Preparation method and system for realizing transparent flame-retardant light diffusion polypropylene material

Abstract

The invention relates to the technical field of material chemical industry, in particular to a preparation method and system for a transparent flame-retardant light-diffusion polypropylene material, and the method comprises the following steps: pretreating a production raw material set to obtain pretreated polypropylene powder and a pretreatment auxiliary agent, mixing according to an optimal mixing ratio to obtain a mixed raw material, and preparing the transparent flame-retardant light-diffusion polypropylene material. The preparation method comprises the following steps: carrying out melt extrusion on mixed raw materials according to a plurality of melting temperatures to obtain a polypropylene melt, carrying out cooling shaping to obtain a polypropylene finished body, carrying out performance test on the polypropylene finished body to obtain an optimal melting temperature, carrying out scale preparation by using the optimal mixing ratio and the optimal melting temperature to obtain a polypropylene granule finished body, and carrying out granulation treatment on the polypropylene granule finished body to obtain the polypropylene composite material. And carrying out morphology filtration on the plurality of polypropylene samples to obtain a defect-free granular material set, and carrying out hot pressing treatment on the defect-free granular material set to obtain the polypropylene sheet. The transparent flame-retardant light diffusion polypropylene material can solve the problem that the transparent flame-retardant light diffusion polypropylene material is difficult to consider high transparency, high flame retardancy and uniform light diffusion performance at the same time.

Description

Technical Field

[0001] This invention relates to the field of materials and chemical engineering, and in particular to a method and system for preparing transparent, flame-retardant, light-diffusing polypropylene materials. Background Technology

[0002] With the rapid development of the materials and chemical industry, the preparation of transparent flame-retardant light-diffusing polypropylene materials faces new challenges. The difficulty in simultaneously achieving high transparency, high flame retardancy, and uniform light diffusion performance in transparent flame-retardant light-diffusing polypropylene materials can be addressed through systematic formulation optimization, parallel testing of multiple melting temperatures, and morphology screening.

[0003] Currently, the extraction of natural pigments is mainly achieved using fixed process parameters. While polypropylene materials can be prepared using fixed process parameters, the process suffers from low efficiency, high energy consumption, and reliance on a single set of process parameters. Therefore, optimizing the preparation method for transparent, flame-retardant, light-diffusing polypropylene materials is of great significance for improving the production quality and efficiency of polypropylene materials. Summary of the Invention

[0004] This invention provides a method for preparing transparent flame-retardant light-diffusing polypropylene materials and a computer-readable storage medium. Its main purpose is to solve the problem that transparent flame-retardant light-diffusing polypropylene materials are difficult to achieve simultaneously with high transparency, high flame retardancy, and uniform light diffusion performance.

[0005] To achieve the above objectives, the present invention provides a method for preparing a transparent, flame-retardant, light-diffusing polypropylene material, comprising: Obtain material production specifications and determine the optimal blending ratio based on those specifications. The pre-confirmed set of production raw materials is pre-treated to obtain pre-treated polypropylene powder and pre-treatment additives. Pretreated polypropylene powder and pretreated additives are mixed in the optimal mixing ratio to obtain mixed raw materials. The mixed raw materials are then grouped according to multiple preset melting temperatures to obtain multiple groups of mixed raw materials. For each of the multiple batches of mixed raw materials, perform the following operations: The mixed raw materials are melt-extruded using the melting temperature corresponding to the mixed raw materials to obtain polypropylene melt; The polypropylene melt is cooled and shaped to obtain the polypropylene body; The performance of the polypropylene molecule was tested, and a test report was obtained. By summarizing the test reports, multiple test reports are obtained; A comprehensive performance score set is obtained by using multiple test reports. The comprehensive performance score set includes multiple comprehensive performance scores, and each comprehensive performance score corresponds one-to-one with the mixed raw materials. The optimal melting temperature is determined based on multiple comprehensive performance scores. Polypropylene granules were prepared on a large scale using the optimal mixing ratio and optimal melting temperature. Polypropylene granules are pelletized to obtain a polypropylene sample set, which includes multiple polypropylene samples. Multiple polypropylene samples were subjected to morphology filtration to obtain a defect-free granule set, which included multiple defect-free granules. All defect-free granules were subjected to hot pressing to obtain polypropylene sheets.

[0006] Optionally, obtaining the optimal blending ratio based on material production specifications includes: A material ratio set is obtained based on the material production specifications, wherein the material ratio set includes multiple material ratios; Obtain historical production data for each of the multiple material proportions to obtain multiple historical production data sets; Perform the following operation on each of the multiple historical production data sets: Obtain energy consumption per unit output, production cycle, and product qualification rate from historical production data; Normalize the energy consumption per unit output, production cycle and product qualification rate respectively to obtain normalized energy consumption per unit output, normalized production cycle and normalized product qualification rate. Efficiency values ​​are calculated using normalized unit output energy consumption, normalized production cycle, and normalized product qualification rate. By summing the efficiency values, multiple efficiency values ​​are obtained; The maximum efficiency value is obtained based on multiple efficiency values, and the material ratio corresponding to the maximum efficiency value is taken as the optimal mixing ratio.

[0007] Optionally, the pretreatment of the pre-confirmed set of production raw materials to obtain pretreated polypropylene powder and pretreatment additives includes: Polypropylene powder and production aids are extracted from raw materials. Polypropylene powder is subjected to segmented gradient drying to obtain pre-dried powder. The moisture content of the pre-dried powder was tested to obtain the moisture content value; If the moisture content is greater than or equal to the preset moisture content threshold, the pre-dried powder is used as polypropylene powder, and the process returns to the step of performing segmented gradient drying on the polypropylene powder until the moisture content is less than the moisture content threshold, and the pre-dried powder is used as pretreated polypropylene powder. The production aids are surface activated to obtain pretreated aids.

[0008] Optionally, the step of mixing the pretreated polypropylene powder and pretreatment additives according to the optimal mixing ratio to obtain the compounded raw material includes: Pretreated polypropylene powder was subjected to segmented preheating treatment using a pre-confirmed high-speed mixer to obtain preheated polypropylene powder. Preheated polypropylene powder and pretreatment additives are mixed according to the optimal mixing ratio to obtain proportioned polypropylene powder and proportioned additives. Transparent flame retardants and light diffusing agents were extracted from the formulation additives; The polypropylene powder and transparent flame retardant were initially mixed to obtain the initial mixed raw material; The initial raw materials and light diffusing agent are subjected to high-speed activation and mixing to obtain a uniform premix; The uniform premix is ​​stirred at low temperature to obtain the compounded raw materials.

[0009] Optionally, the step of melting and extruding the mixed raw materials using the melting temperature corresponding to the mixed raw materials to obtain polypropylene melt includes: The mixed raw materials are heated in stages and sections to obtain a preliminary molten material; High-temperature, high-shear melting of pre-molten material is performed using the melting temperature to obtain a flowing melt; Vacuum devolatilization is performed on the flowing melt to obtain a low-volatility melt; Low-volatility melts are homogenized at low temperatures to obtain homogenized melts; The homogenized melt is subjected to graded filtration to obtain a high-purity melt. The high-purity melt is then subjected to impurity detection to obtain an impurity detection report. The qualified high-purity melt was confirmed using the impurity test report and was then used as the polypropylene melt.

[0010] Optionally, the performance testing of the polypropylene molecule to obtain a test report includes: The thickness of the polypropylene matrix is ​​measured using a preset length interval to obtain a set of thickness values, which includes multiple thickness values. Obtain the thickness standard deviation using multiple thickness values; The total transmitted light flux was measured on the polypropylene matrix to obtain the total transmitted light flux. Parallel transmission light flux was measured on the polypropylene matrix to obtain the parallel transmission light flux. Haze is calculated using the total transmitted luminous flux and the parallel transmitted luminous flux, as shown in the following formula: in, Indicates fog level. This represents the total transmitted luminous flux. This represents the parallel transmission luminous flux. Indicates the standard deviation of thickness. This indicates the preset thickness-haze sensitivity coefficient; Transmittance of polypropylene matrices is measured within a preset visible light range at a preset scanning step size to obtain a transmittance value set. A spectral transmission curve is then constructed based on the visible light range and the transmittance value set. Light transmittance is obtained using spectral transmission curves; The transparency of the polypropylene matrix was measured to obtain the transparency. The test report is obtained by summarizing the haze, light transmittance, and transparency.

[0011] Optionally, the transparency test of the polypropylene matrix to obtain transparency includes: Images of polypropylene adult bodies are acquired using a preset acquisition time interval to obtain a polypropylene adult body image set, which includes multiple polypropylene adult body images. For each of the multiple polypropylene adult images, perform the following operation: The polypropylene solid image was converted to grayscale to obtain a grayscale image. A Gaussian filter is applied to the grayscale image to obtain the filtered image; Edge detection is performed on the filtered image to obtain the horizontal and vertical gradients; The gradient magnitude of each pixel in the filtered image is obtained by using the horizontal and vertical gradients, resulting in multiple gradient magnitudes. Gradient energy is obtained by using multiple gradient magnitudes, and reference transparency is obtained by using gradient energy. The reference transparencys are summarized to obtain multiple reference transparencys, and the transparency is obtained by using multiple reference transparencys.

[0012] Optionally, obtaining a comprehensive performance score set using multiple test reports includes: Multiple haze, transmittance, and transparency values ​​were obtained using multiple test reports; Multiple haze values, multiple transmittance values, and multiple transparency values ​​are normalized to obtain multiple normalized haze values, multiple normalized transmittance values, and multiple normalized transparency values. Perform the following operations on each of the multiple sets of mixed raw materials: The overall performance score is calculated using the normalized haze corresponding to multiple normalized haze values, the normalized transmittance corresponding to multiple normalized transmittance values, and the normalized transparency corresponding to multiple normalized transparency values ​​of the mixed raw materials. The calculation formula is shown below: in, This indicates the overall performance score. This represents the preset haze weighting coefficient. Indicates normalized haze. This represents the preset transmittance weighting coefficient. Represents normalized transmittance. This represents the preset transparency weighting coefficient. Indicates normalized transparency. This represents the preset temperature influence factor. Indicates the melting temperature. This represents the preset optimal processing temperature reference value. This indicates the preset allowable temperature fluctuation range; The overall performance scores are summarized to obtain an overall performance score set.

[0013] Optionally, the step of morphological filtering of multiple polypropylene samples to obtain a defect-free pellet set includes: Multiple polypropylene samples were initially separated using a pre-constructed gas splitter to obtain multiple sieved granules. For each of the plurality of screened granules, the following operation is performed: Acquire multiple images of the screened granules; A three-dimensional point cloud model was constructed using multiple images of granular material. The 3D point cloud model is registered with the pre-confirmed standard cylindrical model by the nearest point to obtain the aligned point cloud model. The contour deviation value is calculated using the aligned point cloud model and the standard cylinder model; The contour deviation value is compared with the preset contour deviation threshold, and the screened granules with a contour deviation value less than the contour deviation threshold are regarded as defect-free granules. By summarizing the defect-free granules, a defect-free granule set is obtained.

[0014] To achieve the above objectives, the present invention also provides a system for preparing transparent flame-retardant light-diffusing polypropylene materials, comprising: The raw material blending module is used to obtain the material production specifications and obtain the optimal blending ratio based on the material production specifications. The pre-confirmed set of production raw materials is pre-treated to obtain pre-treated polypropylene powder and pre-treatment additives. Pretreated polypropylene powder and pretreated additives are mixed in the optimal mixing ratio to obtain mixed raw materials. The mixed raw materials are then grouped according to multiple preset melting temperatures to obtain multiple groups of mixed raw materials. The production condition confirmation module is used to perform the following operations on each of the multiple sets of mixed raw materials: The mixed raw materials are melt-extruded using the melting temperature corresponding to the mixed raw materials to obtain polypropylene melt; The polypropylene melt is cooled and shaped to obtain the polypropylene body; The performance of the polypropylene molecule was tested, and a test report was obtained. By summarizing the test reports, multiple test reports are obtained; A comprehensive performance score set is obtained by using multiple test reports. The comprehensive performance score set includes multiple comprehensive performance scores, and each comprehensive performance score corresponds one-to-one with the mixed raw materials. The optimal melting temperature is determined based on multiple comprehensive performance scores. The pellet product production module is used to prepare polypropylene pellets on a large scale using the optimal mixing ratio and optimal melting temperature. Polypropylene granules are pelletized to obtain a polypropylene sample set, which includes multiple polypropylene samples. The finished product quality inspection module is used to perform morphology filtering on multiple polypropylene samples to obtain a defect-free granule set. The defect-free granule set includes multiple defect-free granules, and the multiple defect-free granules are subjected to hot pressing to obtain polypropylene sheets.

[0015] To address the above problems, the present invention also provides an electronic device, the electronic device comprising: Memory, storing at least one instruction; and The processor executes the instructions stored in the memory to implement the above-described method for preparing transparent flame-retardant light-diffusing polypropylene material.

[0016] To address the aforementioned problems, the present invention also provides a computer-readable storage medium storing at least one instruction, which is executed by a processor in an electronic device to implement the above-described method for preparing a transparent flame-retardant light-diffusing polypropylene material.

[0017] To address the problems described in the background art, this invention obtains material production specifications, determines the optimal blending ratio based on these specifications, preprocesses a pre-confirmed set of production raw materials to obtain pre-treated polypropylene powder and pre-treatment additives, blends the pre-treated polypropylene powder and pre-treatment additives according to the optimal blending ratio, and groups the blended raw materials according to multiple preset melting temperatures to obtain multiple sets of mixed raw materials. It is evident that this invention, through parallelized multi-set melting temperature experimental design and a data-driven optimization and screening mechanism, effectively overcomes the high energy consumption and low efficiency of traditional serial trial-and-error methods, achieving rapid and accurate optimization of process parameters. Furthermore, this invention performs the following steps on each set of mixed raw materials in the multiple sets of mixed raw materials: The process involves melting and extruding the mixed raw materials at the melt temperature corresponding to the raw materials to obtain a polypropylene melt. The polypropylene melt is then cooled and shaped to obtain a polypropylene pellet. Performance tests are performed on the polypropylene pellet to obtain test reports. These test reports are then compiled to obtain multiple test reports. A comprehensive performance score set is obtained from these multiple test reports. This comprehensive performance score set includes multiple comprehensive performance scores, each corresponding one-to-one with the mixed raw materials. Based on these multiple comprehensive performance scores, the optimal melting temperature is obtained. It is evident that this embodiment of the invention, through parallel experiments and a quantitative scoring mechanism, accurately selects the optimal melting temperature, effectively solving the key problem that traditional single process parameters cannot simultaneously achieve a balance of multiple properties, significantly improving the overall material performance and preparation efficiency. Next, this invention utilizes the optimal mixing ratio and optimal melting temperature for large-scale preparation to obtain polypropylene pellet pellets. These pellet pellets are then granulated to obtain a polypropylene sample set, which includes multiple polypropylene samples. It is evident that this embodiment of the invention, by directly applying the optimized process parameters to large-scale preparation, ensures the efficient and stable transformation of laboratory optimization results into industrial production, fundamentally solving the industry-wide problem of inconsistencies between laboratory formulations and large-scale production performance. Furthermore, this invention obtains a defect-free particle set by morphology filtering of multiple polypropylene samples. This defect-free particle set includes multiple defect-free particles, which are then hot-pressed to obtain polypropylene sheets. It is evident that this invention, by introducing morphology filtering and defect-free particle screening steps, effectively eliminates performance errors in hot-pressed sheets caused by particle geometric defects, ensuring the accuracy and reliability of subsequent test data and guaranteeing the acquisition of high-performance, consistent final products. Therefore, this invention solves the problem of transparent, flame-retardant, and light-diffusing polypropylene materials struggling to simultaneously achieve high transparency, high flame retardancy, and uniform light diffusion performance. Attached Figure Description

[0018] Figure 1 This is a schematic flowchart of a method for preparing a transparent flame-retardant light-diffusing polypropylene material according to an embodiment of the present invention; Figure 2 This is a functional block diagram of a system for preparing transparent flame-retardant light-diffusing polypropylene material according to an embodiment of the present invention; Figure 3 This is a schematic diagram of an electronic device for implementing the method for preparing transparent flame-retardant light-diffusing polypropylene material according to an embodiment of the present invention.

[0019] Explanation of reference numerals in the attached figures: 10. Electronic device; 11. Processor; 12. Memory; 13. Bus.

[0020] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0021] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0022] This application provides a method for preparing a transparent, flame-retardant, light-diffusing polypropylene material. The execution entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the method for preparing the transparent, flame-retardant, light-diffusing polypropylene material can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0023] Reference Figure 1 The diagram shown is a schematic flow chart of a method for preparing a transparent flame-retardant light-diffusing polypropylene material according to an embodiment of the present invention. In this embodiment, the method for preparing the transparent flame-retardant light-diffusing polypropylene material includes: S1. Obtain the material production specifications and obtain the optimal blending ratio based on the material production specifications.

[0024] It should be explained that obtaining the optimal blending ratio based on material production specifications includes: A material ratio set is obtained based on the material production specifications, wherein the material ratio set includes multiple material ratios; Obtain historical production data for each of the multiple material proportions to obtain multiple historical production data sets; Perform the following operation on each of the multiple historical production data sets: Obtain energy consumption per unit output, production cycle, and product qualification rate from historical production data; Normalize the energy consumption per unit output, production cycle and product qualification rate respectively to obtain normalized energy consumption per unit output, normalized production cycle and normalized product qualification rate. Efficiency values ​​are calculated using normalized unit output energy consumption, normalized production cycle, and normalized product qualification rate. By summing the efficiency values, multiple efficiency values ​​are obtained; The maximum efficiency value is obtained based on multiple efficiency values, and the material ratio corresponding to the maximum efficiency value is taken as the optimal mixing ratio.

[0025] Furthermore, obtaining material production specifications refers to the key information that production managers obtain for this production based on order requirements, such as production quantity, usage needs, and product specifications. A material proportion set is a collection containing multiple material proportions. A material proportion is a feasible ratio of each component raw material to meet the material production specifications. For example, polypropylene powder. Light diffusing agent Transparent flame retardant = 89% 9% 2%. Historical production data refers to data such as unit output energy consumption, production cycle, and product qualification rate recorded in past production using the corresponding material ratio. Unit output energy consumption is the amount of energy (electricity) consumed to produce each unit of qualified product (e.g., per ton). Production cycle is the total time required to produce each unit of qualified product from the start of material input to the output of the finished product. Product qualification rate is the percentage of qualified product weight out of the total weight of materials input in the production of each unit of qualified product. Normalization is the process of transforming data with different dimensions to dimensionless values ​​within the [0-1] interval. Optionally, Min-Max normalization is used as the normalization method. Normalized unit output energy consumption is the dimensionless value obtained after normalizing unit output energy consumption. Normalized production cycle is the dimensionless value obtained after normalizing production cycle. Normalized product qualification rate is the dimensionless value obtained after normalizing product qualification rate. Efficiency value is a quantitative indicator that comprehensively characterizes production efficiency, where a larger efficiency value indicates higher production efficiency corresponding to the material ratio. The formula for calculating the efficiency value is as follows: in, Indicates the efficiency value. This represents the preset energy consumption coefficient. This represents the preset production cycle coefficient. This represents the preset pass rate coefficient. This represents the energy consumption per unit of output under normalized conditions. Indicates the normalized production cycle. This represents the normalized product qualification rate. The energy consumption coefficient, production cycle coefficient, and qualification rate coefficient can be obtained from historical production data. Optionally, the analytic hierarchy process (AHP) can be used to obtain the energy consumption coefficient, production cycle coefficient, and qualification rate coefficient.

[0026] Understandably, the maximum efficiency value is the highest value within the set of efficiency values. The optimal blending ratio is the proportion of material used in actual production that corresponds to the maximum efficiency value. For example, polypropylene powder. Light diffusing agent Transparent flame retardant = 89% 9% 2%.

[0027] S2. Pre-treat the pre-confirmed raw material set to obtain pre-treated polypropylene powder and pre-treatment additives.

[0028] It should be explained that the pretreatment of the pre-confirmed set of production raw materials to obtain pretreated polypropylene powder and pretreatment additives includes: Polypropylene powder and production aids are extracted from raw materials. Polypropylene powder is subjected to segmented gradient drying to obtain pre-dried powder. The moisture content of the pre-dried powder was tested to obtain the moisture content value; If the moisture content is greater than or equal to the preset moisture content threshold, the pre-dried powder is used as polypropylene powder, and the process returns to the step of performing segmented gradient drying on the polypropylene powder until the moisture content is less than the moisture content threshold, and the pre-dried powder is used as pretreated polypropylene powder. The production aids are surface activated to obtain pretreated aids.

[0029] Furthermore, the production raw material set is a collection of various production raw materials (polypropylene powder, light diffusing agent, and transparent flame retardant). Polypropylene powder is a thermoplastic polymer powder. Production auxiliaries are auxiliary substances used to improve the properties of polypropylene materials, such as light diffusing agents and transparent flame retardants. Segmented gradient drying refers to a process of drying the polypropylene powder in stages at different temperatures to gradually reduce its moisture content and prevent the degradation of heat-sensitive components due to sudden temperature increases. Optionally, multi-stage drying can be used as the segmented gradient drying method. The pre-dried powder is the polypropylene powder after segmented gradient drying. Moisture content detection is a method for detecting the moisture content in the pre-dried powder. Optionally, near-infrared spectroscopy can be used as the moisture content detection method. The moisture content value is the amount of moisture in the pre-dried powder obtained through moisture content detection. Moisture content refers to the ratio of the weight of water to the weight of the pre-dried powder. The moisture content threshold is a preset maximum allowable moisture content value used to determine whether the pre-dried powder is qualified. For example, 0.05%. The pretreated polypropylene powder is a partially dried powder with a moisture content below a certain threshold after staged gradient drying. Surface activation is an operation that introduces active groups onto the surface of the light diffusing agent and transparent flame retardant particles to improve their compatibility with the polypropylene powder. The aim is to reduce the agglomeration of production additives, improve dispersion uniformity and flame retardant efficiency, and ensure stable haze. Optionally, plasma treatment can be used as the surface activation method. The pretreated additive is a mixture of surface-activated light diffusing agent and transparent flame retardant.

[0030] S3. The pretreated polypropylene powder and pretreatment additives are mixed according to the optimal mixing ratio to obtain the mixed raw materials. The mixed raw materials are grouped according to multiple preset melting temperatures to obtain multiple groups of mixed raw materials.

[0031] It should be explained that the process of mixing pretreated polypropylene powder and pretreatment additives according to the optimal mixing ratio to obtain the compounded raw materials includes: Pretreated polypropylene powder was subjected to segmented preheating treatment using a pre-confirmed high-speed mixer to obtain preheated polypropylene powder. Preheated polypropylene powder and pretreatment additives are mixed according to the optimal mixing ratio to obtain proportioned polypropylene powder and proportioned additives. Transparent flame retardants and light diffusing agents were extracted from the formulation additives; The polypropylene powder and transparent flame retardant were initially mixed to obtain the initial mixed raw material; The initial raw materials and light diffusing agent are subjected to high-speed activation and mixing to obtain a uniform premix; The uniform premix is ​​stirred at low temperature to obtain the compounded raw materials.

[0032] Furthermore, the high-speed mixer is equipped with segmented temperature control for rapid and uniform dispersion while avoiding localized overheating. Segmented preheating involves dividing the preheating process into two or more stages, heating the polypropylene powder at different temperatures or speeds to gradually and uniformly raise its temperature to the target preheating temperature. This is to prevent localized overheating that could lead to polypropylene powder denaturation. The target preheating temperature is 90°C. Preheated polypropylene powder is polypropylene powder that has undergone segmented preheating treatment. Proportioning is the process of weighing the pretreated polypropylene powder and pretreatment additives according to the optimal mixing ratio. Proportioned polypropylene powder is a predetermined amount of preheated polypropylene powder weighed according to the optimal mixing ratio. Proportioned additives are a collection of predetermined amounts of transparent flame retardant and light diffusing agent weighed according to the optimal mixing ratio.

[0033] For example, the optimal blending ratio is polypropylene powder. Light diffusing agent Transparent flame retardant = 89% 9% The production plan is for 100 kg of compounded raw materials, which is 2%. Therefore, 89 kg of preheated polypropylene powder, 9 kg of light diffusing agent, and 2 kg of transparent flame retardant need to be weighed. This will ultimately yield 89 kg of compounded polypropylene powder and a certain amount of compounding additives, including 9 kg of light diffusing agent and 2 kg of transparent flame retardant. The transparent flame retardant is a functional additive added to polypropylene materials to inhibit, delay, or prevent combustion while maintaining the material's optical transparency. In this scheme, the total addition amount of transparent flame retardant is 2%, and its compound composition is: organic aluminum hypophosphite: 1%, melamine hydrobromic acid: 0.5%, and methyl methacrylate: 0.5%.

[0034] Understandably, the initial mixing involves mixing the proportioned polypropylene powder and the transparent flame retardant in a high-speed mixer at 600 rpm and 90 rpm. The 5-minute mixing process aims to ensure the transparent flame retardant adheres evenly to the surface of the polypropylene powder, forming a primary uniform distribution and reducing the risk of subsequent delamination. The initial mixture is the mixture of polypropylene powder and the transparent flame retardant after preliminary mixing. High-speed activation mixing involves mixing the initial mixture with the light diffusing agent in a high-speed mixer at 1200 rpm and 90°C. The mixing process takes 3 minutes. The purpose is to ensure the light-diffusing agent is fully dispersed while maintaining frictional heat at 90°C. This promotes the reaction of surface-active groups on polypropylene, further improving the bonding strength. The homogeneous premix is ​​a mixture of the initial raw materials and the light-diffusing agent after high-speed activation mixing. Low-temperature stirring involves cooling the homogeneous premix to 40°C in a high-speed mixer. The mixture is stirred at a low speed of 200 rpm for 2 minutes. The purpose is to eliminate static electricity, lower the temperature, and prevent the homogeneous premix from clumping due to residual heat. The raw materials for compounding are homogeneous premixes that have been stirred at low temperature.

[0035] Furthermore, melt temperature refers to the high-temperature, high-shear melting temperature value set for the extrusion of compounded raw materials, which allows the material to completely melt without excessive degradation. For example, this scheme presets three sets of melt temperatures: 180... 200 and 220 The raw materials are grouped according to a preset melting temperature to obtain multiple sets of mixed raw materials. This means dividing the raw materials into three equal parts, each marked and corresponding to a melting temperature (180°C). 200 220 Three sets of mixed raw materials were formed. The purpose was to compare the effects of different melting temperatures on the optical properties of the polypropylene matrix in subsequent performance tests, in order to determine the optimal melting temperature.

[0036] S4. The mixed raw materials are melt-extruded using the melting temperature corresponding to the mixed raw materials to obtain polypropylene melt.

[0037] It should be explained that the process of using the melting temperature corresponding to the mixed raw materials to perform melt extrusion of the mixed raw materials to obtain polypropylene melt includes: The mixed raw materials are heated in stages and sections to obtain a preliminary molten material; High-temperature, high-shear melting of pre-molten material is performed using the melting temperature to obtain a flowing melt; Vacuum devolatilization is performed on the flowing melt to obtain a low-volatility melt; Low-volatility melts are homogenized at low temperatures to obtain homogenized melts; The homogenized melt is subjected to graded filtration to obtain a high-purity melt. The high-purity melt is then subjected to impurity detection to obtain an impurity detection report. The qualified high-purity melt was confirmed using the impurity test report and was then used as the polypropylene melt.

[0038] Furthermore, zoned and stepped heating refers to setting a 120°C temperature at the front section of the extruder barrel. -150 -180 The process involves heating the mixed raw materials using a three-stage temperature gradient, gradually softening them from room temperature. This aims to prevent the decomposition of the transparent flame retardant or the degradation of polypropylene due to sudden high temperatures, and to reduce the formation of unmelted lumps. An extruder relies on the pressure and shear force generated by the rotating screw to fully plasticize and uniformly mix the material, forming it through a die. The extruder includes a front section of the barrel, a middle vacuum section, and a homogenization section. The function of each stage can be found in subsequent embodiments. The initially melted material is a paste-like mixture that has softened and partially melted but still contains a small amount of solid particles after being heated in stages. High-temperature, high-shear melting utilizes the middle section of the extruder to increase the screw speed to 400 rpm and raise the temperature to the melting point, resulting in a fully melted, highly fluid melt. The flowing melt is the product of high-temperature, high-shear melting with a uniform temperature distribution around 180°C. -220 The melt. Vacuum devolatilization is the process of removing moisture and volatiles such as low-molecular-weight siloxanes from a flowing melt. For example, applying a vacuum in the vacuum section of an extruder... A vacuum of 0.08 MPa and a residence time of 30-60 seconds reduce the volatile content to below 300 ppm, avoiding extrusion bubbles and surface defects in the product. Low-volatility melts are fluid melts with significantly reduced volatile content, reduced odor, and improved mechanical properties and thermal stability after vacuum devolatilization.

[0039] Understandably, low-temperature homogenization involves reducing the temperature to 150°C in the homogenization section of the extruder. -160 The screw speed is reduced to 150 rpm to make the internal temperature of the melt more consistent with the composition, eliminate local overheating, reduce internal stress, and improve the stability of subsequent molding. Homogenized melt is a low-volatility melt after low-temperature homogenization treatment. Staged filtration uses a three-stage melt filter (60-80-120 mesh) arranged in series to remove undispersed agglomerated particles, metallic impurities, and carbonized black spots step by step. The purpose is to ensure melt purity, so that the homogenized melt can obtain a higher overall performance score in subsequent performance testing. High-purity melt is the melt after staged filtration. Impurity detection is a method to determine the number, size, and distribution of solid particles in the melt to assess melt purity. Optionally, a particle counting system can be used as the instrument for impurity detection. The impurity detection report is a report recording the number of particles in the high-purity melt based on the impurity detection results. For example: 15 particles / 25g.

[0040] Furthermore, confirming the qualified high-purity melt using the impurity test report means that if the impurity test report indicators are qualified (particle count ≤ 20 / 25g), then the high-purity melt corresponding to that impurity test report is considered a qualified high-purity melt; if the impurity test report indicators are unqualified (particle count > 20 / 25g), then the high-purity melt corresponding to that impurity test report is directly used as the initial molten material, and the process returns to the step of high-temperature, high-shear melting of the initial molten material using the melting temperature, until the impurity test report indicators are qualified, at which point the high-purity melt corresponding to that impurity test report is considered a qualified high-purity melt. A qualified high-purity melt is one with a particle count ≤ 20 / 25g verified by the impurity test report.

[0041] S5. Cool and solidify the polypropylene melt to obtain a polypropylene matrix. Perform performance tests on the polypropylene matrix to obtain test reports. Summarize the test reports to obtain multiple test reports.

[0042] It should be explained that the performance testing of the polypropylene molecule, and the resulting test report, includes: The thickness of the polypropylene matrix is ​​measured using a preset length interval to obtain a set of thickness values, which includes multiple thickness values. Obtain the thickness standard deviation using multiple thickness values; The total transmitted light flux was measured on the polypropylene matrix to obtain the total transmitted light flux. Parallel transmission light flux was measured on the polypropylene matrix to obtain the parallel transmission light flux. Haze is calculated using the total transmitted luminous flux and the parallel transmitted luminous flux, as shown in the following formula: in, Indicates fog level. This represents the total transmitted luminous flux. This represents the parallel transmission luminous flux. Indicates the standard deviation of thickness. This indicates the preset thickness-haze sensitivity coefficient; Transmittance of polypropylene matrices is measured within a preset visible light range at a preset scanning step size to obtain a transmittance value set. A spectral transmission curve is then constructed based on the visible light range and the transmittance value set. Light transmittance is obtained using spectral transmission curves; The transparency of the polypropylene matrix was measured to obtain the transparency. The test report is obtained by summarizing the haze, light transmittance, and transparency.

[0043] Furthermore, cooling and shaping involves the polypropylene melt undergoing a 20-minute cooling process. The circulating water-cooled molding mold is rapidly cooled to 40°C. The following describes the process of curing and maintaining the designed cross-sectional shape (e.g., a 2mm thick sheet) of the polypropylene assembly. The purpose is to eliminate internal stress in the polypropylene assembly and prevent warping. The polypropylene assembly is a sheet obtained after cooling and shaping. A length interval is the interval at which the thickness of the polypropylene assembly is measured along its length. For example, 100mm. Thickness measurement is the process of measuring the thickness of the polypropylene assembly at each length interval. Optionally, a thickness gauge is used as the instrument for thickness measurement. A thickness value set is a collection of multiple thickness values. A thickness value is the thickness of the polypropylene assembly at the starting point of a length interval. The thickness standard deviation is the standard deviation of the multiple thickness values ​​in the thickness value set. Total transmitted light flux (TLP) testing is a method for characterizing the overall light transmittance of a material by measuring the total transmitted light energy passing through the polypropylene assembly. Optionally, a large integrating sphere spectrophotometer is used as the method for TLP testing. Total transmitted light flux is the percentage of total light energy remaining after the light passes through the polypropylene assembly, as obtained from the TLP testing. For example, 92%. Parallel transmission light flux measurement is a method for measuring the energy of transmitted light parallel to the incident direction, used to quantify the direct light transmittance of polypropylene matrices. Optionally, parallel transmission light flux measurement is used as the method for measuring parallel transmission light flux. Parallel transmission light flux, obtained through parallel transmission light flux measurement, is the percentage of transmitted light energy used to characterize the direct light transmittance of polypropylene matrices. For example, 88%. Haze is a calculated comprehensive scattering index reflecting the degree of haze caused by internal and surface scattering of the material. The thickness-haze sensitivity coefficient is an experimentally calibrated correction factor used to eliminate errors caused by thickness inhomogeneity. For example, k=0.15. .

[0044] Understandably, the visible light range refers to the wavelength interval of 380nm-780nm. During transmittance detection, a sampling interval of 5nm is used to collect transmittance values ​​within the visible light range. Transmittance detection is the process of scanning the polypropylene assembly wavelength by wavelength and recording the transmittance. Optionally, a spectrophotometer is used as the instrument for transmittance detection. The transmittance value set is a collection of multiple transmittance values. The transmittance value is the transmittance value corresponding to each visible light wavelength obtained through transmittance detection. The spectral transmittance curve is a continuous curve plotted with visible light wavelength as the horizontal axis and transmittance as the vertical axis. Transmittance is a percentage of overall transmittance obtained by taking the arithmetic mean of multiple transmittance values, for example, 89.6%. Transparency testing is the process of obtaining the transparency of the polypropylene assembly. Specific operating methods can be found in subsequent embodiments. Transparency is a numerical value obtained through transparency detection used to represent the transparency level of the polypropylene assembly. The test report includes the haze, transmittance, and transparency of the polypropylene assembly.

[0045] It should be explained that the transparency test of the polypropylene matrix to obtain transparency includes: Images of polypropylene adult bodies are acquired using a preset acquisition time interval to obtain a polypropylene adult body image set, which includes multiple polypropylene adult body images. For each of the multiple polypropylene adult images, perform the following operation: The polypropylene solid image was converted to grayscale to obtain a grayscale image. A Gaussian filter is applied to the grayscale image to obtain the filtered image; Edge detection is performed on the filtered image to obtain the horizontal and vertical gradients; The gradient magnitude of each pixel in the filtered image is obtained by using the horizontal and vertical gradients, resulting in multiple gradient magnitudes. Gradient energy is obtained by using multiple gradient magnitudes, and reference transparency is obtained by using gradient energy. The reference transparencys are summarized to obtain multiple reference transparencys, and the transparency is obtained by using multiple reference transparencys.

[0046] Furthermore, grayscale conversion is a method of converting a color image into a single-channel grayscale image. A grayscale image is a polypropylene solid image with pixel values ​​ranging from 0 to 255 after grayscale conversion. Gaussian filtering is a method for image noise reduction. Gaussian filtering is existing technology and will not be elaborated upon here. The filtered image is the grayscale image after Gaussian filtering. Edge detection is a method that uses the Sobel operator to calculate pixel gradients in both the horizontal and vertical directions to identify regions of abrupt brightness changes. Edge detection is existing technology and will not be elaborated upon here. The horizontal gradient is the numerical value of the rate of brightness change of each pixel in the horizontal direction. The vertical gradient is the numerical value of the rate of brightness change of each pixel in the vertical direction.

[0047] Obtaining the gradient magnitude of each pixel in the filtered image using horizontal and vertical gradients, resulting in multiple gradient magnitudes, refers to calculating the gradient magnitude using the horizontal and vertical gradients corresponding to each pixel and a pre-constructed gradient magnitude calculation formula. The gradient magnitude calculation formula is as follows: Where D represents the gradient magnitude. Represents the horizontal gradient. This represents the vertical gradient.

[0048] Understandably, gradient magnitude is a numerical value representing the edge strength of a single pixel, obtained through the gradient magnitude calculation formula. Gradient energy is an energy value used to quantify the overall sharpness of the image, obtained by averaging the squared gradient magnitudes of all pixels in the filtered image; the higher the energy value, the sharper the image. Transparency is a dimensionless value obtained by substituting the gradient energy into a pre-constructed calibration function, as shown below: in, For reference transparency, This is the experimental calibration coefficient, for example, 0.02. Let be the gradient energy, where The larger the value, the fewer internal and surface defects the polypropylene matrix has, and the higher the visual clarity.

[0049] Furthermore, obtaining transparency by using multiple reference transparencys refers to averaging multiple reference transparencys to obtain an average value, which is then used as the transparency.

[0050] S6. Obtain a comprehensive performance score set using multiple test reports. The comprehensive performance score set includes multiple comprehensive performance scores, and each comprehensive performance score corresponds one-to-one with the mixed raw materials. Obtain the optimal melting temperature based on the multiple comprehensive performance scores.

[0051] It should be explained that the process of obtaining a comprehensive performance score set using multiple test reports includes: Multiple haze, transmittance, and transparency values ​​were obtained using multiple test reports; Multiple haze values, multiple transmittance values, and multiple transparency values ​​are normalized to obtain multiple normalized haze values, multiple normalized transmittance values, and multiple normalized transparency values. Perform the following operations on each of the multiple sets of mixed raw materials: The overall performance score is calculated using the normalized haze corresponding to multiple normalized haze values, the normalized transmittance corresponding to multiple normalized transmittance values, and the normalized transparency corresponding to multiple normalized transparency values ​​of the mixed raw materials. The calculation formula is shown below: in, This indicates the overall performance score. This represents the preset haze weighting coefficient. Indicates normalized haze. This represents the preset transmittance weighting coefficient. Represents normalized transmittance. This represents the preset transparency weighting coefficient. Indicates normalized transparency. This represents the preset temperature influence factor. Indicates the melting temperature. This represents the preset optimal processing temperature reference value. This indicates the preset allowable temperature fluctuation range; The overall performance scores are summarized to obtain an overall performance score set.

[0052] Furthermore, normalization is a method that maps raw test values ​​(haze, transmittance, transparency) to a 0-1 range to eliminate dimensional differences and make subsequent weighted calculations comparable. Optionally, Min-Max normalization is used as the normalization method. Normalized haze is the normalized haze. Normalized transmittance is the normalized transmittance. Normalized transparency is the normalized transparency. The comprehensive performance score is a dimensionless index representing the comprehensive optical performance of the polypropylene body at the melting temperature, calculated from the normalized haze, normalized transmittance, and normalized transparency corresponding to the mixed raw materials. The haze weighting coefficient is the weighting coefficient of normalized haze in the comprehensive score. For example, 0.3. The transmittance weighting coefficient is the weighting coefficient of normalized transmittance in the comprehensive score. For example, 0.4. The transparency weighting coefficient is the weighting coefficient of normalized transparency in the comprehensive score. For example, 0.3. The temperature influence factor is a penalty coefficient when the melting temperature deviates from the benchmark value. For example, 0.02. The optimal processing temperature baseline is the temperature value that corresponds to the minimum number of defects in polypropylene material during melt extrusion, obtained based on historical data. For example, 190. The permissible temperature fluctuation range is the maximum positive and negative deviation allowed by the process. For example, 20... .

[0053] Understandably, obtaining the optimal melting temperature based on multiple comprehensive performance scores means taking the melting temperature corresponding to the highest comprehensive performance score among the multiple comprehensive performance scores as the optimal melting temperature.

[0054] S7. Using the optimal mixing ratio and optimal melting temperature, polypropylene granules are prepared on a large scale to obtain polypropylene pellets. The polypropylene pellets are then granulated to obtain a polypropylene sample set, which includes multiple polypropylene samples.

[0055] It should be explained that large-scale preparation is a process of continuous and stable industrial production using optimal blending ratios and optimal melting temperatures to continuously melt-extrude pretreated raw materials, vacuum devolatilization, graded filtration, and cooling molding. Polypropylene granules are polypropylene cylindrical strips obtained after large-scale preparation. Pelletizing is the process of cutting polypropylene granules into uniform cylindrical particles using a pelletizer. A polypropylene sample set is a collection of multiple polypropylene samples. A polypropylene sample is a polypropylene particle obtained from pelletizing.

[0056] S8. Morphological filtration was performed on multiple polypropylene samples to obtain a defect-free granule set, wherein the defect-free granule set included multiple defect-free granules. The multiple defect-free granules were subjected to hot pressing to obtain polypropylene sheets.

[0057] It should be explained that the morphology filtering of multiple polypropylene samples to obtain a defect-free particle set includes: Multiple polypropylene samples were initially separated using a pre-constructed gas splitter to obtain multiple sieved granules. For each of the plurality of screened granules, the following operation is performed: Acquire multiple images of the screened granules; A three-dimensional point cloud model was constructed using multiple images of granular material. The 3D point cloud model is registered with the pre-confirmed standard cylindrical model by the nearest point to obtain the aligned point cloud model. The contour deviation value is calculated using the aligned point cloud model and the standard cylinder model; The contour deviation value is compared with the preset contour deviation threshold, and the screened granules with a contour deviation value less than the contour deviation threshold are regarded as defect-free granules. By summarizing the defect-free granules, a defect-free granule set is obtained.

[0058] Furthermore, the gas separator is a gas classification device. Optionally, an air classifier is used as the gas separator. Primary separation is the process of separating light dust, debris, and irregular particles from the polypropylene sample by adjusting the airflow speed of the gas separator and the cyclone separator. The sieved granules are polypropylene granules that have undergone primary separation and from which light dust, debris, and irregular particles have been removed. Granule images are images taken from different angles (e.g., top, bottom, and side views) using a high-speed industrial camera for subsequent defect identification. The 3D point cloud model is a model generated by 3D reconstruction of multiple granule images from different angles, used to characterize the surface 3D geometry of the sieved granules. Optionally, a motion-reconstructed structure is used as the method for constructing the 3D point cloud model. The standard cylinder model is a model generated based on the ideal cylindrical shape of the ideal granules. The standard cylinder model has a standard diameter, height, and smooth side surfaces, serving as a benchmark for comparison. Ideal granules refer to screened granules formed during the production process that fully conform to the design specifications. The specifications of ideal granules can be obtained from the material production specifications. Closest point registration is a method that aligns the 3D point cloud model and the standard cylindrical model in 3D space by iteratively calculating the minimum distance between surface points of the 3D point cloud model and the standard cylindrical model. Optionally, the ICP algorithm can be used as the closest point registration method. The aligned point cloud model is the 3D point cloud model after closest point registration. The aligned point cloud model and the standard cylindrical model have achieved optimal spatial overlap, providing a benchmark for subsequent contour deviation calculations. The contour deviation value is a numerical quantification result obtained by calculating the minimum distance from each point in the aligned point cloud model to the surface of the standard cylindrical model and calculating the root mean square error of multiple minimum distances. It is used to characterize the degree of deviation between the screened granules and the ideal granules. The contour deviation threshold is a pre-set value based on the quality standard of polypropylene granules. If the contour deviation value exceeds the contour deviation threshold, the screened granules are determined to have morphological defects, such as surface depressions or edge defects. Defect-free aggregates are sieved aggregates whose profile deviation value is less than the profile deviation threshold. A set of defect-free aggregates is a collection containing multiple defect-free aggregates.

[0059] Understandably, hot pressing is the process of hot-pressing multiple defect-free granules to obtain polypropylene sheets. Polypropylene sheets are sheets obtained by hot pressing multiple defect-free granules. A material warehouse is a storage facility for polypropylene sheets.

[0060] For example, in 200 Under 5MPa conditions, multiple defect-free granules were placed in a 180mm×180mm×2mm mirror steel mold and hot-pressed for 3 minutes, followed by water cooling to 40°C. A polypropylene sample sheet with a thickness of 2 mm was obtained.

[0061] To address the problems described in the background art, this invention obtains material production specifications, determines the optimal blending ratio based on these specifications, preprocesses a pre-confirmed set of production raw materials to obtain pre-treated polypropylene powder and pre-treatment additives, blends the pre-treated polypropylene powder and pre-treatment additives according to the optimal blending ratio, and groups the blended raw materials according to multiple preset melting temperatures to obtain multiple sets of mixed raw materials. It is evident that this invention, through parallelized multi-set melting temperature experimental design and a data-driven optimization and screening mechanism, effectively overcomes the high energy consumption and low efficiency of traditional serial trial-and-error methods, achieving rapid and accurate optimization of process parameters. Furthermore, this invention performs the following steps on each set of mixed raw materials in the multiple sets of mixed raw materials: The process involves melting and extruding the mixed raw materials at the melt temperature corresponding to the raw materials to obtain a polypropylene melt. The polypropylene melt is then cooled and shaped to obtain a polypropylene pellet. Performance tests are performed on the polypropylene pellet to obtain test reports. These test reports are then compiled to obtain multiple test reports. A comprehensive performance score set is obtained from these multiple test reports. This comprehensive performance score set includes multiple comprehensive performance scores, each corresponding one-to-one with the mixed raw materials. Based on these multiple comprehensive performance scores, the optimal melting temperature is obtained. It is evident that this embodiment of the invention, through parallel experiments and a quantitative scoring mechanism, accurately selects the optimal melting temperature, effectively solving the key problem that traditional single process parameters cannot simultaneously achieve a balance of multiple properties, significantly improving the overall material performance and preparation efficiency. Next, this invention utilizes the optimal mixing ratio and optimal melting temperature for large-scale preparation to obtain polypropylene pellet pellets. These pellet pellets are then granulated to obtain a polypropylene sample set, which includes multiple polypropylene samples. It is evident that this embodiment of the invention, by directly applying the optimized process parameters to large-scale preparation, ensures the efficient and stable transformation of laboratory optimization results into industrial production, fundamentally solving the industry-wide problem of inconsistencies between laboratory formulations and large-scale production performance. Furthermore, this invention obtains a defect-free particle set by morphology filtering of multiple polypropylene samples. This defect-free particle set includes multiple defect-free particles, which are then hot-pressed to obtain polypropylene sheets. It is evident that this invention, by introducing morphology filtering and defect-free particle screening steps, effectively eliminates performance errors in hot-pressed sheets caused by particle geometric defects, ensuring the accuracy and reliability of subsequent test data and guaranteeing the acquisition of high-performance, consistent final products. Therefore, this invention solves the problem of transparent, flame-retardant, and light-diffusing polypropylene materials struggling to simultaneously achieve high transparency, high flame retardancy, and uniform light diffusion performance.

[0062] like Figure 2 The diagram shown is a functional block diagram of a system for preparing transparent flame-retardant light-diffusing polypropylene material according to an embodiment of the present invention.

[0063] The preparation system 100 for transparent flame-retardant light-diffusing polypropylene material described in this invention can be installed in an electronic device. Depending on the functions implemented, the preparation system 100 may include a raw material mixing module 101, a production condition verification module 102, a granule finished product production module 103, and a finished product quality inspection module 104. The module described in this invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and perform a fixed function, stored in the memory of the electronic device.

[0064] The raw material blending module 101 is used to obtain the material production specifications and obtain the optimal blending ratio based on the material production specifications. The pre-confirmed set of production raw materials is pre-treated to obtain pre-treated polypropylene powder and pre-treatment additives. Pretreated polypropylene powder and pretreated additives are mixed in the optimal mixing ratio to obtain mixed raw materials. The mixed raw materials are then grouped according to multiple preset melting temperatures to obtain multiple groups of mixed raw materials. The production condition confirmation module 102 is used to perform the following operations on each of the multiple sets of mixed raw materials: The mixed raw materials are melt-extruded using the melting temperature corresponding to the mixed raw materials to obtain polypropylene melt; The polypropylene melt is cooled and shaped to obtain the polypropylene body; The performance of the polypropylene molecule was tested, and a test report was obtained. By summarizing the test reports, multiple test reports are obtained; A comprehensive performance score set is obtained by using multiple test reports. The comprehensive performance score set includes multiple comprehensive performance scores, and each comprehensive performance score corresponds one-to-one with the mixed raw materials. The optimal melting temperature is determined based on multiple comprehensive performance scores. The pellet product production module 103 is used to prepare polypropylene pellets on a large scale using the optimal mixing ratio and optimal melting temperature. Polypropylene granules are pelletized to obtain a polypropylene sample set, which includes multiple polypropylene samples. The finished product quality inspection module 104 is used to perform morphology filtering on multiple polypropylene samples to obtain a defect-free granule set, wherein the defect-free granule set includes multiple defect-free granules, and the multiple defect-free granules are subjected to hot pressing to obtain polypropylene sheets.

[0065] In detail, the modules in the preparation system 100 for realizing transparent flame-retardant light-diffusing polypropylene material described in this embodiment of the invention employ the same methods as described above during use. Figure 1The same technical means are used to prepare transparent flame-retardant light-diffusing polypropylene materials as described in the previous section, and can produce the same technical effects, so they will not be repeated here.

[0066] like Figure 3 The diagram shown is a schematic representation of an electronic device provided in an embodiment of the present invention for implementing a method for preparing transparent flame-retardant light-diffusing polypropylene material.

[0067] The electronic device 1 may include a processor 10, a memory 11 and a bus 12, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a method program for preparing transparent flame-retardant light-diffusing polypropylene material.

[0068] The memory 11 includes at least one type of readable storage medium, such as flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 1, such as the portable hard drive of the electronic device 1. In other embodiments, the memory 11 can be an external storage device of the electronic device 1, such as a plug-in portable hard drive, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the electronic device 1. Furthermore, the memory 11 includes both internal storage units and external storage devices of the electronic device 1. The memory 11 can be used not only to store application software and various types of data installed on the electronic device 1, such as code for implementing a method for preparing transparent flame-retardant light-diffusing polypropylene material, but also to temporarily store data that has been output or will be output.

[0069] In some embodiments, the processor 10 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control unit of the electronic device, connecting various components of the entire electronic device via various interfaces and lines. It executes programs or modules stored in the memory 11 (e.g., a method for preparing transparent flame-retardant light-diffusing polypropylene materials) and calls data stored in the memory 11 to perform various functions of the electronic device 1 and process data.

[0070] The bus 12 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus 12 can be divided into an address bus, a data bus, a control bus, etc. The bus 12 is configured to realize the connection and communication between the memory 11 and at least one processor 10, etc.

[0071] Figure 3 Only electronic devices with components are shown; it will be understood by those skilled in the art that... Figure 3 The structure shown does not constitute a limitation on the electronic device 1, and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0072] For example, although not shown, the electronic device 1 may also include a power supply (such as a battery) to power the various components. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management system, thereby enabling functions such as charging management, discharging management, and power consumption management through the power management system. The power supply may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device 1 may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0073] Furthermore, the electronic device 1 may also include a network interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, a Bluetooth interface, etc.), which is typically used to establish communication connections between the electronic device 1 and other electronic devices.

[0074] Optionally, the electronic device 1 may further include a user interface, which may be a display, an input unit (such as a keyboard), and optionally, a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the electronic device 1 and to display a visual user interface.

[0075] It should be understood that the embodiments described are for illustrative purposes only and are not limited to this structure in the scope of the patent application.

[0076] The program for preparing a transparent, flame-retardant, light-diffusing polypropylene material, stored in the memory 11 of the electronic device 1, is a combination of multiple instructions. When run in the processor 10, it can achieve the following: Obtain material production specifications and determine the optimal blending ratio based on those specifications. The pre-confirmed set of production raw materials is pre-treated to obtain pre-treated polypropylene powder and pre-treatment additives. Pretreated polypropylene powder and pretreated additives are mixed in the optimal mixing ratio to obtain mixed raw materials. The mixed raw materials are then grouped according to multiple preset melting temperatures to obtain multiple groups of mixed raw materials. For each of the multiple batches of mixed raw materials, perform the following operations: The mixed raw materials are melt-extruded using the melting temperature corresponding to the mixed raw materials to obtain polypropylene melt; The polypropylene melt is cooled and shaped to obtain the polypropylene body; The performance of the polypropylene molecule was tested, and a test report was obtained. By summarizing the test reports, multiple test reports are obtained; A comprehensive performance score set is obtained by using multiple test reports. The comprehensive performance score set includes multiple comprehensive performance scores, and each comprehensive performance score corresponds one-to-one with the mixed raw materials. The optimal melting temperature is determined based on multiple comprehensive performance scores. Polypropylene granules were prepared on a large scale using the optimal mixing ratio and optimal melting temperature. Polypropylene granules are pelletized to obtain a polypropylene sample set, which includes multiple polypropylene samples. Multiple polypropylene samples were subjected to morphology filtration to obtain a defect-free granule set, which included multiple defect-free granules. All defect-free granules were subjected to hot pressing to obtain polypropylene sheets.

[0077] Specifically, the processor 10's implementation method for the above instructions can be found in [reference needed]. Figures 1 to 3 The descriptions of the relevant steps in the corresponding embodiments are not repeated here.

[0078] Furthermore, if the modules / units integrated in the electronic device 1 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium may include: any entity or system capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0079] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor of an electronic device, can perform the following: Obtain material production specifications and determine the optimal blending ratio based on those specifications. The pre-confirmed set of production raw materials is pre-treated to obtain pre-treated polypropylene powder and pre-treatment additives. Pretreated polypropylene powder and pretreated additives are mixed in the optimal mixing ratio to obtain mixed raw materials. The mixed raw materials are then grouped according to multiple preset melting temperatures to obtain multiple groups of mixed raw materials. For each of the multiple batches of mixed raw materials, perform the following operations: The mixed raw materials are melt-extruded using the melting temperature corresponding to the mixed raw materials to obtain polypropylene melt; The polypropylene melt is cooled and shaped to obtain the polypropylene body; The performance of the polypropylene molecule was tested, and a test report was obtained. By summarizing the test reports, multiple test reports are obtained; A comprehensive performance score set is obtained by using multiple test reports. The comprehensive performance score set includes multiple comprehensive performance scores, and each comprehensive performance score corresponds one-to-one with the mixed raw materials. The optimal melting temperature is determined based on multiple comprehensive performance scores. Polypropylene granules were prepared on a large scale using the optimal mixing ratio and optimal melting temperature. Polypropylene granules are pelletized to obtain a polypropylene sample set, which includes multiple polypropylene samples. Multiple polypropylene samples were subjected to morphology filtration to obtain a defect-free granule set, which included multiple defect-free granules. All defect-free granules were subjected to hot pressing to obtain polypropylene sheets.

[0080] In the embodiments provided by this invention, it should be understood that the disclosed devices, systems, and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative, and actual implementations may have other classification methods.

[0081] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0082] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0083] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0084] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or systems stated in a system claim may also be implemented by a single unit or system through software or hardware. The term "second class" is used to indicate names and does not indicate any specific order.

[0085] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for preparing transparent, flame-retardant, light-diffusing polypropylene material, characterized in that, The method includes: Obtain material production specifications and determine the optimal blending ratio based on those specifications. The pre-confirmed set of production raw materials is pre-treated to obtain pre-treated polypropylene powder and pre-treatment additives. Pretreated polypropylene powder and pretreated additives are mixed in the optimal mixing ratio to obtain mixed raw materials. The mixed raw materials are then grouped according to multiple preset melting temperatures to obtain multiple groups of mixed raw materials. For each of the multiple batches of mixed raw materials, perform the following operations: The mixed raw materials are melt-extruded using the melting temperature corresponding to the mixed raw materials to obtain polypropylene melt; The polypropylene melt is cooled and shaped to obtain the polypropylene body; The performance of the polypropylene molecule was tested, and a test report was obtained. By summarizing the test reports, multiple test reports are obtained; A comprehensive performance score set is obtained by using multiple test reports. The comprehensive performance score set includes multiple comprehensive performance scores, and each comprehensive performance score corresponds one-to-one with the mixed raw materials. The optimal melting temperature is determined based on multiple comprehensive performance scores. Polypropylene granules were prepared on a large scale using the optimal mixing ratio and optimal melting temperature. Polypropylene granules are pelletized to obtain a polypropylene sample set, which includes multiple polypropylene samples. Multiple polypropylene samples were subjected to morphology filtration to obtain a defect-free granule set, which included multiple defect-free granules. All defect-free granules were subjected to hot pressing to obtain polypropylene sheets.

2. The method for preparing transparent flame-retardant light-diffusing polypropylene material as described in claim 1, characterized in that, The process of obtaining the optimal blending ratio based on material production specifications includes: A material ratio set is obtained based on the material production specifications, wherein the material ratio set includes multiple material ratios; Obtain historical production data for each of the multiple material proportions to obtain multiple historical production data sets; Perform the following operation on each of the multiple historical production data sets: Obtain energy consumption per unit output, production cycle, and product qualification rate from historical production data; Normalize the energy consumption per unit output, production cycle and product qualification rate respectively to obtain normalized energy consumption per unit output, normalized production cycle and normalized product qualification rate. Efficiency values ​​are calculated using normalized unit output energy consumption, normalized production cycle, and normalized product qualification rate. By summing the efficiency values, multiple efficiency values ​​are obtained; The maximum efficiency value is obtained based on multiple efficiency values, and the material ratio corresponding to the maximum efficiency value is taken as the optimal mixing ratio.

3. The method for preparing transparent flame-retardant light-diffusing polypropylene material as described in claim 2, characterized in that, The pretreatment of the pre-confirmed set of production raw materials to obtain pretreated polypropylene powder and pretreatment additives includes: Polypropylene powder and production aids are extracted from raw materials. Polypropylene powder is subjected to segmented gradient drying to obtain pre-dried powder. The moisture content of the pre-dried powder was tested to obtain the moisture content value; If the moisture content is greater than or equal to the preset moisture content threshold, the pre-dried powder is used as polypropylene powder, and the process returns to the step of performing segmented gradient drying on the polypropylene powder until the moisture content is less than the moisture content threshold, and the pre-dried powder is used as pretreated polypropylene powder. The production aids are surface activated to obtain pretreated aids.

4. The method for preparing a transparent, flame-retardant, light-diffusing polypropylene material as described in claim 3, characterized in that, The process of mixing pretreated polypropylene powder and pretreatment additives according to the optimal mixing ratio to obtain a compound raw material includes: Pretreated polypropylene powder was subjected to segmented preheating treatment using a pre-confirmed high-speed mixer to obtain preheated polypropylene powder. Preheated polypropylene powder and pretreatment additives are mixed according to the optimal mixing ratio to obtain proportioned polypropylene powder and proportioned additives. Transparent flame retardants and light diffusing agents were extracted from the formulation additives; The polypropylene powder and transparent flame retardant were initially mixed to obtain the initial mixed raw material; The initial raw materials and light diffusing agent are subjected to high-speed activation and mixing to obtain a uniform premix; The uniform premix is ​​stirred at low temperature to obtain the compounded raw materials.

5. The method for preparing a transparent, flame-retardant, light-diffusing polypropylene material as described in claim 4, characterized in that, The process of melting and extruding the mixed raw materials at the melting temperature corresponding to the mixed raw materials to obtain polypropylene melt includes: The mixed raw materials are heated in stages and sections to obtain a preliminary molten material; High-temperature, high-shear melting of pre-molten material is performed using the melting temperature to obtain a flowing melt; Vacuum devolatilization is performed on the flowing melt to obtain a low-volatility melt; Low-volatility melts are homogenized at low temperatures to obtain homogenized melts; The homogenized melt is subjected to graded filtration to obtain a high-purity melt. The high-purity melt is then subjected to impurity detection to obtain an impurity detection report. The qualified high-purity melt was confirmed using the impurity test report and was then used as the polypropylene melt.

6. The method for preparing a transparent, flame-retardant, light-diffusing polypropylene material as described in claim 5, characterized in that, The performance testing of the polypropylene molecule, and the resulting test report, includes: The thickness of the polypropylene matrix is ​​measured using a preset length interval to obtain a set of thickness values, which includes multiple thickness values. Obtain the thickness standard deviation using multiple thickness values; The total transmitted light flux was measured on the polypropylene matrix to obtain the total transmitted light flux. Parallel transmission light flux was measured on the polypropylene matrix to obtain the parallel transmission light flux. Haze is calculated using the total transmitted luminous flux and the parallel transmitted luminous flux, as shown in the following formula: in, Indicates fog level. This represents the total transmitted luminous flux. This represents the parallel transmission luminous flux. Indicates the standard deviation of thickness. This indicates the preset thickness-haze sensitivity coefficient; Transmittance of polypropylene matrices is measured within a preset visible light range at a preset scanning step size to obtain a transmittance value set. A spectral transmission curve is then constructed based on the visible light range and the transmittance value set. Light transmittance is obtained using spectral transmission curves; The transparency of the polypropylene matrix was measured to obtain the transparency. The test report is obtained by summarizing the haze, light transmittance, and transparency.

7. The method for preparing a transparent, flame-retardant, light-diffusing polypropylene material as described in claim 6, characterized in that, The transparency test of the polypropylene matrix to obtain the transparency includes: Images of polypropylene adult bodies are acquired using a preset acquisition time interval to obtain a polypropylene adult body image set, which includes multiple polypropylene adult body images. For each of the multiple polypropylene adult images, perform the following operation: The polypropylene solid image was converted to grayscale to obtain a grayscale image. A Gaussian filter is applied to the grayscale image to obtain the filtered image; Edge detection is performed on the filtered image to obtain the horizontal and vertical gradients; The gradient magnitude of each pixel in the filtered image is obtained by using the horizontal and vertical gradients, resulting in multiple gradient magnitudes. Gradient energy is obtained by using multiple gradient magnitudes, and reference transparency is obtained by using gradient energy. The reference transparencys are summarized to obtain multiple reference transparencys, and the transparency is obtained by using multiple reference transparencys.

8. The method for preparing a transparent, flame-retardant, light-diffusing polypropylene material as described in claim 7, characterized in that, The method of obtaining a comprehensive performance score set using multiple test reports includes: Multiple haze, transmittance, and transparency values ​​were obtained using multiple test reports; Multiple haze values, multiple transmittance values, and multiple transparency values ​​are normalized to obtain multiple normalized haze values, multiple normalized transmittance values, and multiple normalized transparency values. Perform the following operations on each of the multiple sets of mixed raw materials: The overall performance score is calculated using the normalized haze corresponding to multiple normalized haze values, the normalized transmittance corresponding to multiple normalized transmittance values, and the normalized transparency corresponding to multiple normalized transparency values ​​of the mixed raw materials. The calculation formula is shown below: in, This indicates the overall performance score. This represents the preset haze weighting coefficient. Indicates normalized haze. This represents the preset transmittance weighting coefficient. Represents normalized transmittance. This represents the preset transparency weighting coefficient. Indicates normalized transparency. This represents the preset temperature influence factor. Indicates the melting temperature. This represents the preset optimal processing temperature reference value. This indicates the preset allowable temperature fluctuation range; The overall performance scores are summarized to obtain an overall performance score set.

9. The method for preparing a transparent, flame-retardant, light-diffusing polypropylene material as described in claim 8, characterized in that, The process of morphological filtering of multiple polypropylene samples to obtain a defect-free particle set includes: Multiple polypropylene samples were initially separated using a pre-constructed gas splitter to obtain multiple sieved granules. For each of the plurality of screened granules, the following operation is performed: Acquire multiple images of the screened granules; A three-dimensional point cloud model was constructed using multiple images of granular material. The 3D point cloud model is registered with the pre-confirmed standard cylindrical model by the nearest point to obtain the aligned point cloud model. The contour deviation value is calculated using the aligned point cloud model and the standard cylinder model; The contour deviation value is compared with the preset contour deviation threshold, and the screened granules with a contour deviation value less than the contour deviation threshold are regarded as defect-free granules. By summarizing the defect-free granules, a defect-free granule set is obtained.

10. A system for preparing transparent, flame-retardant, light-diffusing polypropylene materials, characterized in that, The system includes: The raw material blending module is used to obtain the material production specifications and obtain the optimal blending ratio based on the material production specifications. The pre-confirmed set of production raw materials is pre-treated to obtain pre-treated polypropylene powder and pre-treatment additives. Pretreated polypropylene powder and pretreated additives are mixed in the optimal mixing ratio to obtain mixed raw materials. The mixed raw materials are then grouped according to multiple preset melting temperatures to obtain multiple groups of mixed raw materials. The production condition confirmation module is used to perform the following operations on each of the multiple sets of mixed raw materials: The mixed raw materials are melt-extruded using the melting temperature corresponding to the mixed raw materials to obtain polypropylene melt; The polypropylene melt is cooled and shaped to obtain the polypropylene body; The performance of the polypropylene molecule was tested, and a test report was obtained. By summarizing the test reports, multiple test reports are obtained; A comprehensive performance score set is obtained by using multiple test reports. The comprehensive performance score set includes multiple comprehensive performance scores, and each comprehensive performance score corresponds one-to-one with the mixed raw materials. The optimal melting temperature is determined based on multiple comprehensive performance scores. The pellet product production module is used to prepare polypropylene pellets on a large scale using the optimal mixing ratio and optimal melting temperature. Polypropylene granules are pelletized to obtain a polypropylene sample set, which includes multiple polypropylene samples. The finished product quality inspection module is used to perform morphology filtering on multiple polypropylene samples to obtain a defect-free granule set. The defect-free granule set includes multiple defect-free granules, and the multiple defect-free granules are subjected to hot pressing to obtain polypropylene sheets.

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