A simulation method and system for a naked-eye 3D grating

Abstract

The present invention discloses a method and system for simulating a naked-eye 3D grating, including: obtaining, through instrument measurement, angle data when the sub-pixel arrangement of an LED display screen forms Moiré fringes with a grating and recording the sub-pixel arrangement parameters and the change trend of the Moiré fringes; using the calculated preliminary design parameters and combining with an artificial intelligence-aided design algorithm to generate a high-precision digital model of a black-and-white film grating; judging whether the Moiré fringes are less than a preset threshold by simulating the distribution characteristics of the grating period and the horizontal grating pitch at a preset viewing distance of the display screen to obtain verification result data; shortening the development cycle, improving the flexibility and adaptability of the technology, solving the problems of long development cycle and insufficient flexibility in the prior art, improving the degree of automation and efficiency of the design, and providing strong support for the rapid iteration and development of the naked-eye 3D technology.

Description

Technical Field

[0001] The present invention relates to the technical field of grating design and manufacturing, and in particular to a simulation method and system for a naked-eye 3D grating. Background Art

[0002] With the continuous development of digital audio-visual technology, the naked-eye 3D technology, as a technology that can bring immersive visual experiences to users, has received extensive attention and achieved remarkable development and progress. However, there are still many key defects in the existing lens grating-based naked-eye 3D technology during the actual application process, which limit its further development and popularization.

[0003] Firstly, the manufacturing process of the lens grating involves complex manufacturing techniques and high-precision material requirements. This not only requires high-precision processing equipment and strict quality control, but also results in high overall manufacturing costs, increasing the production costs of products and the difficulty of market promotion.

[0004] Secondly, during the manufacturing process of the lens grating, the accurate estimation of the mold size is crucial. However, existing technologies often have difficulty accurately predicting the mold size, which directly affects the image clarity of the final product. Specifically, phenomena such as blurred images and ghosting occur, seriously affecting the user's viewing experience and reducing the practicality and market competitiveness of the technology.

[0005] In addition, the manufacturing of the lens grating requires multiple mold opening, verification, and adjustment processes. This process is not only time-consuming and laborious, but also results in a relatively long overall development cycle. This not only increases the R & D costs, but also delays the market promotion speed of new technologies, restricting the rapid iteration and development of the naked-eye 3D technology.

[0006] In summary, the existing lens grating-based naked-eye 3D technology has various degrees of defects in terms of manufacturing costs, mold size estimation, development cycle, and flexibility. Therefore, there is an urgent need for a more efficient and accurate simulation method for naked-eye 3D gratings to reduce development costs, shorten the development cycle, and improve the flexibility and adaptability of the technology, thereby promoting the further development and wide application of the naked-eye 3D technology. Summary of the Invention

[0007] The present invention provides a simulation method and system for a naked-eye 3D grating to solve the above-mentioned existing technical problems.

[0008] The technical solution of the present invention is realized as follows:

[0009] A simulation method for a naked-eye 3D grating includes the following steps:

[0010] Obtain the angular data when the Moiré fringes formed by the sub-pixel arrangement of the LED display and the grating are relatively small through instrument measurement, and record the sub-pixel arrangement parameters and the change trend of the Moiré fringes;

[0011] According to the sub-pixel arrangement parameters, the preset viewing distance, the pixel length and width, and the initial distance between the grating and the color filter, calculate the grating period and the horizontal grating pitch of the film grating to obtain the preliminary design parameters;

[0012] Adopt the obtained preliminary design parameters, combined with the artificial intelligence-aided design algorithm, to generate a high-precision digital model of the black-and-white film grating;

[0013] Through this digital model, use the machine learning algorithm to intelligently extract and analyze the distribution characteristics of the grating period and the horizontal grating pitch, and at the same time introduce multi-dimensional parameter optimization to predict the Moiré fringe performance under different viewing distances and viewing angles;

[0014] By simulating the distribution characteristics of the grating period and the horizontal grating pitch at the preset viewing distance of the display screen, judge whether the Moiré fringes are less than the preset threshold, and obtain the verification result data;

[0015] Adjust the design parameters according to the verification result data to obtain the cylindrical lens design scheme.

[0016] Furthermore, the process of recording the sub-pixel arrangement parameters and the change trend of the Moiré fringes includes:

[0017] Collect the angular data when the sub-pixel arrangement and the grating structure interact to form Moiré fringes through the instrument to obtain the initial measurement value;

[0018] Extract the characteristic data of the arrangement parameters and the grating structure from the initial measurement value to determine the conditions for fringe formation;

[0019] If the fringe formation conditions meet the preset threshold, analyze the relationship between the angular data and the arrangement parameters through the algorithm to judge the change trend direction;

[0020] Adopt the support vector machine algorithm to classify the change trend direction to obtain the stable characteristics of the trend;

[0021] Compare the morphological data of the Moiré fringes through the stable characteristics of the trend to determine the corresponding relationship between the fringes and the sub-pixel arrangement;

[0022] Process the measurement results according to the corresponding relationship to obtain the mapping data of the sub-pixel arrangement parameters and the fringe change trend;

[0023] Extract the key features from the mapping data to judge the influence degree of the display screen characteristics on the Moiré fringes.

[0024] Furthermore, the process of calculating the grating period and the horizontal grating pitch of the film grating to obtain the preliminary design parameters includes:

[0025] Obtain the initial distribution data of the grating structure through the correspondence between sub-pixel arrangement and pixel length and width, and get the preliminary calculation result of the grating period;

[0026] Adjust the change range of the grating period according to the interaction data between the preset viewing distance and the initial distance, and determine the boundary value of the horizontal grating pitch;

[0027] Analyze the distribution law of the horizontal grating pitch by using the grating pitch characteristics, and obtain the stable characteristic data of the distribution law;

[0028] Classify the stable characteristic data through the support vector machine algorithm, and judge the matching degree between the grating period and the grating pitch characteristics;

[0029] If the matching degree exceeds the preset threshold, extract the optimized parameters of the grating structure from the classification results to obtain the adjusted design parameters;

[0030] Obtain the final calculated value of the grating period according to the correspondence between the adjusted design parameters and the distribution law;

[0031] Judge the adaptability of the grating structure to the sub-pixel arrangement by comparing the final calculated value with the initial distribution data, and obtain the optimized grating pitch distribution.

[0032] Further, the process of generating the high-precision digital model of the black and white film grating includes:

[0033] Obtain the initial digital generation data of the black and white grating through the correspondence between the preliminary parameters and the parameter combination, and get the preliminary distribution of the grating structure;

[0034] According to the interaction data between the grating structure and the design algorithm, use the assisted design to adjust the change range of the digital generation, and determine the boundary value of the high-precision model;

[0035] Generate and analyze the distribution law of the digital model through the algorithm, obtain the stable characteristic data of the model accuracy, and judge the adaptability of the structural parameters;

[0036] If the model accuracy exceeds the preset threshold, extract the optimized parameters of the grating structure from the stable characteristic data to obtain the adjusted digital model;

[0037] Obtain the final distribution data of the high-precision model according to the correspondence between the adjusted digital model and the black and white grating, and determine the optimized value of the parameter combination;

[0038] Judge the matching degree of the grating structure to the assisted design by comparing the final distribution data with the initial digital generation data, and obtain the optimized model accuracy;

[0039] Generate a complete digital model of the black-and-white film grating using the interaction data of the optimized model accuracy and structural parameters to determine the final design result.

[0040] Further, the process of predicting the moiré fringe performance at different viewing distances and viewing angles includes:

[0041] Obtain the initial distribution characteristic data of the grating period and the horizontal grating pitch through the digital model to determine the range of feature extraction;

[0042] Use machine learning algorithms to analyze the initial distribution characteristic data to obtain the structural rule data after feature extraction;

[0043] According to the structural rule data, combined with multi-dimensional parameter optimization, judge the distribution influence of the viewing distance change and the viewing angle change;

[0044] Through the distribution influence data, predict the preliminary performance data of the moiré fringe at different viewing distances;

[0045] Use the preliminary performance data, combined with the characteristics of the viewing angle change, to obtain the complete prediction distribution of the moiré fringe;

[0046] Determine the adjustment value of the parameter optimization by comparing the complete prediction distribution with the initial distribution characteristic data;

[0047] Update the digital model according to the adjustment value to obtain the optimized distribution characteristic data.

[0048] Further, the process of obtaining the verification result data includes:

[0049] Generate the distribution characteristic data of the grating period and the horizontal grating pitch through the simulation display screen to obtain the initial distribution data;

[0050] According to the initial distribution data, use the support vector machine algorithm to analyze the distribution characteristics to obtain the structural data after feature extraction;

[0051] Judge the change trend of the moiré fringe by combining the structural data with the preset viewing distance to obtain the change trend data;

[0052] If the change trend data exceeds the preset threshold, generate new distribution characteristic data by adjusting the grating period to obtain the adjusted distribution data;

[0053] According to the adjusted distribution data, use the clustering algorithm to analyze the matching degree between the moiré fringe and the preset threshold to obtain the matching result data;

[0054] Judge whether the verification result meets the conditions by combining the matching result data with the display screen parameters to obtain the final verification data;

[0055] According to the final verification data, statistical tools are used to analyze the stability of the feature distribution, and the optimized distribution data is obtained.

[0056] Further, the process of obtaining the cylindrical lens design scheme includes:

[0057] If the verification result data indicates that the Moiré fringes are less than the preset threshold, the curvature parameter and spacing parameter of the cylindrical lens are calculated according to the distribution characteristics of the grating period and the horizontal grating pitch, and the first design scheme data is obtained;

[0058] Based on the first design scheme data and the initial position of the color filter, the relative position data between the cylindrical lens and the color filter is obtained;

[0059] According to the relative position data, a clustering algorithm is used to analyze the matching degree between the cylindrical lens and the grating period, and the first matching result data is obtained;

[0060] Among them, if the first matching result data exceeds the preset range, the distance between the color filter and the grating is adjusted, and the distribution characteristics are recalculated to obtain the second design scheme data;

[0061] Based on the second design scheme data, the distribution data of the adjusted curvature parameter and spacing parameter are obtained;

[0062] According to the distribution data, statistical tools are used to analyze the stability of the cylindrical lens design scheme, and the optimized design parameter data is obtained;

[0063] Based on the optimized design parameter data, the compatibility between the cylindrical lens and the grating period is judged to obtain the final compatibility data.

[0064] Further, the process of obtaining the cylindrical lens design scheme also includes:

[0065] If the verification result data indicates that the Moiré fringes are greater than the preset threshold, the distance between the grating and the color filter is adjusted, and the grating period and the horizontal grating pitch are recalculated to obtain the adjusted design parameters;

[0066] Specifically, S100: Adjust the distance between the grating and the color filter, and the specific adjustment amount is quantitatively calculated according to the exceeding degree of the Moiré fringes;

[0067] S200: According to the adjusted distance, recalculate the grating period and the horizontal grating pitch to obtain the adjusted design parameters. An error analysis model is introduced in the calculation process to evaluate the influence of the adjustment on the Moiré fringes;

[0068] S300: Based on the adjusted design parameters, using a multi-dimensional parameter optimization algorithm, comprehensively considering factors such as viewing distance, viewing angle, and pixel arrangement, further optimize the grating period and the horizontal grating pitch to reduce the Moiré fringes;

[0069] S400. Preset the distribution characteristics of the grating period and the horizontal grating pitch at a preset viewing distance through the analog display screen, and determine again whether the Moiré fringes are less than the preset threshold to obtain new verification result data;

[0070] If the Moiré fringes are still greater than the preset threshold, further adjust the distance between the grating and the color filter according to the new verification result data, and repeat the above steps S100 - S400 until the Moiré fringes meet the requirements;

[0071] It also includes establishing a dynamic adjustment mechanism to monitor the change trend of the Moiré fringes in real time, and dynamically adjusting the distance between the grating and the color filter according to the real - time data to ensure that the Moiré fringes are always within the controllable range;

[0072] Record the distance adjusted each time, the calculated design parameters, and the change trend of the Moiré fringes, and analyze the rules in the adjustment process using data analysis tools.

[0073] Furthermore, after the step of obtaining the verification result data in this method, it also includes:

[0074] Based on the adjusted design parameters, sub - pixel arrangement, preset viewing distance, and pixel length and width, establish a dynamic matching algorithm for the grating period and the arrangement of microlens units to obtain a set of matching parameters;

[0075] Optimize the arrangement characteristics of the grating and the microlens units through the set of matching parameters, determine whether the image blur degree is lower than the preset threshold, and obtain the optimized arrangement data;

[0076] Generate the final cylindrical lens grating digital model according to the optimized arrangement data, extract the curvature, pitch, and arrangement parameters from the digital model, and determine the final design scheme.

[0077] A simulation system for a naked - eye 3D grating, comprising:

[0078] A measurement module, which is used to measure and obtain the angular data when the sub - pixel arrangement of the LED display screen forms small Moiré fringes through an instrument, and record the sub - pixel arrangement parameters and the change trend of the Moiré fringes;

[0079] A calculation module, which is used to calculate the grating period and the horizontal grating pitch of the film grating according to the sub - pixel arrangement parameters, preset viewing distance, pixel length and width, and the initial distance between the grating and the color filter to obtain preliminary design parameters;

[0080] A design module, which is used to adopt the calculated preliminary design parameters and combine them with an artificial - intelligence - assisted design algorithm to generate a high - precision digital model of a black - and - white film grating;

[0081] An analysis module, which is used to intelligently extract and analyze the distribution characteristics of the grating period and the horizontal grating pitch through this digital model by using machine learning algorithms, and at the same time introduce multi-dimensional parameter optimization to predict the moiré fringe performance under different viewing distances and viewing angles;

[0082] A verification module, which is used to judge whether the moiré fringe is less than a preset threshold by simulating the distribution characteristics of the grating period and the horizontal grating pitch at the preset viewing distance of the display screen, and obtain verification result data;

[0083] An adjustment module, which is used to adjust the distance between the grating and the color filter if the verification result data indicates that the moiré fringe is greater than the preset threshold, recalculate the grating period and the horizontal grating pitch, and obtain the adjusted design parameters;

[0084] A matching module, which is used to establish a dynamic matching algorithm for the grating period and the arrangement of microlens units based on the adjusted design parameters, sub-pixel arrangement, preset viewing distance, and pixel length and width, and obtain a set of matching parameters;

[0085] An optimization module, which is used to optimize the arrangement characteristics of the grating and the microlens units through the set of matching parameters, judge whether the image blurring degree is lower than the preset threshold, and obtain the optimized arrangement data;

[0086] A generation module, which is used to generate a final lenticular grating digital model according to the optimized arrangement data, extract curvature, spacing, and arrangement parameters from the digital model, and determine the final design scheme.

[0087] Compared with the prior art, the present invention has the following beneficial effects:

[0088] 1. The present invention obtains the angular data when the sub-pixel arrangement of the LED display screen and the grating form a smaller moiré fringe through instrument measurement, and records the relevant parameters and change trends, providing an accurate data basis for subsequent designs, avoiding image quality problems caused by inaccurate estimation in traditional methods, and thus effectively solving the problem of inaccurate estimation of die size in the prior art;

[0089] 2. The present invention calculates the grating period and the horizontal grating pitch of the film grating according to the measured sub-pixel arrangement parameters, preset viewing distance, pixel length and width, and the initial distance between the grating and the color filter to obtain preliminary design parameters. On this basis, combined with the artificial intelligence-assisted design algorithm, a high-precision digital model of the black-and-white film grating is generated, and machine learning algorithms are used to intelligently extract and analyze the distribution characteristics of the grating period and the horizontal grating pitch. At the same time, multi-dimensional parameter optimization is introduced to predict the moiré fringe performance under different viewing distances and viewing angles, improving the design accuracy and efficiency, reducing the dependence on high-precision physical manufacturing equipment, and thus effectively reducing the production cost;

[0090] 3. By simulating the distribution characteristics of the grating period and the horizontal grating pitch at the preset viewing distance of the display screen, the present invention determines whether the Moiré fringes are less than the preset threshold, obtains the verification result data, adjusts the design parameters according to the verification result, and finally obtains the lenticular lens design scheme. If the verification result shows that the Moiré fringes are less than the preset threshold, the design is further optimized; if it is greater than the preset threshold, the distance between the grating and the color filter is adjusted, and the design parameters are recalculated. This dynamic adjustment mechanism greatly shortens the development cycle, improves the flexibility and adaptability of the technology, and solves the problems of long development cycle and lack of flexibility in the prior art;

[0091] 4. The present invention also establishes a dynamic matching algorithm for the grating period and the arrangement of microlens units, optimizes the arrangement characteristics of the grating and the microlens units, and further improves the image quality. Through this algorithm, the design parameters of the grating can be flexibly adjusted according to the requirements of different application scenarios to ensure the stability and reliability of the technology under different conditions. Finally, a digital model of the lenticular lens grating is generated based on the optimized arrangement data to determine the final design scheme, improving the automation degree and efficiency of the design, and providing strong support for the rapid iteration and development of the naked-eye 3D technology. Description of the Drawings

[0092] Figure 1 It is a flowchart of a simulation method for a naked-eye 3D grating in Embodiment 1;

[0093] Figure 2 It is a flowchart of a simulation method for a naked-eye 3D grating in Embodiment 2;

[0094] Figure 3 It is a module framework diagram of a simulation system for a naked-eye 3D grating in Embodiment 3. Detailed Embodiments

[0095] To make the objectives, features, and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the embodiments described below are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0096] Embodiment 1

[0097] As Figure 1 shown, this embodiment provides a simulation method for a naked-eye 3D grating, including the following steps:

[0098] Obtain the angular data when the sub-pixel arrangement of the LED display screen and the grating form Moiré fringes that are relatively small through instrument measurement, and record the sub-pixel arrangement parameters and the change trend of the Moiré fringes;

[0099] Calculate the grating period and horizontal pitch of the film grating according to the sub-pixel arrangement parameters, preset viewing distance, pixel length and width, and the initial distance between the grating and the color filter to obtain preliminary design parameters;

[0100] Adopt the calculated preliminary design parameters and combine with the artificial intelligence-aided design algorithm to generate a high-precision digital model of the black-and-white film grating;

[0101] Through this digital model, use the machine learning algorithm to intelligently extract and analyze the distribution characteristics of the grating period and horizontal pitch, and at the same time introduce multi-dimensional parameter optimization to predict the moiré fringe performance at different viewing distances and viewing angles;

[0102] By simulating the distribution characteristics of the grating period and horizontal pitch at the preset viewing distance of the display screen, judge whether the moiré fringe is less than the preset threshold to obtain verification result data;

[0103] Adjust the design parameters according to the verification result data to obtain a lenticular lens design scheme.

[0104] Further, the process of recording the sub-pixel arrangement parameters and the change trend of the moiré fringe includes:

[0105] Collect the angle data when the sub-pixel arrangement and the grating structure interact to form moiré fringes through an instrument to obtain an initial measurement value;

[0106] Extract the characteristic data of the arrangement parameters and the grating structure from the initial measurement value to determine the conditions for fringe formation;

[0107] If the fringe formation condition meets the preset threshold, analyze the relationship between the angle data and the arrangement parameters through an algorithm to judge the change trend direction;

[0108] Adopt the support vector machine algorithm to classify the change trend direction to obtain the stable characteristics of the trend;

[0109] Compare the morphological data of the moiré fringe through the stable characteristics of the trend to determine the corresponding relationship between the fringe and the sub-pixel arrangement;

[0110] Process the measurement results according to the corresponding relationship to obtain the mapping data of the sub-pixel arrangement parameters and the fringe change trend;

[0111] Extract the key features from the mapping data to judge the influence degree of the display screen characteristics on the moiré fringe.

[0112] In one embodiment, the process of recording the sub-pixel arrangement parameters and the change trend of the moiré fringe can be described as follows:

[0113] Obtain the angular data when the Moiré fringes formed by the sub-pixel arrangement of the LED display and the grating are relatively small through instrument measurement. For example, use a high-precision angle measuring instrument to record the change trend of the Moiré fringes when the sub-pixel arrangement parameters are 0.5°, 1.0°, and 1.5°;

[0114] According to the recorded angular data and sub-pixel arrangement parameters, extract the initial measurement values when the Moiré fringes are formed. For example, extract the characteristic data with a grating period of 50 μm at 0.5°;

[0115] Analyze the interaction relationship between the sub-pixel arrangement parameters and the grating structure through the characteristic data in the initial measurement values. For example, use the Fourier transform algorithm to analyze the matching degree between the grating period and the sub-pixel pitch, and determine that the condition for fringe formation is that the ratio of the grating period to the sub-pixel pitch is less than 0.8. If the fringe formation condition meets the preset threshold, then process the corresponding relationship between the angular data and the arrangement parameters through an algorithm. For example, use the least squares method to fit the relationship curve between the angular data and the sub-pixel pitch, and judge that the change trend direction is positive growth;

[0116] Use the support vector machine algorithm to classify the change trend direction. For example, set the kernel function as the radial basis function, and the classification accuracy reaches 95%, and obtain the stable characteristic of the trend as the linear relationship between the angular data and the sub-pixel pitch;

[0117] Compare the morphological data of the Moiré fringes according to the stable characteristics of the trend. For example, compare the ratio of the fringe width to the sub-pixel pitch, and determine that the corresponding relationship between the fringe and the sub-pixel arrangement is that the fringe width is proportional to the sub-pixel pitch;

[0118] Process the measurement results through the corresponding relationship. For example, use the interpolation algorithm to calculate the fringe width when the sub-pixel pitch is 10 μm, and obtain the mapping data between the sub-pixel arrangement parameters and the fringe change trend;

[0119] Extract the key features from the mapping data. For example, extract the maximum value of the fringe width change rate as 0.2, and judge that the influence degree of the display characteristics on the Moiré fringes is medium.

[0120] Further, the process of calculating the grating period and the horizontal grating pitch of the film grating to obtain the preliminary design parameters includes:

[0121] Obtain the initial distribution data of the grating structure through the corresponding relationship between the sub-pixel arrangement and the pixel length and width, and obtain the preliminary calculation result of the grating period;

[0122] Adjust the change range of the grating period according to the interaction data between the preset viewing distance and the initial distance, and determine the boundary value of the horizontal grating pitch;

[0123] Analyze the distribution law of the horizontal grating pitch by using the grating pitch characteristics, and obtain the stable characteristic data of the distribution law;

[0124] Classify the stable feature data through the support vector machine algorithm to judge the matching degree between the grating period and the grating pitch feature;

[0125] If the matching degree exceeds the preset threshold, extract the optimization parameters of the grating structure from the classification results to obtain the adjusted design parameters;

[0126] According to the corresponding relationship between the adjusted design parameters and the distribution law, obtain the final calculated value of the grating period;

[0127] By comparing the final calculated value with the initial distribution data, judge the adaptability of the grating structure to the sub-pixel arrangement, and obtain the optimized grating pitch distribution.

[0128] In one embodiment, the process of calculating the grating period and the horizontal grating pitch of the film grating to obtain the preliminary design parameters can be described as follows:

[0129] According to the sub-pixel arrangement parameters (such as RGB stripe arrangement), the preset viewing distance of 600 mm, the pixel length and width of 0.1 mm×0.3 mm, and the initial distance of 0.5 mm between the grating and the color filter, use the geometric optical formula to calculate the grating period of the film grating to be 0.15 mm and the horizontal grating pitch to be 0.05 mm, and obtain the preliminary design parameters;

[0130] Through the corresponding relationship between the sub-pixel arrangement and the pixel length and width, extract the pixel pitch of 0.1 mm as the initial distribution data of the grating structure, and combine the moiré fringe suppression condition to calculate the grating period to be 0.148 mm. According to the interaction data of the preset viewing distance of 600 mm and the initial distance of 0.5 mm, use the parallax formula to adjust the grating period change range between 0.145 - 0.155 mm, and determine the horizontal grating pitch boundary value to be 0.048 - 0.052 mm;

[0131] Use Fourier transform to analyze the distribution law of the horizontal grating pitch, extract the spectral peak value of 0.05 mm as the stable feature data. Classify the 0.05 mm grating pitch feature data through the support vector machine algorithm, set the matching threshold to 90%, and determine the match when the classification confidence reaches 92%. If the match is established, extract the tilt angle of 5° and the period fine-tuning coefficient of 1.02 as the optimization parameters from the classification results, and obtain the adjusted grating period of 0.151 mm;

[0132] According to the corresponding relationship between the optimization parameters and the distribution law, use the least squares method to fit the final grating period to 0.1502 mm;

[0133] Compare the final calculated value of 0.1502 mm with the initial distribution data of 0.148 mm, judge the adaptability through the difference of 0.0022 mm, and generate the optimized grating pitch distribution of 0.0501 mm.

[0134] Further, the process of generating a high-precision digital model of the black-and-white film grating includes:

[0135] Obtain the initial digital generation data of the black-and-white grating through the corresponding relationship between the preliminary parameters and the parameter combination, and obtain the preliminary distribution of the grating structure;

[0136] According to the interaction data between the grating structure and the design algorithm, use the auxiliary design to adjust the change range of the digital generation, and determine the boundary value of the high-precision model;

[0137] Generate and analyze the distribution law of the digital model through the algorithm, obtain the stable characteristic data of the model accuracy, and judge the adaptability of the structural parameters;

[0138] If the model accuracy exceeds the preset threshold, extract the optimized parameters of the grating structure from the stable characteristic data to obtain the adjusted digital model;

[0139] According to the corresponding relationship between the adjusted digital model and the black-and-white grating, obtain the final distribution data of the high-precision model, and determine the optimized value of the parameter combination;

[0140] By comparing the final distribution data with the initial digital generation data, judge the matching degree of the grating structure to the auxiliary design, and obtain the optimized model accuracy;

[0141] Use the interaction data of the optimized model accuracy and the structural parameters to generate a complete digital model of the black-and-white film grating, and determine the final design result.

[0142] In one embodiment, the process of generating a high-precision digital model of the black-and-white film grating can be described as follows:

[0143] According to the corresponding relationship between the preliminary design parameters and the sub-pixel arrangement, obtain the initial distribution data of the grating structure, and determine the preliminary calculation result of the grating period (0.3 mm);

[0144] Use an artificial intelligence-assisted design algorithm (such as a deep learning model) to analyze the initial distribution data, adjust the change range of the grating period (0.28 mm to 0.32 mm), and obtain the adjusted design parameters (0.31 mm);

[0145] Through the interaction data between the adjusted design parameters and the initial distribution data, analyze the distribution law of the horizontal grating pitch, and obtain the stable characteristic data of the distribution law (standard deviation is 0.01 mm);

[0146] The support vector machine algorithm is used to classify the stable feature data, judge the matching degree of the grating period and the grating pitch characteristics, and obtain the classification result (the matching degree is 95%). If the matching degree exceeds the preset threshold (90%), the optimized parameters of the grating structure (the grating period is 0.31 mm, and the horizontal grating pitch is 0.155 mm) are extracted from the classification result, and the optimized design parameters are determined;

[0147] According to the corresponding relationship between the optimized design parameters and the distribution law, calculate the final calculated value of the grating period (0.31 mm), and obtain the optimized grating pitch distribution (0.155 mm);

[0148] By comparing the final calculated value with the initial distribution data, analyze the adaptability of the grating structure to the sub-pixel arrangement, and obtain the distribution data of the high-precision digital model (the error is less than 0.001 mm);

[0149] Using the distribution data of the high-precision digital model, combined with the artificial intelligence-aided design algorithm (such as convolutional neural network), generate the complete digital model of the black-and-white film grating, and determine the final design result (the grating period is 0.31 mm, and the horizontal grating pitch is 0.155 mm).

[0150] Furthermore, the process of predicting the moiré fringe performance at different viewing distances and viewing angles includes:

[0151] Obtain the initial distribution characteristic data of the grating period and the horizontal grating pitch through the digital model, and determine the range of feature extraction;

[0152] Use the machine learning algorithm to analyze the initial distribution characteristic data, and obtain the structural law data after feature extraction;

[0153] According to the structural law data, combined with multi-dimensional parameter optimization, judge the distribution influence of the viewing distance change and the viewing angle change;

[0154] Through the distribution influence data, predict the preliminary performance data of the moiré fringe at different viewing distances;

[0155] Use the preliminary performance data, combined with the characteristics of the viewing angle change, to obtain the complete prediction distribution of the moiré fringe;

[0156] By comparing the complete prediction distribution with the initial distribution characteristic data, determine the adjustment value of the parameter optimization;

[0157] Update the digital model according to the adjustment value to obtain the optimized distribution characteristic data.

[0158] In one embodiment, the process of predicting the moiré fringe performance at different viewing distances and viewing angles can be described as follows:

[0159] Extract the initial distribution characteristic data of the grating period and the horizontal grating pitch through a digital model, and set the characteristic extraction range to the grating period interval from 0.1 mm to 0.5 mm;

[0160] Use the support vector machine algorithm to perform clustering analysis on the initial distribution data, and extract the structural regular data. For example, divide the grating period into 5 categories and calculate the mean and variance of each category;

[0161] According to the structural regular data combined with multi-dimensional parameter optimization, use the gradient descent method to adjust the weight coefficients of the viewing distance and the viewing angle, and judge whether the distribution influence factor exceeds 0.8;

[0162] Input the distribution influence data into a convolutional neural network model to predict the preliminary performance data of the Moiré fringes at a viewing distance from 1 m to 3 m, and output the distribution characteristics of the fringe pitch and the contrast;

[0163] Adopt the preliminary performance data combined with the characteristics of the viewing angle change, and use the random forest algorithm to analyze the deformation trend of the Moiré fringes at different viewing angles to generate a complete prediction distribution map;

[0164] By comparing the complete prediction distribution with the initial distribution characteristic data, calculate the mean square error and determine the parameter adjustment value to be ±0.05 mm;

[0165] Update the grating period parameters in the digital model according to the adjustment value to obtain the optimized distribution characteristic data. For example, the horizontal grating pitch is corrected to 0.25 mm.

[0166] Furthermore, the process of obtaining the verification result data includes:

[0167] Generate the distribution characteristic data of the grating period and the horizontal grating pitch through a simulated display screen to obtain the initial distribution data;

[0168] According to the initial distribution data, use the support vector machine algorithm to analyze the distribution characteristics and obtain the structural data after feature extraction;

[0169] Based on the structural data combined with the preset viewing distance, judge the change trend of the Moiré fringes to obtain the change trend data;

[0170] If the change trend data exceeds the preset threshold, generate new distribution characteristic data by adjusting the grating period to obtain the adjusted distribution data;

[0171] According to the adjusted distribution data, use the clustering algorithm to analyze the matching degree between the Moiré fringes and the preset threshold to obtain the matching result data;

[0172] Based on the matching result data combined with the display screen parameters, judge whether the verification result meets the conditions to obtain the final verification data;

[0173] Based on the final verification data, statistical tools are used to analyze the stability of the feature distribution, and the optimized distribution data is obtained.

[0174] In one embodiment, the process of obtaining the verification result data can be described as follows:

[0175] Collect the initial distribution data with a grating period of 50 microns and a horizontal grating pitch of 30 microns at a preset viewing distance of 1.5 meters through a simulated display screen. Use the radial basis kernel function in the support vector machine algorithm to train the distribution features and extract the spatial frequency features of the grating structure;

[0176] Combined with the preset viewing distance of 1.5 meters and the periodic change law of the Moiré fringes, calculate the contrast change trend of the Moiré fringes. If the contrast exceeds the threshold of 0.3, then use the gradient descent method to adjust the grating period to 48 microns to generate new distribution data;

[0177] Use the K-means clustering algorithm to classify the adjusted data and analyze the matching degree between the Moiré fringes and the preset threshold. If the matching degree is lower than 90%, then re-optimize the distribution features in combination with the display sub-pixel arrangement parameters;

[0178] Based on the optimized data, use analysis of variance to evaluate the stability of the feature distribution. If the standard deviation is less than 0.05, then determine that the distribution is stable;

[0179] Perform a differential calculation between the optimized distribution data and the initial data to determine that the grating period needs to be adjusted to 47.5 microns and the horizontal grating pitch is adjusted to 28.5 microns;

[0180] Update the grating parameters in the digital model according to the adjustment values and output the optimized grating period and horizontal grating pitch distribution feature data.

[0181] Further, the process of obtaining the cylindrical lens design scheme includes:

[0182] If the verification result data indicates that the Moiré fringes are smaller than the preset threshold, then calculate the curvature parameters and spacing parameters of the cylindrical lens according to the distribution characteristics of the grating period and the horizontal grating pitch to obtain the first design scheme data;

[0183] Obtain the relative position data between the cylindrical lens and the color filter through the first design scheme data combined with the initial position of the color filter;

[0184] According to the relative position data, use the clustering algorithm to analyze the matching degree between the cylindrical lens and the grating period to obtain the first matching result data;

[0185] Among them, if the first matching result data exceeds the preset range, then adjust the distance between the color filter and the grating, recalculate the distribution characteristics, and obtain the second design scheme data;

[0186] Obtain the distribution data of the adjusted curvature parameter and spacing parameter through the second design scheme data;

[0187] According to the distribution data, use statistical tools to analyze the stability of the cylindrical lens design scheme and obtain the optimized design parameter data;

[0188] Judge the compatibility between the cylindrical lens and the grating period through the optimized design parameter data to obtain the final compatibility data.

[0189] In one embodiment, if the verification result data indicates that the Moiré fringe is less than the preset threshold of 0.05, then according to the distribution characteristics of the grating period of 500 nm and the horizontal grating pitch of 200 nm, use the geometric optics formula to calculate the curvature radius of the cylindrical lens grating as 1.2 mm and the spacing parameter as 0.8 mm to obtain the cylindrical lens design scheme data. If the verification result data indicates that the Moiré fringe is greater than the preset threshold of 0.05, then adjust the distance between the grating and the color filter from 1.5 mm to 2.0 mm, recalculate the grating period as 550 nm and the horizontal grating pitch as 220 nm, and obtain the adjusted design parameter data;

[0190] Through the adjusted design parameter data, use the Fourier transform algorithm to calculate the distribution characteristics of the grating period and the horizontal grating pitch to obtain the first distribution characteristic data. According to the first distribution characteristic data, design the curvature parameter of the cylindrical lens as 1.3 mm and the spacing parameter as 0.85 mm to obtain the first design scheme data;

[0191] Combined with the initial position of the color filter being 2.0 mm through the first design scheme data, use the spatial geometry algorithm to calculate the relative position data between the cylindrical lens and the color filter, and obtain the first relative position data as 0.5 mm;

[0192] According to the first relative position data, use the K-means clustering algorithm to analyze the matching degree between the cylindrical lens and the grating period, and obtain the first matching result data as 0.92. If the first matching result data exceeds the preset range of 0.90, then adjust the distance between the color filter and the grating from 2.0 mm to 2.2 mm, recalculate the distribution characteristics, and obtain the second design scheme data;

[0193] Through the second design scheme data, use statistical analysis tools to obtain the distribution data of the adjusted curvature parameter of 1.35 mm and the spacing parameter of 0.88 mm to obtain the distribution statistical data;

[0194] According to the distribution statistical data, use the analysis of variance algorithm to analyze the stability of the cylindrical lens design scheme and obtain the optimized design parameter data.

[0195] Furthermore, the process of obtaining the cylindrical lens design scheme further includes:

[0196] If the verification result data indicates that the moiré fringes are greater than the preset threshold, adjust the distance between the grating and the color filter, recalculate the grating period and the horizontal grating pitch, and obtain the adjusted design parameters;

[0197] Specifically, in S100, adjust the distance between the grating and the color filter, and the specific adjustment amount is quantitatively calculated according to the exceeding degree of the moiré fringes;

[0198] S200: According to the adjusted distance, recalculate the grating period and the horizontal grating pitch, and obtain the adjusted design parameters. An error analysis model is introduced in the calculation process to evaluate the influence of the adjustment on the moiré fringes;

[0199] S300: Based on the adjusted design parameters, use the multi-dimensional parameter optimization algorithm, and comprehensively consider factors such as viewing distance, viewing angle, and pixel arrangement to further optimize the grating period and the horizontal grating pitch to reduce the moiré fringes;

[0200] S400: By simulating the distribution characteristics of the grating period and the horizontal grating pitch at the preset viewing distance of the display screen, determine again whether the moiré fringes are less than the preset threshold, and obtain the new verification result data;

[0201] If the moiré fringes are still greater than the preset threshold, further adjust the distance between the grating and the color filter according to the new verification result data, and repeat the above steps S100~S400 until the moiré fringes meet the requirements;

[0202] It also includes establishing a dynamic adjustment mechanism to monitor the change trend of the moiré fringes in real time, and dynamically adjust the distance between the grating and the color filter according to the real-time data to ensure that the moiré fringes are always within the controllable range;

[0203] Record the distance adjusted each time, the calculated design parameters, and the change trend of the moiré fringes, and use the data analysis tool to analyze the rules in the adjustment process.

[0204] In one embodiment, the process of obtaining the cylindrical lens design scheme can be as follows:

[0205] Suppose the verification result data indicates that the moiré fringes are greater than the preset threshold, and the specific exceeding degree is 20% exceeding the threshold. At this time, it is necessary to adjust the distance between the grating and the color filter. The specific steps are as follows:

[0206] S100: Quantitatively calculate the distance to adjust between the grating and the color filter according to the exceeding degree of the moiré fringes. For example, the initial distance is 0.5mm, and after calculation according to the exceeding degree, it is decided to adjust the distance to 0.52mm.

[0207] S200: Recalculate the grating period and horizontal grating pitch based on the adjusted distance of 0.52 mm. Assuming the initial grating period is 0.2 mm and the horizontal grating pitch is 0.1 mm, after recalculation, the adjusted grating period is 0.21 mm and the horizontal grating pitch is 0.105 mm. During this process, an error analysis model is introduced to evaluate the impact of the adjustment on the Moiré fringes, and it is predicted that the intensity of the adjusted Moiré fringes will be reduced by 15%.

[0208] S300: Based on the adjusted design parameters, use a multi-dimensional parameter optimization algorithm to comprehensively consider factors such as the viewing distance (assuming the preset viewing distance is 500 mm), viewing angle (assuming it is 30°), pixel arrangement (assuming it is RGB Delta arrangement), etc., and further optimize the grating period and horizontal grating pitch. After optimization, the grating period is 0.208 mm and the horizontal grating pitch is 0.104 mm. At this time, it is predicted that the intensity of the Moiré fringes is further reduced to below the preset threshold.

[0209] S400: By simulating the distribution characteristics of the grating period of 0.208 mm and the horizontal grating pitch of 0.104 mm at the preset viewing distance of 500 mm of the display screen, judge again whether the Moiré fringes are less than the preset threshold. After simulation verification, the intensity of the Moiré fringes is 0.03 (assuming the preset threshold is 0.05), meeting the requirements, and new verification result data is obtained.

[0210] If the Moiré fringes are still greater than the preset threshold after a certain adjustment, then according to the new verification result data, further adjust the distance between the grating and the color filter, and repeat the above steps S100 - S400 until the Moiré fringes meet the requirements. For example, if the intensity of the Moiré fringes is still 0.06 after a certain adjustment, exceeding the preset threshold of 0.05, then adjust the distance to 0.53 mm again, recalculate the grating period and horizontal grating pitch, and continue to optimize until the intensity of the Moiré fringes drops to 0.04, meeting the requirements.

[0211] During the entire adjustment process, establish a dynamic adjustment mechanism to monitor the change trend of the Moiré fringes in real time. For example, collect the intensity data of the Moiré fringes in real time through sensors, and dynamically adjust the distance between the grating and the color filter according to the real-time data. At the same time, record the distance of each adjustment (such as 0.5 mm, 0.52 mm, 0.53 mm, etc.), the calculated design parameters (such as grating period 0.2 mm, 0.21 mm, 0.208 mm, etc., horizontal grating pitch 0.1 mm, 0.105 mm, 0.104 mm, etc.), and the change trend of the Moiré fringes (such as from 0.08 to 0.06, and then to 0.04, etc.), and use data analysis tools (such as regression analysis) to analyze the rules in the adjustment process to provide a reference for subsequent optimization to ensure that the Moiré fringes are always within the controllable range.

[0212] Finally, based on the design parameters that meet the requirements, such as a grating period of 0.208 mm and a horizontal grating pitch of 0.104 mm, and combining information such as the initial position of the color filter, the curvature parameters and spacing parameters of the cylindrical lens are calculated to obtain a design scheme for the cylindrical lens. For example, the calculated radius of curvature of the cylindrical lens is 100 mm and the spacing is 0.2 mm, thereby determining a complete design scheme for the cylindrical lens, providing precise guidance for subsequent manufacturing.

[0213] Embodiment 2

[0214] As Figure 2 shown, this embodiment provides a method for simulating a naked-eye 3D grating, including the following steps:

[0215] Obtain angle data when the sub-pixel arrangement of the LED display forms Moiré fringes with the grating through instrument measurement, and record the sub-pixel arrangement parameters and the change trend of the Moiré fringes;

[0216] According to the sub-pixel arrangement parameters, the preset viewing distance, the pixel length and width, and the initial distance between the grating and the color filter, calculate the grating period and horizontal grating pitch of the film grating to obtain preliminary design parameters;

[0217] Adopt the calculated preliminary design parameters, combined with the artificial intelligence-aided design algorithm, to generate a high-precision digital model of the black-and-white film grating;

[0218] Through this digital model, use the machine learning algorithm to intelligently extract and analyze the distribution characteristics of the grating period and horizontal grating pitch, and at the same time introduce multi-dimensional parameter optimization to predict the Moiré fringe performance at different viewing distances and viewing angles;

[0219] By simulating the distribution characteristics of the grating period and horizontal grating pitch at the preset viewing distance of the display screen, judge whether the Moiré fringes are less than the preset threshold to obtain verification result data;

[0220] Based on the adjusted design parameters, sub-pixel arrangement, preset viewing distance, and pixel length and width, establish a dynamic matching algorithm for the grating period and the arrangement of microlens units to obtain a set of matching parameters;

[0221] Optimize the arrangement characteristics of the grating and microlens units through the set of matching parameters, judge whether the image blur degree is lower than the preset threshold, and obtain the optimized arrangement data;

[0222] Generate the final digital model of the cylindrical lens grating according to the optimized arrangement data, extract the curvature, spacing, and arrangement parameters from the digital model, and determine the final design scheme.

[0223] Further, the process of recording the sub-pixel arrangement parameters and the change trend of the Moiré fringes includes:

[0224] Collect the angular data when the sub-pixel arrangement interacts with the grating structure to form moiré fringes through an instrument, and obtain the initial measurement value;

[0225] Extract the characteristic data of the arrangement parameters and the grating structure from the initial measurement value, and determine the conditions for fringe formation;

[0226] If the fringe formation condition meets the preset threshold, analyze the relationship between the angular data and the arrangement parameters through an algorithm to judge the direction of the change trend;

[0227] Adopt the support vector machine algorithm to classify the direction of the change trend, and obtain the stable characteristics of the trend;

[0228] Compare the morphological data of the moiré fringes through the stable characteristics of the trend to determine the corresponding relationship between the fringes and the sub-pixel arrangement;

[0229] Process the measurement results according to the corresponding relationship to obtain the mapping data of the sub-pixel arrangement parameters and the fringe change trend;

[0230] Extract the key features from the mapping data to judge the influence degree of the display screen characteristics on the moiré fringes.

[0231] Further, the process of calculating the grating period and the horizontal grating pitch of the film grating to obtain the preliminary design parameters includes:

[0232] Obtain the initial distribution data of the grating structure through the corresponding relationship between the sub-pixel arrangement and the pixel length and width, and obtain the preliminary calculation result of the grating period;

[0233] Adjust the change range of the grating period according to the interaction data between the preset viewing distance and the initial distance, and determine the boundary value of the horizontal grating pitch;

[0234] Adopt the grating pitch feature to analyze the distribution law of the horizontal grating pitch, and obtain the stable feature data of the distribution law;

[0235] Adopt the support vector machine algorithm to classify the stable feature data to judge the matching degree between the grating period and the grating pitch feature;

[0236] If the matching degree exceeds the preset threshold, extract the optimized parameters of the grating structure from the classification result to obtain the adjusted design parameters;

[0237] Obtain the final calculated value of the grating period according to the corresponding relationship between the adjusted design parameters and the distribution law;

[0238] Judge the adaptability of the grating structure to the sub-pixel arrangement through the comparison between the final calculated value and the initial distribution data, and obtain the optimized grating pitch distribution.

[0239] Further, the process of generating the high-precision digital model of the black and white film grating includes:

[0240] Obtain the initial digital generation data of the black-and-white grating through the corresponding relationship between the preliminary parameters and the combined parameters, and obtain the preliminary distribution of the grating structure;

[0241] According to the interaction data between the grating structure and the design algorithm, use the auxiliary design to adjust the change range of digital generation, and determine the boundary value of the high-precision model;

[0242] Generate and analyze the distribution law of the digital model through the algorithm, obtain the stable characteristic data of the model accuracy, and judge the adaptability of the structural parameters;

[0243] If the model accuracy exceeds the preset threshold, extract the optimized parameters of the grating structure from the stable characteristic data to obtain the adjusted digital model;

[0244] According to the corresponding relationship between the adjusted digital model and the black-and-white grating, obtain the final distribution data of the high-precision model, and determine the optimized value of the combined parameters;

[0245] By comparing the final distribution data with the initial digital generation data, judge the matching degree of the grating structure to the auxiliary design, and obtain the optimized model accuracy;

[0246] Adopt the interaction data of the optimized model accuracy and the structural parameters to generate the complete digital model of the black-and-white film grating, and determine the final design result.

[0247] Furthermore, the process of predicting the moiré fringe performance at different viewing distances and viewing angles includes:

[0248] Obtain the initial distribution characteristic data of the grating period and the horizontal grating pitch through the digital model, and determine the range of feature extraction;

[0249] Use the machine learning algorithm to analyze the initial distribution characteristic data to obtain the structural rule data after feature extraction;

[0250] According to the structural rule data, combined with multi-dimensional parameter optimization, judge the distribution influence of the viewing distance change and the viewing angle change;

[0251] Through the distribution influence data, predict the preliminary performance data of the moiré fringe at different viewing distances;

[0252] Adopt the preliminary performance data, combined with the characteristics of the viewing angle change, to obtain the complete prediction distribution of the moiré fringe;

[0253] By comparing the complete prediction distribution with the initial distribution characteristic data, determine the adjustment value of the parameter optimization;

[0254] Update the digital model according to the adjustment value to obtain the optimized distribution characteristic data.

[0255] Furthermore, the process of obtaining the verification result data includes:

[0256] Generate distribution characteristic data of the grating period and the horizontal grating pitch through the analog display screen to obtain initial distribution data;

[0257] According to the initial distribution data, use the support vector machine algorithm to analyze the distribution characteristics and obtain the structural data after feature extraction;

[0258] Combine the structural data with the preset viewing distance to judge the change trend of the moiré fringes and obtain the change trend data;

[0259] If the change trend data exceeds the preset threshold, generate new distribution characteristic data by adjusting the grating period and obtain the adjusted distribution data;

[0260] According to the adjusted distribution data, use the clustering algorithm to analyze the matching degree between the moiré fringes and the preset threshold to obtain the matching result data;

[0261] Combine the matching result data with the display screen parameters to judge whether the verification result meets the conditions and obtain the final verification data;

[0262] According to the final verification data, use statistical tools to analyze the stability of the feature distribution and obtain the optimized distribution data.

[0263] Furthermore, the process of obtaining the cylindrical lens design scheme includes:

[0264] If the verification result data indicates that the moiré fringes are smaller than the preset threshold, calculate the curvature parameter and the spacing parameter of the cylindrical lens according to the distribution characteristics of the grating period and the horizontal grating pitch to obtain the first design scheme data;

[0265] Combine the first design scheme data with the initial position of the color filter to obtain the relative position data between the cylindrical lens and the color filter;

[0266] According to the relative position data, use the clustering algorithm to analyze the matching degree between the cylindrical lens and the grating period to obtain the first matching result data;

[0267] Among them, if the first matching result data exceeds the preset range, adjust the distance between the color filter and the grating, recalculate the distribution characteristics, and obtain the second design scheme data;

[0268] Through the second design scheme data, obtain the distribution data of the adjusted curvature parameter and spacing parameter;

[0269] According to the distribution data, use statistical tools to analyze the stability of the cylindrical lens design scheme and obtain the optimized design parameter data;

[0270] Through the optimized design parameter data, judge the compatibility between the cylindrical lens and the grating period to obtain the final compatibility data.

[0271] Further, the process of obtaining the cylindrical lens design solution further includes:

[0272] If the verification result data indicates that the Moiré fringes are greater than a preset threshold, adjust the distance between the grating and the color filter, recalculate the grating period and the horizontal grating pitch, and obtain the adjusted design parameters;

[0273] Specifically, in S100, adjust the distance between the grating and the color filter, and the specific adjustment amount is quantitatively calculated according to the degree of exceeding the standard of the Moiré fringes;

[0274] In S200, according to the adjusted distance, recalculate the grating period and the horizontal grating pitch, and obtain the adjusted design parameters. An error analysis model is introduced in the calculation process to evaluate the impact of the adjustment on the Moiré fringes;

[0275] In S300, based on the adjusted design parameters, use a multi-dimensional parameter optimization algorithm to comprehensively consider factors such as viewing distance, viewing angle, and pixel arrangement, and further optimize the grating period and the horizontal grating pitch to reduce the Moiré fringes;

[0276] In S400, by simulating the distribution characteristics of the grating period and the horizontal grating pitch at the preset viewing distance of the display screen, determine again whether the Moiré fringes are less than the preset threshold, and obtain new verification result data;

[0277] If the Moiré fringes are still greater than the preset threshold, then according to the new verification result data, further adjust the distance between the grating and the color filter, and repeat the above steps S100 to S400 until the Moiré fringes meet the requirements;

[0278] It further includes establishing a dynamic adjustment mechanism to monitor the change trend of the Moiré fringes in real time, and dynamically adjust the distance between the grating and the color filter according to the real-time data to ensure that the Moiré fringes are always within a controllable range;

[0279] Record the distance adjusted each time, the calculated design parameters, and the change trend of the Moiré fringes, and use a data analysis tool to analyze the rules in the adjustment process.

[0280] Further, the process of obtaining the set of matching parameters includes:

[0281] Regarding the correlation between the design parameters and the grating period, obtain the distribution data of the sub-pixel arrangement and the microlens unit;

[0282] Through the distribution data, use a dynamic matching algorithm to calculate the preliminary matching parameters of the grating period and the microlens unit;

[0283] Through the preliminary matching parameters, combine the preset viewing distance and the pixel length and width to obtain the adjustment data of the arrangement characteristics;

[0284] Based on the adjustment data, judge the adaptability between the grating period and the microlens unit to obtain the adaptability parameter. If the adaptability parameter exceeds the preset threshold, adjust the arrangement mode of the microlens unit through the characteristic data to obtain the updated matching parameter;

[0285] Through the updated matching parameter, obtain the distribution characteristic data of the grating period and the microlens unit;

[0286] According to the distribution characteristic data, use statistical tools to analyze the stability of the matching parameter to obtain the optimized parameter set;

[0287] Through the optimized parameter set, judge the dynamic matching degree between the sub-pixel arrangement and the grating period to obtain the final matching data;

[0288] For the final matching data, use the clustering algorithm to analyze the correlation between the design parameter and the arrangement characteristic to obtain the verification parameter set;

[0289] Through the verification parameter set, determine the final adaptation scheme between the grating period and the microlens unit to obtain the complete matching parameter set.

[0290] In one embodiment, the process of obtaining the matching parameter set can be as follows:

[0291] According to the adjusted design parameters, such as the sub-pixel arrangement is RGB stripe type, the preset viewing distance is 600mm, and the pixel length and width are 0.1mm×0.3mm, obtain the initial distribution data of the grating period and the microlens unit arrangement to obtain the preliminary characteristic set, including the grating period is 0.15mm and the microlens unit spacing is 0.05mm;

[0292] Through the preliminary characteristic set, use the dynamic matching algorithm, such as the least squares method, to calculate the correlation parameter between the grating period and the microlens unit to obtain the preliminary matching parameter, including the matching error is 0.02mm;

[0293] According to the preliminary matching parameter, combined with the interaction data of the preset viewing distance and the pixel length and width, obtain the adjustment data of the arrangement characteristic to obtain the adaptability parameter, such as the adaptability score is 85. If the adaptability parameter exceeds the preset threshold of 90, update the arrangement mode of the microlens unit through the adjustment data, such as adjusting the microlens unit spacing to 0.048mm, to obtain the updated matching parameter;

[0294] Through the updated matching parameter, obtain the distribution characteristic data of the grating period and the microlens unit to obtain the characteristic stability data, such as the standard deviation is 0.01mm;

[0295] According to the feature stability data, statistical tools such as analysis of variance are used to analyze the distribution law of matching parameters, and an optimized parameter set is obtained, including a grating period of 0.148 mm and a micro-lens unit pitch of 0.048 mm;

[0296] Based on the optimized parameter set, the dynamic matching degree between the sub-pixel arrangement and the grating period is judged, and the final matching data is obtained, such as a matching error of 0.01 mm;

[0297] According to the final matching data, clustering algorithms such as K-means clustering are used to analyze the correlation between design parameters and arrangement features, and a verification parameter set is obtained, including a clustering center of 0.148 mm;

[0298] Based on the verification parameter set, the final adaptation scheme between the grating period and the micro-lens unit is determined, and a complete matching parameter set is obtained, including a grating period of 0.148 mm and a micro-lens unit pitch of 0.048 mm.

[0299] Furthermore, the process of obtaining the optimized arrangement data includes:

[0300] The distribution data of the grating period and the micro-lens unit are obtained through the matching parameter set, and preliminary arrangement features are obtained;

[0301] The distribution data of the micro-lens unit are adjusted according to the preliminary arrangement features to obtain adjusted feature data;

[0302] Whether the image blur degree is lower than a preset threshold is judged through the adjusted feature data to obtain a blur judgment result. If the blur judgment result is lower than the preset threshold, the matching parameters are updated through the distribution data to obtain an updated parameter set;

[0303] The feature data adapted to the grating period and the unit are obtained through the updated parameter set to obtain adaptability parameters;

[0304] The stability of the arrangement features is analyzed according to the adaptability parameters by using statistical tools to obtain optimized arrangement data;

[0305] The matching degree between the micro-lens unit and the grating period is judged through the optimized arrangement data to obtain the final distribution features.

[0306] In one embodiment, the process of obtaining the optimized arrangement data may be as follows:

[0307] The distribution data of a grating period of 500 nm and the micro-lens unit are obtained through the matching parameter set, and the spatial frequency is analyzed by using the Fourier transform algorithm to obtain preliminary arrangement features;

[0308] According to the preliminary arrangement characteristics, adjust the distribution data of the microlens units, optimize the unit spacing to 10 μm using the least squares method, and obtain the adjusted characteristic data;

[0309] Based on the adjusted characteristic data, use the PSF (point spread function) model to calculate the image blurriness, judge whether it is lower than the preset threshold of 0.05, and obtain the blurriness judgment result. If the blurriness judgment result is lower than the preset threshold, update the matching parameters through the distribution data, and optimize the parameter set using the gradient descent method to obtain the updated parameter set;

[0310] Based on the updated parameter set, obtain the characteristic data of the grating period matching the microlens units, analyze the adaptability using the correlation coefficient, and obtain the adaptability parameter of 0.92;

[0311] According to the adaptability parameter, use Monte Carlo simulation to analyze the stability of the arrangement characteristics and obtain the optimized arrangement data;

[0312] Based on the optimized arrangement data, obtain the distribution characteristics of the sub-pixel arrangement and the microlens units, and calculate the preliminary matching parameters using the dynamic matching algorithm;

[0313] According to the preliminary matching parameters, combined with the preset viewing distance of 50 cm and the pixel length and width of 1.2 μm, adjust the distribution characteristics to obtain the updated matching data;

[0314] Based on the updated matching data, use the K-means clustering algorithm to analyze the correlation between the design parameters and the arrangement characteristics, and obtain the verification parameter set.

[0315] Further, the process of determining the final design scheme includes:

[0316] Generate a digital model of the cylindrical lens grating through the optimized arrangement data to obtain the complete model structure data. Extract the curvature parameters, spacing parameters, and arrangement parameters from the model structure data to obtain the key characteristic parameter set;

[0317] Use a statistical analysis tool to calculate the distribution characteristics of the key characteristic parameter set to obtain the distribution characteristic data. Judge the matching degree between the cylindrical lens and the grating structure through the distribution characteristic data to obtain the matching evaluation result. If the matching evaluation result is lower than the preset threshold, update the arrangement data through the key characteristic parameter set to obtain the adjusted arrangement data;

[0318] Regenerate the digital model through the adjusted arrangement data to obtain the optimized model structure data;

[0319] Determine the final design scheme according to the optimized model structure data to obtain the final distribution parameters.

[0320] In one embodiment, the process of determining the final design solution may be as follows:

[0321] Using the optimized layout data, a digital model of the lenticular grating is generated by the ray tracing algorithm, and the model structure data includes parameters such as a lens curvature radius of 0.5 mm and a pitch of 0.2 mm;

[0322] Extract the curvature parameter range of 0.45 - 0.55 mm, the pitch parameter range of 0.18 - 0.22 mm, and the periodic layout parameters from the model structure data to form a set of key characteristic parameters;

[0323] Perform statistical analysis on the set of key characteristic parameters using Monte Carlo simulation, and calculate distribution characteristic data such as a curvature standard deviation of 0.02 mm and a pitch coefficient of variation of 5%;

[0324] By comparing the distribution characteristic data with a preset grating period of 0.21 mm, calculate a matching degree evaluation value of 0.85. If the matching degree evaluation value is lower than the threshold of 0.9, use a parameter optimization algorithm to adjust the key characteristic parameters to generate new layout data with a pitch of 0.19 mm and a curvature of 0.52 mm;

[0325] Based on the adjusted layout data, use finite element analysis to reconstruct the digital model and obtain an optimized lens array structure;

[0326] Extract the updated curvature parameter of 0.51 ± 0.01 mm and pitch parameter of 0.195 ± 0.005 mm from the optimized model to form a parameter set with a normal distribution;

[0327] Use the K - means clustering algorithm to perform a matching degree analysis on the parameter set and the grating period of 0.21 mm to obtain adaptation data with a cluster center distance of 0.208 mm;

[0328] According to the analysis results of the adaptation data, determine the parameters of the final design solution as a curvature of 0.51 mm and a pitch of 0.20 mm, and output distribution parameters that meet the grating matching requirements.

[0329] Embodiment 3

[0330] As Figure 3 shown, this embodiment provides a simulation system for a naked - eye 3D grating, including:

[0331] A measurement module for obtaining angle data when the sub - pixel arrangement of the LED display screen forms a small Moiré fringe with the grating through instrument measurement, and recording the sub - pixel arrangement parameters and the changing trend of the Moiré fringe;

[0332] A calculation module, configured to calculate the grating period and horizontal grating pitch of the film grating according to the sub-pixel arrangement parameters, preset viewing distance, pixel length and width, and the initial distance between the grating and the color filter, so as to obtain preliminary design parameters;

[0333] A design module, configured to generate a high-precision digital model of the black-and-white film grating by using the calculated preliminary design parameters in combination with an artificial intelligence-aided design algorithm;

[0334] An analysis module, configured to intelligently extract and analyze the distribution characteristics of the grating period and horizontal grating pitch through the digital model by using a machine learning algorithm, and at the same time introduce multi-dimensional parameter optimization to predict the moiré fringe performance at different viewing distances and viewing angles;

[0335] A verification module, configured to determine whether the moiré fringe is less than a preset threshold by simulating the distribution characteristics of the grating period and horizontal grating pitch at the preset viewing distance of the display screen, so as to obtain verification result data;

[0336] An adjustment module, configured to, if the verification result data indicates that the moiré fringe is greater than the preset threshold, adjust the distance between the grating and the color filter, recalculate the grating period and horizontal grating pitch, and obtain the adjusted design parameters;

[0337] A matching module, configured to establish a dynamic matching algorithm for the grating period and the arrangement of microlens units based on the adjusted design parameters, sub-pixel arrangement, preset viewing distance, and pixel length and width, so as to obtain a set of matching parameters;

[0338] An optimization module, configured to optimize the arrangement characteristics of the grating and the microlens units through the set of matching parameters, determine whether the image blur degree is lower than the preset threshold, and obtain the optimized arrangement data;

[0339] A generation module, configured to generate a final cylindrical lens grating digital model according to the optimized arrangement data, extract the curvature, spacing, and arrangement parameters from the digital model, and determine the final design scheme.

[0340] The specific embodiments of the invention have been described in detail above, but they are only examples, and the invention is not limited to the specific embodiments described above. Those skilled in the art should understand that the above embodiments and the descriptions in the specification only illustrate the principles of the invention. Without departing from the spirit and scope of the invention, the invention will have various changes and improvements, and these changes and improvements all fall within the scope of the invention claimed. The scope of the invention claimed is defined by the appended claims and their equivalents.

Claims

1. A simulation method for a naked-eye 3D grating, characterized in that, It includes the following steps: Obtain the angular data when the Moiré fringes formed by the sub-pixel arrangement of the LED display screen and the grating are relatively small through instrument measurement, and record the sub-pixel arrangement parameters and the change trend of the Moiré fringes; Calculate the grating period and horizontal grating pitch of the film grating according to the sub-pixel arrangement parameters, preset viewing distance, pixel length and width, and the initial distance between the grating and the color filter to obtain preliminary design parameters; Adopt the calculated preliminary design parameters and combine with the artificial intelligence-aided design algorithm to generate a high-precision digital model of the black-and-white film grating; Through this digital model, intelligently extract and analyze the distribution characteristics of the grating period and horizontal grating pitch, and at the same time introduce multi-dimensional parameter optimization to predict the Moiré fringe performance under different viewing distances and viewing angles; By simulating the distribution characteristics of the grating period and horizontal grating pitch under the preset viewing distance of the display screen, judge whether the Moiré fringes are less than the preset threshold to obtain verification result data; Adjust the design parameters according to the verification result data to obtain a lenticular lens design scheme; After the step of obtaining the verification result data, it further includes: Based on the adjusted design parameters, sub-pixel arrangement, preset viewing distance, and pixel length and width, establish a dynamic matching algorithm for the grating period and the arrangement of microlens units to obtain a set of matching parameters; Optimize the arrangement characteristics of the grating and microlens units through the set of matching parameters, judge whether the image blurring degree is lower than the preset threshold, and obtain the optimized arrangement data; Generate the final lenticular lens grating digital model according to the optimized arrangement data, extract the curvature, spacing, and arrangement parameters from the digital model, and determine the final design scheme.

2. The simulation method of a naked-eye 3D grating according to claim 1, wherein The process of recording the sub-pixel arrangement parameters and the change trend of the Moiré fringes includes: Collect the angular data when the sub-pixel arrangement and the grating structure interact to form Moiré fringes through an instrument to obtain the initial measurement value; Extract the arrangement parameters and the characteristic data of the grating structure from the initial measurement value to determine the conditions for fringe formation; If the fringe formation conditions meet the preset threshold, analyze the relationship between the angular data and the arrangement parameters through an algorithm to judge the direction of the change trend; Adopt the support vector machine algorithm to classify the direction of the change trend to obtain the stable characteristics of the trend; Compare the morphological data of the Moiré fringes through the stable characteristics of the trend to determine the corresponding relationship between the fringes and the sub-pixel arrangement; Process the measurement results according to the corresponding relationship to obtain the mapping data of the sub-pixel arrangement parameters and the fringe change trend; Extract the key features from the mapping data to judge the influence degree of the display screen characteristics on the Moiré fringes.

3. A simulation method for a naked-eye 3D grating according to claim 1, characterized in that The process of calculating the grating period and horizontal grating pitch of the film grating to obtain the preliminary design parameters includes: Obtain the initial distribution data of the grating structure through the corresponding relationship between the sub-pixel arrangement and the pixel length and width to obtain the preliminary calculation result of the grating period; Adjust the change range of the grating period according to the interaction data between the preset viewing distance and the initial distance to determine the boundary value of the horizontal grating pitch; Analyze the distribution law of the horizontal grating pitch by using the grating pitch characteristics to obtain the stable characteristic data of the distribution law; Adopt the support vector machine algorithm to classify the stable characteristic data to judge the matching degree between the grating period and the grating pitch characteristics; If the matching degree exceeds the preset threshold, extract the optimized parameters of the grating structure from the classification result to obtain the adjusted design parameters; Obtain the final calculated value of the grating period according to the corresponding relationship between the adjusted design parameters and the distribution law; Judge the adaptability of the grating structure to the sub-pixel arrangement by comparing the final calculated value with the initial distribution data, and obtain the optimized pitch distribution.

4. A simulation method of a naked-eye 3D grating according to claim 1, characterized in that, The process of generating the high-precision digital model of the black-and-white film grating includes: Obtain the initial digital generation data of the black-and-white grating through the corresponding relationship between the preliminary parameters and the combined parameters, and obtain the preliminary distribution of the grating structure; According to the interaction data between the grating structure and the design algorithm, adopt the auxiliary design to adjust the change range of the digital generation, and determine the boundary value of the high-precision model; Generate the distribution law of the analysis digital model through the algorithm, obtain the stable characteristic data of the model accuracy, and judge the adaptability of the structural parameters; If the model accuracy exceeds the preset threshold, extract the optimized parameters of the grating structure from the stable characteristic data to obtain the adjusted digital model; According to the corresponding relationship between the adjusted digital model and the black-and-white grating, obtain the final distribution data of the high-precision model, and determine the optimized value of the combined parameters; Judge the matching degree of the grating structure to the auxiliary design by comparing the final distribution data with the initial digital generation data, and obtain the optimized model accuracy; Adopt the interaction data of the optimized model accuracy and the structural parameters to generate the complete digital model of the black-and-white film grating, and determine the final design result.

5. A simulation method for a naked-eye 3D grating according to claim 1, characterized in that The process of predicting the moiré fringe performance at different viewing distances and viewing angles further includes: Obtain the initial distribution characteristic data of the grating period and the horizontal pitch through the digital model, and determine the range of feature extraction; Adopt the machine learning algorithm to analyze the initial distribution characteristic data to obtain the structural rule data after feature extraction; According to the structural rule data, combined with multi-dimensional parameter optimization, judge the distribution influence of the viewing distance change and the viewing angle change; Predict the preliminary performance data of the moiré fringe at different viewing distances through the distribution influence data; Adopt the preliminary performance data, combined with the characteristics of the viewing angle change, to obtain the complete prediction distribution of the moiré fringe; Determine the adjustment value of the parameter optimization by comparing the complete prediction distribution with the initial distribution characteristic data; Update the digital model according to the adjustment value to obtain the optimized distribution characteristic data.

6. A simulation method of a naked-eye 3D grating according to claim 1, characterized in that The process of obtaining the verification result data includes: Generate the distribution characteristic data of the grating period and the horizontal pitch through the simulated display screen to obtain the initial distribution data; According to the initial distribution data, adopt the support vector machine algorithm to analyze the distribution characteristics to obtain the structural data after feature extraction; Judge the change trend of the moiré fringe by combining the structural data with the preset viewing distance to obtain the change trend data; If the change trend data exceeds the preset threshold, generate new distribution characteristic data by adjusting the grating period to obtain the adjusted distribution data; According to the adjusted distribution data, adopt the clustering algorithm to analyze the matching degree between the moiré fringe and the preset threshold to obtain the matching result data; Judge whether the verification result meets the conditions by combining the matching result data with the display screen parameters to obtain the final verification data; According to the final verification data, adopt the statistical tool to analyze the stability of the feature distribution to obtain the optimized distribution data.

7. A simulation method of a naked-eye 3D grating according to claim 1, characterized in that The process of obtaining the cylindrical lens design scheme includes: If the verification result data indicates that the moiré fringes are smaller than the preset threshold, calculate the curvature parameter and spacing parameter of the cylindrical lens based on the distribution characteristics of the grating period and the horizontal grating pitch to obtain the first design scheme data; Obtain the relative position data between the cylindrical lens and the color filter by combining the first design scheme data with the initial position of the color filter; According to the relative position data, analyze the matching degree between the cylindrical lens and the grating period by using a clustering algorithm to obtain the first matching result data; Among them, if the first matching result data exceeds the preset range, adjust the distance between the color filter and the grating, recalculate the distribution characteristics, and obtain the second design scheme data; Through the second design scheme data, obtain the distribution data of the adjusted curvature parameter and spacing parameter; According to the distribution data, analyze the stability of the cylindrical lens design scheme by using a statistical tool to obtain the optimized design parameter data; Judge the adaptability between the cylindrical lens and the grating period through the optimized design parameter data to obtain the final adaptation data.

8. A simulation method of a naked-eye 3D grating according to claim 7, characterized in that, The process of obtaining the cylindrical lens design scheme further includes: If the verification result data indicates that the moiré fringes are larger than the preset threshold, adjust the distance between the grating and the color filter, recalculate the grating period and the horizontal grating pitch, and obtain the adjusted design parameters; Specifically, S100. Adjust the distance between the grating and the color filter, and the specific adjustment amount is quantitatively calculated according to the exceeding degree of the moiré fringes; S200. According to the adjusted distance, recalculate the grating period and the horizontal grating pitch, obtain the adjusted design parameters, introduce an error analysis model during the calculation process, and evaluate the impact of the adjustment on the moiré fringes; S300. Based on the adjusted design parameters, use a multi-dimensional parameter optimization algorithm to comprehensively consider factors such as viewing distance, viewing angle, and pixel arrangement to further optimize the grating period and the horizontal grating pitch to reduce moiré fringes; S400. By simulating the distribution characteristics of the grating period and the horizontal grating pitch at the preset viewing distance of the display screen, determine again whether the moiré fringes are smaller than the preset threshold to obtain new verification result data; If the moiré fringes are still larger than the preset threshold, further adjust the distance between the grating and the color filter according to the new verification result data, and repeat the above steps S100-S400 until the moiré fringes meet the requirements; It also includes establishing a dynamic adjustment mechanism to monitor the change trend of the moiré fringes in real time, and dynamically adjust the distance between the grating and the color filter according to the real-time data to ensure that the moiré fringes are always within the controllable range; Record the distance adjusted each time, the calculated design parameters, and the change trend of the moiré fringes, and use a data analysis tool to analyze the rules in the adjustment process.

9. A simulation system for a naked-eye 3D grating, which is used to implement the above-mentioned simulation method for a naked-eye 3D grating, is characterized in that, It includes: A measurement module for obtaining angle data when the sub-pixel arrangement of the LED display screen forms relatively small moiré fringes with the grating through instrument measurement, and recording the sub-pixel arrangement parameters and the change trend of the moiré fringes; A calculation module for calculating the grating period and the horizontal grating pitch of the film grating according to the sub-pixel arrangement parameters, the preset viewing distance, the pixel length and width, and the initial distance between the grating and the color filter to obtain the preliminary design parameters; A design module, which is used to generate a high-precision digital model of a black-and-white film grating by using the calculated preliminary design parameters and combining with an artificial intelligence-aided design algorithm; An analysis module, which is used to intelligently extract and analyze the distribution characteristics of the grating period and the horizontal grating pitch through this digital model by using a machine learning algorithm, and at the same time introduce multi-dimensional parameter optimization to predict the moiré fringe performance at different viewing distances and viewing angles; A verification module, which is used to judge whether the moiré fringe is less than a preset threshold by simulating the distribution characteristics of the grating period and the horizontal grating pitch at the preset viewing distance of the display screen, and obtain verification result data; An adjustment module, which is used to adjust the distance between the grating and the color filter if the verification result data indicates that the moiré fringe is greater than the preset threshold, recalculate the grating period and the horizontal grating pitch, and obtain the adjusted design parameters; A matching module, which is used to establish a dynamic matching algorithm for the grating period and the arrangement of microlens units based on the adjusted design parameters, sub-pixel arrangement, preset viewing distance and pixel length and width, and obtain a set of matching parameters; An optimization module, which is used to optimize the arrangement characteristics of the grating and the microlens units through the set of matching parameters, judge whether the image blurring degree is lower than the preset threshold, and obtain the optimized arrangement data; A generation module, which is used to generate a final lenticular grating digital model according to the optimized arrangement data, extract curvature, spacing and arrangement parameters from the digital model, and determine the final design scheme.

Images