling channel and the low-load cooling channel is divided by the feed port number data and the exhaust port number data to generate a high-bubble area and a low-bubble area; the bubble hot melt analysis is performed on the high-load channel heat conduction simulation data and the low-load area heat conduction simulation data using the high-bubble area and the low-bubble area. When the high-load cooling channel is in the high-bubble area, the feed port number data and the exhaust port number data are adjusted by the first air port so that the exhaust port number data is always greater than the feed port number data, and the first feed and exhaust adjustment data is generated; when the low-load cooling channel is in the high-bubble area, the feed port number data and the exhaust port number data are adjusted by the second air port so that the exhaust port number data is greater than or equal to the feed port number data, and the second feed and exhaust adjustment data is generated; When the high-load cooling channel is in the low-bubble area or the low-load cooling channel is in the low-bubble area, the third air port adjustment is performed on the feed port quantity data and the exhaust port quantity data, so that the feed port quantity data is greater than the exhaust port quantity data, and the feed and exhaust third adjustment data is generated; the working filling simulation is performed according to the feed and exhaust first adjustment data, the feed and exhaust second adjustment data, and the feed and exhaust third adjustment data to generate the mold forming module.

6. The method for rendering a three-dimensional design model based on a precision hardware mold according to claim 3, characterized in that: The mold operation control module modeling process in step S24 includes the following steps: The mold forming module and the mold base module are used to model the guide element of the mold operation control structure data to generate the guide positioning element geometric model; the mold motion space analysis is performed on the guide positioning element geometric model to generate the mold X-axis motion data, the mold Y-axis motion data and the mold Z-axis motion data; According to the X-axis motion data, Y-axis motion data and Z-axis motion data of the mold, the driving force analysis of the geometric model of the guide positioning element is performed to generate the mold motion driving force data; based on the mold motion driving force data, the ejector mechanism of the guide positioning element geometric model is designed to generate the mold ejector mechanism data; The mold ejector mechanism data is parameterized by the spring fastener to generate the mold ejector spring fastener parameterized data; the mold ejector mechanism data is evaluated for mold residual material by using the mold ejector spring fastener parameterized data to generate the mold residual material evaluation data; Design the cutting blade based on the mold residual material evaluation data to generate the mold cutting blade; use the mold cutting blade to perform space cutting of the mold model on the geometric model of the guide positioning element based on the mold ejector mechanism data to generate the mold manipulation control geometric model; perform kinematic simulation analysis on the mold manipulation control geometric model to generate the mold manipulation control module, where the kinematic simulation analysis includes ejector motion analysis and spring rebound analysis; The mold manipulation control module, mold forming module and mold base module are integrated to generate a precise hardware hierarchical three-dimensional model.

7. The method for rendering a three-dimensional design model based on a precision hardware mold according to claim 1, characterized in that: Step S3 includes the following steps: Step S31: performing mold material analysis on the precision hardware hierarchical three-dimensional model to generate precision hardware hierarchical material analysis data; collecting material attributes on the precision hardware hierarchical three-dimensional model to generate precision hardware hierarchical material attribute analysis data; Step S32: Based on the material allocation algorithm, material allocation is performed through the precision hardware level material attribute analysis data and the precision hardware level material analysis data to generate precision hardware level material allocation data; the precision hardware level material allocation data is mapped to the precision hardware level three-dimensional model to perform model material association to generate material attribute mapping data; Step S33: Formulate model material conversion rules according to the material attribute mapping data to generate material conversion rules; dynamically render the precision hardware hierarchical three-dimensional model through the material conversion rules to generate a precision hardware mold dynamic rendering model.

8. The method for rendering a three-dimensional design model based on a precision hardware mold according to claim 7, characterized in that: Step S33 includes the following steps: Step S331: dividing the mold model operation process of the precision hardware hierarchical three-dimensional model according to the material attribute mapping data to generate model operation process division data; Step S332: collecting model operation environment data on the model operation process division data to obtain model operation environment collection data; performing operation part environment impact identification on the model operation process division data based on the model operation environment collection data to generate model operation part environment change identification data, wherein the model operation part environment change identification data includes high temperature impact data and impact impact data; Step S333: adding initial material to the precision hardware hierarchical three-dimensional model to generate initial model material data; monitoring the data change of the model operation part environment change identification data based on the initial model material data, when high temperature impact data is monitored, the corresponding model operation part of the precision hardware hierarchical three-dimensional model is converted to a high temperature resistant alloy material to generate a high temperature conversion material rule; when impact impact data is monitored, the corresponding model operation part of the precision hardware hierarchical three-dimensional model is converted to a high-strength alloy steel material to generate an impact conversion material rule; Step S334: Integrate the high temperature conversion material rule and the impact conversion material rule to generate a material conversion rule; perform a model field of view distance analysis on the precision hardware hierarchical three-dimensional model through the material conversion rule to generate model field of view distance data; Step S335: Rendering the precision hardware hierarchical three-dimensional model by field of view distance segment based on the model field of view distance data, thereby generating a precision hardware mold hierarchical rendering model.

9. The method for rendering a three-dimensional design model based on a precision hardware mold according to claim 8, characterized in that: Step S335 includes the following steps: Step S3351: confirming the initial point position of the view of the precision hardware layered three-dimensional model based on the model view distance data, and generating the model observation initial view position; analyzing the view range of the precision hardware layered three-dimensional model according to the model observation initial view position, and generating the model observation view range data; Step S3352: Perform model corner point analysis on the model observation field of view range data to generate model corner point data; use the model corner point data to connect the corner points of the model observation initial field of view position to generate field of view corner point connection lines; perform line dimension reduction projection on the field of view corner point connection lines to generate model field of view corner point dimension reduction connection lines; Step S3353: performing projection distance analysis on the dimension reduction connection lines of the model view corner points based on the model view distance data to generate model view corner point projection distance data; dividing the model view corner point projection distance data into distance segments to generate high-distance observation segments, medium-distance observation segments, and low-distance observation segments; Step S3354: performing hierarchical precision rendering on the precision hardware hierarchical three-dimensional model according to the high-distance observation segment, the medium-distance observation segment, and the low-distance observation segment to generate a precision hardware mold hierarchical rendering model; The specific steps of layered precision rendering include: When the initial viewing angle of the model observation is in the high-distance observation segment, the precision hardware level three-dimensional model is rendered with low precision; when the initial viewing angle of the model observation is in the medium-distance observation segment, the precision hardware level three-dimensional model is rendered with medium precision; when the initial viewing angle of the model observation is in the low-distance observation segment, the precision hardware level three-dimensional model is rendered with high precision.

10. The method for rendering a three-dimensional design model based on a precision hardware mold according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: performing ray tracing simulation on the hierarchical rendering model of the precision hardware mold to generate ray tracing simulation data; performing texture mapping on the hierarchical rendering model of the precision hardware mold according to the ray tracing simulation data to generate a comprehensive rendering model of the precision hardware mold; Step S42: Perform rendering degree analysis on the comprehensive rendering model of precision hardware molds to generate rendering degree analysis data; divide the rendering degree analysis data into data sets to generate a model training set and a model test set; perform model training on the model training set using a support vector machine algorithm to generate a mold rendering performance training model; perform model testing on the mold rendering performance training model using a model test set to generate a mold rendering performance prediction model; Step S43: Import the rendering degree analysis data into the mold rendering performance prediction model to perform rendering performance evaluation and generate mold rendering performance evaluation data; perform rendering adjustment on the precision hardware mold comprehensive rendering model based on the mold rendering performance evaluation data to achieve real-time dynamic adjustment of the rendering of the precision hardware mold three-dimensional design model.

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