Intelligent manufacturing method of colored glaze glass and related device

Abstract

The present application provides an intelligent manufacturing method for colored glaze glass and related devices. The method: real-time acquisition of the surface temperature of the out-of-furnace glass of the target object; the target object is colored glaze glass, and the acquisition method is high-resolution scanning; a real-time temperature distribution map is generated according to the surface temperature of the out-of-furnace glass; the real-time temperature distribution map contains the real-time temperature values ​​of each surface area in the target object; the real-time temperature distribution map is input into the glass stress distribution model to generate the wind pressure control parameters applied to each surface area; the wind pressure control parameters are used to indicate the real-time target wind pressure required to be achieved by the quenching air grid module corresponding to each surface area; the wind pressure control parameters are used to control the corresponding independent air grid areas in the quenching air grid module. The present application can adjust the real-time wind pressure of each surface area to make the cooling rate of each surface area consistent, solve the temperature difference and stress imbalance problems in the tempering of colored glaze glass, and improve the overall quality of the product.

Description

Technical Field

[0001] The present application relates to the technical field of curtain wall equipment, and in particular to an intelligent manufacturing method for colored glaze glass and related devices. Background Art

[0002] Colored glaze glass is a specially processed glass. A layer of colored glaze is applied on the glass surface by printing, spraying, etc. This layer of colored glaze usually contains inorganic pigments and low-melting-point glass powder. During the high-temperature firing process, the low-melting-point glass powder in the colored glaze will melt and sinter on the glass surface together with the inorganic pigment to form a solid colored decorative layer.

[0003] Tempered production of colored glaze glass is a manufacturing process that strengthens colored glaze glass in order to enhance the strength and safety of the glass. In related technologies, during the tempered production process, the heat absorption capacity of the colored glaze coating differs significantly from that of the transparent glass area, resulting in uneven surface temperature of the glass when it leaves the furnace, affecting the cooling rate and thermal stress release. During the rapid cooling process, the wind grid wind pressure distribution cannot be dynamically adjusted with temperature changes, resulting in inconsistent cooling rates in different areas, leading to an imbalance in stress distribution on the glass surface, which can easily cause irregular arch deformation or other optical performance defects. The existing technology mainly relies on workers' experience to adjust wind pressure parameters, and subsequent detection and remediation, resulting in a delayed response, making it difficult to meet the high efficiency and high quality requirements of modern production. In addition, due to the lack of a real-time control system, test adjustments consume a lot of energy and time, resulting in a waste of resources.

[0004] Therefore, it is urgent to design a new technical solution to solve at least one of the above technical problems. Summary of the invention

[0005] In order to solve or improve the above problems, the embodiments of the present application provide an intelligent manufacturing method and related devices for colored glaze glass.

[0006] In one embodiment of the present application, a smart manufacturing method for colored glaze glass is provided, comprising:

[0007] Real-time acquisition of the surface temperature of the target object's out-of-furnace glass; where the target object is colored glaze glass, the acquisition method is high-resolution scanning;

[0008] Generate a real-time temperature distribution map according to the surface temperature of the glass out of the furnace; the real-time temperature distribution map includes the real-time temperature values ​​of each surface area in the target object;

[0009] The real-time temperature distribution map is input into the glass stress distribution model to generate wind pressure control parameters applied to each surface area; the wind pressure control parameters are used to indicate the real-time target wind pressure required to be achieved by the quenching air grid module corresponding to each surface area;

[0010] The wind pressure control parameters are used to control the corresponding independent wind grid areas in the rapid cooling wind grid module to adjust the real-time wind pressure of each surface area so that the cooling rate of each surface area is consistent.

[0011] In another embodiment of the present application, an intelligent manufacturing device for colored glaze glass is provided, comprising at least the following units:

[0012] The acquisition unit is used to acquire the surface temperature of the out-of-furnace glass of the target object in real time; wherein the target object is colored glaze glass, and the acquisition method is high-resolution scanning;

[0013] A generating unit, for generating a real-time temperature distribution diagram according to the surface temperature of the out-of-furnace glass; the real-time temperature distribution diagram includes the real-time temperature values ​​of each surface area in the target object; the real-time temperature distribution diagram is input into the glass stress distribution model to generate the wind pressure control parameters applied to each surface area; the wind pressure control parameters are used to indicate the real-time target wind pressure required to be achieved by the quenching air grid module corresponding to each surface area;

[0014] The temperature control unit is used to control the corresponding independent air grid areas in the rapid cooling air grid module by using the air pressure control parameters to adjust the real-time air pressure of each surface area so that the cooling rate of each surface area is consistent.

[0015] In one embodiment of the present application, an electronic device includes:

[0016] at least one processor, memory, and input-output unit;

[0017] The memory is used to store a computer program, and the processor is used to call the computer program stored in the memory to execute the intelligent manufacturing method of colored glaze glass in the first embodiment.

[0018] In one embodiment of the present application, a computer-readable storage medium is provided, which includes instructions. When the instructions are executed on a computer, the computer executes the intelligent manufacturing method of colored glaze glass in the first embodiment described above.

[0019] In the technical solution provided in the embodiment of the present application, the surface temperature of the out-of-furnace glass of the target object is collected in real time; the target object is colored glaze glass, and the collection method is high-resolution scanning; a real-time temperature distribution map is generated according to the surface temperature of the out-of-furnace glass; the real-time temperature distribution map contains the real-time temperature values ​​of each surface area in the target object; the real-time temperature distribution map is input into the glass stress distribution model to generate the wind pressure control parameters applied to each surface area; the wind pressure control parameters are used to indicate the real-time target wind pressure required to be achieved by the quenching air grid module corresponding to each surface area; the wind pressure control parameters are used to control the corresponding independent air grid areas in the quenching air grid module. The present application can adjust the real-time wind pressure of each surface area to make the cooling rate of each surface area consistent, solve the temperature difference and stress imbalance problems in the tempering of colored glaze glass, and improve the overall quality of the product. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0021] Figure 1 A schematic diagram of the structure of a colored glaze glass manufacturing device provided in one embodiment of the present application;

[0022] Figure 2 A schematic diagram of a process for an intelligent manufacturing method of colored glaze glass provided in one embodiment of the present application;

[0023] Figure 3 A schematic diagram of the structure of an electronic device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0024] The present application provides the following embodiments to solve or improve at least some of the above problems. In order to enable people in the technical field to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0025] In some features described in the specification, claims and the above-mentioned drawings of this application, descriptions such as "first" and "second" are used to distinguish different components, parts, modules, devices, etc., and do not represent the order of precedence, nor do they limit "first" and "second" to be different types. In addition, the embodiments described below are only some embodiments of the present application, not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of this application.

[0026] In order to solve the above technical problems, an intelligent manufacturing device for colored glaze glass provided in an embodiment of the present application includes the following units:

[0027] The acquisition unit is used to acquire the surface temperature of the out-of-furnace glass of the target object in real time; wherein the target object is colored glaze glass, and the acquisition method is high-resolution scanning;

[0028] A generating unit, for generating a real-time temperature distribution diagram according to the surface temperature of the out-of-furnace glass; the real-time temperature distribution diagram includes the real-time temperature values ​​of each surface area in the target object; the real-time temperature distribution diagram is input into the glass stress distribution model to generate the wind pressure control parameters applied to each surface area; the wind pressure control parameters are used to indicate the real-time target wind pressure required to be achieved by the quenching air grid module corresponding to each surface area;

[0029] The temperature control unit is used to control the corresponding independent air grid areas in the rapid cooling air grid module by using the air pressure control parameters to adjust the real-time air pressure of each surface area so that the cooling rate of each surface area is consistent.

[0030] The intelligent manufacturing device for colored glaze glass described above can implement each step in the method embodiment. Please refer to the specific description of the method embodiment below, which will not be expanded here.

[0031] In the embodiment of the present application, high-resolution scanning is used to collect the surface temperature of the colored glaze glass after it comes out of the furnace in real time, which can provide very accurate temperature data. This high-precision collection method can capture the temperature difference of small areas on the glass surface, which is crucial for subsequent precise control. For example, when producing glass with complex patterns or multiple layers of colored glaze, different colors of colored glaze or different parts of the pattern may have different sensitivities to temperature changes, and high-resolution scanning can accurately detect these subtle temperature changes.

[0032] The feature of real-time data collection enables the temperature data of the production process to be obtained in a timely manner. This is like installing a real-time thermometer in the production process. Once the temperature of the glass surface fluctuates abnormally, it can be monitored immediately. In glass production, the temperature changes very quickly after leaving the furnace. Real-time data collection can grasp the temperature information at the critical initial cooling stage, provide timely data support for subsequent adjustments, and avoid product quality degradation due to temperature out of control.

[0033] The target object is glazed glass, which allows the acquisition unit to be optimized for the characteristics of glazed glass. Compared with ordinary glass, the surface temperature distribution of glazed glass may be affected by factors such as glaze composition and thickness due to the presence of glaze layer. The acquisition unit focuses on glazed glass and can better adapt to this special temperature acquisition demand and improve the accuracy and reliability of data.

[0034] By generating a real-time temperature distribution graph, abstract temperature data is converted into an intuitive graphical representation. Production personnel can see at a glance the temperature of each area on the glass surface, just like having a "temperature map" of the glass surface. This visual method helps to quickly evaluate the overall temperature status of the glass. For example, it is easy to find areas with too high or too low temperatures, which facilitates targeted treatment.

[0035] The real-time temperature distribution map is input into the glass stress distribution model to generate wind pressure control parameters, realizing intelligent production control. Based on glass material science and thermal principles, the model can accurately calculate the wind pressure required for each surface area according to the temperature distribution to achieve the ideal cooling effect. This replaces the traditional control method that relies on experience or fixed parameters, improves the accuracy of wind pressure control, and effectively reduces the internal stress of the glass and improves product quality.

[0036] Since the corresponding wind pressure control parameters can be generated for each surface area, personalized control of the glass cooling process can be achieved. Different surface areas may require different cooling conditions due to factors such as the shape, thickness, and glaze distribution of the glass. This personalized control function of the generation unit can meet these complex and diverse needs and ensure that each area can be cooled at an appropriate cooling rate.

[0037] The temperature control unit uses the generated wind pressure control parameters to control each independent wind grid area in the quench wind grid module, achieving precise adjustment of the wind pressure in each area of ​​the glass surface. This precise control ensures that the wind pressure in each area can reach the real-time target wind pressure, so that the cooling rate can achieve the expected consistency. For example, when producing large glazed glass, the edge and center parts may require different wind pressures to balance the cooling rate due to different heat dissipation conditions. The temperature control unit can accurately achieve this control.

[0038] The beneficial effect of the cooling rate equalization core is to make the cooling rate of each surface area consistent. This is crucial to the quality of colored glaze glass, because uneven cooling rate will cause stress inside the glass, which will cause problems such as glass deformation, cracking or glaze peeling. By adjusting the wind pressure to make the cooling rate consistent, these quality defects can be effectively avoided and the product qualification rate and quality stability can be improved.

[0039] The temperature control unit helps to ensure the quality of colored glaze glass by precisely controlling the cooling process. While ensuring product quality, the ability to optimize the cooling process makes the glass production process more stable and efficient, reduces rework and waste caused by quality problems, reduces production costs, and improves production efficiency.

[0040] Figure 1The structure diagram of the colored glaze glass manufacturing equipment provided by an embodiment of the present application is shown. Figure 1 As shown, the embodiment of the present application provides a colored glaze glass manufacturing device. Figure 1 In this diagram, we show the layout of a production line, which may be used for production processes such as metal heat treatment or glass processing that require precise temperature control. Here are the functions and principles of each part:

[0041] The tempering furnace is the core of the entire production line. It is mainly used to heat materials (such as glass or metal) to the temperature required for tempering. During the tempering process, the internal structure of the material will change, making it stronger and more heat-resistant. The material is heated by a heating element (such as a resistance wire), usually to a higher temperature (for example, glass tempering may need to be heated to 600-700°C). During the heating process, the stress inside the material will be redistributed, thus achieving the tempering effect.

[0042] The heating zone is a specific area in the tempering furnace, which is mainly used to heat the material evenly. It ensures that the material reaches the required temperature before entering the next process. The heat generated by the heating element is used to radiate heat to the material, so that the molecules inside the material can obtain enough energy to change its physical properties, such as Figure 1 As shown, the heating zone consists of a preheating zone, a soaking zone and a lifting zone.

[0043] The preheating zone is used to preheat the material before it enters the heating zone. This process helps reduce stress that may occur in the material when it is heated rapidly. The material is heated gradually to 300 to 500°C by a relatively low power heating element.

[0044] The soaking zone is used to ensure that the temperature of the material is evenly distributed during the heating process. Avoid temperature gradients inside the material, which can lead to stress concentration. The material is kept at a uniform high temperature in this area, for example, in the range of 500 to 700°C, using heating elements and possible thermal circulation systems.

[0045] At the same time, during the glass tempering process, the main function of the lifting zone is to accelerate the temperature uniformity between the surface and the inside of the glass, and to begin to form surface compressive stress while maintaining tensile stress inside. After the glass passes through the uniform heating zone with the preheating temperature raised, it enters the lifting zone for cooling. The lifting zone quickly cools the glass surface in a specific way, while allowing the cooling speed of the inside of the glass to be relatively slow. In this way, a layer of compressive stress is formed on the surface of the glass, while tensile stress is maintained inside. When the glass is subjected to external forces, the surface compressive stress will help offset the external forces, making the glass less likely to break than ordinary glass, thereby improving the strength and safety performance of the glass. The rapid cooling wind grid is used to quickly cool the material after it comes out of the tempering furnace. Rapid cooling helps to fix the stress inside the material, so that it can achieve the tempering effect. The high-temperature material is quickly cooled by the strong wind generated by the high-pressure fan, so that the surface of the material is quickly cooled, thereby forming a stable stress structure inside the material.

[0046] The out-of-furnace temperature detection is used to monitor the temperature of the material when it comes out of the tempering furnace. Ensure that the material reaches the required temperature before entering the cooling zone. Use thermocouples or other temperature sensors to measure the material surface temperature in real time and feed the data back to the control system.

[0047] Polarized stress testing is used to detect the stress distribution inside the material. It ensures that the stress inside the material is evenly distributed as expected during the tempering process. By using a polarized microscope or other stress testing equipment, the distribution of internal stress can be determined by observing the interference fringes of the material under polarized light.

[0048] The transition plate is used to provide a transition platform when the material enters the cooling zone from the heating zone. It ensures that the material will not produce excessive stress due to sudden temperature changes during the movement. The transition plate is usually made of high temperature resistant materials, which can withstand the passage of high temperature materials and provide a smooth transition.

[0049] The cooling zone is used to further cool the high-temperature materials coming out of the tempering furnace. Ensure that the materials reach room temperature when leaving the production line. Use air cooling or water cooling system to cool the materials so that their temperature gradually drops to room temperature.

[0050] Ceramic coating is used to form a protective film on the surface of the material. Improve the wear resistance and corrosion resistance of the material. Through spraying or other coating processes, a uniform ceramic coating is formed on the surface of the material to protect the surface of the material.

[0051] Pressure sensors are used to monitor the pressure conditions in various parts of the production line. They ensure that the pressure of the equipment is within a safe range during operation. They sense pressure changes and convert them into electrical signals, which are then fed back to the control system for monitoring and adjustment.

[0052] The rack is used to support the various components of the entire production line. It ensures the stability of the equipment during operation. The rack is usually made of high-strength steel and can withstand the weight of the various parts of the production line and the stress generated during operation.

[0053] The motor is used to drive the conveyor belt or other moving parts of the production line. It ensures that the materials can move smoothly on the production line. By converting electrical energy into mechanical energy, the conveyor belt or other moving parts are driven to run at the set speed and direction.

[0054] Through the coordinated work of these components, the production line can achieve efficient and precise tempering processing of materials, ensuring product quality and production efficiency.

[0055] It should be added here that the control logic of the relevant device will be introduced in detail in the method embodiment below.

[0056] An embodiment of the present application provides an intelligent manufacturing method for colored glaze glass. The execution subject of the method described in this embodiment can be the intelligent manufacturing device for colored glaze glass in the above embodiment, and it is implemented on the basis of the structure of the intelligent manufacturing device for colored glaze glass in the above embodiment. Figure 2 As shown, the method may include the following steps:

[0057] 101. Real-time acquisition of the surface temperature of the out-of-furnace glass of the target object; wherein the target object is colored glaze glass, and the acquisition method is high-resolution scanning;

[0058] 102. Generate a real-time temperature distribution map according to the surface temperature of the out-of-furnace glass; the real-time temperature distribution map includes real-time temperature values ​​of each surface area in the target object;

[0059] 103. Input the real-time temperature distribution diagram into the glass stress distribution model to generate wind pressure control parameters applied to each surface area; the wind pressure control parameters are used to indicate the real-time target wind pressure required to be achieved by the quenching air grid module corresponding to each surface area;

[0060] 104. Use the wind pressure control parameters to control the corresponding independent wind grid areas in the rapid cooling wind grid module to adjust the real-time wind pressure of each surface area to make the cooling rate of each surface area consistent.

[0061] The traditional glass cooling process may cause stress concentration inside the glass due to uneven cooling. In the embodiment of the present application, the surface temperature of the out-of-furnace glass is collected in real time through high-resolution scanning and a temperature distribution diagram is generated, so that the temperature conditions of each surface area of ​​the glass can be accurately grasped. The wind pressure control parameters are generated using the glass stress distribution model to make the cooling rate of each surface area consistent. This effectively avoids the stress concentration phenomenon caused by local cooling that is too fast or too slow, thereby reducing the quality problems of glass such as cracking and deformation during the cooling process. For example, in the manufacture of colored glaze glass for construction, if stress concentration may cause the glass to explode after installation or during use, this uniform cooling method can greatly reduce such risks.

[0062] For colored glaze glass, a uniform cooling rate helps the colored glaze adhere better to the glass surface. Uneven cooling may cause inconsistent shrinkage or expansion of the colored glaze, which in turn affects the color, flatness and adhesion of the colored glaze. By precisely controlling the wind pressure to make the cooling rate consistent, the quality of the colored glaze can be guaranteed, making the appearance of the colored glaze glass more beautiful and the color more uniform, thereby improving the decorativeness and aesthetics of the product.

[0063] Since the cooling process of the glass is effectively controlled during the manufacturing process, the physical properties of the produced colored glaze glass are more stable. For example, the thermal expansion coefficient of the glass is more uniform in different areas, which makes the dimensional changes of the glass more regular under different temperature environments, improves the stability of the glass in actual use, and is suitable for occasions with high requirements for dimensional accuracy and stability, such as high-end building curtain walls, precision optical instruments, etc.

[0064] The whole process realizes intelligent manufacturing by collecting temperature in real time, generating temperature distribution diagrams and automatically generating wind pressure control parameters to control the quenching air grid module. This automated control method reduces the manual intervention process and avoids the errors and instability that may be caused by manual operation. Operators do not need to frequently adjust the cooling equipment manually, which saves labor costs, improves production efficiency and makes the production process smoother.

[0065] Since the temperature can be monitored in real time and the wind pressure can be adjusted quickly, the cooling process of the glass can be optimized in time according to the actual situation. Compared with the traditional method of relying on experience and fixed cooling parameters, this dynamic adjustment method can shorten the cooling time of the glass, thereby shortening the entire production cycle. For example, on a continuous production line, a faster cooling speed can increase the amount of colored glaze glass produced per unit time, thereby improving the production capacity of the production line.

[0066] As an optional embodiment, after the wind pressure control parameters are used to control the corresponding independent wind grid areas in the rapid cooling wind grid module to adjust the real-time wind pressure of each surface area, a polarizing device can be used to detect whether the surface stress distribution of the target object meets the qualified conditions after the target object is cooled; the qualified conditions include: a qualified value for indicating the minimum surface stress of each surface area. If the target object does not meet the qualified conditions, the target object is returned to the furnace for tempering or scrapped, and the real-time temperature value of each surface area and / or the wind pressure control parameters are stored as unqualified data in the process database for dynamic optimization of the glass stress distribution model. If the target object meets the qualified conditions, it is determined that the target object enters the film output process, and the real-time temperature value of each surface area and / or the wind pressure control parameters are stored as qualified data in the process database for dynamic optimization of the glass stress distribution model.

[0067] Polarized light devices use the polarization properties of light to detect stress distribution in glass. When light passes through stressed glass, the stress causes the glass to undergo birefringence, causing the polarization state of the light to change. By analyzing the change in the polarization state of the outgoing light, the distribution of stress inside the glass can be obtained.

[0068] The minimum qualified value of surface stress in each surface area is set as the judgment standard. This is determined based on the mechanical properties of the glass and the actual application requirements. If the surface stress of the glass is lower than the qualified value, problems such as cracking or deformation may occur during use.

[0069] According to the test results, the real-time temperature values ​​and / or wind pressure control parameters of each surface area of ​​the glass are stored as qualified data or unqualified data. These data reflect the relationship between the control parameters in the production process and the quality of the final product.

[0070] The stored data is used to dynamically optimize the glass stress distribution model. For unqualified data, the temperature value and wind pressure control parameters are analyzed to find out the reasons for the unqualified products, and then adjust the model, such as correcting the wind pressure control algorithm or the temperature-stress relationship model. For qualified data, the production parameters can be further optimized through analysis to improve the stability of product quality and production efficiency.

[0071] By detecting the surface stress distribution through the polarizing device, it is possible to accurately determine whether the colored glaze glass meets the quality requirements. This prevents unqualified products from entering the market and ensures the consistency and reliability of product quality. By re-tempering or scrapping unqualified products and analyzing the reasons for the unqualified products, problems in the production process can be discovered in a timely manner and measures can be taken to solve them, such as timely adjusting the wind pressure control parameters to make the target object meet the qualified conditions. With the continuous optimization of the production process, the qualified rate of products will gradually increase.

[0072] In the process database, the temperature values ​​and wind pressure control parameters in the production process are stored as a process database, providing data support for the long-term optimization of the production process. This database can be used as an accumulation of production experience for the enterprise to guide future production operations. Using the stored data to dynamically optimize the glass stress distribution model can make the production process more intelligent. With the continuous accumulation of production data, the model will predict and control the stress distribution of the glass more and more accurately, reduce manual intervention in the production process, and improve production efficiency and product quality.

[0073] In this way, by timely testing and re-tempering or scrapping unqualified products and optimizing the production process, the generation of waste can be reduced and production costs can be reduced. The optimized production process can reduce the production cycle and increase the output per unit time, thereby reducing the production cost per unit product and improving the economic benefits of the enterprise.

[0074] As an optional embodiment, it is assumed that the high-resolution scanning method is implemented by an infrared sensor array; a plurality of high-resolution infrared detection elements are deployed in the infrared sensor array, and the coverage range of the plurality of high-resolution infrared detection elements is greater than the sum of the surface areas of the target object. Based on this, the surface temperature of the out-of-furnace glass of the target object is collected in real time, including:

[0075] Through the multiple high-resolution infrared detection elements, linear scanning or two-dimensional scanning is performed on each surface area of ​​the target object to obtain the real-time infrared radiation intensity corresponding to each surface area; based on the mapping relationship between the real-time infrared radiation intensity, the pre-recorded infrared radiation intensity and the temperature, the surface temperature of the out-of-furnace glass corresponding to each surface area is generated.

[0076] The high-resolution infrared detection elements in the infrared sensor array can detect the infrared radiation emitted by the surface of the target object (enameled glass). All objects radiate infrared rays according to their own temperature. The higher the temperature, the greater the radiation intensity. These high-resolution infrared detection elements have high sensitivity and spatial resolution, and can accurately capture the infrared radiation conditions of different areas on the glass surface.

[0077] By scanning the glass surface linearly (line by line) or in two dimensions (similar to matrix scanning), the surface area of ​​the glass can be fully covered. This scanning method ensures that the temperature data of the entire glass surface can be collected.

[0078] The pre-recorded mapping relationship between infrared radiation intensity and temperature is based on the blackbody radiation law (such as Planck's law). Although the actual object is not an ideal blackbody, the corresponding relationship between infrared radiation intensity and temperature can be approximately determined through calibration and empirical formulas. Based on this mapping relationship, once the infrared radiation intensity of a certain area on the glass surface is detected, the temperature corresponding to that area can be calculated.

[0079] In this way, high-resolution infrared detection elements can provide accurate temperature data and capture temperature differences in small areas of the glass surface. This is very important for colored glaze glass, which may have uneven surface temperature, and helps to find local overheating or overcooling areas. Since the coverage of multiple detection elements is greater than the sum of the glass surface areas, it can ensure that every corner of the glass surface can be scanned without missing any area, thus achieving comprehensive temperature collection.

[0080] This scanning method can obtain the surface temperature of the glass when it comes out of the furnace in real time. During the glass production process, the temperature changes rapidly after it comes out of the furnace. Real-time temperature data can allow production personnel to understand the thermal state of the glass in a timely manner, facilitating timely adjustment of production parameters. Accurate real-time temperature data can be fed back to subsequent wind pressure control and other systems to achieve precise control of the glass cooling process, ensuring that the cooling rate of each surface area is consistent, thereby improving product quality.

[0081] Accurate temperature data provides a basis for optimizing the production process. By analyzing these temperature data, we can further understand the thermal behavior of glass during heating and cooling, which helps to optimize the heating and cooling process, reduce internal stress in the glass, and improve product qualification rate. Combined with subsequent automated operations such as wind pressure control, this temperature acquisition method based on infrared sensor arrays helps to realize the intelligent production of colored glaze glass, reduce manual intervention, and improve production efficiency.

[0082] As an optional embodiment, the generation of the surface temperature of the out-of-furnace glass corresponding to each surface area based on the mapping relationship between the real-time infrared radiation intensity and the pre-recorded infrared radiation intensity and temperature includes: converting the real-time infrared radiation intensity into a corresponding real-time temperature matrix according to the mapping relationship; the real-time temperature data points in the real-time temperature matrix correspond to the surface area one by one. Furthermore, the generation of a real-time temperature distribution map according to the surface temperature of the out-of-furnace glass includes: performing spatial smoothing on the real-time temperature data, and performing pseudo-color encoding on the real-time temperature data after spatial smoothing to construct the real-time temperature distribution map; wherein the color of the pseudo-color encoding is associated with the numerical value of the real-time temperature data.

[0083] Specifically, based on the blackbody radiation law, there is a specific mathematical relationship between the infrared radiation intensity and temperature of an object. The pre-entered mapping relationship between infrared radiation intensity and temperature is obtained through the practical application and calibration of the blackbody radiation law. When the real-time infrared radiation intensity is detected, it is converted into the corresponding temperature value through this mapping relationship. Since each surface area of ​​the glass is scanned, each surface area corresponds to an infrared radiation intensity data, and a real-time temperature matrix is ​​obtained after conversion. Each data point in this matrix corresponds to a specific area on the glass surface. Since the temperature data may be affected by noise interference or some errors of the detector itself during the collection process, the temperature data may fluctuate to a certain extent. Spatial smoothing is a digital image processing technology that reduces noise and local irregularities in the data by performing algorithms such as weighted averaging of adjacent data points, making the temperature data more continuous and smooth in space.

[0084] Pseudo color coding is to map the temperature value to the color space through a certain algorithm. Usually, different temperature ranges are matched with different colors. For example, low temperature may be represented by blue, high temperature may be represented by red, and intermediate temperature may be represented by green, yellow, etc. This color coding method allows people to intuitively judge the distribution of glass surface temperature from the color.

[0085] In this way, by converting the infrared radiation intensity into a temperature matrix, the temperature of each area on the glass surface can be accurately represented. This accuracy is crucial for the subsequent control of the cooling process and ensuring the quality of the glass. For example, when producing enameled glass, accurate temperature data can help avoid enameled quality problems caused by local temperatures being too high or too low. The temperature matrix format facilitates subsequent mathematical operations and data processing. Whether it is for statistical analysis of temperature data or for passing it as input to the glass stress distribution model, data in matrix form is more convenient to operate.

[0086] The pseudo-color coded temperature distribution map after spatial smoothing allows operators to intuitively see the temperature distribution on the glass surface. The difference in color can quickly determine the high and low temperature areas, so as to promptly discover potential production problems. For example, if local overheating is found on the glass surface, measures can be taken immediately to adjust the cooling parameters. This intuitive temperature distribution map helps to optimize the production process. By analyzing the temperature distribution map of multiple batches of glass production, the laws and abnormalities of temperature distribution can be summarized, and then the production process can be adjusted. For example, the power and position of the heating or cooling equipment can be adjusted to achieve a more uniform temperature distribution, reduce the internal stress of the glass, and improve the product qualification rate.

[0087] In the production process, the real-time temperature distribution map can serve as an important basis for quality control. If there are quality problems with glass products, such as cracking or deformation, the possible causes can be traced back by viewing the temperature distribution map at that time, such as whether there is uneven cooling, etc., thereby achieving fault diagnosis and continuous improvement of the production process.

[0088] Further optionally, the human eye has a stronger ability to distinguish colors than grayscale. By mapping temperature data to a color space, the temperature distribution can be more intuitively displayed. For example, the color space can be RGB (red, green, blue), HSV (hue, saturation, brightness), etc. In pseudo-color encoding, these color spaces are usually selected for temperature-color mapping. Set a temperature range, for example, the lowest value of the glass surface temperature is Tmin, and the highest value is Tmax. At the same time, select the corresponding color range in the color space, such as in the RGB space, low temperature corresponds to blue (0, 0, 255), and high temperature corresponds to red (255, 0, 0). The mapping of intermediate temperatures is achieved by linear interpolation. Assuming that the ratio of a certain temperature T in the temperature range is k=(T—Tmin) / (Tmax—Tmin), the corresponding color can be obtained by linear interpolation between blue and red. For example, in the RGB space, the corresponding color R = 255*k, G = 0, B = 255*(1—k). The temperature range can be divided into multiple sub-ranges, each of which corresponds to a different color change pattern. For example, in the low temperature range, it may change from dark blue to light blue, in the medium temperature range, it may change from light blue to green, and in the high temperature range, it may change from green to red. This multi-segment linear mapping can show the temperature distribution in more detail.

[0089] In the HSV color space, hue can be used to represent temperature. For example, the range of hue (0-360 degrees) is divided into 0 degrees corresponding to low temperature (such as blue), 180 degrees corresponding to medium temperature (such as green), and 360 degrees corresponding to high temperature (such as red). Saturation and value can be adjusted according to actual needs. Generally, they can be set to fixed values, or fine-tuned according to the absolute or relative value of the temperature to enhance color contrast and visual effects. A temperature-color lookup table can be established in advance. For a given temperature value, the corresponding color value is directly obtained through the lookup table. This method is more efficient in practical applications, especially when processing a large amount of temperature data. The lookup table can be pre-calculated using experimental data, empirical formulas, or the above-mentioned linear / nonlinear mapping methods.

[0090] In this way, pseudo color coding can effectively map temperature values ​​to color space and generate intuitive temperature distribution diagrams to control temperature conditions during the production process.

[0091] As an optional embodiment, before generating the surface temperature of the out-of-furnace glass corresponding to each surface area based on the real-time infrared radiation intensity and the mapping relationship between the pre-recorded infrared radiation intensity and the temperature, the glass attribute information to which the target object belongs can also be identified; the glass attribute information at least includes: glass material type, glass size information, and product type. Furthermore, the number and distribution density of the surface areas of the target object are configured based on the glass attribute information.

[0092] Specifically, first of all, different types of glass materials (such as ordinary flat glass, tempered glass, laminated glass, etc.) have different thermophysical properties, including thermal conductivity, thermal expansion coefficient, etc. These properties will affect the temperature change law of glass during heating and cooling. Glass size information (such as length, width, thickness) is also critical. The time and method of heat transfer during heating and cooling of larger-sized glass are different from those of small-sized glass, and different product types (such as architectural glass, automotive glass, decorative glass, etc.) may also have different requirements for temperature control accuracy and surface quality. By identifying these glass attribute information, the number and distribution density of surface areas can be reasonably configured according to the thermal properties, dimensional factors and product quality requirements of different glass materials. For example, for architectural glass with low thermal conductivity and large size, in order to control the temperature more accurately, it may be necessary to divide more surface areas and set a higher distribution density in areas where the temperature change may be large, such as the edge and center, to ensure that the temperature of each part of the glass can be accurately monitored and controlled. In the configuration process, the heat conduction equation, empirical formulas and research results on the production process of different products may be used to determine the appropriate number and distribution of areas.

[0093] This method can significantly improve the accuracy and effectiveness of temperature monitoring. By configuring the number and distribution density of surface areas according to different glass properties, the temperature changes on the glass surface can be captured more accurately. For complex glass products, such as glass with special shapes or multi-layer structures, it can better adapt to its temperature distribution characteristics and avoid temperature monitoring blind spots or excessive monitoring caused by unreasonable area division. From the perspective of production quality, this helps to better control the cooling process of the glass, because accurate temperature monitoring is the prerequisite for ensuring consistent cooling rates in each surface area. This effectively reduces the internal stress of the glass and reduces the probability of quality problems such as glass cracking and deformation. Moreover, this refined temperature monitoring method can be customized according to different product requirements, improves the flexibility of the production process, can meet the requirements of different customers for the quality and performance of glass products, and enhances the competitiveness of products in the market. At the same time, it also helps to optimize the production process, reduce unnecessary data collection and processing through reasonable area configuration, and improve production efficiency.

[0094] As an optional embodiment, the mapping relationship is expressed as the following formula: ;in, is the real-time infrared radiation intensity, is the infrared radiation intensity, is a preset constant.

[0095] This formula describes a quantitative relationship between real-time infrared radiation intensity and temperature. The existence of preset constants is to calibrate this relationship based on physical laws and empirical data. This relationship is likely derived from the blackbody radiation law. In practical applications, although glass is not an ideal blackbody, this formula combined with constants can be used to approximately convert the detected infrared radiation intensity into temperature. Through such a mathematical expression, the corresponding temperature value can be calculated based on the real-time infrared radiation intensity obtained by the detection element using known constants, thereby realizing a quantitative estimation of the glass surface temperature. This formulated mapping relationship provides an accurate and repeatable temperature calculation method. The temperature calculation process is standardized, and the corresponding temperature estimate can be quickly and accurately obtained according to this formula each time the real-time infrared radiation intensity is collected. This helps to improve the temperature monitoring accuracy in the production process and provide a reliable data basis for subsequent process control (such as generating wind pressure control parameters based on temperature). At the same time, this formulated relationship is easy to adjust and optimize during the production process. If it is found that the temperature calculation result deviates from the actual situation, the accuracy of the calculation can be improved by adjusting the preset constants, so as to better adapt to different production environments and glass product characteristics.

[0096] As an optional embodiment, the real-time temperature distribution map is input into a glass stress distribution model to generate wind pressure control parameters applied to each surface area, including:

[0097] The real-time temperature distribution map is converted into a stress distribution on the glass surface; the stress distribution on the glass surface is divided into a plurality of stress distribution units, and the stress numerical differences between the plurality of stress distribution units are analyzed; the plurality of stress distribution units correspond to respective surface regions; the plurality of stress distribution units are iterated multiple times according to the stress numerical differences to obtain the glass surface stress optimization values ​​corresponding to the plurality of stress distribution units; the number of iterations is associated with the structural complexity within the surface region corresponding to the stress distribution unit; and the wind pressure control parameter is generated according to the glass surface stress optimization value.

[0098] Specifically, first converting the real-time temperature distribution map into the stress distribution on the glass surface is based on thermal stress theory. During the heating and cooling process of the glass, the uneven temperature distribution will cause thermal stress inside. The stress distribution can be derived from the temperature distribution through certain physical models and calculation methods. The stress distribution on the glass surface is divided into multiple stress distribution units, and these units are made to correspond to each surface area in order to be able to finely analyze and process stress differences. Because different surface areas have different stress conditions due to different temperature changes.

[0099] By analyzing the difference in stress values ​​between stress distribution units, an iterative approach is used to obtain the stress optimization value. The iterative process takes into account the structural complexity within the surface area, because areas with complex structures (such as glaze patterns, thickness changes, etc.) have their own particularities in the stress generation and transmission process. Complex structural areas may require more iterations to more accurately calculate stress changes, thereby obtaining reasonable stress optimization values. Finally, the generation of wind pressure control parameters based on the glass surface stress optimization value is based on the principle of the influence of wind pressure on the glass cooling rate. Wind pressure can adjust the cooling rate of the glass surface, thereby changing the stress distribution inside the glass. By establishing the relationship between wind pressure and stress optimization value, appropriate wind pressure control parameters can be generated to control the cooling process of the glass.

[0100] In terms of accuracy, this method can more accurately consider the stress conditions in each area of ​​the glass surface. By dividing the unit and iteratively calculating the stress optimization value, it effectively copes with the stress change problem caused by uneven temperature and complex structure on the glass surface, making the analysis and control of glass stress more detailed. In terms of product quality, the generated wind pressure control parameters can more accurately adjust the wind pressure in each surface area, ensuring that the cooling rate of each area of ​​the glass is more consistent during the cooling process, thereby effectively reducing the stress concentration inside the glass and reducing the probability of quality problems such as deformation, cracking or glaze peeling. In terms of production efficiency, although iterative calculation considering the structural complexity in the surface area increases a certain amount of calculation, from the perspective of the overall production process, precise control can reduce the production of unqualified products, avoid rework due to product quality problems, and improve the product qualification rate, thereby improving production efficiency. In addition, this refined control helps to flexibly adjust production parameters under different production conditions and glass product requirements, and enhances the adaptability of the production process.

[0101] As an optional embodiment, converting the real-time temperature distribution map into glass surface stress distribution includes:

[0102] Extracting thermal strain tensor features from the real-time temperature distribution map;

[0103] The thermal strain tensor characteristics are converted into glass surface stress characteristics by using a preset formula, and the glass surface stress distribution is constructed by using the glass surface stress characteristics;

[0104] The relationship between the glass surface stress characteristics and the glass surface stress characteristics is expressed as follows: ;

[0105] in, is the glass surface stress characteristic corresponding to the surface area in row i and column j, is the thermal strain tensor feature corresponding to the surface area in row i and column j, is the real-time temperature corresponding to the area in row i and column j, is the temperature threshold, and is the preset constant, , , E is the surface tension characteristic parameter of glass material, v is the temperature sensitivity parameter of glass material, is the invariant corresponding to the thermal strain tensor characteristics, is the Kronecker symbol. When i equals j, Set to 1; when i is equal to j, Set to 0.

[0106] In another example, the thermodynamic module is the foundation of the entire model. Its core is to use finite element analysis (FEA) to describe the relationship between the temperature distribution and thermal stress on the glass surface. During the rapid cooling of the glass, due to the rapid change in temperature, the glass will experience thermal expansion and contraction. The thermodynamic module simulates the physical process of thermal expansion and contraction, providing a temperature-related basis for the subsequent calculation of the stress distribution on the glass surface.

[0107] The mechanics module is built on the output of the thermodynamics module. Since there are glazed areas and transparent areas in glass, the material properties of different areas are different, so they need to be considered separately when calculating the residual stress distribution. For each area, a stress distribution model is established based on its unique material properties (such as elastic modulus, Poisson's ratio, etc.), and the residual stress distribution on the glass surface is accurately calculated.

[0108] The data correction module is mainly used to optimize model parameters. It adjusts the deviation between the model's predicted value and the actual value based on historical test data, such as polarization test results. In the actual production process, due to the influence of various complex factors, the model's predicted results may have certain errors from the actual situation. The data correction module continuously corrects the model parameters by analyzing and learning historical data to make its predicted results more accurate.

[0109] The role of the feedback optimization module is to ensure the adaptability of the model to the actual production process. It combines real-time temperature measurement data to dynamically update the model. During the production process, the temperature, stress and other states of the glass are constantly changing. By receiving real-time temperature measurement data and feeding it back to the model, the model can adjust its calculations and predictions in a timely manner to better reflect the actual situation in the current production process.

[0110] Thermal stress calculation formula principle, glass will generate thermal stress when the temperature changes. The elastic modulus reflects the ability of glass to resist elastic deformation. The higher the elastic modulus, the greater the stress generated by the glass under the same temperature change. This is because glass with a high elastic modulus is less likely to deform when it is subjected to the "tendency" of expansion or contraction caused by temperature changes, and thus generates greater stress to resist this tendency. The thermal expansion coefficient determines the degree of expansion or contraction of the glass when the temperature changes. The larger the thermal expansion coefficient, the greater the dimensional change of the glass under the same temperature change. When this dimensional change is restricted (for example, the temperature change of different parts of the glass is uneven), stress will be generated. Local temperature changes are the direct cause of thermal stress. The temperature difference at different locations on the glass surface will cause different degrees of expansion or contraction. If the temperature changes of adjacent areas are different, they will restrict each other, thus generating stress. The greater the temperature change, the greater the thermal stress generated. Poisson's ratio describes the ratio of the absolute value of the lateral normal strain to the axial normal strain when the material is subjected to unidirectional tension or compression. When calculating thermal stress, Poisson's ratio will affect the calculated results of stress. It reflects a characteristic of the material when it is deformed under stress and has a certain corrective effect on the final size of thermal stress.

[0111] There are different areas in glass, such as glaze areas and transparent areas. The material properties of these areas are different, and the stress generated when the temperature changes is also different. Different areas (such as the i-th area) will generate their own local stress when the temperature changes. Due to differences in material properties (such as elastic modulus, thermal expansion coefficient, etc.), the stress magnitude and distribution of each area are different. The weight (wi) is used to comprehensively consider the contribution of the stress in each area to the total stress. It is usually calculated based on the area or temperature difference of the area. If an area is large, then its contribution to the total stress may be relatively large, and the weight will be larger; similarly, if the temperature difference in an area is large, the stress generated will have a greater impact on the total stress, and its weight will also be larger accordingly. By multiplying the local stress of each area by the corresponding weight and summing them, a more accurate total stress distribution of the glass can be obtained, thereby comprehensively considering the stress conditions caused by differences in material properties and temperature changes in different areas.

[0112] The stress distribution diagram generated by the above model uses color coding to intuitively represent the stress magnitude in different areas. This visualization method is very convenient for operators to observe and analyze. For example, stress concentration areas (such as the edge of colored glaze) are highlighted in red, which allows operators to quickly identify stress concentration areas and then optimize wind pressure parameters based on this information to ensure that the stress distribution of the glass is more uniform during the cooling process, reducing the possibility of quality problems such as glass cracking and deformation.

[0113] The real-time temperature distribution diagram is the key input data for model calculation, which provides spatial information on the temperature distribution of the glass surface. By obtaining the temperature conditions at various locations on the glass surface, the model can calculate the generation and distribution of thermal stress based on temperature changes. The material parameters of glass and glaze, such as physical parameters such as elastic modulus and thermal expansion coefficient, are also essential inputs to the model. These parameters reflect the characteristics of the material itself and are crucial for accurately calculating stress distribution. Different types of glass and glaze have different material parameters, and the model needs to obtain these parameter values ​​based on the actual materials used.

[0114] The specific process can be realized as follows: First, the temperature distribution map is converted into the stress distribution on the glass surface through the thermodynamic module. In this process, numerical simulation methods such as the finite element method are used to analyze the stress difference between the glaze area and the transparent area in detail. Due to the different material properties of the two areas, the temperature change has different effects on their stress, and this difference can be accurately captured by numerical simulation. In the stress correction stage, the model compares the historical polarization detection results with its own predicted values. Using the error feedback mechanism, the model is optimized by continuously adjusting the model parameters. Especially in complex areas such as the glaze boundary, due to the complex stress distribution, the model may require multiple iterations to approach the actual stress value, thereby improving the accuracy of stress calculation. After the model outputs the stress distribution map, it is compared with the target stress uniformity requirement to identify the stress concentration area. Then, the stress information is transmitted to the control system, and the quenching wind pressure is dynamically adjusted according to the stress distribution. For areas with higher stress, the wind pressure is increased to increase the cooling rate so that the stress in the area can be released and balanced faster; for areas with lower stress, the wind pressure is reduced to reduce the cooling rate to avoid excessive cooling and cause new stress. Through this wind pressure adjustment method, the stress distribution on the glass surface is made more uniform.

[0115] Optionally, the model has a closed-loop feedback mechanism, which can receive temperature feedback after wind pressure adjustment in real time, and update the stress distribution prediction results based on this feedback information. This closed-loop control method enables the model to continuously adapt to dynamic changes in the production line, such as changes in glass materials, changes in the production environment, etc. As the production process proceeds, the model gradually optimizes its own prediction and control capabilities through continuous learning and adjustment, ensuring that stress control in the glass production process is more accurate and stable.

[0116] In the embodiment of the present application, the surface temperature of the out-of-furnace glass of the target object is collected in real time; the target object is colored glaze glass, and the collection method is high-resolution scanning; a real-time temperature distribution map is generated according to the surface temperature of the out-of-furnace glass; the real-time temperature distribution map contains the real-time temperature values ​​of each surface area in the target object; the real-time temperature distribution map is input into the glass stress distribution model to generate the wind pressure control parameters applied to each surface area; the wind pressure control parameters are used to indicate the real-time target wind pressure required to be achieved by the quenching air grid module corresponding to each surface area; the wind pressure control parameters are used to control the corresponding independent air grid areas in the quenching air grid module. The present application can adjust the real-time wind pressure of each surface area to make the cooling rate of each surface area consistent, solve the temperature difference and stress imbalance problems in the tempering of colored glaze glass, and improve the overall quality of the product.

[0117] Based on the same implementation principle, the embodiment of the present application provides an intelligent manufacturing device for colored glaze glass, which includes at least the following units:

[0118] The acquisition unit is used to acquire the surface temperature of the out-of-furnace glass of the target object in real time; wherein the target object is colored glaze glass, and the acquisition method is high-resolution scanning;

[0119] A generating unit, for generating a real-time temperature distribution diagram according to the surface temperature of the out-of-furnace glass; the real-time temperature distribution diagram includes the real-time temperature values ​​of each surface area in the target object; the real-time temperature distribution diagram is input into the glass stress distribution model to generate the wind pressure control parameters applied to each surface area; the wind pressure control parameters are used to indicate the real-time target wind pressure required to be achieved by the quenching air grid module corresponding to each surface area;

[0120] The temperature control unit is used to control the corresponding independent air grid areas in the rapid cooling air grid module by using the air pressure control parameters to adjust the real-time air pressure of each surface area so that the cooling rate of each surface area is consistent.

[0121] The specific implementation of each unit in the above device can refer to the previous embodiment, which will not be elaborated here.

[0122] Based on the same implementation principle, the embodiment of the present application also provides an electronic device, Figure 3is a structural block diagram of the electronic device 300, such as Figure 3 As shown, the electronic device 300 includes: a processor 301, a memory 302, a communication interface 303, a communication bus 304 and a controller 305; wherein the processor 301, the memory 302, and the communication interface 303 communicate with each other via the communication bus 304; the memory 302 is used to store computer programs; the processor 301 is used to execute the programs stored in the memory 302 to realize the corresponding processing functions; the communication bus 304 is used for communication between the electronic device 300 and other devices; the controller 305 is used to realize the intelligent manufacturing method of colored glaze glass described in the above method embodiment.

[0123] In the embodiment of the present application, the communication bus 304 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus 304 may be divided into an address bus, a data bus, a control bus, etc., and the specific form is not limited. For ease of representation, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0124] The memory 302 may include a random access memory (RAM) or a non-volatile memory (non-volatile memory), such as at least one disk memory. Optionally, the memory may also be at least one storage device located far away from the processor 301 .

[0125] The processor 301 can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other editable logic devices, discrete gate or transistor logic devices, discrete hardware components, and the specific form can be determined according to actual needs.

[0126] Accordingly, an embodiment of the present application further provides a computer-readable storage medium storing a computer program, which, when executed, can implement each step that can be performed by an electronic device in the above method embodiment.

[0127] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. An intelligent manufacturing method for colored glaze glass, characterized in that: The method comprises: Real-time acquisition of the surface temperature of the target object's out-of-furnace glass; where the target object is colored glaze glass, the acquisition method is high-resolution scanning; Generate a real-time temperature distribution map according to the surface temperature of the glass out of the furnace; the real-time temperature distribution map includes the real-time temperature values ​​of each surface area in the target object; Converting the real-time temperature distribution map into a stress distribution on the glass surface; dividing the stress distribution on the glass surface into a plurality of stress distribution units, and analyzing the stress value differences between the plurality of stress distribution units; the plurality of stress distribution units correspond to respective surface regions; performing multiple iterations on the plurality of stress distribution units according to the stress value differences, so as to obtain the glass surface stress optimization values ​​corresponding to the plurality of stress distribution units respectively; the number of iterations is associated with the structural complexity in the surface region corresponding to the stress distribution unit; Generate wind pressure control parameters according to the glass surface stress optimization value; the wind pressure control parameters are used to indicate the real-time target wind pressure that the quenching air grid modules corresponding to each surface area need to achieve; The wind pressure control parameters are used to control the corresponding independent wind grid areas in the quench wind grid module to adjust the real-time wind pressure of each surface area so that the cooling rate of each surface area is consistent; Wherein, converting the real-time temperature distribution map into glass surface stress distribution includes: Extracting thermal strain tensor features from the real-time temperature distribution map; The thermal strain tensor characteristics are converted into glass surface stress characteristics by using a preset formula, and the glass surface stress distribution is constructed by using the glass surface stress characteristics; The relationship between the thermal strain tensor characteristic and the glass surface stress characteristic is expressed as follows: ;in, is the glass surface stress characteristic corresponding to the surface area in row i and column j, is the thermal strain tensor feature corresponding to the surface area in row i and column j, is the real-time temperature corresponding to the area in row i and column j, is the temperature threshold, and is the preset constant, , , E is the surface tension characteristic parameter of glass material, v is the temperature sensitivity parameter of glass material, is the invariant corresponding to the thermal strain tensor characteristics, is the Kronecker symbol.

2. The method according to claim 1, characterized in that: After the wind pressure control parameters are used to control the corresponding independent wind grid areas in the quench wind grid module to adjust the real-time wind pressure of each surface area, the method further includes: After the target object is cooled, a polarizing device is used to detect whether the surface stress distribution of the target object meets the qualified conditions; the qualified conditions include: the minimum surface stress qualified value of each surface area; If the target object does not meet the qualified conditions, the target object is returned to the furnace for tempering or scrapped, and the real-time temperature value of each surface area and / or the wind pressure control parameter are stored as unqualified data in the process database, so as to dynamically optimize the glass stress distribution model and timely adjust the wind pressure control parameter to make the target object meet the qualified conditions; If the target object meets the qualified conditions, the target object is determined to enter the sheet output process, and the real-time temperature value of each surface area and / or the wind pressure control parameter is stored as qualified data in the process database to dynamically optimize the glass stress distribution model.

3. The method according to claim 1, characterized in that The high-resolution scanning method is realized by an infrared sensor array; a plurality of high-resolution infrared detection elements are deployed in the infrared sensor array, and the coverage area of ​​the plurality of high-resolution infrared detection elements is greater than the sum of the surface areas of the target object; The real-time acquisition of the surface temperature of the out-of-furnace glass of the target object comprises: By using the plurality of high-resolution infrared detection elements, linear scanning or two-dimensional scanning is performed on each surface area of ​​the target object to obtain the real-time infrared radiation intensity corresponding to each surface area; Based on the real-time infrared radiation intensity, the mapping relationship between the pre-recorded infrared radiation intensity and the temperature, the surface temperature of the out-of-furnace glass corresponding to each surface area is generated.

4. The method according to claim 3, characterized in that The method of generating the surface temperature of the out-of-furnace glass corresponding to each surface area based on the real-time infrared radiation intensity and the mapping relationship between the pre-recorded infrared radiation intensity and the temperature includes: Converting the real-time infrared radiation intensity into a corresponding real-time temperature matrix according to the mapping relationship; the real-time temperature data points in the real-time temperature matrix correspond one-to-one to the surface areas; The generating of a real-time temperature distribution diagram according to the surface temperature of the out-of-furnace glass comprises: The real-time temperature data is spatially smoothed, and the real-time temperature data after spatial smoothing is pseudo-color encoded to construct the real-time temperature distribution map; wherein the color of the pseudo-color encoding is associated with the numerical value of the real-time temperature data.

5. The method according to claim 4, characterized in that Before generating the surface temperature of the out-of-furnace glass corresponding to each surface area based on the real-time infrared radiation intensity and the mapping relationship between the pre-recorded infrared radiation intensity and the temperature, the method further includes: Identify the glass property information of the target object; the glass property information at least includes: glass material type, glass size information, and product type; The number and distribution density of the surface areas of the target object are configured based on the glass property information.

6. The method according to any one of claims 3 to 5, characterized in that: The mapping relationship is expressed as the following formula: ;in, is the real-time infrared radiation intensity, is the infrared radiation intensity, is a preset constant.

7. An intelligent manufacturing device for colored glaze glass, characterized in that: The device at least comprises the following units, wherein The acquisition unit is used to acquire the surface temperature of the out-of-furnace glass of the target object in real time; wherein the target object is colored glaze glass, and the acquisition method is high-resolution scanning; A generating unit is used to generate a real-time temperature distribution map according to the surface temperature of the out-of-furnace glass; the real-time temperature distribution map includes the real-time temperature values ​​of each surface area in the target object; the real-time temperature distribution map is converted into a stress distribution on the glass surface; the stress distribution on the glass surface is divided into a plurality of stress distribution units, and the stress numerical differences between the plurality of stress distribution units are analyzed; the plurality of stress distribution units correspond to each surface area respectively; the plurality of stress distribution units are iterated multiple times according to the stress numerical differences to obtain the glass surface stress optimization values ​​corresponding to each of the plurality of stress distribution units; the number of iterations is associated with the structural complexity in the surface area corresponding to the stress distribution unit; the wind pressure control parameter is generated according to the glass surface stress optimization value; the wind pressure control parameter is used to indicate the real-time target wind pressure required to be achieved by the quenching air grid module corresponding to each surface area; wherein, the converting of the real-time temperature distribution map into the stress distribution on the glass surface comprises: extracting the thermal strain tensor feature in the real-time temperature distribution map; converting the thermal strain tensor feature into the glass surface stress feature using a preset formula, and constructing the glass surface stress distribution with the glass surface stress feature; wherein the relationship between the thermal strain tensor feature and the glass surface stress feature is expressed as follows: ;in, is the glass surface stress characteristic corresponding to the surface area in row i and column j, is the thermal strain tensor feature corresponding to the surface area in row i and column j, is the real-time temperature corresponding to the area in row i and column j, is the temperature threshold, and is the preset constant, , , E is the surface tension characteristic parameter of glass material, v is the temperature sensitivity parameter of glass material, is the invariant corresponding to the thermal strain tensor characteristics, is the Kronecker symbol; The temperature control unit is used to control the corresponding independent air grid areas in the rapid cooling air grid module by using the air pressure control parameters to adjust the real-time air pressure of each surface area so that the cooling rate of each surface area is consistent.

8. An electronic device, characterized in that: include: Memory for storing computer software programs; A processor is used to read and execute the computer software program, thereby implementing the intelligent manufacturing method of colored glaze glass as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium, characterized in that: The storage medium stores a computer software program, and when the computer software program is executed by the processor, the intelligent manufacturing method for colored glaze glass according to any one of claims 1 to 6 is implemented.

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