Method and system for generating glass mold surface

Abstract

The invention relates to the technical field of generation of glass mold surfaces, in particular to a method and a system for generating a glass mold surface. The method comprises the following steps: acquiring glass design data, extracting raw materials according to the design data, and performing microscopic characteristic evaluation; the thermal phase change behavior and the thermally induced damage state of the material are analyzed, and microdefects are calculated; constructing a glass mold surface shape, and constructing an initial mold surface in combination with defect data; by simulating a manufacturing process, flaws of finished glass are analyzed, and a mold surface is optimized. According to the method, high-quality generation of a glass mold surface is ensured through multi-level micro analysis and simulation optimization, and the method is suitable for manufacturing high-precision optical glass; according to the invention, the generation method of the glass mold surface is optimized, so that the generation precision of the glass mold surface is higher.

Description

Technical Field

[0001] The present invention relates to the technical field of glass mold surface generation, and in particular to a glass mold surface generation method and system. Background Art

[0002] With the continuous development of modern industry, glass products are increasingly used in many fields such as construction, automobiles, home appliances, electronics, etc. Traditional glass processing technology mainly relies on manual or simple mechanical processing, which is inefficient and the quality of finished products is uneven. In order to meet the market demand for high-quality and high-precision glass products, especially in mold manufacturing and surface treatment, it is particularly important to develop an efficient, accurate and cost-controlled glass mold surface generation method. With the rapid development of computer technology, numerical control technology and laser processing technology, new glass processing technologies have gradually been proposed, and these technologies have shown good application prospects in improving the efficiency and quality of glass mold surface generation. For example, the use of CNC machine tools for precision cutting and grinding of glass can effectively realize the processing of glass mold surfaces with complex shapes. At the same time, laser processing technology is increasingly used in micro-machining of glass surfaces due to its high energy density and excellent focusing characteristics. However, the traditional method for generating glass mold surfaces has the problems of low glass mold surface generation accuracy and poor optical properties of mold surface generated glass. Summary of the invention

[0003] Based on this, it is necessary to provide a method and system for generating a glass mold surface to solve at least one of the above technical problems.

[0004] To achieve the above object, a method for generating a glass mold surface is provided, the method comprising the following steps:

[0005] Step S1: Acquire glass design data; extract glass raw materials according to the glass design data to obtain glass raw material data; evaluate optical microscopic properties according to the glass raw material data to obtain glass optical microscopic property data;

[0006] Step S2: Analyze the thermal phase change behavior according to the microstructure data of the glass material to obtain the microscopic thermal phase change behavior data of the glass; evaluate the thermal damage state according to the microscopic thermal phase change behavior data of the glass to obtain the optical thermal damage state data of the glass; calculate the thermal phase change microscopic defects of the glass according to the optical thermal damage state data of the glass to obtain the thermal phase change microscopic defect data of the glass;

[0007] Step S3: constructing a glass mold surface shape according to the glass design data to obtain glass mold surface shape data; constructing an initial glass mold surface according to the glass thermal phase change micro defect data and the glass mold surface shape data to obtain initial glass mold surface data;

[0008] Step S4: Perform glass manufacturing simulation according to the initial glass mold surface data to obtain glass manufacturing simulation data; perform glass defect analysis on the finished glass product according to the glass manufacturing simulation data to obtain glass finished product defect data; perform mold surface optimization on the initial glass mold surface data according to the glass finished product defect data to obtain glass mold surface optimization data. Perform glass mold surface generation operation according to the glass mold surface optimization data.

[0009] The present invention ensures that the mold design is highly consistent with the requirements of the final product by obtaining glass design data, and provides an accurate basis for subsequent material selection and characteristic evaluation. By extracting glass raw materials, it can be ensured that the selected materials have excellent physical and chemical properties and are suitable for specific application scenarios. This process can quantify the optical properties of the material, such as transmittance, refractive index, etc., to provide necessary optical parameter support for subsequent mold design and ensure the optical performance of the product in use. By analyzing the thermal phase change behavior of the microstructure of the glass material, the performance of the material in a high temperature environment is identified, and temperature adaptability data is provided for mold design. This evaluation can identify the risk of thermal damage in advance, avoid the breakage of the mold due to temperature changes during use, and extend the service life of the mold. By calculating the microscopic defects of the thermal phase change, it is possible to provide defect distribution information for the subsequent mold design, so that the impact of these defects on the quality of the final product is considered in the early stage of the design, and the design of the mold is optimized. The mold surface shape is constructed according to the glass design data, which can ensure that the shape of the mold matches the geometric characteristics of the final product and improve the production accuracy. In combination with the microscopic defect data of the thermal phase change, the initial glass mold surface is constructed, which can better adapt to the characteristics and defect distribution of the material and reduce the adjustment and correction in the subsequent processing. Through manufacturing simulation, the performance of the mold in the manufacturing process can be predicted before actual production, the cost of trial and error can be reduced, production efficiency can be improved, and defect analysis can be performed on the simulation data to identify defects that affect the quality of the finished product. The mold design or manufacturing parameters can be adjusted in time to ensure that the quality of the final product meets the standards. Optimizing the initial mold surface according to the finished product defect data can further improve the accuracy and applicability of the mold and ensure the production of high-quality glass products. Therefore, the present invention is an optimization process for a traditional method for generating a glass mold surface, which solves the problems of low accuracy in generating a glass mold surface and poor optical properties of the glass generated by the mold surface in a traditional method for generating a glass mold surface, and improves the accuracy of generating a glass mold surface and the optical properties of the glass generated by the mold surface.

[0010] Preferably, step S1 comprises the following steps:

[0011] Step S11: obtaining glass design data;

[0012] Step S12: extracting glass raw materials according to the glass design data to obtain glass raw material data;

[0013] Step S13: performing microstructure symmetry analysis and lattice structure calculation according to the glass raw material data to obtain microstructure symmetry data and lattice structure data of the glass material;

[0014] Step S14: evaluating the optical microscopic properties according to the microscopic structure symmetry data and the lattice structure data of the glass material to obtain the optical microscopic property data of the glass.

[0015] The present invention lays the foundation for the subsequent entire mold generation process by obtaining glass design data. This data ensures that the mold design is highly consistent with the requirements of the final product. Reasonable design data can effectively guide the subsequent raw material selection and avoid resource waste and production errors caused by improper design. Ensure that the selected raw materials have excellent physical and chemical properties and are suitable for specific application scenarios. Through the scientific selection of raw materials, the performance of the mold is effectively improved, and its stability and durability during use are ensured, which provides a reliable basis for subsequent microstructure analysis and optical performance evaluation. Understand its symmetry and lattice arrangement, which are important factors affecting glass performance. Through an in-depth understanding of the microstructure, the design of the mold is optimized to ensure that its optical and mechanical properties in practical applications meet the expected goals. In addition, the evaluation of the symmetry of the microstructure can also help identify defects, so as to make necessary adjustments in the design stage and reduce the risks in later production. Through the analysis of the microstructure, the performance of the material in optical properties, such as key indicators such as transmittance, refractive index and dispersion, is evaluated. These optical properties directly affect the function and quality of the final product. Therefore, through this evaluation, it is ensured that the designed mold has ideal optical properties to meet the demand for glass products in the high-end market.

[0016] Preferably, step S14 comprises the following steps:

[0017] Step S141: performing glass microscopic short-range arrangement analysis according to the glass material microscopic structure symmetry data to obtain glass microscopic structure short-range arrangement data;

[0018] Step S142: performing microscopic local structure unit analysis according to the glass microscopic structure short-range arrangement data to obtain glass microscopic local structure unit data;

[0019] Step S143: performing local atomic missing calculation according to the glass microscopic local structural unit data to obtain glass microscopic local atomic missing data;

[0020] Step S144: calculating the transmittance according to the microscopic local atomic missing data and the lattice structure data of the glass to obtain the transmittance data of the glass microstructure;

[0021] Step S145: Calculating the reflectivity based on the glass microscopic local atomic missing data and the glass microscopic structure transmittance data to obtain the glass microscopic structure reflectivity data;

[0022] Step S146: performing optical microscopic property evaluation according to the glass microstructure transmittance data and the glass microstructure reflectivity data to obtain glass optical microscopic property data.

[0023] The present invention obtains the short-range arrangement data of the glass microstructure by performing microscopic short-range arrangement analysis on the symmetry data of the microstructure of the glass material. This process helps to understand the arrangement mode of the material at the microscopic level and reveal the uniformity and orderliness of its internal structure. The good degree of short-range arrangement is directly related to the physical properties of the glass, such as strength and toughness. The microscopic local structure unit analysis is performed based on the short-range arrangement data of the glass microstructure to obtain the glass microscopic local structure unit data. This analysis can identify and characterize the local structural characteristics inside the glass, including atomic clusters and local defects. By calculating the local atomic loss of the glass microscopic local structure unit data, the glass microscopic local atomic loss data is obtained. The existence of local atomic loss leads to a decrease in material performance, such as reduced strength and transparency. Therefore, identifying and quantifying these losses is crucial to optimizing the manufacturing process of glass. Understanding the distribution of missing atoms will help to make necessary adjustments in the mold design stage to reduce the impact of defects on the performance of the final product. The transmittance is calculated based on the glass microscopic local atomic loss data and lattice structure data to obtain the glass microstructure transmittance data. Transmittance is one of the key indicators to measure the optical properties of glass, which directly affects the visibility and optical effect of glass in practical applications. The reflectivity is calculated based on the microscopic local atomic loss data and transmittance data of the glass to obtain the reflectivity data of the glass microstructure. Reflectivity is another important optical property that affects the transmission and reflection behavior of light. By calculating the reflectivity, the optical properties of the glass are comprehensively evaluated to provide comprehensive data support for mold design. The optical microscopic properties are evaluated based on the transmittance data and reflectance data of the glass microstructure to obtain the optical microscopic properties data of the glass. The key to this step is to comprehensively consider the transmittance and reflectivity to comprehensively evaluate the optical properties of the material.

[0024] Preferably, step S2 comprises the following steps:

[0025] Step S21: performing thermal phase change behavior analysis based on the glass optical microscopic property data to obtain the glass optical microscopic property thermal phase change behavior data;

[0026] Step S22: evaluating the state of thermal damage according to the thermal phase change behavior data of the optical microscopic properties of the glass, and obtaining the state data of the optical thermal damage of the glass;

[0027] Step S23: performing microstructure optical uniformity defect analysis according to the glass optical thermal damage state data to obtain glass microstructure optical uniformity defect data;

[0028] Step S24: Calculate the glass thermal phase transition microscopic defects according to the glass microstructure optical uniformity defect data and the glass optical thermal damage state data to obtain the glass thermal phase transition microscopic defect data.

[0029] The present invention obtains the thermal phase change behavior data of the optical microscopic properties of glass by analyzing the thermal phase change behavior according to the optical microscopic property data of glass. This analysis process can reveal the change of optical properties of the material under different temperature conditions and understand the stability and adaptability of the glass during the heat treatment process. This is very important for designing glass molds for high temperature processes, ensuring that the mold can effectively resist the performance degradation caused by temperature fluctuations in practical applications, thereby improving the reliability and consistency of the product. The evaluation process can identify the thermal damage suffered by the glass under high temperature or rapid temperature change conditions. This evaluation discovers potential quality problems in advance, allowing designers to take preventive measures in the mold design stage to reduce the risk of mold breakage or failure during the production process, thereby reducing production costs and improving production efficiency. Identify uniformity problems of the material at the microscopic level, such as the inhomogeneity of atomic arrangement or local defects. These defects can lead to a reduction in optical properties, such as instability of transmittance and reflectivity. By identifying these problems early, optimization is performed in material selection and mold design to ensure consistency and reliability in optical properties of the final product. This calculation can provide detailed information about microscopic defects generated by the material during the thermal phase change process, such as cracks, bubbles or other structural defects. This information is crucial for optimizing the glass production process and material formulation, and can help designers make necessary adjustments during the mold design stage, thereby improving the overall performance and quality of the glass.

[0030] Preferably, step S24 comprises the following steps:

[0031] Step S241: extracting microcrack features according to the optical uniformity defect data of the glass microstructure to obtain microcrack data of the glass microstructure;

[0032] Step S242: performing statistics on the spatial distribution of microcracks according to the microcrack data of the glass microstructure to obtain the spatial distribution data of microcracks of the glass microstructure;

[0033] Step S243: calculating the optical thermal damage depth according to the glass optical thermal damage state data to obtain the glass optical thermal damage depth data;

[0034] Step S244: analyzing the influence degree of optical thermal damage according to the optical thermal damage depth data of the glass, and obtaining the influence degree data of optical thermal damage of the glass;

[0035] Step S245: Calculate the glass thermal phase transition micro defects according to the glass microstructure micro crack spatial distribution data and the glass optical thermal damage influence degree data to obtain the glass thermal phase transition micro defect data.

[0036] The present invention extracts microcrack characteristics and deeply understands the microstructural defects of glass, thereby providing basic data for material optimization and supporting subsequent improvement measures. The spatial distribution statistics of microcracks provide an important basis for evaluating the uniformity and potential weaknesses of materials, which helps engineers to carry out effective quality control during the design and manufacturing process. The calculation of the depth of optical thermal damage quantifies the impact of thermal effects on the internal structure of the material, and then evaluates its safety and stability in long-term use. By analyzing the degree of influence of optical thermal damage, we can more comprehensively understand how these damages affect the overall performance of the material, and help develop glass products that are more resistant to high temperatures and thermal stress. In addition, combining the spatial distribution data of microcracks with the degree of influence of optical thermal damage to calculate the microscopic defects of thermal phase change can reveal the microscopic defect characteristics of glass materials under different heat treatment conditions, thereby providing a scientific basis for optimizing the heat treatment process of glass and improving its application performance in high temperature environments. The effective implementation of this series of steps not only helps to improve the quality and performance of glass materials, but also lays a solid foundation for future research and development.

[0037] Preferably, step S3 comprises the following steps:

[0038] Step S31: extracting the glass geometric shape according to the glass design data to obtain the glass geometric shape data;

[0039] Step S32: measuring the glass geometric dimensions according to the glass geometric shape data to obtain the glass shape geometric dimension data;

[0040] Step S33: constructing the glass mold surface shape according to the glass geometric shape data and the glass shape geometric size data to obtain the glass mold surface shape data;

[0041] Step S34: constructing an initial glass mold surface according to the glass thermal phase change micro defect data and the glass mold surface shape data to obtain initial glass mold surface data.

[0042] The present invention extracts geometric shapes according to glass design data to ensure that an accurate geometric model is obtained at the beginning of production. This process provides a reliable basis for all subsequent processing and molding processes, thereby reducing material waste and production delays caused by design errors and improving the overall efficiency of production. In addition, the accuracy of the geometric shape also directly affects the subsequent product assembly and use performance, ensuring that the product can achieve the expected function during use. The measurement of geometric dimensions is a key step to ensure that glass products meet design specifications. Through accurate dimension measurement, the existing dimensional deviations can be discovered and corrected in time to avoid subsequent processing and installation problems caused by inappropriate dimensions. The mold surface shape is constructed through glass geometric shape data and geometric dimension data, effectively improving the design accuracy of the mold. This process not only improves the matching degree between the mold and the glass, but also significantly improves the surface quality and appearance of the finished product. High-quality mold design can ensure the stability of the glass during the molding process, reduce the generation of defects, and improve the market competitiveness of the finished product. The initial glass mold surface is constructed in combination with the microscopic defect data of the glass thermal phase change, so that the mold design can fully consider the performance of the material under high temperature conditions. This process ensures that the mold has better durability and molding effect in actual use, and can effectively reduce the failure rate and maintenance cost in the production process.

[0043] Preferably, step S34 includes the following steps:

[0044] Step S341: using the glass thermal phase change micro defect data to evaluate the defect impact on the glass mold surface shape data, and obtaining the glass mold surface defect impact data;

[0045] Step S342: analyzing the stress concentration points on the mold surface according to the glass mold surface defect influence data to obtain the stress concentration point data on the glass mold surface;

[0046] Step S343: performing a mold surface stress concentration point brittleness test according to the glass mold surface stress concentration point data to obtain the glass mold surface stress concentration brittleness data;

[0047] Step S344: optimizing the stress concentration brittleness of the glass according to the stress concentration brittleness data of the glass mold surface to obtain the optimized data of the stress concentration brittleness of the glass;

[0048] Step S345: constructing an initial glass mold surface according to the glass stress concentration brittleness optimization data and the glass mold surface shape data to obtain initial glass mold surface data.

[0049] The present invention uses the thermal phase change micro-defect data to evaluate the defect impact on the mold surface shape, and fully understands the potential impact of internal defects of the material on the performance of the mold. This process enables the design team to identify the key factors that lead to mold failure at an early stage, thereby providing a scientific basis for subsequent optimization and ensuring the reliability and stability of the mold in actual production. By performing stress concentration point analysis on the mold surface defect impact data, the stress distribution characteristics of the mold under load are deeply explored. This analysis not only helps to understand the stress concentration of the mold under high temperature and high pressure conditions, but also reveals the weak links in the mold design, thereby providing guidance for strengthening the design and avoiding the risk of accidental damage or failure of the mold during use. The brittleness test of the stress concentration point on the mold surface is a key step to ensure the strength and durability of the mold. By obtaining stress concentration brittleness data, designers can evaluate the brittleness performance of the mold under specific conditions. This data not only helps to understand the behavior of the material under extreme conditions, but also provides a reference basis for subsequent material selection and design improvements. Stress concentration brittleness optimization is an important part of improving mold performance. Through the analysis and optimization of brittleness data, the design team specifically adjusted the mold design, improved its overall structure, increased the tensile strength and durability of the mold, and reduced the risk of failure caused by brittleness. The initial mold surface was constructed by combining the optimized stress concentration brittleness data with the mold surface shape data to ensure that the designed mold can achieve optimal performance in actual production. This process not only increases the service life of the mold, but also significantly improves the overall quality of the product and reduces production costs.

[0050] Preferably, step S4 comprises the following steps:

[0051] Step S42: analyzing the finished glass product status according to the glass manufacturing simulation data to obtain the finished glass product status data;

[0052] Step S43: performing glass defect analysis on the finished glass product according to the finished glass product status data to obtain finished glass product defect data;

[0053] Step S44: Initially optimize the glass mold surface according to the defect data of the finished glass product to obtain glass mold surface optimization data.

[0054] The present invention analyzes the finished product state of glass manufacturing simulation data to fully understand the physical and chemical properties of glass during the production process. This state analysis can not only identify the finished product characteristics under different production conditions, but also help manufacturers optimize production parameters to ensure that the produced glass products meet the expected standards in terms of strength, transparency and other key performance indicators, thereby improving the consistency and reliability of the products. By deeply exploring the types of defects and their distribution in the finished products, the production team can be helped to identify potential production defects and quality problems. This process helps to promptly discover defective products in the production process, thereby reducing the production of defective products, reducing production costs, and improving customer satisfaction. In addition, the analysis of defect data enables producers to make improvements to specific problems, continuously optimize the production process, and further improve the overall quality of the finished product. By combining defect data with mold design, the deficiencies in the mold design are identified and corresponding improvements are made. This optimization ensures that the mold can better adapt to the actual needs of glass finished products, reduce the defect rate in the production process, and improve the service life and production efficiency of the mold. Ultimately, this series of analysis and optimization steps not only improves the scientificity and rationality of the production process, but also improves the quality of glass products as a whole, enhances market competitiveness, and brings higher economic benefits and customer satisfaction to the company. Through this systematic analysis and optimization, manufacturers can maintain their leading position in the fierce market environment and achieve sustainable development.

[0055] Preferably, step S43 includes the following steps:

[0056] Step S431: measuring the heterogeneous thickness and calculating the number of bubbles in the finished glass according to the finished glass state data, to obtain the heterogeneous thickness data and the number of bubbles in the finished glass;

[0057] Step S432: performing an impact resistance test according to the heterogeneous thickness data of the finished glass product to obtain the impact resistance data of the finished glass product;

[0058] Step S433: performing a glass bearing limit test according to the heterogeneous thickness data of the finished glass product and the impact resistance data of the finished glass product to obtain the glass bearing limit data;

[0059] Step S434: using the glass bearing limit data and the heterogeneous thickness data of the finished glass product to perform glass durability simulation on the finished glass product state data, and obtain the durability data of the finished glass product;

[0060] Step S435: performing glass transmittance attenuation analysis according to the bubble data of the finished glass product and the heterogeneous thickness data of the finished glass product to obtain glass transmittance attenuation data;

[0061] Step S436: performing glass optical performance degradation analysis according to the glass transmittance attenuation data and the glass finished product bubble data to obtain glass optical performance degradation data;

[0062] Step S437: Perform glass defect analysis on the finished glass product according to the glass optical performance degradation data and the glass finished product durability data to obtain glass finished product defect data.

[0063] The present invention effectively identifies defects and non-uniformity in finished glass products by measuring heterogeneous thickness and calculating the number of bubbles. This process not only provides basic data for subsequent performance tests, but also helps manufacturers identify potential problems in the early stages of production, thereby timely adjusting production parameters, reducing the generation of defective products, and improving the consistency and reliability of finished products. By measuring the impact resistance, manufacturers can understand the performance of glass when subjected to external impact. This data is crucial to ensuring the safety and stability of glass products in actual use, especially in the fields of construction, automobiles, etc., where the impact resistance directly affects the safety and use experience of users. The bearing limit test is carried out in combination with the heterogeneous thickness data and the impact resistance data to further clarify the performance of glass under different load conditions. This test not only provides the bearing capacity limit of glass, but also provides an important reference basis for subsequent design and application, ensuring the adaptability of the product in design and actual use. Through durability simulation, the performance changes of glass during long-term use are evaluated. This process helps manufacturers predict the service life of glass under different environmental conditions, thereby providing a scientific basis for the practical application of glass and ensuring the reliability and safety of products during use. The transmittance attenuation analysis based on the number of bubbles and heterogeneous thickness data helps to understand the degradation of glass in optical properties. This analysis not only provides data support for improving the aesthetics of the product, but also ensures the effectiveness of the product in optical applications, especially in the optoelectronics and construction industries. Combining optical performance degradation analysis with durability data can provide a comprehensive basis for the identification of glass defects. This process ensures that manufacturers can promptly identify potential problems in production and application, so as to implement targeted improvement measures.

[0064] Preferably, the present invention further provides a system for generating a glass mold surface, which is used to execute the method for generating a glass mold surface as described above, and the system for generating a glass mold surface comprises:

[0065] An optical microscopic property evaluation module is used to obtain glass design data; extract glass raw materials according to the glass design data to obtain glass raw material data; and evaluate optical microscopic properties according to the glass raw material data to obtain glass optical microscopic property data;

[0066] The glass thermal phase change micro defect calculation module is used to analyze the thermal phase change behavior according to the microstructure data of the glass material to obtain the glass micro thermal phase change behavior data; to evaluate the heat-induced damage state according to the glass micro thermal phase change behavior data to obtain the glass optical heat-induced damage state data; to calculate the glass thermal phase change micro defect according to the glass optical heat-induced damage state data to obtain the glass thermal phase change micro defect data;

[0067] An initial glass mold surface construction module is used to construct the glass mold surface shape according to the glass design data to obtain the glass mold surface shape data; to construct the initial glass mold surface according to the glass thermal phase change micro defect data and the glass mold surface shape data to obtain the initial glass mold surface data;

[0068] The glass mold surface module is used to perform glass manufacturing simulation based on the initial glass mold surface data to obtain glass manufacturing simulation data; perform glass defect analysis on the finished glass product based on the glass manufacturing simulation data to obtain glass finished product defect data; and perform initial mold surface shape optimization on the glass mold surface based on the glass finished product defect data to obtain glass mold surface optimization data.

[0069] The beneficial effects of the present invention are as follows: by obtaining glass design data, the present invention ensures that the mold design is highly consistent with the requirements of the final product, and provides an accurate basis for subsequent material selection and property evaluation. By extracting glass raw materials, it can be ensured that the selected materials have excellent physical and chemical properties and are suitable for specific application scenarios. This process can quantify the optical properties of the material, such as transmittance, refractive index, etc., to provide necessary optical parameter support for subsequent mold design and ensure the optical performance of the product in use. By analyzing the thermal phase change behavior of the microstructure of the glass material, the performance of the material in a high temperature environment is identified, and temperature adaptability data is provided for mold design. This evaluation can identify the risk of thermal damage in advance, avoid damage to the mold caused by temperature changes during use, and extend the service life of the mold. By calculating the microscopic defects of thermal phase change, it is possible to provide defect distribution information for subsequent mold design, so that the impact of these defects on the quality of the final product is considered in the early stage of design, and the design of the mold is optimized. The mold surface shape is constructed according to the glass design data, which can ensure that the shape of the mold matches the geometric characteristics of the final product and improve the production accuracy. Combining the thermal phase change micro defect data to construct the initial glass mold surface can better adapt to the characteristics and defect distribution of the material and reduce adjustments and corrections in subsequent processing. Through manufacturing simulation, the performance of the mold in the manufacturing process can be predicted before actual production, reducing trial and error costs, improving production efficiency, performing defect analysis on the simulation data, identifying defects that affect the quality of the finished product, and adjusting the mold design or manufacturing parameters in time to ensure that the quality of the final product meets the standards. Optimizing the initial mold surface according to the finished product defect data can further improve the accuracy and applicability of the mold and ensure the production of high-quality glass products. Therefore, the present invention is an optimization of a traditional method and system for generating a glass mold surface, which solves the problems of low accuracy in glass mold surface generation and poor optical properties of glass generated by the mold surface in a traditional method and system for generating a glass mold surface, and improves the accuracy of glass mold surface generation and the optical properties of glass generated by the mold surface. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 A schematic diagram of the steps of a method for generating a glass mold surface;

[0071] Figure 2 for Figure 1 Detailed implementation steps of step S2 in the flowchart;

[0072] Figure 3 for Figure 1 Detailed implementation steps of step S4 in FIG.

[0073] 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

[0074] The technical method of the present invention is described clearly and completely below 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.

[0075] 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.

[0076] 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.

[0077] To achieve this, please refer to Figures 1 to 3 , a method for generating a glass mold surface, the method comprising the following steps:

[0078] Step S1: Acquire glass design data; extract glass raw materials according to the glass design data to obtain glass raw material data; evaluate optical microscopic properties according to the glass raw material data to obtain glass optical microscopic property data;

[0079] Step S2: Analyze the thermal phase change behavior according to the microstructure data of the glass material to obtain the microscopic thermal phase change behavior data of the glass; evaluate the thermal damage state according to the microscopic thermal phase change behavior data of the glass to obtain the optical thermal damage state data of the glass; calculate the thermal phase change microscopic defects of the glass according to the optical thermal damage state data of the glass to obtain the thermal phase change microscopic defect data of the glass;

[0080] Step S3: constructing a glass mold surface shape according to the glass design data to obtain glass mold surface shape data; constructing an initial glass mold surface according to the glass thermal phase change micro defect data and the glass mold surface shape data to obtain initial glass mold surface data;

[0081] Step S4: Perform glass manufacturing simulation based on the initial glass mold surface data to obtain glass manufacturing simulation data; perform glass defect analysis on the finished glass product based on the glass manufacturing simulation data to obtain glass finished product defect data; perform mold surface optimization on the initial glass mold surface data based on the glass finished product defect data to obtain glass mold surface optimization data.

[0082] In the embodiment of the present invention, reference Figure 1 The above is a schematic flow chart of the steps of a method for generating a glass mold surface according to the present invention. In this example, the method for generating a glass mold surface includes the following steps:

[0083] Step S1: Acquire glass design data; extract glass raw materials according to the glass design data to obtain glass raw material data; evaluate optical microscopic properties according to the glass raw material data to obtain glass optical microscopic property data;

[0084] In the embodiment of the present invention, first, the glass design data, including the required glass type, thickness, curvature and optical performance requirements, etc., are obtained through computer-aided design (CAD) software. Then, based on these design data, the required glass raw material data, such as the ratio and purity of silicon dioxide, sodium oxide and calcium oxide, are extracted. On this basis, optical microscopic properties are evaluated using optical theory and experimental data, and the refractive index, absorption coefficient and transmittance of the glass are determined using spectral analysis technology. The results of the optical property evaluation will form a database of glass optical microscopic property data for subsequent analysis.

[0085] Step S2: Analyze the thermal phase change behavior according to the microstructure data of the glass material to obtain the microscopic thermal phase change behavior data of the glass; evaluate the thermal damage state according to the microscopic thermal phase change behavior data of the glass to obtain the optical thermal damage state data of the glass; calculate the thermal phase change microscopic defects of the glass according to the optical thermal damage state data of the glass to obtain the thermal phase change microscopic defect data of the glass;

[0086] In the embodiments of the present invention, the thermal phase change behavior of the glass is analyzed by molecular dynamics simulation method using the microstructure data of the glass material (such as atomic arrangement and crystal defect information), focusing on the phase change characteristics at different temperatures, such as changes in glass transition temperature (Tg) and crystallization temperature (Tc). Subsequently, based on the thermal phase change behavior data, the thermal damage state of the glass is evaluated, and thermal analysis technology (such as differential scanning calorimetry DSC) is used to obtain thermal damage data, and defects such as local cracks and bubbles that appear in the glass under high temperature environment are analyzed. Finally, based on these thermal damage state data, the thermal phase change micro defects are calculated, and the type, size and distribution of the defects are recorded in detail to form glass thermal phase change micro defect data.

[0087] Step S3: constructing a glass mold surface shape according to the glass design data to obtain glass mold surface shape data; constructing an initial glass mold surface according to the glass thermal phase change micro defect data and the glass mold surface shape data to obtain initial glass mold surface data;

[0088] In the embodiment of the present invention, the shape of the glass mold surface is constructed using 3D modeling software (such as SolidWorks or AutoCAD) based on the glass design data, and the mold surface profile that meets the optical requirements is designed, including the required concave-convex shape and slope, etc. Next, the initial glass mold surface is constructed in combination with the thermal phase change micro defect data and the mold surface shape data to ensure that the mold surface design can effectively compensate for the micro defects that occur during the thermal phase change process, and the finite element analysis method is used to evaluate the stress distribution and deformation of the initial mold surface to ensure the rationality and manufacturability of the design.

[0089] Step S4: Perform glass manufacturing simulation based on the initial glass mold surface data to obtain glass manufacturing simulation data; perform glass defect analysis on the finished glass product based on the glass manufacturing simulation data to obtain glass finished product defect data; perform mold surface optimization on the initial glass mold surface data based on the glass finished product defect data to obtain glass mold surface optimization data.

[0090] In the embodiment of the present invention, after the initial glass mold surface structure is completed, advanced computer simulation software (such as ANSYS or COMSOL) is used to simulate glass manufacturing, simulate the temperature field, pressure field and flow behavior of the entire manufacturing process, and obtain glass manufacturing simulation data. By analyzing these data, the defects of the finished glass, such as bubbles, cracks and unevenness, are identified, and defect analysis is performed to quantify the impact of these defects. Finally, according to the defect data of the finished glass, the initial mold surface data is optimized, the shape and parameters of the mold surface are adjusted to reduce the defect incidence, and the optimized mold surface data is generated to ensure that the quality and performance of the final product meet the expected standards.

[0091] Preferably, step S1 comprises the following steps:

[0092] Step S11: obtaining glass design data;

[0093] Step S12: extracting glass raw materials according to the glass design data to obtain glass raw material data;

[0094] Step S13: performing microstructure symmetry analysis and lattice structure calculation according to the glass raw material data to obtain microstructure symmetry data and lattice structure data of the glass material;

[0095] Step S14: evaluating the optical microscopic properties according to the microscopic structure symmetry data and the lattice structure data of the glass material to obtain the optical microscopic property data of the glass.

[0096] In an embodiment of the present invention, glass design data is obtained using computer-aided design (CAD) software (such as AutoCAD or SolidWorks). The designer first defines the purpose of the glass (such as optical components, architectural glass, etc.), and then enters the required parameters, including the thickness, shape (such as flat, curved or polyhedron), optical performance requirements (such as transmittance, refractive index, etc.) and strength requirements of the glass. All design data will be stored in a database to form a structured design data set for subsequent raw material extraction and analysis. In addition, the design data should also include production process requirements to ensure the manufacturability and economy of the design. Extraction of glass raw materials. First, determine the required glass type (such as silicate glass, lead glass or high borosilicate glass), and select suitable raw materials according to their characteristics. For example, for silicate glass, raw materials such as silicon dioxide, sodium oxide, and calcium oxide need to be extracted and their mass fractions determined. Through chemical analysis and physical testing, the purity and quality of the raw materials are verified to ensure that they meet the design requirements. Finally, a detailed glass raw material data report is formed, including the source, specification, batch number and test results of each raw material, to ensure the reliability and consistency of the subsequent process. After obtaining the raw material data of glass, use computational simulation software (such as Materials Studio or VASP) to perform microstructure symmetry analysis and lattice structure calculation. First, use molecular dynamics simulation method to construct an atomic model of glass material and analyze the symmetry of its microstructure. By calculating the relative position and distance between atoms, the symmetry data of the microstructure is obtained, and the lattice structure is calculated using quantum mechanics calculation methods (such as density functional theory DFT) to obtain the lattice constant, atomic arrangement and band structure information of the glass material. Evaluate the optical microscopic properties. First, use optical simulation software (such as COMSOL Multiphysics) to simulate the propagation of light in glass materials and calculate its refractive index, absorption coefficient and scattering characteristics. Specifically, the optical response of glass is analyzed by changing the wavelength and angle of the incident light to obtain its transmittance and reflectivity. In addition, combined with experimental data (such as spectral analysis), the accuracy of the simulation results is verified to ensure that the obtained optical properties truly reflect the performance of the material.

[0097] Preferably, step S14 comprises the following steps:

[0098] Step S141: performing glass microscopic short-range arrangement analysis according to the glass material microscopic structure symmetry data to obtain glass microscopic structure short-range arrangement data;

[0099] Step S142: performing microscopic local structure unit analysis according to the glass microscopic structure short-range arrangement data to obtain glass microscopic local structure unit data;

[0100] Step S143: performing local atomic missing calculation according to the glass microscopic local structural unit data to obtain glass microscopic local atomic missing data;

[0101] Step S144: calculating the transmittance according to the microscopic local atomic missing data and the lattice structure data of the glass to obtain the transmittance data of the glass microstructure;

[0102] Step S145: Calculating the reflectivity based on the glass microscopic local atomic missing data and the glass microscopic structure transmittance data to obtain the glass microscopic structure reflectivity data;

[0103] Step S146: performing optical microscopic property evaluation according to the glass microstructure transmittance data and the glass microstructure reflectivity data to obtain glass optical microscopic property data.

[0104] In an embodiment of the present invention, an atomic level model of glass is generated by molecular dynamics simulation, the distance and angular distribution between atoms are analyzed, and the characteristics of short-range arrangement are determined. Specifically, the coordination number and radial distribution function (RDF) between atoms are calculated, and these data reveal the degree of order of atoms in the short range. Cluster analysis methods (such as Voronoi diagrams or density-based spatial clustering) are used to identify and extract local structural units. By analyzing the local atomic environment, the geometric characteristics (such as angles, bond lengths, and coordination numbers) of each unit are calculated, and atomic groups with similar structures are identified. Software (such as OVITO) is used to visualize these local structural units for easy observation and analysis of their distribution characteristics. Using the atomic missing model, potential atomic missing sites are identified by simulating local stress or thermal excitation conditions. The number of atomic missing under different environmental conditions is evaluated by calculation methods (such as Monte Carlo simulations). During the calculation process, the influence of missing atoms is taken into account, and its influence on the stability of local structural units is analyzed. Optical transmission theory is applied to evaluate the influence of local missing on transmittance by calculating the propagation path and scattering mechanism of light in glass. Using spectral analysis software (such as OptiFDTD), input the wavelength range and missing rate of the material, simulate the propagation of light in the glass, and calculate the transmittance of light. Specifically, by comparing the transmittance of the complete model with that of the model containing the missing, quantify the impact of the missing on the optical performance. Using the same optical simulation software as the transmittance calculation (such as COMSOLMultiphysics), input the microscopic local atomic missing data and transmittance data to simulate the reflection behavior of light on the glass surface. Specifically, the Fresnel equation is used to calculate the reflectivity at different incident angles and wavelengths, considering the effects of surface roughness and missing on light reflection. By establishing a model, the change of reflectivity with the wavelength and incident angle of light is evaluated, thereby forming a glass microstructure reflectivity data report, recording the reflectivity value and corresponding conditions in detail, and evaluating the optical microscopic properties.

[0105] Preferably, step S2 comprises the following steps:

[0106] Step S21: performing thermal phase change behavior analysis based on the glass optical microscopic property data to obtain the glass optical microscopic property thermal phase change behavior data;

[0107] Step S22: evaluating the state of thermal damage according to the thermal phase change behavior data of the optical microscopic properties of the glass, and obtaining the state data of the optical thermal damage of the glass;

[0108] Step S23: performing microstructure optical uniformity defect analysis according to the glass optical thermal damage state data to obtain glass microstructure optical uniformity defect data;

[0109] Step S24: Calculate the glass thermal phase transition microscopic defects according to the glass microstructure optical uniformity defect data and the glass optical thermal damage state data to obtain the glass thermal phase transition microscopic defect data.

[0110] As an example of the present invention, refer to Figure 2 As shown, in this example, step S2 includes:

[0111] Step S21: performing thermal phase change behavior analysis based on the glass optical microscopic property data to obtain the glass optical microscopic property thermal phase change behavior data;

[0112] In an embodiment of the present invention, a thermal phase change behavior analysis is performed based on the obtained optical microscopic property data of the glass. A thermal analysis technique such as differential scanning calorimetry (DSC) is used to evaluate the phase change characteristics of the glass under different temperature conditions. First, the glass sample is heated to its glass transition temperature (Tg), and the change in heat flow during the heating process is recorded. By analyzing the heat flow curve, the thermal phase change behavior data of the glass is obtained, including the melting temperature, crystallization temperature and related thermal enthalpy values. This data reveals the stability and phase change characteristics of the glass under heating conditions. Finally, a report is formed to record in detail the characteristics and energy changes during the thermal phase change process, providing basic data for subsequent thermal damage assessments.

[0113] Step S22: evaluating the state of thermal damage according to the thermal phase change behavior data of the optical microscopic properties of the glass, and obtaining the state data of the optical thermal damage of the glass;

[0114] In the embodiment of the present invention, after obtaining the thermal phase change behavior data of the optical microscopic properties of the glass, the thermal damage state is evaluated. Thermal damage simulation software (such as ANSYS or COMSOL Multiphysics) is used to simulate the thermal stress and thermal fatigue behavior of the glass under different temperatures and thermal cycle conditions. The specific steps include setting thermal loading conditions (such as temperature gradient and heating rate), and observing the stress distribution and crack formation of the glass under these conditions. By analyzing the simulation results, the degree of thermal damage is evaluated, and a thermal damage state data report is generated to record the damage of the glass under different temperatures and loading conditions, with special attention to the formation and expansion of micro cracks.

[0115] Step S23: performing microstructure optical uniformity defect analysis according to the glass optical thermal damage state data to obtain glass microstructure optical uniformity defect data;

[0116] In an embodiment of the present invention, a microstructure optical uniformity defect analysis is performed based on the obtained optical thermal damage state data. A high-resolution microscope (such as a scanning electron microscope SEM or a transmission electron microscope TEM) is used to observe the glass sample, focusing on analyzing the microscopic defects and inhomogeneities caused by thermal damage in the sample. The type, quantity, size and distribution of defects are quantitatively analyzed by image analysis software (such as ImageJ). Specifically, cracks, bubbles or other defects caused by thermal damage are identified, and the impact of these defects on optical properties is evaluated.

[0117] Step S24: Calculate the glass thermal phase transition microscopic defects according to the glass microstructure optical uniformity defect data and the glass optical thermal damage state data to obtain the glass thermal phase transition microscopic defect data.

[0118] In the embodiment of the present invention, a thermal phase change micro defect model is established by combining the heat-induced damage state data and the uniformity defect data. Computational software (such as MATLAB or Python) is used to simulate the influence of defects on optical properties during the thermal phase change process, and the scattering and absorption effects of defects on light propagation are calculated. Specifically, the Monte Carlo method is used to simulate the propagation of light in defective glass, and the influence of defects on optical properties is evaluated by analyzing the scattering and transmission of light.

[0119] Preferably, step S24 comprises the following steps:

[0120] Step S241: extracting microcrack features according to the optical uniformity defect data of the glass microstructure to obtain microcrack data of the glass microstructure;

[0121] Step S242: performing statistics on the spatial distribution of microcracks according to the microcrack data of the glass microstructure to obtain the spatial distribution data of microcracks of the glass microstructure;

[0122] Step S243: calculating the optical thermal damage depth according to the glass optical thermal damage state data to obtain the glass optical thermal damage depth data;

[0123] Step S244: analyzing the influence degree of optical thermal damage according to the optical thermal damage depth data of the glass, and obtaining the influence degree data of optical thermal damage of the glass;

[0124] Step S245: Calculate the glass thermal phase transition micro defects according to the glass microstructure micro crack spatial distribution data and the glass optical thermal damage influence degree data to obtain the glass thermal phase transition micro defect data.

[0125] In an embodiment of the present invention, microcrack feature extraction is performed according to the optical uniformity defect data of the glass microstructure. First, a high-resolution scanning electron microscope (SEM) is used to observe the glass sample to obtain a clear image of the microcracks. Then, the acquired image is analyzed using image processing software (such as ImageJ or Matlab), and the contour of the microcracks is extracted using an edge detection algorithm (such as the Canny algorithm). By analyzing the parameters such as the length, width and shape of the microcracks, the glass microstructure microcrack data is obtained, and the microcrack data obtained in the previous step is used to study the distribution characteristics of the microcracks in the sample by a spatial analysis method (such as K-function analysis or Voronoi diagram). The specific steps include importing the coordinate data of the microcracks into statistical software (such as R or Python's Scipy library) to calculate the spatial distribution density, aggregation and uniformity index of the microcracks. By generating a heat map, the distribution of microcracks is intuitively displayed, and the aggregation area and sparse area of ​​the microcracks are identified. The thermal damage area is observed using an optical microscope or a laser scanning microscope (LSM) to record the surface characteristics of the optical thermal damage. Then, the depth of the thermal damage area is evaluated by combining optical transmission theory and reflectivity measurement, using Fourier transform infrared spectroscopy (FTIR) and other techniques. Specifically, by analyzing the reflection and transmission spectra, the thickness of the damaged layer is calculated, and the propagation of light of different wavelengths in the layer is evaluated. Based on the previous thermal damage depth data and combined with the changes in optical properties, optical simulation software (such as COMSOL Multiphysics) is used to simulate the propagation and reflection process of light in the thermal damage area. The changes in the transmittance and reflectivity of light passing through the damaged layer are specifically analyzed to evaluate the specific impact of the thermal damage depth on the optical properties. By comparing the optical properties of the undamaged and damaged areas, the degree of influence of the damage on the transmittance, reflectivity and scattering rate is calculated. A thermal phase change model is established, combined with microcrack and thermal damage data, and simulated by finite element analysis (FEA) software (such as ABAQUS or ANSYS). The specific steps include setting the thermal phase change conditions (such as temperature change rate and phase change temperature) and analyzing the effects of microcracks and thermal damage on the thermal phase change process. Through simulation calculations, the stress concentration and defect extension caused by microcracks and thermal damage under different conditions are evaluated.

[0126] Preferably, step S3 comprises the following steps:

[0127] Step S31: extracting the glass geometric shape according to the glass design data to obtain the glass geometric shape data;

[0128] Step S32: measuring the glass geometric dimensions according to the glass geometric shape data to obtain the glass shape geometric dimension data;

[0129] Step S33: constructing the glass mold surface shape according to the glass geometric shape data and the glass shape geometric size data to obtain the glass mold surface shape data;

[0130] Step S34: constructing an initial glass mold surface according to the glass thermal phase change micro defect data and the glass mold surface shape data to obtain initial glass mold surface data.

[0131] In an embodiment of the present invention, a computer-aided design (CAD) software (such as AutoCAD or SolidWorks) is first used to extract geometric shapes from glass design data. The designer defines the geometric shape of the glass according to the intended use of the glass (such as an optical lens, a window or decorative glass), including a plane, a curved surface or a composite shape. The extracted geometric shape data will include the contour, thickness, radius of curvature and edge features of the glass. After obtaining the geometric shape data of the glass, the geometric dimensions of the glass are measured. In the specific operation, a high-precision three-dimensional laser scanner or a digital caliper is used to measure the actual sample. By scanning, various geometric dimension information of the glass is obtained, including length, width, thickness and angle. During the measurement process, it is necessary to ensure that the influence of environmental conditions (such as temperature and humidity) on the measurement results is minimized. The obtained data is compared with the CAD model, and an error analysis is performed to ensure the accuracy of the geometric dimension data. The glass mold surface shape is constructed. In the CAD software, the designer creates a three-dimensional model of the mold surface according to the geometric data of the glass. The specific steps include defining the curvature, edge chamfers and other features of the mold surface to ensure that the mold surface shape can accurately reflect the design requirements of the glass. During the design process, the thermal deformation and stress distribution of the die surface during forming, processing and use should be considered to ensure the stability and strength of the die surface. Use finite element analysis software (such as ANSYS or ABAQUS) to input the die surface shape data to simulate the stress and thermal deformation that occur during the processing. At the same time, combined with the thermal phase change micro defect data, evaluate the impact of defects on the die surface shape. Through multiple iterations and optimization, adjust the geometric parameters of the die surface to ensure that the die surface can effectively resist deformation during heat treatment and cooling.

[0132] Preferably, step S34 includes the following steps:

[0133] Step S341: using the glass thermal phase change micro defect data to evaluate the defect impact on the glass mold surface shape data, and obtaining the glass mold surface defect impact data;

[0134] Step S342: analyzing the stress concentration points on the mold surface according to the glass mold surface defect influence data to obtain the stress concentration point data on the glass mold surface;

[0135] Step S343: performing a mold surface stress concentration point brittleness test according to the glass mold surface stress concentration point data to obtain the glass mold surface stress concentration brittleness data;

[0136] Step S344: optimizing the stress concentration brittleness of the glass according to the stress concentration brittleness data of the glass mold surface to obtain the optimized data of the stress concentration brittleness of the glass;

[0137] Step S345: constructing an initial glass mold surface according to the glass stress concentration brittleness optimization data and the glass mold surface shape data to obtain initial glass mold surface data.

[0138] In an embodiment of the present invention, first, a finite element analysis software (such as ANSYS or COMSOL Multiphysics) is used to combine the die surface shape data with the thermal phase change micro defect data to establish a die surface model containing defects. By applying different temperature and stress conditions, the influence of defects on the die surface performance is simulated, and the influence of defects on the strength and stability of the die surface under high temperature environment is focused on. The stress distribution of the die surface under different conditions is calculated, and the above-mentioned finite element analysis model is used to focus on the characteristics of the stress concentration area. Specifically, the stress distribution data is extracted through a post-processing program, the areas with the highest stress are identified, and the specific coordinates and stress values ​​of these areas are determined. Combined with the strength characteristics of the material, the potential failure modes caused by these stress concentration points are analyzed. A detailed glass die surface stress concentration point data report is formed, recording the location of the stress concentration point, the stress value and its influence on the overall performance of the die surface. After obtaining the die surface stress concentration point data, the brittleness test of the die surface stress concentration point is performed. First, the stress concentration point is selected as the test position, and a microhardness test (such as a Vickers hardness test) and a fracture toughness test are used to evaluate the brittleness and bearing capacity of these points by applying gradually increasing loads. The specific method includes observing the microstructural changes at the stress concentration points under a microscope, recording the relationship between load and displacement, and calculating the brittleness index. Analyze the brittleness test results, identify stress concentration points with higher brittleness, and evaluate their impact on the stability of the die surface. Use optimization algorithms (such as genetic algorithms or particle swarm optimization) to adjust the shape and material distribution of the die surface to reduce stress concentration. Specifically, the stress value at the stress concentration point is reduced by changing the geometry of the die surface (such as increasing the transition radius and changing the thickness distribution). Reconstruct the three-dimensional model of the die surface in the CAD software based on the optimized data to ensure that the new design can effectively reduce stress concentration and enhance the durability of the die surface. Specific steps include performing finite element analysis on the new die surface, verifying its thermal stress and mechanical stress distribution during the production process, and ensuring that the die surface has good strength and stability.

[0139] Preferably, step S4 comprises the following steps:

[0140] Step S41: performing glass manufacturing simulation according to the initial glass mold surface data to obtain glass manufacturing simulation data;

[0141] Step S42: analyzing the finished glass product status according to the glass manufacturing simulation data to obtain the finished glass product status data;

[0142] Step S43: performing glass defect analysis on the finished glass product according to the finished glass product status data to obtain finished glass product defect data;

[0143] Step S44: Initially optimize the glass mold surface according to the defect data of the finished glass product to obtain glass mold surface optimization data.

[0144] As an example of the present invention, refer to Figure 3 As shown, in this example, step S4 includes:

[0145] Step S41: performing glass manufacturing simulation according to the initial glass mold surface data to obtain glass manufacturing simulation data;

[0146] In the embodiment of the present invention, first, a finite element analysis software (such as ANSYS or COMSOL Multiphysics) is used to establish a three-dimensional model including the initial mold surface geometry and material properties. By simulating the molding process of glass in a molten state, appropriate temperature fields and pressure fields are applied to simulate the heat conduction and flow behavior at different stages. Specifically, the melting temperature, cooling rate and heat exchange characteristics of the glass are set, and the stress and deformation state of the glass during the molding process are monitored.

[0147] Step S42: analyzing the finished glass product status according to the glass manufacturing simulation data to obtain the finished glass product status data;

[0148] In the embodiment of the present invention, the stress and temperature changes experienced by the finished product during the cooling process are analyzed using simulation data to determine the final geometric shape and physical properties of the finished product. The specific operation includes evaluating the residual stress distribution, surface finish and internal stress state of the finished product, and using numerical calculation methods (such as thermal stress analysis) to evaluate the structural integrity of the finished product. By comparing with the design parameters, it is confirmed whether the finished product meets the quality standards.

[0149] Step S43: performing glass defect analysis on the finished glass product according to the finished glass product status data to obtain finished glass product defect data;

[0150] In the embodiment of the present invention, non-destructive testing technology (such as ultrasonic testing, infrared thermal imaging or X-ray testing) is used to comprehensively inspect the finished glass to identify existing defects such as bubbles, cracks and unevenness. Image processing software (such as ImageJ) is used to analyze the test results to extract the type, number and location of the defects. The specific steps include classifying and quantitatively analyzing the detected defects to determine the degree of influence of the defects on the performance of the glass.

[0151] Step S44: Initially optimize the glass mold surface according to the defect data of the finished glass product to obtain glass mold surface optimization data.

[0152] In the embodiment of the present invention, the defect data is analyzed to determine the main causes of defects (such as mold design defects, uneven cooling rate, etc.). The mold surface is redesigned using CAD software, and consideration is given to increasing the ventilation holes of the mold, adjusting the cooling system, or optimizing the geometry of the mold to better control the flow and cooling of the glass during the molding process. Specifically, simulation verification is performed to ensure that the optimized mold surface design can reduce the incidence of defects.

[0153] Preferably, step S43 includes the following steps:

[0154] Step S431: measuring the heterogeneous thickness and calculating the number of bubbles in the finished glass according to the finished glass state data, to obtain the heterogeneous thickness data and the number of bubbles in the finished glass;

[0155] Step S432: performing an impact resistance test according to the heterogeneous thickness data of the finished glass product to obtain the impact resistance data of the finished glass product;

[0156] Step S433: performing a glass bearing limit test according to the heterogeneous thickness data of the finished glass product and the impact resistance data of the finished glass product to obtain the glass bearing limit data;

[0157] Step S434: using the glass bearing limit data and the heterogeneous thickness data of the finished glass product to perform glass durability simulation on the finished glass product state data, and obtain the durability data of the finished glass product;

[0158] Step S435: performing glass transmittance attenuation analysis according to the bubble data of the finished glass product and the heterogeneous thickness data of the finished glass product to obtain glass transmittance attenuation data;

[0159] Step S436: performing glass optical performance degradation analysis according to the glass transmittance attenuation data and the glass finished product bubble data to obtain glass optical performance degradation data;

[0160] Step S437: Perform glass defect analysis on the finished glass product according to the glass optical performance degradation data and the glass finished product durability data to obtain glass finished product defect data.

[0161] In an embodiment of the present invention, a high-precision laser thickness gauge is used to measure the heterogeneous thickness of the finished glass. By setting multiple measurement points on the glass surface, the thickness data is obtained and a thickness distribution map is generated. The number of bubbles in the finished glass is counted by combining microscopic observation and image processing software (such as ImageJ). The specific operation includes using an image processing algorithm to identify the edge of the bubble, and calculating the number of bubbles and their diameter distribution. The obtained heterogeneous thickness data of the finished glass is subjected to impact resistance testing. The glass samples are tested using standardized impact resistance testing equipment (such as a drop hammer tester) to set different impact forces and impact angles. The specific steps include recording the fracture of the glass under different impact conditions, and determining its fracture energy and failure mode. Through data analysis, the impact resistance of different thickness areas is evaluated, and an electric loader is used to apply a gradually increasing load to the finished glass until it breaks or deforms. During the test, the deformation and failure point of the glass are monitored in real time, and the relationship between the loading weight and the deformation of the glass at each stage is recorded. The specific operation includes analyzing the bearing capacity of different heterogeneous thickness areas and determining the limit bearing weight of the glass. The durability simulation of the finished glass is performed. Use finite element analysis software (such as ABAQUS or COMSOL Multiphysics) to establish a glass model with heterogeneous thickness and load-bearing limit characteristics. In the simulation, long-term static loads and dynamic impact loads are applied to evaluate the durability performance of the glass under different environmental conditions. By analyzing the simulation results, the fatigue life and failure mode of the glass under multiple loads are evaluated. Use a spectrophotometer to measure the transmittance of the glass sample, record the transmittance data at different wavelengths, and combine the number of bubbles and thickness distribution to evaluate the effect of bubbles on transmittance. The specific operation includes analyzing the attenuation effect of thickness and bubbles on light propagation through calculation rules (such as Beer-Lambert law), and after obtaining the glass transmittance attenuation data, the degradation analysis of the optical properties of the glass is performed. First, combine the transmittance attenuation data and the finished product bubble data, use optical simulation software (such as ZEMAX or TracePro) to perform optical performance analysis, combine the optical performance degradation data with the durability data, and analyze the effects of different types of defects (such as bubbles, cracks, and uneven thickness) on the optical properties of the glass. Statistical analysis software (such as SPSS or Python's Pandas library) is used to perform correlation analysis on the data to determine the relationship between defects and optical properties (such as transmittance, reflectance and chromatic aberration). A multivariate regression model is established to quantify the specific impact of different defects on optical properties. For example, the contribution of the number and size of bubbles to the attenuation of transmittance, and the impact of thickness changes on overall optical uniformity are analyzed. Microscopes and image processing software (such as ImageJ) are used to quantitatively analyze defects and extract the number and location of each defect and its correlation with the degradation of optical properties.

[0162] Preferably, the present invention further provides a system for generating a glass mold surface, which is used to execute the method for generating a glass mold surface as described above, and the system for generating a glass mold surface comprises:

[0163] An optical microscopic property evaluation module is used to obtain glass design data; extract glass raw materials according to the glass design data to obtain glass raw material data; and evaluate optical microscopic properties according to the glass raw material data to obtain glass optical microscopic property data;

[0164] The glass thermal phase change micro defect calculation module is used to analyze the thermal phase change behavior according to the microstructure data of the glass material to obtain the glass micro thermal phase change behavior data; to evaluate the heat-induced damage state according to the glass micro thermal phase change behavior data to obtain the glass optical heat-induced damage state data; to calculate the glass thermal phase change micro defect according to the glass optical heat-induced damage state data to obtain the glass thermal phase change micro defect data;

[0165] An initial glass mold surface construction module is used to construct the glass mold surface shape according to the glass design data to obtain the glass mold surface shape data; to construct the initial glass mold surface according to the glass thermal phase change micro defect data and the glass mold surface shape data to obtain the initial glass mold surface data;

[0166] The glass mold surface module is used to perform glass manufacturing simulation based on the initial glass mold surface data to obtain glass manufacturing simulation data; perform glass defect analysis on the finished glass product based on the glass manufacturing simulation data to obtain glass finished product defect data; and perform initial mold surface shape optimization on the glass mold surface based on the glass finished product defect data to obtain glass mold surface optimization data.

[0167] 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.

[0168] 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 method for generating a glass mold surface, characterized in that: The following steps are involved: Step S1: obtaining glass design data; Extract glass raw materials according to glass design data to obtain glass raw material data; Evaluate the optical microscopic properties of glass according to the raw material data of glass to obtain the optical microscopic properties data of glass; Step S2: analyzing the thermal phase change behavior of the glass material according to the microstructure data to obtain the microscopic thermal phase change behavior data of the glass; According to the glass microscopic thermal phase change behavior data, the thermal damage state is evaluated to obtain the glass optical thermal damage state data; according to the glass optical thermal damage state data, the glass thermal phase change microscopic defects are calculated to obtain the glass thermal phase change microscopic defect data; Step S3: constructing a glass mold surface shape according to the glass design data to obtain glass mold surface shape data; constructing an initial glass mold surface according to the glass thermal phase change micro defect data and the glass mold surface shape data to obtain initial glass mold surface data; Step S4: Perform glass manufacturing simulation based on the initial glass mold surface data to obtain glass manufacturing simulation data; perform glass defect analysis on the finished glass product based on the glass manufacturing simulation data to obtain glass finished product defect data; perform mold surface optimization on the initial glass mold surface data based on the glass finished product defect data to obtain glass mold surface optimization data.

2. The method for generating a glass mold surface according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: obtaining glass design data; Step S12: extracting glass raw materials according to the glass design data to obtain glass raw material data; Step S13: performing microstructure symmetry analysis and lattice structure calculation according to the glass raw material data to obtain microstructure symmetry data and lattice structure data of the glass material; Step S14: evaluating the optical microscopic properties according to the microscopic structure symmetry data and the lattice structure data of the glass material to obtain the optical microscopic property data of the glass.

3. The method for generating a glass mold surface according to claim 2, characterized in that: Step S14 includes the following steps: Step S141: performing glass microscopic short-range arrangement analysis according to the glass material microscopic structure symmetry data to obtain glass microscopic structure short-range arrangement data; Step S142: performing microscopic local structure unit analysis according to the glass microscopic structure short-range arrangement data to obtain glass microscopic local structure unit data; Step S143: performing local atomic missing calculation according to the glass microscopic local structural unit data to obtain glass microscopic local atomic missing data; Step S144: calculating the transmittance according to the microscopic local atomic missing data and the lattice structure data of the glass to obtain the transmittance data of the glass microstructure; Step S145: Calculating the reflectivity based on the glass microscopic local atomic missing data and the glass microscopic structure transmittance data to obtain the glass microscopic structure reflectivity data; Step S146: performing optical microscopic property evaluation according to the glass microstructure transmittance data and the glass microstructure reflectivity data to obtain glass optical microscopic property data.

4. The method for generating a glass mold surface according to claim 1, characterized in that: Step S2 includes the following steps: Step S21: performing thermal phase change behavior analysis based on the glass optical microscopic property data to obtain the glass optical microscopic property thermal phase change behavior data; Step S22: evaluating the state of thermal damage according to the thermal phase change behavior data of the optical microscopic properties of the glass, and obtaining the state data of the optical thermal damage of the glass; Step S23: performing microstructure optical uniformity defect analysis according to the glass optical thermal damage state data to obtain glass microstructure optical uniformity defect data; Step S24: Calculate the glass thermal phase transition microscopic defects according to the glass microstructure optical uniformity defect data and the glass optical thermal damage state data to obtain the glass thermal phase transition microscopic defect data.

5. The method for generating a glass mold surface according to claim 4, characterized in that: Step S24 includes the following steps: Step S241: extracting microcrack features according to the optical uniformity defect data of the glass microstructure to obtain microcrack data of the glass microstructure; Step S242: performing statistics on the spatial distribution of microcracks according to the microcrack data of the glass microstructure to obtain the spatial distribution data of microcracks of the glass microstructure; Step S243: calculating the optical thermal damage depth according to the glass optical thermal damage state data to obtain the glass optical thermal damage depth data; Step S244: analyzing the influence degree of optical thermal damage according to the optical thermal damage depth data of the glass, and obtaining the influence degree data of optical thermal damage of the glass; Step S245: Calculate the glass thermal phase transition micro defects according to the glass microstructure micro crack spatial distribution data and the glass optical thermal damage influence degree data to obtain the glass thermal phase transition micro defect data.

6. The method for generating a glass mold surface according to claim 1, characterized in that: Step S3 includes the following steps: Step S31: extracting the glass geometric shape according to the glass design data to obtain the glass geometric shape data; Step S32: measuring the glass geometric dimensions according to the glass geometric shape data to obtain the glass shape geometric dimension data; Step S33: constructing the glass mold surface shape according to the glass geometric shape data and the glass shape geometric size data to obtain the glass mold surface shape data; Step S34: constructing an initial glass mold surface according to the glass thermal phase change micro defect data and the glass mold surface shape data to obtain initial glass mold surface data.

7. The method for generating a glass mold surface according to claim 6, characterized in that: Step S34 includes the following steps: Step S341: using the glass thermal phase change micro defect data to evaluate the defect impact on the glass mold surface shape data, and obtaining the glass mold surface defect impact data; Step S342: analyzing the stress concentration points on the mold surface according to the glass mold surface defect influence data to obtain the stress concentration point data on the glass mold surface; Step S343: performing a mold surface stress concentration point brittleness test according to the glass mold surface stress concentration point data to obtain the glass mold surface stress concentration brittleness data; Step S344: optimizing the stress concentration brittleness of the glass according to the stress concentration brittleness data of the glass mold surface to obtain the optimized data of the stress concentration brittleness of the glass; Step S345: constructing an initial glass mold surface according to the glass stress concentration brittleness optimization data and the glass mold surface shape data to obtain initial glass mold surface data.

8. The method for generating a glass mold surface according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: performing glass manufacturing simulation according to the initial glass mold surface data to obtain glass manufacturing simulation data; Step S42: analyzing the finished glass product status according to the glass manufacturing simulation data to obtain the finished glass product status data; Step S43: performing glass defect analysis on the finished glass product according to the finished glass product status data to obtain finished glass product defect data; Step S44: Initially optimize the glass mold surface according to the defect data of the finished glass product to obtain glass mold surface optimization data.

9. The method for generating a glass mold surface according to claim 8, characterized in that: Step S3 includes the following steps: Step S431: measuring the heterogeneous thickness and calculating the number of bubbles in the finished glass according to the finished glass state data, to obtain the heterogeneous thickness data and the number of bubbles in the finished glass; Step S432: performing an impact resistance test according to the heterogeneous thickness data of the finished glass product to obtain the impact resistance data of the finished glass product; Step S433: performing a glass bearing limit test according to the heterogeneous thickness data of the finished glass product and the impact resistance data of the finished glass product to obtain the glass bearing limit data; Step S434: using the glass bearing limit data and the heterogeneous thickness data of the finished glass product to perform glass durability simulation on the finished glass product state data, and obtain the durability data of the finished glass product; Step S435: performing glass transmittance attenuation analysis according to the bubble data of the finished glass product and the heterogeneous thickness data of the finished glass product to obtain glass transmittance attenuation data; Step S436: performing glass optical performance degradation analysis according to the glass transmittance attenuation data and the glass finished product bubble data to obtain glass optical performance degradation data; Step S437: Perform glass defect analysis on the finished glass product according to the glass optical performance degradation data and the glass finished product durability data to obtain glass finished product defect data.

10. A system for generating a glass mold surface, characterized in that: For executing the method for generating a glass mold surface as claimed in claim 1, the system for generating a glass mold surface comprises: An optical microscopic property evaluation module is used to obtain glass design data; extract glass raw materials according to the glass design data to obtain glass raw material data; and evaluate optical microscopic properties according to the glass raw material data to obtain glass optical microscopic property data; The glass thermal phase change micro defect calculation module is used to analyze the thermal phase change behavior according to the microstructure data of the glass material to obtain the glass micro thermal phase change behavior data; to evaluate the heat-induced damage state according to the glass micro thermal phase change behavior data to obtain the glass optical heat-induced damage state data; to calculate the glass thermal phase change micro defect according to the glass optical heat-induced damage state data to obtain the glass thermal phase change micro defect data; An initial glass mold surface construction module is used to construct the glass mold surface shape according to the glass design data to obtain the glass mold surface shape data; to construct the initial glass mold surface according to the glass thermal phase change micro defect data and the glass mold surface shape data to obtain the initial glass mold surface data; The glass mold surface module is used to perform glass manufacturing simulation based on the initial glass mold surface data to obtain glass manufacturing simulation data; perform glass defect analysis on the finished glass product based on the glass manufacturing simulation data to obtain glass finished product defect data; and perform initial mold surface shape optimization on the glass mold surface based on the glass finished product defect data to obtain glass mold surface optimization data.

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