Liquid crystal panel aging test method and system

Abstract

The invention relates to the technical field of panel testing, in particular to a liquid crystal panel aging test method and system. The method comprises the following steps: acquiring a liquid crystal panel display interface; performing dynamic image display on the liquid crystal panel display interface to generate a liquid crystal panel dynamic image display interface; performing a liquid crystal panel dynamic image display aging test on the liquid crystal panel dynamic image display interface based on preset operation display time to generate a first sequence test result of the liquid crystal panel; performing display aging evaluation on the display change analysis data of the liquid crystal panel based on the first sequence test result of the liquid crystal panel to generate display aging evaluation data of the liquid crystal panel; according to the first sequence test result of the liquid crystal display panel, a temperature and humidity cyclic change test is conducted on the display interface of the liquid crystal display panel, and a second sequence test result of the liquid crystal display panel is generated. Dynamic display, temperature and humidity change test, multi-dimensional evaluation, regional difference analysis and an intelligent evaluation model are introduced, so that the test precision and comprehensiveness are improved.

Description

Technical Field

[0001] The present invention relates to the field of panel testing technology, and in particular to a liquid crystal panel aging test method and system. Background Art

[0002] Early LCD panel aging tests mainly relied on manual observation and simple accelerated aging methods, such as testing in high temperature and high humidity environments. Although these methods can accelerate the aging process of LCD panels, they lack precise test standards and repeatability, and cannot effectively simulate the aging conditions in actual use. With the development of display technology, aging test methods have gradually developed in the direction of automation and digitization. In the 1990s, electronic measuring instruments began to be introduced into LCD panel test equipment. Through automated test systems, performance indicators such as panel brightness, color deviation, and contrast can be more accurately monitored, reducing human errors and improving test efficiency and reliability. After entering the 21st century, the aging test of LCD panels has further developed towards intelligent and multi-dimensional evaluation. Combined with computer vision, machine learning, and big data analysis technology, modern aging test methods not only focus on the surface performance of the panel, but also analyze the pixel-level changes of the panel and predict its service life. The application of these technologies enables aging tests to be closer to the actual use environment and provide more scientific evaluation. However, the current LCD panel aging tests in the existing technology often rely on static test images or simple accelerated aging tests, which cannot fully simulate the dynamic image display in actual use. At the same time, traditional aging tests are difficult to independently evaluate the differences in different areas of the LCD panel, and usually can only provide overall aging data, which leads to low test accuracy and comprehensiveness. Summary of the invention

[0003] Based on this, it is necessary to provide a liquid crystal panel aging test method and system to solve at least one of the above technical problems.

[0004] To achieve the above object, a liquid crystal panel aging test method is provided, the method comprising the following steps:

[0005] Step S1: obtaining a liquid crystal panel display interface; performing a dynamic image display on the liquid crystal panel display interface to generate a liquid crystal panel dynamic image display interface; performing a liquid crystal panel dynamic image display aging test on the liquid crystal panel dynamic image display interface based on a preset running display time to generate a first-order test result of the liquid crystal panel; performing a display aging evaluation on the liquid crystal panel display change analysis data based on the first-order test result of the liquid crystal panel to generate liquid crystal panel display aging evaluation data;

[0006] Step S2: performing a temperature and humidity cycle change test on the display interface of the liquid crystal panel according to the first sequence test results of the liquid crystal panel to generate a second sequence test result of the liquid crystal panel; performing a thermal management evaluation on the second sequence test result of the liquid crystal panel to generate thermal management aging evaluation data of the liquid crystal panel;

[0007] Step S3: Perform model training on the LCD panel display aging evaluation data and the LCD panel thermal management aging evaluation data to generate an LCD panel aging status evaluation model; import the LCD panel first-order test results and the LCD panel second-order test results into the LCD panel aging status evaluation model to perform aging status evaluation to generate the LCD panel global aging status evaluation data; perform panel area aging independent difference evaluation on the LCD panel according to the LCD panel aging status evaluation data to generate panel area aging local difference evaluation data; visualize the aging data of the LCD panel global aging status evaluation data and the panel area aging local difference evaluation data to perform the LCD panel aging test evaluation operation.

[0008] The present invention can more realistically simulate the display effect and aging process of the liquid crystal panel in actual use by introducing dynamic image display and aging test based on preset running time, avoid the limitations of traditional static test, and improve the accuracy and authenticity of the test. The generation of display aging evaluation data is helpful to fully understand the performance degradation of the liquid crystal panel in actual application and ensure product quality. On the basis of the display aging test of the liquid crystal panel, a temperature and humidity cycle change test is added, and a thermal management evaluation is performed. This step can effectively simulate the aging of the liquid crystal panel under various environmental changes, comprehensively consider the influence of temperature, humidity and thermal management on the performance of the panel, thereby improving the comprehensiveness and practicality of the test, and providing a more scientific basis for the reliability evaluation of the liquid crystal panel. By training the display aging evaluation data and the thermal management aging evaluation data, a liquid crystal panel aging state evaluation model is generated, and the overall aging trend of the panel can be scientifically predicted. The first and second order test results of the liquid crystal panel are imported into the evaluation model to generate global aging state evaluation data, which provides an accurate basis for the long-term stability and performance degradation prediction of the liquid crystal panel. At the same time, regional difference evaluation helps to detect the aging of the local area of ​​the panel and improve the evaluation accuracy and pertinence. Visualizing the global aging status assessment data and the local area aging difference assessment data not only makes the aging test results more intuitive and easy to understand, but also facilitates the rapid identification of potential problem areas in practical applications, guides subsequent quality improvements or design optimization, and improves the efficiency and accuracy of aging test assessment operations. Therefore, the present invention improves the accuracy and comprehensiveness of the test by introducing dynamic display, temperature and humidity change testing, multi-dimensional evaluation, regional difference analysis, and intelligent evaluation models.

[0009] Preferably, step S1 comprises the following steps:

[0010] Step S11: obtaining a liquid crystal panel display interface;

[0011] Step S12: randomly generating a dynamic image sequence for the liquid crystal panel display interface to obtain a dynamic image random sequence; performing dynamic image display on the liquid crystal panel display interface according to the dynamic image random sequence to generate a liquid crystal panel dynamic image display interface;

[0012] Step S13: performing a liquid crystal panel display change analysis on the liquid crystal panel dynamic image display interface based on a preset running display time, and generating liquid crystal panel display change analysis data, wherein the liquid crystal panel display change analysis includes color shift, brightness attenuation and response time;

[0013] Step S14: using the LCD panel display change analysis data to perform an LCD panel dynamic image display aging test on the LCD panel dynamic image display interface to generate a first-order test result of the LCD panel; based on the first-order test result of the LCD panel, performing a display aging evaluation on the LCD panel display change analysis data to generate an LCD panel display aging evaluation data.

[0014] The present invention can better simulate the real use scenario and provide a more comprehensive display performance test by randomly generating a dynamic image sequence and displaying it on a liquid crystal panel. This helps to evaluate the display effect of the liquid crystal panel under various dynamic contents and improve the authenticity and comprehensiveness of the test. By analyzing factors such as color shift, brightness decay and response time of the display interface, the performance of the liquid crystal panel after long-term use can be deeply understood. This enables more detailed and accurate data support to be obtained when performing quality control and life prediction of the liquid crystal panel. The display aging of the liquid crystal panel is one of the key factors affecting its long-term performance and reliability. By performing an aging test on the display change analysis data of the liquid crystal panel, the durability of the panel and the speed of performance decay can be effectively evaluated, thereby providing a basis for product optimization and design improvement. The display aging evaluation based on the first order test results provides important data support for the reliability and life cycle of the product. This helps manufacturers better understand the service life of the product, predict its performance problems, and take appropriate measures in the product design and production process to improve the stability and market competitiveness of the product.

[0015] Preferably, randomly generating a dynamic image sequence for a liquid crystal panel display interface includes:

[0016] Constructing an image material library; performing image enhancement on images in the image material library to obtain an image enhancement material library, wherein the image enhancement includes color correction, blur processing, and reflected light simulation;

[0017] Perform image label classification on the image enhancement material library to generate label images, and set the material generation probability for the label images to obtain probabilistic label images; set the sequence time length for the probabilistic label images to generate the probabilistic label image duration;

[0018] Based on the duration of the probability label images, random image selection is performed on the probability label images to generate the law of image content change; a random number generator is used to combine the image display order of the probability label images according to the law of image content change, thereby generating a random sequence of dynamic images.

[0019] The present invention provides a rich original image material for generating a dynamic image sequence by constructing an image material library, ensuring that the test covers a wide range of display scenarios. This can simulate different types of content and display effects in practical applications, and comprehensively evaluate the performance of liquid crystal panels under various usage conditions. Through image enhancement technologies such as color correction, blur processing and reflected light simulation, the quality and diversity of image materials can be effectively improved. These enhancement technologies can simulate display effects (such as color distortion, illumination changes, etc.) under different environments and conditions, enhance the practical significance of test results, and make them closer to display effects in practical applications. By labeling and classifying images and setting material generation probabilities, display sequences that are more in line with specific needs can be generated according to different types of image content. Through this classification, it can be ensured that images of different categories are combined and displayed according to a predetermined probability, thereby more accurately simulating the dynamic display performance of liquid crystal panels under different conditions. By setting the duration of image display, the display time of each image in the dynamic image sequence can be accurately controlled to simulate the fluency and response speed in the actual display process. This helps to evaluate the performance of liquid crystal panels under different display durations, especially the test of response time and transition effects. By using a random number generator to generate random image selection and display order based on the temporal pattern of the probabilistic label image, it is possible to ensure that the image sequence for each test is not exactly the same, thereby simulating a wider range of dynamic display scenarios. This randomness enhances the comprehensiveness of the test, avoids the monotony of the image display order, and improves the randomness and representativeness of the test. Through this series of steps, the generated dynamic image sequence can better reflect the display effect in the real usage scenario. This helps to comprehensively evaluate key factors such as display effect, color accuracy, response time, etc. when conducting dynamic performance tests on LCD panels, and provides data support for the optimization and upgrade of LCD panels.

[0020] Preferably, step S2 comprises the following steps:

[0021] Step S21: performing a temperature and humidity cycle change test on the display interface of the liquid crystal panel according to the first sequence test result of the liquid crystal panel to generate a second sequence test result of the liquid crystal panel;

[0022] Step S22: performing extreme test temperature screening on the second order test results of the liquid crystal panel to obtain extreme test temperature data; performing liquid crystal panel temperature distribution analysis on the liquid crystal panel display interface based on the extreme test temperature data to generate liquid crystal panel extreme temperature distribution data;

[0023] Step S23: performing heat diffusion analysis on the display interface of the liquid crystal panel according to the extreme temperature distribution data of the liquid crystal panel, and generating liquid crystal panel display heat diffusion data;

[0024] Step S24: Performing thermal management evaluation using the liquid crystal panel extreme temperature distribution data and the liquid crystal panel display heat diffusion data to generate liquid crystal panel thermal management aging evaluation data.

[0025] The present invention can simulate the temperature and humidity changes of the liquid crystal panel in the actual use environment by performing a temperature and humidity cycle change test according to the first order test results, and evaluate the stability and reliability of the liquid crystal panel under different environmental conditions. This helps to discover temperature-related problems of the liquid crystal panel in advance, such as color distortion, brightness attenuation, etc. By screening the performance of the liquid crystal panel under extreme temperature conditions, the extreme performance of the liquid crystal panel under high or low temperature environments can be identified. This screening can help manufacturers understand the adaptability of the liquid crystal panel in harsh environments and ensure that it can operate stably for a long time under extreme temperatures. By analyzing the temperature distribution of the liquid crystal panel under extreme temperatures, the temperature changes of the liquid crystal panel in different areas can be accurately grasped, and the temperature hot spot area can be found. The temperature distribution data provides a basis for subsequent thermal diffusion analysis and thermal management optimization, helping to determine whether the liquid crystal panel has the risk of overheating or thermal runaway. Thermal diffusion analysis can provide an in-depth understanding of the transfer and distribution of heat in the liquid crystal panel at different temperatures. This analysis can reveal whether the heat generated by the liquid crystal panel during operation has been effectively dispersed and managed, and help evaluate the thermal stability and thermal effects of the liquid crystal panel under long-term use. Combining temperature distribution and thermal diffusion data for thermal management evaluation can comprehensively analyze the thermal management capabilities of the liquid crystal panel. Through this assessment, it is possible to determine whether the LCD panel has an effective thermal management design, such as whether the heat dissipation system is sufficient and whether it can avoid overheating or temperature runaway problems, thereby ensuring the long-term stability and performance of the LCD panel. The thermal management aging assessment data provides a more accurate basis for analyzing the aging process of the LCD panel. By understanding the thermal effects of the LCD panel under extreme temperatures, it is possible to predict the thermal aging problems of the LCD panel after long-term use, and provide important guidance for the design optimization and quality control of the LCD panel.

[0026] Preferably, performing a temperature and humidity cycle change test on the display interface of the liquid crystal panel according to the first sequence test result of the liquid crystal panel includes:

[0027] Set up a temperature and humidity control system, and perform high temperature environment setting, high humidity environment setting and low temperature environment setting on the temperature and humidity control system, and perform simulation cycle quantification on the set environment to generate a temperature and humidity control simulation cycle;

[0028] Based on the temperature and humidity control simulation cycle, the LCD panel display interface is subjected to periodic simulation alternating cycles, each cycle is 48 hours, and at least 10 rounds of temperature and humidity cycle tests are completed;

[0029] Under the above-mentioned temperature and humidity cycle test conditions, the panel performance of the LCD panel display interface is measured, and the screen brightness, color, and response time of the LCD panel display interface are simultaneously recorded to generate the second order test results of the LCD panel.

[0030] The present invention can test the performance of the liquid crystal panel under different temperature and humidity conditions by setting high temperature, high humidity and low temperature environments and performing periodic simulation. This simulates the working conditions of the liquid crystal panel in different actual use environments, especially for those liquid crystal panels used in environments with large temperature and humidity changes (such as outdoor display screens, car displays, etc.). The periodic quantitative setting of the temperature and humidity control system and the 48-hour periodic simulation alternating cycle can accurately simulate the temperature and humidity changes experienced by the liquid crystal panel in actual applications. The time length of each cycle and the alternating frequency of the simulation help to evaluate the stability of the liquid crystal panel in long-term use, especially the impact on the durability and life of the liquid crystal panel. During the temperature and humidity cycle test, performance parameters such as brightness, color and response time of the liquid crystal panel are recorded synchronously. This not only helps to evaluate the basic display performance of the liquid crystal panel under different temperature and humidity conditions, but also can deeply analyze the long-term impact of temperature and humidity changes on the display effect of the liquid crystal panel, such as whether there is color shift, brightness attenuation, response hysteresis and other problems. Through multiple rounds of temperature and humidity cycle tests, the durability of the liquid crystal panel after repeated changes in temperature and humidity can be effectively detected. Long-term high temperature, high humidity, and low temperature alternating cycle simulation can reveal the reliability of LCD panels in extreme environments and determine whether they will have structural damage, display failures, screen aging, and other problems. By obtaining the second-order test results of LCD panels, manufacturers can identify potential performance degradation problems of LCD panels during long-term use. These data can provide valuable basis for improving LCD panel design, material selection, and production processes, ensuring that the final product can operate stably in various environments.

[0031] Preferably, performing a liquid crystal panel temperature distribution analysis on a liquid crystal panel display interface using extreme test temperature data includes:

[0032] The panel surface and key areas of the LCD panel display interface are segmented by using extreme test temperature data to generate the LCD panel surface area and the LCD panel key area; the temperature of the LCD panel surface area and the LCD panel key area is scanned by using an infrared thermal imager to obtain a two-dimensional distribution map of the LCD panel area temperature;

[0033] The temperature difference between adjacent areas of the two-dimensional temperature distribution diagram of the LCD panel area is calculated to generate temperature gradient data of adjacent areas; the balance of the panel surface temperature of the LCD panel display interface is evaluated based on the temperature gradient data of adjacent areas to generate extreme temperature distribution data of the LCD panel.

[0034] The present invention uses an infrared thermal imager to perform temperature scanning on the surface area and key areas of the liquid crystal panel, and can obtain a high-precision two-dimensional temperature distribution map. This method can reflect the temperature distribution of the liquid crystal panel in different areas in detail, which is helpful to find potential hot spots and uneven temperature. Ensure that the temperature control and heat dissipation effect of the liquid crystal panel in practical applications meet the design requirements. By performing temperature scanning on key areas of the liquid crystal panel (such as sensitive parts such as power supply and connection line interface), the thermal stress and heat load of the liquid crystal panel in these areas can be accurately monitored. This provides important data support for evaluating the reliability and durability of the liquid crystal panel in high or low temperature environments. By calculating the temperature difference between adjacent areas, the temperature gradient on the surface of the liquid crystal panel can be effectively analyzed. This analysis can reveal the mode and speed of temperature change diffusion on the panel surface, provide a basis for judging the thermal diffusion efficiency and thermal conductivity of the liquid crystal panel, help find areas with excessive temperature differences, and avoid panel damage or performance degradation caused by thermal stress. Based on the temperature gradient data, the surface temperature balance of the liquid crystal panel is evaluated to determine whether the liquid crystal panel maintains a uniform temperature distribution under extreme temperatures. Temperature balance is the key to long-term stable operation of LCD panels. If the temperature in certain areas is too high or too low, it will cause display distortion, accelerated aging, and even panel damage. Therefore, balance assessment helps optimize the thermal management design of LCD panels and improve their long-term performance.

[0035] Preferably, step S23 includes the following steps:

[0036] Step S231: acquiring steady-state temperature data of the liquid crystal panel display interface through the extreme temperature distribution data of the liquid crystal panel to obtain a steady-state test temperature of the liquid crystal panel display interface; discretizing the panel space region of the liquid crystal panel display interface according to the steady-state test temperature of the liquid crystal panel display interface to generate a panel space discretization region;

[0037] Step S232: performing heat diffusion simulation on the panel space discretization area to generate panel area heat diffusion simulation temperature data; performing temperature contour map conversion on the panel area heat diffusion simulation temperature data to generate panel area surface temperature contour map;

[0038] Step S233: Based on the heat conduction equation, the heat diffusion time of the panel area surface temperature contour map is estimated to obtain the panel surface heat diffusion time; wherein the heat conduction equation and the heat diffusion time estimation formula are as follows:

[0039]

[0040] In the formula, It is expressed as a heat conduction equation, α is the thermal diffusion coefficient of the material, is the Laplace operator of temperature, T is the temperature, t is the time, t steady It is represented as the heat diffusion time on the panel surface, and L is the length scale of the panel area;

[0041] Step S234: Identify the heat diffusion area of ​​the LCD panel display interface according to the panel surface heat diffusion time and the panel area surface temperature contour map to generate heat diffusion area identification data; perform heat load concentration area analysis on the heat diffusion area identification data to generate LCD panel display heat diffusion data.

[0042] The present invention acquires steady-state temperature data of the liquid crystal panel through extreme temperature distribution data, and can accurately describe the temperature state of the liquid crystal panel under continuous operation. This step helps determine the temperature stability of the surface of the liquid crystal panel and the thermal effect during long-term operation. The display interface of the liquid crystal panel is spatially discretized, and the panel surface is divided into multiple regions for analysis, which further improves the accuracy of the temperature analysis. Spatial discretization can carefully reflect the temperature changes in different regions, providing a basis for subsequent thermal diffusion simulation and thermal management optimization. By performing thermal diffusion simulation on the spatial discretization area of ​​the panel and generating panel area thermal diffusion simulation temperature data, the heat transfer of the liquid crystal panel in different regions can be simulated. This provides intuitive and accurate data support for evaluating the thermal stability and heat dissipation design of the liquid crystal panel. The temperature contour map conversion helps to visualize the temperature distribution of the panel area, intuitively display the distribution of the surface temperature of the liquid crystal panel, and identify the temperature hot spot area. This is of great significance for further optimizing the thermal management design, reducing heat accumulation and improving the heat dissipation effect. Through the heat conduction equation Estimating the heat diffusion time provides an accurate mathematical model for the heat diffusion process. This model helps evaluate the time required for heat diffusion on the panel surface, thus providing a theoretical basis for designing heat dissipation solutions and improving thermal management. The calculated heat diffusion time (t_steady) can reveal the time required for the surface of the LCD panel to reach a thermal steady state, help predict the thermal stability of the LCD panel after startup, and avoid affecting the display effect of the panel due to heat accumulation. Based on the contour map of the heat diffusion time and temperature on the panel surface, the heat propagation area identification data is generated, which can identify the distribution range of the heat of the LCD panel and its propagation path. This analysis helps to find the heat accumulation area in the panel, and timely measures can be taken to balance the heat. The heat load concentration analysis of the heat propagation area helps identify the area with the most concentrated heat load and provides data support for optimizing the thermal design of the LCD panel. By accurately analyzing the heat load, it is possible to effectively prevent damage to the LCD panel caused by local overheating, such as color distortion, brightness attenuation and other problems.

[0043] Preferably, step S3 comprises the following steps:

[0044] Step S31: collecting historical evaluation data of the liquid crystal panel display aging evaluation data and the liquid crystal panel thermal management aging evaluation data to obtain liquid crystal panel aging evaluation historical data; dividing the liquid crystal panel aging evaluation historical data into data sets to generate a model training set and a model test set;

[0045] Step S32: training the model training set by a recurrent neural network algorithm to generate a pre-model for evaluating the aging state of a liquid crystal panel; optimizing and iterating the pre-model for evaluating the aging state of a liquid crystal panel by using a model test set, thereby generating a liquid crystal panel aging state evaluation model;

[0046] Step S33: importing the first order test results of the liquid crystal panel and the second order test results of the liquid crystal panel into the liquid crystal panel aging state evaluation model to perform aging state evaluation, and generate liquid crystal panel global aging state evaluation data;

[0047] Step S34: Perform independent panel area aging difference evaluation on the LCD panel according to the LCD panel aging status evaluation data to generate panel area aging local difference evaluation data; visualize the aging data of the LCD panel global aging status evaluation data and the panel area aging local difference evaluation data to perform the LCD panel aging test evaluation operation.

[0048] The present invention comprehensively records the aging process of the liquid crystal panel through the collection of historical evaluation data, covering factors such as different working environments, temperature changes and use cycles. This provides a rich source of training data for the subsequent aging state evaluation model. The data set is divided into a training set and a test set, which ensures that the training and verification of the model are based on different data sources, thereby improving the reliability and generalization ability of the evaluation model. Recurrent neural network (RNN) is a deep learning algorithm that is good at processing time series data and sequence data, and can effectively capture the time series change characteristics in the aging process of the liquid crystal panel. In the aging process of the liquid crystal panel, many changes occur gradually, and RNN can capture these dynamic and nonlinear changes, so as to accurately predict the aging state of the liquid crystal panel. By learning the training set, the RNN model can deeply understand the law of liquid crystal panel aging, generate a pre-model for liquid crystal panel aging state evaluation, and provide a preliminary judgment for the aging evaluation of the liquid crystal panel. The pre-model for liquid crystal panel aging state evaluation is optimized and iterated using the model test set, so that the model can effectively predict in more real scenarios. Each optimization iteration makes the model more accurate in evaluating the aging state of the liquid crystal panel, avoiding overfitting and underfitting problems. Independent difference evaluation of panel areas makes it possible to evaluate the aging status of LCD panels not only globally, but also to focus on the aging status of different areas (such as the center, edge, corner, etc. of the screen). This regional analysis helps to find performance degradation, color shift or uneven brightness in specific areas of the LCD panel.

[0049] Preferably, performing independent difference evaluation of panel area aging on the liquid crystal panel according to the liquid crystal panel aging state evaluation data includes:

[0050] According to the aging status evaluation data of the liquid crystal panel, the liquid crystal panel is divided into four corners to generate the four corner division areas of the liquid crystal panel; the division corner points of the four corner division areas of the liquid crystal panel are confirmed to obtain the division corner points of the four corner areas;

[0051] Connecting adjacent corner points of the four corner area division corner points to obtain an adjacent corner point connection area, and marking it as a liquid crystal panel edge division area;

[0052] The core area of ​​the LCD panel is divided by the edge division area of ​​the LCD panel to generate the core division area of ​​the LCD panel; the global aging status assessment data of the LCD panel is evaluated by using the four corner division areas of the LCD panel, the edge division areas of the LCD panel and the core division areas of the LCD panel to perform independent difference evaluation of panel area aging to generate local difference evaluation data of panel area aging.

[0053] The present invention can analyze the aging differences of different areas of the liquid crystal panel in a more refined manner by dividing the liquid crystal panel into four corners, an edge and a core area. Since different areas of the liquid crystal panel show different aging speeds and degrees due to factors such as temperature, humidity, and frequency of use, this regionalized evaluation method can provide independent aging status analysis for each area, thereby improving the accuracy and meticulousness of the evaluation. The four corner areas are usually the parts of the liquid crystal panel that are most susceptible to aging changes because the use environment, temperature distribution or edge effect of these areas are different from those of the central area. By dividing and analyzing the four corner areas separately, it can help identify these extreme aging areas and promptly discover existing problems such as color shift and brightness attenuation. This evaluation method allows the four corners of the liquid crystal panel to receive special attention during the aging process, which helps to discover early signs of aging and provide a basis for later optimization design. The edge area is often affected by different use than the core area (such as differences in heat and light distribution), resulting in different edge aging speeds and characteristics. By independently dividing and analyzing the edge area of ​​the liquid crystal panel, the aging status of the edge area can be more accurately evaluated. Independent analysis of the edge area not only helps to improve the quality control of the liquid crystal panel, but also provides specific data support for optimizing edge design and thermal management. The core area is usually the display area of ​​the LCD panel, carrying most of the display functions and visual effects. Independent evaluation of the aging status of the core area helps to accurately determine whether the display performance is affected, such as color accuracy, contrast, and brightness uniformity. Through meticulous core area division, it can help detect and optimize the display effect of the LCD panel and prevent screen quality problems caused by aging in the core area. Combined with independent analysis of the four corner areas, edge areas, and core areas, comprehensive area division can cover all key areas of the LCD panel to ensure the comprehensiveness of aging evaluation. This can not only promptly discover potential problems with the overall aging of the LCD panel, but also identify aging differences in specific areas to form complete local difference evaluation data.

[0054] In this specification, a liquid crystal panel aging test system is provided, which is used to perform the above-mentioned liquid crystal panel aging test method. The liquid crystal panel aging test system includes:

[0055] A display aging test module is used to obtain a liquid crystal panel display interface; perform dynamic image display on the liquid crystal panel display interface to generate a liquid crystal panel dynamic image display interface; perform a liquid crystal panel dynamic image display aging test on the liquid crystal panel dynamic image display interface based on a preset running display time to generate a first-order test result of the liquid crystal panel; perform a display aging evaluation on the liquid crystal panel display change analysis data based on the first-order test result of the liquid crystal panel to generate a liquid crystal panel display aging evaluation data;

[0056] The temperature change cycle test module is used to perform a temperature and humidity cycle change test on the LCD panel display interface according to the first order test results of the LCD panel, and generate the second order test results of the LCD panel; perform a thermal management evaluation on the second order test results of the LCD panel, and generate thermal management aging evaluation data of the LCD panel;

[0057] The comprehensive aging assessment module is used to perform model training on the display aging assessment data of the LCD panel and the thermal management aging assessment data of the LCD panel to generate an aging status assessment model for the LCD panel; import the first-order test results of the LCD panel and the second-order test results of the LCD panel into the LCD panel aging status assessment model to perform aging status assessment and generate global aging status assessment data for the LCD panel; perform independent difference assessment on the aging of the LCD panel in the panel area according to the aging status assessment data of the LCD panel to generate local difference assessment data on the aging of the panel area; and perform aging data visualization on the global aging status assessment data of the LCD panel and the local difference assessment data on the aging of the panel area to perform LCD panel aging test assessment operations.

[0058] The beneficial effect of the present invention is that by generating a dynamic image display interface of a liquid crystal panel and performing an aging test, the display aging of the liquid crystal panel in a real use scenario can be simulated. This test method can accurately evaluate the performance changes of the liquid crystal panel in different display modes, especially the display characteristics such as color, brightness, and contrast. It effectively avoids the dynamic use that cannot be reflected by the static test. According to the first order test results, the temperature and humidity cycle change test can simulate the performance changes of the liquid crystal panel under various environmental conditions, especially the stability in extreme environments such as high temperature and high humidity. This test can help manufacturers evaluate the performance of the panel in a real use environment, especially the impact of thermal stress and humidity changes caused by temperature changes on the display effect. The comprehensive aging evaluation module performs deep learning and model training on the aging state of the liquid crystal panel by combining the liquid crystal panel display aging evaluation data and the thermal management aging evaluation data. This process can generate a more accurate liquid crystal panel aging state evaluation model, providing accurate predictions for the service life and performance changes of the liquid crystal panel. The evaluation model not only takes into account display aging, but also integrates multiple factors such as thermal management, providing a comprehensive aging evaluation perspective. The global aging state evaluation data of the liquid crystal panel and the local difference evaluation data of the panel area aging are visualized to make the aging test results more operational. Visual presentation enables engineers and technicians to intuitively understand the aging of LCD panels at different stages of use and environmental conditions, and then adjust the production process or design plan to optimize product quality and performance. Therefore, the present invention improves the accuracy and comprehensiveness of the test by introducing dynamic display, temperature and humidity change test, multi-dimensional evaluation, regional difference analysis and intelligent evaluation model. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 A schematic diagram of the steps of a liquid crystal panel aging test method;

[0060] Figure 2 for Figure 1 Detailed implementation steps of step S2 in the flowchart;

[0061] Figure 3 for Figure 1 Detailed implementation steps of step S3 in FIG.

[0062] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0063] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0064] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0065] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0066] To achieve this, please refer to Figures 1 to 3 , a liquid crystal panel aging test method, the method comprising the following steps:

[0067] Step S1: obtaining a liquid crystal panel display interface; performing a dynamic image display on the liquid crystal panel display interface to generate a liquid crystal panel dynamic image display interface; performing a liquid crystal panel dynamic image display aging test on the liquid crystal panel dynamic image display interface based on a preset running display time to generate a first-order test result of the liquid crystal panel; performing a display aging evaluation on the liquid crystal panel display change analysis data based on the first-order test result of the liquid crystal panel to generate liquid crystal panel display aging evaluation data;

[0068] Step S2: performing a temperature and humidity cycle change test on the display interface of the liquid crystal panel according to the first sequence test results of the liquid crystal panel to generate a second sequence test result of the liquid crystal panel; performing a thermal management evaluation on the second sequence test result of the liquid crystal panel to generate thermal management aging evaluation data of the liquid crystal panel;

[0069] Step S3: Perform model training on the LCD panel display aging evaluation data and the LCD panel thermal management aging evaluation data to generate an LCD panel aging status evaluation model; import the LCD panel first-order test results and the LCD panel second-order test results into the LCD panel aging status evaluation model to perform aging status evaluation to generate the LCD panel global aging status evaluation data; perform panel area aging independent difference evaluation on the LCD panel according to the LCD panel aging status evaluation data to generate panel area aging local difference evaluation data; visualize the aging data of the LCD panel global aging status evaluation data and the panel area aging local difference evaluation data to perform the LCD panel aging test evaluation operation.

[0070] The present invention can more realistically simulate the display effect and aging process of the liquid crystal panel in actual use by introducing dynamic image display and aging test based on preset running time, avoid the limitations of traditional static test, and improve the accuracy and authenticity of the test. The generation of display aging evaluation data is helpful to fully understand the performance degradation of the liquid crystal panel in actual application and ensure product quality. On the basis of the display aging test of the liquid crystal panel, a temperature and humidity cycle change test is added, and a thermal management evaluation is performed. This step can effectively simulate the aging of the liquid crystal panel under various environmental changes, comprehensively consider the influence of temperature, humidity and thermal management on the performance of the panel, thereby improving the comprehensiveness and practicality of the test, and providing a more scientific basis for the reliability evaluation of the liquid crystal panel. By training the display aging evaluation data and the thermal management aging evaluation data, a liquid crystal panel aging state evaluation model is generated, and the overall aging trend of the panel can be scientifically predicted. The first and second order test results of the liquid crystal panel are imported into the evaluation model to generate global aging state evaluation data, which provides an accurate basis for the long-term stability and performance degradation prediction of the liquid crystal panel. At the same time, regional difference evaluation helps to detect the aging of the local area of ​​the panel and improve the evaluation accuracy and pertinence. Visualizing the global aging status assessment data and the local area aging difference assessment data not only makes the aging test results more intuitive and easy to understand, but also facilitates the rapid identification of potential problem areas in practical applications, guides subsequent quality improvements or design optimization, and improves the efficiency and accuracy of aging test assessment operations. Therefore, the present invention improves the accuracy and comprehensiveness of the test by introducing dynamic display, temperature and humidity change testing, multi-dimensional evaluation, regional difference analysis, and intelligent evaluation models.

[0071] In the embodiment of the present invention, reference Figure 1 FIG. 1 is a schematic diagram of a flow chart of steps of a liquid crystal panel aging test method of the present invention. In this example, the liquid crystal panel aging test method includes the following steps:

[0072] Step S1: obtaining a liquid crystal panel display interface; performing a dynamic image display on the liquid crystal panel display interface to generate a liquid crystal panel dynamic image display interface; performing a liquid crystal panel dynamic image display aging test on the liquid crystal panel dynamic image display interface based on a preset running display time to generate a first-order test result of the liquid crystal panel; performing a display aging evaluation on the liquid crystal panel display change analysis data based on the first-order test result of the liquid crystal panel to generate liquid crystal panel display aging evaluation data;

[0073] In an embodiment of the present invention, a control system (such as a microcontroller, a display driver circuit, etc.) is connected through a hardware interface to ensure that the liquid crystal panel can display images normally. The display content is configured according to the resolution (for example: 1920x1080, 2560x1440, etc.) and color depth (for example: 24-bit color) of the liquid crystal panel. The control signal of the liquid crystal panel is transmitted to the panel through a driver to ensure that the liquid crystal panel can display dynamic images according to the input signal. The layout of the display interface is designed, including the position, font, icon, text, etc. of the image elements. The display interface can be a test pattern, a graphical interface or a dynamic image. Suitable image materials (such as color filling, geometric figures, text, etc.) are selected and set as the display content of the liquid crystal panel. Different images (for example: color gradient, dynamically changing graphics or animation sequences) are selected from the image material library as dynamic content to simulate real-time changes in screen content. A dynamic image sequence is generated using a preset dynamic change algorithm (for example, image sliding, deformation, color change, video playback, etc.). It is also possible to consider using an artificial intelligence algorithm to generate and transform image content to simulate more complex dynamic images. According to the set display time and content change logic, control the order and duration of the image display on the screen. For example: switch to the next image after each dynamic image is displayed for 5 seconds. Through the display control module, the dynamic images are displayed on the LCD panel in a predetermined sequence. Ensure that the display time of each image meets the set requirements, and control the transition effect between images to avoid fast flickering or image dislocation. Set the predetermined operation display time according to the use requirements of the LCD panel. For example: the test display runs for 24 hours, 48 ​​hours or longer. During operation, the dynamic image display content of the LCD panel should continue to change in the manner in step S2. Ensure that the display content and operating conditions are close to the actual use environment, such as changing brightness, contrast, color, etc., to simulate the aging process of the LCD panel during long-term display. Monitor the key parameters of the LCD panel display interface such as brightness, color, response time, etc., collect data in real time and record changes in display performance. In addition to changes in display content, environmental factors such as temperature and humidity should also be recorded, which affect the aging speed of the LCD panel. Record the performance changes of the LCD panel after the test of the predetermined display time, and generate the first order test results of the LCD panel. Analyze the data collected from the first-order test results of the LCD panel to identify the trend of display changes. Evaluate the degree of panel degradation based on the brightness decay data. Measure whether the displayed color deviates from the original value and make a quantitative evaluation. Monitor the change in response time and evaluate its impact on the display effect of the LCD panel. Use statistical analysis methods (such as regression analysis, time series analysis, etc.) to establish a mathematical model of LCD panel display changes and predict the aging trend of the LCD panel after long-term use. Define the display aging evaluation index of the LCD panel based on the display change analysis results.

[0074] Step S2: performing a temperature and humidity cycle change test on the display interface of the liquid crystal panel according to the first sequence test results of the liquid crystal panel to generate a second sequence test result of the liquid crystal panel; performing a thermal management evaluation on the second sequence test result of the liquid crystal panel to generate thermal management aging evaluation data of the liquid crystal panel;

[0075] In the embodiment of the present invention, high-precision temperature and humidity control equipment, such as a temperature and humidity chamber, a constant temperature and humidity equipment, etc., is configured to simulate the working state of the liquid crystal panel under various environmental conditions. The temperature range (e.g., -20°C to 70°C), humidity range (e.g., 20% RH to 90% RH) and different climate conditions are set according to the working environment requirements of the liquid crystal panel. According to the service life of the liquid crystal panel and the influence of environmental factors, the simulation cycle of the temperature and humidity cycle is set (e.g., a 24-hour cycle, or a cycle is set according to the special requirements of the liquid crystal panel use environment). Each cycle may include four environments of high temperature, high humidity, low temperature and normal temperature, which are cycled alternately. Based on the first sequence test results of the liquid crystal panel, the temperature and humidity cycle change test is performed on the liquid crystal panel display interface. Each cycle is set to 48 hours, and at least 10 rounds of cycle tests are performed. Each cycle exposes the liquid crystal panel to different temperature and humidity environments. For example, the liquid crystal panel is exposed to a high temperature environment (e.g., 60°C) to simulate the influence of the high temperature environment on the display performance of the liquid crystal panel. For example, the liquid crystal panel is exposed to a high humidity environment (e.g., 90% RH) to simulate the influence of a humid environment. For example, the LCD panel is exposed to a low temperature environment (such as -20°C) to simulate the display effect of the LCD panel in a cold environment. For example, the LCD panel is exposed to a normal temperature (such as 25°C) to simulate a normal working environment. In each cycle, the performance of the LCD panel is monitored, and the following display parameters of the LCD panel are recorded synchronously to monitor the performance of the LCD panel in different temperature and humidity environments, and generate the second order test results of the LCD panel. Through the results of the temperature and humidity cycle change test, the thermal distribution, thermal attenuation and thermal response of the LCD panel under different temperature and humidity environments are evaluated to predict the long-term stability and aging of the panel under extreme environments. During the operation of the LCD panel, the temperature changes in different areas will affect the LCD display effect, especially the center and edge areas of the panel. Use an infrared thermal imager to perform a thermal scan on the LCD panel to obtain the temperature distribution of the LCD panel under different temperature and humidity conditions in real time. Through the thermal map generated by the thermal imager, the surface temperature distribution of the LCD panel is analyzed to identify areas with concentrated heat loads, such as the center and edge of the display area, or the connection area with a large temperature difference. Analyze the thermal diffusion of the LCD panel to evaluate whether the LCD panel can maintain a relatively balanced temperature distribution after experiencing multiple rounds of temperature and humidity changes. Excessive temperature gradients will accelerate panel aging. Based on the temperature distribution of the LCD panel, evaluate the thermal management capabilities of the LCD panel to see whether it can effectively avoid performance degradation or panel damage caused by local overheating. Generate evaluation indicators such as thermal diffusion coefficient and temperature gradient based on thermal imaging and temperature distribution data. Generate thermal management aging evaluation data for the LCD panel based on the second-order test results and thermal management analysis of the LCD panel.

[0076] Step S3: Perform model training on the LCD panel display aging evaluation data and the LCD panel thermal management aging evaluation data to generate an LCD panel aging status evaluation model; import the LCD panel first-order test results and the LCD panel second-order test results into the LCD panel aging status evaluation model to perform aging status evaluation to generate the LCD panel global aging status evaluation data; perform panel area aging independent difference evaluation on the LCD panel according to the LCD panel aging status evaluation data to generate panel area aging local difference evaluation data; visualize the aging data of the LCD panel global aging status evaluation data and the panel area aging local difference evaluation data to perform the LCD panel aging test evaluation operation.

[0077] In an embodiment of the present invention, the display aging evaluation data of the liquid crystal panel and the thermal management aging evaluation data of the liquid crystal panel are divided into two parts: the training set is used to train the model, which is usually 70%-80% of the data set. The test set is used for model evaluation and verification, which is usually 20%-30% of the data set. The features that best reflect the aging state of the liquid crystal panel are selected, such as brightness attenuation, color shift, thermal diffusion coefficient, etc. All input data are normalized or standardized to ensure that the data range of different features is within the same scale to avoid excessive influence of certain features on model training. Recurrent neural network (RNN) is suitable for time series data and can capture the changing trend of liquid crystal panels in long-term use. The selected model is trained using the training set to optimize the parameters of the model (such as learning rate, regularization coefficient, etc.). Cross-validation technology is used to evaluate the performance of the model to prevent overfitting. The model parameters are adjusted and iterative training is performed until the optimal aging evaluation model is obtained. Generate a liquid crystal panel aging state evaluation model. After the training is completed, the model can predict and evaluate the aging state of the liquid crystal panel. The trained model is verified using the test set to evaluate its performance in real situations, mainly including evaluation indicators such as precision, recall rate, and F1 score. Based on the results of the test set, the model parameters are optimized, such as adjusting the number of network layers and increasing regularization, to further improve the prediction ability of the model. The first-order test results of the LCD panel and the second-order test results of the LCD panel are imported into the trained LCD panel aging state evaluation model for prediction. The model will generate global aging state evaluation data of the LCD panel based on the input performance data, including: evaluating the overall aging state of the panel based on indicators such as brightness attenuation and color shift of the LCD panel. Predict the aging of the LCD panel in a certain period of time in the future and give an early warning. Based on the global aging state evaluation data, identify the aging differences in different areas of the LCD panel. For example, some areas show more severe aging due to high heat load, while other areas are less affected. Through regional differentiation analysis, the aging speed and influencing factors of each area are evaluated to generate local difference evaluation data of panel regional aging. Local differences include: aging differences between the central area and the edge area and local aging caused by insufficient thermal management. Visualize the global aging status assessment data of the LCD panel and the local difference assessment data of the panel area aging to generate easy-to-understand and easy-to-operate charts, heat maps, 3D graphics, etc.

[0078] Preferably, step S1 comprises the following steps:

[0079] Step S11: obtaining a liquid crystal panel display interface;

[0080] Step S12: randomly generating a dynamic image sequence for the liquid crystal panel display interface to obtain a dynamic image random sequence; performing dynamic image display on the liquid crystal panel display interface according to the dynamic image random sequence to generate a liquid crystal panel dynamic image display interface;

[0081] Step S13: performing a liquid crystal panel display change analysis on the liquid crystal panel dynamic image display interface based on a preset running display time, and generating liquid crystal panel display change analysis data, wherein the liquid crystal panel display change analysis includes color shift, brightness attenuation and response time;

[0082] Step S14: using the LCD panel display change analysis data to perform an LCD panel dynamic image display aging test on the LCD panel dynamic image display interface to generate a first-order test result of the LCD panel; based on the first-order test result of the LCD panel, performing a display aging evaluation on the LCD panel display change analysis data to generate an LCD panel display aging evaluation data.

[0083] In an embodiment of the present invention, a liquid crystal panel is connected through a hardware interface and a display interface is set. According to the application scenario, the interface content can be a static image or a preset dynamic content. This step mainly ensures that the display interface of the liquid crystal panel works normally and prepares for subsequent testing and display analysis. The display content is read or generated by a computer or an embedded control system and transmitted to the liquid crystal panel for display. A series of dynamic images are generated by a random sequence using an image generation algorithm or a predefined dynamic image library. These dynamic images include different image content, color, brightness changes and motion patterns. The dynamically generated image sequence should have sufficient complexity to reflect the performance of the liquid crystal panel under different display conditions. These dynamic image sequences are displayed on the liquid crystal panel, and the display interface content is updated in real time by the controller. In order to achieve a more realistic test, different time intervals and transformation modes can be set by programming. When displaying the dynamic image sequence, the display changes of the liquid crystal panel at different time nodes are recorded. The preset running display time can be set according to the test requirements, such as 30 minutes, 1 hour or longer. By comparing the color difference between the initial display content of the liquid crystal panel and the display content after a period of time, the change of the display effect is evaluated. The commonly used color difference calculation method is CIEDE2000 color difference. Measure the change in brightness of the LCD panel during the display time and evaluate its brightness decay characteristics, usually measured by a brightness meter or photometer. Measure the switching time of the LCD panel from black to white and white to black to evaluate its response speed. Common measurement tools are fast cameras and time analysis software. After the LCD panel undergoes a series of dynamic display image tests, an aging test is performed based on the display change analysis data. Specifically, the first-order test results (such as color shift, brightness decay, and response time) are used to simulate the performance of the LCD panel during long-term use. The LCD panel is displayed for a longer period of time, usually for several hours or days, depending on the test requirements. Accelerate display aging by frequently changing the display content and brightness. Further evaluate the display changes of the LCD panel based on the first-order test results. The aging evaluation will consider the trend of display performance changes, whether there is abnormal decay or significant changes. Evaluate the aging trend of the LCD panel through a data analysis model and output display aging evaluation data. The evaluation data should include the following items: The display aging coefficient represents a quantitative indicator of the performance decay of the LCD panel over a certain period of time, involving color retention, brightness stability, etc. Service life prediction, based on the current display aging evaluation, predict the service life of the LCD panel under the same conditions.

[0084] Preferably, randomly generating a dynamic image sequence for a liquid crystal panel display interface includes:

[0085] Constructing an image material library; performing image enhancement on images in the image material library to obtain an image enhancement material library, wherein the image enhancement includes color correction, blur processing, and reflected light simulation;

[0086] Perform image label classification on the image enhancement material library to generate label images, and set the material generation probability for the label images to obtain probabilistic label images; set the sequence time length for the probabilistic label images to generate the probabilistic label image duration;

[0087] Based on the duration of the probability label images, random image selection is performed on the probability label images to generate the law of image content change; a random number generator is used to combine the image display order of the probability label images according to the law of image content change, thereby generating a random sequence of dynamic images.

[0088] In an embodiment of the present invention, an image material library is created. This material library contains a variety of different types of images to ensure the diversity of content, such as static images, dynamic scenes, characters, scenery, text, etc. The image material can come from a public database, an image generated by a design software, or a photo taken by yourself. The image material library can be generated by collecting high-quality pictures, downloading materials from an image library, or using a generation model (such as GAN). Ensure that the resolution, color and details of the material can adapt to the display requirements of the liquid crystal panel. Perform image enhancement on each image in the image material library to simulate different display environments and usage conditions. The goal of image enhancement is to increase the diversity of the image and make its performance in the display process more realistic and challenging. Apply a color correction algorithm to adjust the color temperature, saturation, contrast, etc. of the image to ensure that the color performance of the image is more natural. Color space conversion, white balance adjustment and other technologies can be used. Use an image blur algorithm (such as Gaussian blur, motion blur) to process the image to simulate the blurring of details in the display of the liquid crystal panel and increase the difficulty of the display test. By adjusting the blur parameters, different display effects can be simulated. Use a light simulation algorithm to add reflected light or halo effects to simulate the performance of the liquid crystal panel under different lighting conditions. This can be achieved by adding reflections of virtual light sources to the image or using physical rendering methods (such as reflection and refraction models). Classify the enhanced image materials to facilitate subsequent selection and generation. Image classification labels can be classified according to the type, scene, color, brightness, etc. of the image content. For example, the image is divided into categories such as natural scenery, urban buildings, portraits, and text. For each category, the corresponding label is annotated, such as natural scenery, city, low-light environment, etc. Classification can be performed manually or automatically using machine learning methods (such as convolutional neural networks, CNN). The accuracy and diversity of classification labels directly affect the effect of subsequent sequence generation. Based on the image label classification results, set the corresponding generation probability for each label. The generation probability determines the frequency and randomness of each label category. Set the display probability of each type of label according to the application scenario or demand. For example, the probability of "natural scenery" appearing can be set to 0.4, the probability of "portrait" appearing can be set to 0.2, and other categories can be set as needed. These probabilities can be flexibly adjusted according to different test requirements. For example, when testing factors such as color and brightness, the frequency of a specific category needs to be adjusted. Assign a display duration to each type of probability label image to simulate the time span in a dynamic image sequence. The display duration affects the continuity and smoothness of the image display. The display time of each frame can be fixed or random. For example, for the "Natural Scenery" label image, set the display duration to 3-5 seconds, and set the display duration range for other labels as needed. When setting the time length, you can adjust the transition effect in the sequence as needed to ensure that the generated dynamic image sequence is neither too fast (causing visual discontinuity) nor too slow (causing the test cycle to be too long).A random number generator is used to select random images according to the generation probability and time length of the probabilistic label image. Each time a selection is made, the generator selects the corresponding image category and its display duration according to the set probability and time constraints. By setting the probability distribution and duration control, the generated dynamic image sequence is ensured to be random and diverse while meeting the predetermined time constraints. For example, a weighted random selection method can be used to select corresponding images from the probabilistic label image library and add them to the dynamic image sequence. Based on the aforementioned random image selection, the selected images are combined in sequence using a random number generator to generate the final dynamic image random sequence. The sequence needs to conform to the specified content change law to ensure the reasonable transition of the image content in the time sequence. The images are combined in sequence to form a dynamic image sequence. When combining, it is necessary to ensure that the transition between images is smooth to avoid abrupt changes. The image switching effect can be optimized by a smoothing algorithm or an easing algorithm. The image sequence can be optimized according to the test objectives (such as color, brightness test, etc.). For example, the repeatability and interval of the same type of images in the time sequence are ensured to test the stability of the LCD panel when continuously displaying the same content. After the above steps, a complete random sequence of dynamic images is finally generated. This sequence can be displayed according to preset rules to simulate the display effect of the LCD panel during actual use. The generated dynamic image sequence can be transmitted to the LCD panel through the hardware interface for display testing. According to different test requirements, the generated dynamic image sequence will contain hundreds or thousands of frames of images to ensure that the various performances of the LCD panel can be fully tested.

[0089] As an example of the present invention, refer to Figure 2 As shown, in this example, step S2 includes:

[0090] Step S21: performing a temperature and humidity cycle change test on the display interface of the liquid crystal panel according to the first sequence test result of the liquid crystal panel to generate a second sequence test result of the liquid crystal panel;

[0091] Step S22: performing extreme test temperature screening on the second order test results of the liquid crystal panel to obtain extreme test temperature data; performing liquid crystal panel temperature distribution analysis on the liquid crystal panel display interface based on the extreme test temperature data to generate liquid crystal panel extreme temperature distribution data;

[0092] Step S23: performing heat diffusion analysis on the display interface of the liquid crystal panel according to the extreme temperature distribution data of the liquid crystal panel, and generating liquid crystal panel display heat diffusion data;

[0093] Step S24: Performing thermal management evaluation using the liquid crystal panel extreme temperature distribution data and the liquid crystal panel display heat diffusion data to generate liquid crystal panel thermal management aging evaluation data.

[0094] In an embodiment of the present invention, by reviewing the first-order test results of the liquid crystal panel, the display performance (such as color shift, brightness attenuation, response time, etc.) of the panel under normal conditions is determined. A temperature and humidity cycle device is set, which can simulate the working conditions of the liquid crystal panel under different environmental temperature and humidity conditions. During the test, the liquid crystal panel will undergo multiple periodic changes in temperature and humidity, such as changes from low temperature (-10°C) to high temperature (70°C), and adjust the humidity (30% RH to 80% RH). After each certain temperature and humidity cycle, the performance of the liquid crystal panel is recorded, including image changes, display stability, response time, color shift, etc. By integrating the data of each test cycle, the second-order test results of the liquid crystal panel are generated, mainly including the performance change data of the panel during the temperature and humidity cycle. According to the working specifications and environmental requirements of the liquid crystal panel, the "extreme temperature" range is defined. Common extreme test temperature ranges are usually: low temperature (-20°C to -30°C) and high temperature (+60°C to +85°C). Data under these extreme temperature ranges are extracted from the second-order test results. These data usually include the display performance of the liquid crystal panel at different temperatures, such as brightness, color, response speed, etc. The collected test data is screened according to the temperature range and performance changes, focusing on the degradation of display performance under extreme temperatures (such as brightness attenuation, color shift, etc.). The screened data is integrated into extreme temperature test data to clarify the performance of the LCD panel under these extreme temperature conditions. Use a thermal imager or temperature sensor to measure the temperature distribution at different locations on the surface and inside the LCD panel. This can help identify the heat source area and cooling area and understand how the heat diffuses within the panel. According to the structure of the LCD panel (such as backlight, display panel, drive circuit, etc.), a heat diffusion model is established. This model is usually based on the theory of heat conduction, combined with parameters such as the thermal conductivity and thickness of the panel material. Use computational fluid dynamics (CFD) simulation software to numerically simulate the heat diffusion process and calculate the heat transfer characteristics of the LCD panel at different extreme temperatures, including the flow of heat, the diffusion rate, and the change in panel surface temperature. Analyze the simulation results, generate the heat diffusion data of the LCD panel, and characterize the change trend of the internal and surface temperature of the panel under extreme temperatures. According to the operating temperature range, heat diffusion characteristics and heat dissipation requirements of the LCD panel, formulate thermal management evaluation standards. These standards usually include temperature tolerance, heat decay rate, heat source isolation capability, etc. The thermal management system of the LCD panel is evaluated using the aforementioned extreme temperature distribution data and heat diffusion data. This includes evaluating the heat dissipation effect of the panel at extreme temperatures, whether there are overheated or overcooled areas, and whether the panel can maintain stable operation for a certain period of time. Through thermal aging tests, the performance of the LCD panel under extreme temperatures for a long time is simulated to check whether the thermal management system effectively delays the aging process of the panel and avoids the degradation of the display effect caused by temperature. The thermal management aging evaluation data of the LCD panel is generated by combining the temperature distribution, heat diffusion and aging simulation results.This data includes key information such as the predicted service life and performance stability of LCD panels under extreme temperatures.

[0095] Preferably, performing a temperature and humidity cycle change test on the display interface of the liquid crystal panel according to the first sequence test result of the liquid crystal panel includes:

[0096] Set up a temperature and humidity control system, and perform high temperature environment setting, high humidity environment setting and low temperature environment setting on the temperature and humidity control system, and perform simulation cycle quantification on the set environment to generate a temperature and humidity control simulation cycle;

[0097] Based on the temperature and humidity control simulation cycle, the LCD panel display interface is subjected to periodic simulation alternating cycles, each cycle is 48 hours, and at least 10 rounds of temperature and humidity cycle tests are completed;

[0098] Under the above-mentioned temperature and humidity cycle test conditions, the panel performance of the LCD panel display interface is measured, and the screen brightness, color, and response time of the LCD panel display interface are simultaneously recorded to generate the second order test results of the LCD panel.

[0099] In an embodiment of the present invention, a temperature and humidity control system (such as a temperature and humidity chamber, a climate environment test chamber, etc.) is selected to simulate high temperature, high humidity and low temperature environments. The system should be able to accurately adjust within the specified temperature and humidity range. The temperature range is set to 50°C to 85°C (specifically adjusted according to the operating temperature range of the liquid crystal panel). At this temperature, the heat resistance of the panel and the display performance at high temperature are tested. The humidity range is set to 70% to 90% RH (relative humidity) to simulate the performance of the liquid crystal panel in a high humidity environment. This setting is suitable for testing whether the panel has water vapor penetration or other display effect problems caused by humidity changes. The temperature range is set to -10°C to -30°C to simulate the impact of a low temperature environment on the performance of the liquid crystal panel, and to evaluate the display effect at low temperature and the responsiveness of the panel. The above-mentioned temperature and humidity environment is simulated and quantified in cycles, and it is ensured that the changes in temperature and humidity in each test cycle meet the requirements. According to the requirements of the liquid crystal panel, a suitable environmental simulation cycle is set (for example, one cycle every 48 hours). Each cycle consists of high temperature, low temperature and humidity changes, and the simulation device can automatically adjust the temperature and humidity according to the set parameters. High temperature (70℃) is maintained for 12 hours → low temperature (-20℃) is maintained for 12 hours → high humidity (85% RH) is maintained for 12 hours → normal temperature (25℃) is restored to the state, and a cycle is completed. Each test cycle is 48 hours, ensuring that at least 10 rounds of temperature and humidity cycle tests are performed to generate a temperature and humidity control simulation cycle. According to the temperature and humidity control simulation cycle set above, each cycle is 48 hours. Within 48 hours, the LCD panel will experience alternating changes in high temperature, high humidity, low temperature and normal temperature, and the duration of each environmental state is strictly adjusted according to the set cycle. The system automatically performs temperature and humidity cycle changes to ensure that the LCD panel has enough time to adapt to different environmental conditions. Each test cycle is 48 hours, and performance measurements and data recording are performed after each round of testing. At least 10 rounds of temperature and humidity cycle tests are completed to ensure the reliability and stability of the test results. Cycle 1: High temperature (70℃) 12 hours → Low temperature (-20℃) 12 hours → High humidity (85% RH) 12 hours → Normal temperature (25℃) recovery 12 hours Cycle 2: Repeat the above settings for alternating cycles. The temperature and humidity control system will continuously monitor and adjust the temperature and humidity status during the entire test process to ensure that the environment remains stable within each cycle and that the changes are smooth and continuous. Use a photometer or brightness meter to measure the brightness of the LCD panel after each test cycle. Brightness changes will be affected by changes in temperature and humidity, and this data can be used to evaluate the brightness stability of the LCD panel. Use a colorimeter or colorimeter to regularly measure the color performance of the LCD panel. Record the color offset and observe whether there is obvious color decay or color difference under temperature and humidity changes. Use a high-speed camera or response time measurement instrument to evaluate the response speed of the LCD panel. By testing the response speed of the panel under changing ambient temperature and humidity, it is determined whether its responsiveness in actual use is affected by the environment.After each temperature and humidity cycle change, all performance test data (brightness, color, response time) should be recorded synchronously and saved together with the current ambient temperature and humidity data of the LCD panel. This ensures the traceability of the test data and facilitates subsequent analysis. The measurement results will be stored in the form of a time series to ensure that the performance changes within each cycle are recorded in detail. The measurement should be performed at least once after each test cycle, and the LCD panel can be checked more frequently as needed. The test cycle and frequency can be flexibly adjusted according to the specific test requirements of the LCD panel. The collected data such as brightness, color, response time, etc. are statistically analyzed to evaluate the performance stability of the LCD panel under high temperature, high humidity and low temperature cycles. By comparing the data of different test cycles, it is determined whether the LCD panel has performance degradation, display instability or aging. Compare the changes in each round of testing and calculate indicators such as brightness attenuation, color shift, and response time increase. Generate a second-order test report based on the measurement data and analysis results.

[0100] Preferably, performing a liquid crystal panel temperature distribution analysis on a liquid crystal panel display interface using extreme test temperature data includes:

[0101] The panel surface and key areas of the LCD panel display interface are segmented by using extreme test temperature data to generate the LCD panel surface area and the LCD panel key area; the temperature of the LCD panel surface area and the LCD panel key area is scanned by using an infrared thermal imager to obtain a two-dimensional distribution map of the LCD panel area temperature;

[0102] The temperature difference between adjacent areas of the two-dimensional temperature distribution diagram of the LCD panel area is calculated to generate temperature gradient data of adjacent areas; the balance of the panel surface temperature of the LCD panel display interface is evaluated based on the temperature gradient data of adjacent areas to generate extreme temperature distribution data of the LCD panel.

[0103] In an embodiment of the present invention, by using the previous temperature and humidity cycle test results of the liquid crystal panel, the test data of the liquid crystal panel under an extreme temperature environment is determined. Including temperature distribution, test cycle and temperature range. Extreme temperature data generally comes from high temperature and low temperature tests, recording the surface temperature of the panel under different environmental conditions. According to the size and structure of the liquid crystal panel, the panel is divided into several areas. Including edge areas, central areas and corners, etc. According to the use scenario of the liquid crystal panel, the area that has a greater impact on the performance (such as the central part of the display screen, the power supply access part, the sensor area, the backlight source, etc.) is determined. These areas are usually where the heat is concentrated when the panel is working, and temperature anomalies are prone to occur. The size and area division method of the liquid crystal panel is used to generate the coordinate information of the panel surface area and the key area. Select a high-precision infrared thermal imager (such as FLIR series or other infrared thermal imaging equipment suitable for industrial testing). Ensure that the device can cover the entire surface area of ​​the liquid crystal panel, and has high resolution and high sensitivity, and can clearly display the temperature changes on the surface of the liquid crystal panel. When the liquid crystal panel is running to the extreme temperature test state, use the infrared thermal imager to perform a temperature scan on the liquid crystal panel. When scanning, ensure that the device and the panel are kept at an appropriate distance to avoid data deviation due to being too close or too far. During the scanning process, the infrared thermal imager will record the temperature data of each area on the surface of the LCD panel and display the temperature difference of different areas through a chromatogram. The scanning results are processed by the infrared thermal imager software to generate a two-dimensional distribution map of the temperature of the LCD panel area. The color temperature in the image represents the temperature state of different areas, for example: red represents high temperature, blue represents low temperature, and green represents medium temperature. Ensure that the temperature distribution map can show the temperature difference of the key areas and the entire surface of the LCD panel to provide basic data for subsequent analysis. Extract the temperature data of each area from the two-dimensional distribution map of the temperature of the LCD panel, and calculate the temperature difference between adjacent areas. The temperature difference formula is as follows: ΔTij=|Ti-Tj|; where ΔTij is the temperature difference between area i and area j, and Ti and Tj are the temperature values ​​of area i and area j respectively. Calculate the temperature difference between all areas and generate a temperature difference data set. The temperature difference between each area can be displayed in the form of a heat map or a data table. Compare the temperature difference between key areas (such as edge areas and central areas) and other areas to evaluate whether the temperature distribution is uniform and whether there is heat concentration. Based on the temperature difference data of adjacent areas, the temperature gradient (i.e., the temperature change rate) of each area of ​​the LCD panel is calculated. The temperature gradient formula is as follows: G = ΔT ÷ d; where G is the temperature gradient, ΔT is the temperature difference of adjacent areas, and d is the distance between the two areas. Through temperature gradient analysis, the temperature change rate of each area on the surface of the LCD panel is determined, and areas with large temperature gradients are identified, especially whether there are prominent high-temperature concentrated areas. Based on the temperature gradient data, the thermal balance of the LCD panel is analyzed. Ideally, the temperature gradient of the LCD panel should be relatively gentle to avoid overheating of certain areas, which may cause the performance of the panel to deteriorate or be damaged.If the temperature gradient in some areas is too large, it indicates that the thermal management system is not well designed and needs to be optimized. Combined with the temperature gradient analysis results, the extreme temperature distribution data of the LCD panel is generated.

[0104] Preferably, step S23 includes the following steps:

[0105] Step S231: acquiring steady-state temperature data of the liquid crystal panel display interface through the extreme temperature distribution data of the liquid crystal panel to obtain a steady-state test temperature of the liquid crystal panel display interface; discretizing the panel space region of the liquid crystal panel display interface according to the steady-state test temperature of the liquid crystal panel display interface to generate a panel space discretization region;

[0106] Step S232: performing heat diffusion simulation on the panel space discretization area to generate panel area heat diffusion simulation temperature data; performing temperature contour map conversion on the panel area heat diffusion simulation temperature data to generate panel area surface temperature contour map;

[0107] Step S233: Based on the heat conduction equation, the heat diffusion time of the panel area surface temperature contour map is estimated to obtain the panel surface heat diffusion time; wherein the heat conduction equation and the heat diffusion time estimation formula are as follows:

[0108]

[0109] In the formula, It is expressed as a heat conduction equation, α is the thermal diffusion coefficient of the material, is the Laplace operator of temperature, T is the temperature, t is the time, t steady It is represented as the heat diffusion time on the panel surface, and L is the length scale of the panel area;

[0110] Step S234: Identify the heat diffusion area of ​​the LCD panel display interface according to the panel surface heat diffusion time and the panel area surface temperature contour map to generate heat diffusion area identification data; perform heat load concentration area analysis on the heat diffusion area identification data to generate LCD panel display heat diffusion data.

[0111] In an embodiment of the present invention, the surface of the liquid crystal panel is divided into a plurality of small areas by spatially discretizing the steady-state test temperature data. The temperature value of each discretized area will be used for subsequent heat diffusion simulation. The size of the discretized area is determined according to the size and structural characteristics of the liquid crystal panel. For example, the panel can be divided into a plurality of square or rectangular grid areas, and the temperature value of each grid is the temperature of the area. These discretized areas will help analyze the temperature changes of each area during the heat diffusion process. Heat diffusion simulation software (such as COMSOL Multiphysics, ANSYS, etc.) is used to perform heat diffusion simulation based on the steady-state temperature data of the liquid crystal panel and the discretized area information. During the simulation process, the temperature change of each area is generated by calculating the heat transfer and heat diffusion process of each area on the panel surface. Factors such as the material properties and thermal conductivity of the liquid crystal panel should be considered during the simulation process to ensure the accuracy of the simulation results. The heat diffusion simulation temperature data is converted into a temperature contour map. The contour map can clearly show the temperature distribution of different areas on the panel surface, and each contour line represents an area with the same temperature. The contour map can help identify areas with uneven temperature on the panel surface, especially where heat concentration occurs. The heat conduction equation describes how temperature spreads over time and space. The heat conduction equation is: Where T represents temperature, t represents time, and α represents the thermal diffusion coefficient of the material. is expressed as the Laplace operator of temperature (i.e., the second derivative of temperature). By solving this equation, we can predict the process of the LCD panel surface temperature changing over time, especially the process of temperature equilibrium when the initial temperature difference is large. Based on the thermal diffusion coefficient of the LCD panel (α) and the length scale of the panel area (L), the thermal diffusion time estimation formula is used to calculate the time required for the LCD panel surface to reach a steady-state temperature: Where L is the length scale of the LCD panel area (e.g., the side length of the panel), and α is the thermal diffusion coefficient of the material. This formula helps predict the time required for temperature equalization by calculating the thermal diffusion time of different areas on the panel surface, especially under extreme temperature conditions. Based on the results of thermal diffusion simulation and thermal diffusion time estimation, identify the areas on the LCD panel display interface where heat propagation is more significant. Heat propagation areas are usually areas where temperature changes are more drastic. Mark these heat propagation areas on the temperature contour map and conduct further analysis. These areas can be identified by color, such as using red to identify high-temperature areas and green to identify low-temperature areas. Perform heat load concentration analysis on the identified heat propagation areas. These areas are usually where temperature changes are most drastic and heat conduction is most concentrated. The heat load model can be used to calculate the heat load of these areas to evaluate whether heat is concentrated in certain areas, causing local overheating of the LCD panel. Analyze the thermal management effect of the LCD panel and whether it is necessary to reduce the problem of excessive heat load by optimizing the heat dissipation design. Based on the heat propagation area identification data and the heat load concentration area analysis results, generate heat diffusion data for the LCD panel display interface. This data can include the following: temperature distribution of each area, thermal diffusion time, heat load concentration area, and heat propagation path.

[0112] As an example of the present invention, refer to Figure 3 As shown, in this example, step S3 includes:

[0113] Step S31: collecting historical evaluation data of the liquid crystal panel display aging evaluation data and the liquid crystal panel thermal management aging evaluation data to obtain liquid crystal panel aging evaluation historical data; dividing the liquid crystal panel aging evaluation historical data into data sets to generate a model training set and a model test set;

[0114] Step S32: training the model training set by a recurrent neural network algorithm to generate a pre-model for evaluating the aging state of a liquid crystal panel; optimizing and iterating the pre-model for evaluating the aging state of a liquid crystal panel by using a model test set, thereby generating a liquid crystal panel aging state evaluation model;

[0115] Step S33: importing the first order test results of the liquid crystal panel and the second order test results of the liquid crystal panel into the liquid crystal panel aging state evaluation model to perform aging state evaluation, and generate liquid crystal panel global aging state evaluation data;

[0116] Step S34: Perform independent panel area aging difference evaluation on the LCD panel according to the LCD panel aging status evaluation data to generate panel area aging local difference evaluation data; visualize the aging data of the LCD panel global aging status evaluation data and the panel area aging local difference evaluation data to perform the LCD panel aging test evaluation operation.

[0117] In an embodiment of the present invention, historical aging evaluation data of liquid crystal panels at different test stages are collected, including liquid crystal panel display aging evaluation data and liquid crystal panel thermal management aging evaluation data. The historical data should include performance changes of liquid crystal panels, such as brightness attenuation, color shift, response time, temperature distribution changes and other indicators. These data can come from aging test results under multiple test cycles or different environmental conditions, including temperature and humidity cycles, extreme temperature tests, thermal diffusion analysis, etc. The historical data of liquid crystal panel aging evaluation are divided to generate a model training set and a model test set. The common ratio of data set division is 70% for training set and 30% for test set, or the data division is optimized by methods such as cross-validation. In the division process, the diversity and representativeness of the data set are ensured to cover different aging conditions, different test environments, etc. The model training set in the historical data of liquid crystal panel aging evaluation is used for training through a recurrent neural network (RNN) algorithm. RNN can effectively process time series data and capture the temporal relationship in the aging process of liquid crystal panels. When training the model, more advanced RNN variants such as long short-term memory network (LSTM) or gated recurrent unit (GRU) can be used to improve the model's modeling ability for long time series data. Use the model test set to evaluate the trained pre-model, calculate the prediction error on the test set (such as mean square error MSE, mean absolute error MAE, etc.), and optimize the model parameters based on the test results. Through multiple iterations, gradually optimize the weights and structure of the network to avoid overfitting or underfitting, and finally generate an accurate LCD panel aging state assessment model. Techniques such as gradient descent method (SGD, Adam optimizer, etc.) and regularization methods (such as dropout, L2 regularization) can be used to improve the generalization ability of the model. Import the results of the LCD panel in different sequence tests, such as the first sequence test results of the LCD panel (based on display changes, aging process, etc.) and the second sequence test results of the LCD panel (based on temperature and humidity cycles and thermal management, etc.) into the trained LCD panel aging state assessment model. Use the model to evaluate the aging state of the LCD panel, including display performance (color shift, brightness attenuation, response time, etc.) and thermal management performance (heat load, temperature distribution, etc.). The model will calculate the aging trend of the LCD panel during the overall use process based on the imported data, including the performance of the panel under different test conditions. Generate global aging status assessment data of the LCD panel, which will reflect the overall aging degree of the LCD panel and can be used for subsequent service life prediction. Based on the global aging status assessment data, further refine it to each area of ​​the LCD panel. For example, the central area, edge area, corner area, etc. of the panel show different aging characteristics due to factors such as heat distribution and frequency of use. Evaluate the aging status of each area differently to analyze whether there are some areas with higher or lower aging degrees due to manufacturing defects, heat concentration and other factors.Generate panel area aging local difference assessment data, which can help identify the areas of the LCD panel that are most susceptible to aging during use. Visualize the global aging state assessment data of the LCD panel and the local difference assessment data of the panel area aging. The visualization method may include: showing the aging degree of different areas of the LCD panel, and the color depth represents the aging degree. Display the aging process of the LCD panel through three-dimensional modeling, combining factors such as time, area and thermal diffusion. Display the changing trend of LCD panel aging under different test stages and conditions. The visualization data helps to intuitively understand the global and local differences in LCD panel aging, support optimization design and improve product quality. Combine the above evaluation and visualization data to perform the aging test assessment operation of the LCD panel. This process can be used to optimize the design and manufacturing process of the LCD panel, especially to improve the thermal management of different areas, panel material selection and other aspects.

[0118] In this specification, a liquid crystal panel aging test system is provided, which is used to perform the above-mentioned liquid crystal panel aging test method. The liquid crystal panel aging test system includes:

[0119] A display aging test module is used to obtain a liquid crystal panel display interface; perform dynamic image display on the liquid crystal panel display interface to generate a liquid crystal panel dynamic image display interface; perform a liquid crystal panel dynamic image display aging test on the liquid crystal panel dynamic image display interface based on a preset running display time to generate a first-order test result of the liquid crystal panel; perform a display aging evaluation on the liquid crystal panel display change analysis data based on the first-order test result of the liquid crystal panel to generate a liquid crystal panel display aging evaluation data;

[0120] The temperature change cycle test module is used to perform a temperature and humidity cycle change test on the LCD panel display interface according to the first order test results of the LCD panel, and generate the second order test results of the LCD panel; perform a thermal management evaluation on the second order test results of the LCD panel, and generate thermal management aging evaluation data of the LCD panel;

[0121] The comprehensive aging assessment module is used to perform model training on the display aging assessment data of the LCD panel and the thermal management aging assessment data of the LCD panel to generate an aging status assessment model for the LCD panel; import the first-order test results of the LCD panel and the second-order test results of the LCD panel into the LCD panel aging status assessment model to perform aging status assessment and generate global aging status assessment data for the LCD panel; perform independent difference assessment on the aging of the LCD panel in the panel area according to the aging status assessment data of the LCD panel to generate local difference assessment data on the aging of the panel area; and perform aging data visualization on the global aging status assessment data of the LCD panel and the local difference assessment data on the aging of the panel area to perform LCD panel aging test assessment operations.

[0122] The beneficial effect of the present invention is that by generating a dynamic image display interface of a liquid crystal panel and performing an aging test, the display aging of the liquid crystal panel in a real use scenario can be simulated. This test method can accurately evaluate the performance changes of the liquid crystal panel in different display modes, especially the display characteristics such as color, brightness, and contrast. It effectively avoids the dynamic use that cannot be reflected by the static test. According to the first order test results, the temperature and humidity cycle change test can simulate the performance changes of the liquid crystal panel under various environmental conditions, especially the stability in extreme environments such as high temperature and high humidity. This test can help manufacturers evaluate the performance of the panel in a real use environment, especially the impact of thermal stress and humidity changes caused by temperature changes on the display effect. The comprehensive aging evaluation module performs deep learning and model training on the aging state of the liquid crystal panel by combining the liquid crystal panel display aging evaluation data and the thermal management aging evaluation data. This process can generate a more accurate liquid crystal panel aging state evaluation model, providing accurate predictions for the service life and performance changes of the liquid crystal panel. The evaluation model not only takes into account display aging, but also integrates multiple factors such as thermal management, providing a comprehensive aging evaluation perspective. The global aging state evaluation data of the liquid crystal panel and the local difference evaluation data of the panel area aging are visualized to make the aging test results more operational. Visual presentation enables engineers and technicians to intuitively understand the aging of LCD panels at different stages of use and environmental conditions, and then adjust the production process or design plan to optimize product quality and performance. Therefore, the present invention improves the accuracy and comprehensiveness of the test by introducing dynamic display, temperature and humidity change test, multi-dimensional evaluation, regional difference analysis and intelligent evaluation model.

[0123] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0124] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A liquid crystal panel aging test method, characterized in that: The following steps are involved: Step S1: obtaining a liquid crystal panel display interface; performing a dynamic image display on the liquid crystal panel display interface to generate a liquid crystal panel dynamic image display interface; performing a liquid crystal panel dynamic image display aging test on the liquid crystal panel dynamic image display interface based on a preset running display time to generate a first-order test result of the liquid crystal panel; performing a display aging evaluation on the liquid crystal panel display change analysis data based on the first-order test result of the liquid crystal panel to generate liquid crystal panel display aging evaluation data; Step S2: performing a temperature and humidity cycle change test on the display interface of the liquid crystal panel according to the first sequence test results of the liquid crystal panel to generate a second sequence test result of the liquid crystal panel; performing a thermal management evaluation on the second sequence test result of the liquid crystal panel to generate thermal management aging evaluation data of the liquid crystal panel; Step S3: Perform model training on the LCD panel display aging evaluation data and the LCD panel thermal management aging evaluation data to generate an LCD panel aging status evaluation model; import the LCD panel first-order test results and the LCD panel second-order test results into the LCD panel aging status evaluation model to perform aging status evaluation to generate the LCD panel global aging status evaluation data; perform panel area aging independent difference evaluation on the LCD panel according to the LCD panel aging status evaluation data to generate panel area aging local difference evaluation data; visualize the aging data of the LCD panel global aging status evaluation data and the panel area aging local difference evaluation data to perform the LCD panel aging test evaluation operation.

2. The liquid crystal panel aging test method according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: obtaining a liquid crystal panel display interface; Step S12: randomly generating a dynamic image sequence for the liquid crystal panel display interface to obtain a dynamic image random sequence; performing dynamic image display on the liquid crystal panel display interface according to the dynamic image random sequence to generate a liquid crystal panel dynamic image display interface; Step S13: performing a liquid crystal panel display change analysis on the liquid crystal panel dynamic image display interface based on a preset running display time, and generating liquid crystal panel display change analysis data, wherein the liquid crystal panel display change analysis includes color shift, brightness attenuation and response time; Step S14: using the LCD panel display change analysis data to perform an LCD panel dynamic image display aging test on the LCD panel dynamic image display interface to generate a first-order test result of the LCD panel; based on the first-order test result of the LCD panel, performing a display aging evaluation on the LCD panel display change analysis data to generate an LCD panel display aging evaluation data.

3. The liquid crystal panel aging test method according to claim 2, characterized in that: Randomly generating a dynamic image sequence for a liquid crystal panel display interface includes: Constructing an image material library; performing image enhancement on the images in the image material library to obtain an image enhancement material library, wherein the image enhancement includes color correction, blur processing, and reflected light simulation; Perform image label classification on the image enhancement material library to generate label images, and set the material generation probability for the label images to obtain probabilistic label images; set the sequence time length for the probabilistic label images to generate the probabilistic label image duration; Based on the duration of the probability label images, random image selection is performed on the probability label images to generate the law of image content change; a random number generator is used to combine the image display order of the probability label images according to the law of image content change, thereby generating a random sequence of dynamic images.

4. The liquid crystal panel aging test method according to claim 1, characterized in that: Step S2 includes the following steps: Step S21: performing a temperature and humidity cycle change test on the display interface of the liquid crystal panel according to the first sequence test result of the liquid crystal panel to generate a second sequence test result of the liquid crystal panel; Step S22: performing extreme test temperature screening on the second order test results of the liquid crystal panel to obtain extreme test temperature data; performing liquid crystal panel temperature distribution analysis on the liquid crystal panel display interface based on the extreme test temperature data to generate liquid crystal panel extreme temperature distribution data; Step S23: performing heat diffusion analysis on the display interface of the liquid crystal panel according to the extreme temperature distribution data of the liquid crystal panel, and generating liquid crystal panel display heat diffusion data; Step S24: Performing thermal management evaluation using the liquid crystal panel extreme temperature distribution data and the liquid crystal panel display heat diffusion data to generate liquid crystal panel thermal management aging evaluation data.

5. The liquid crystal panel aging test method according to claim 4, characterized in that: According to the first order test results of the LCD panel, the temperature and humidity cycle test of the LCD panel display interface includes: Set up a temperature and humidity control system, and perform high temperature environment setting, high humidity environment setting and low temperature environment setting on the temperature and humidity control system, and perform simulation cycle quantification on the set environment to generate a temperature and humidity control simulation cycle; Based on the temperature and humidity control simulation cycle, the LCD panel display interface is subjected to periodic simulation alternating cycles, each cycle is 48 hours, and at least 10 rounds of temperature and humidity cycle tests are completed; Under the above-mentioned temperature and humidity cycle test conditions, the panel performance of the LCD panel display interface is measured, and the screen brightness, color, and response time of the LCD panel display interface are simultaneously recorded to generate the second order test results of the LCD panel.

6. The liquid crystal panel aging test method according to claim 4, characterized in that: The temperature distribution analysis of the LCD panel display interface through extreme test temperature data includes: The panel surface and key areas of the LCD panel display interface are segmented by using extreme test temperature data to generate the LCD panel surface area and the LCD panel key area; the temperature of the LCD panel surface area and the LCD panel key area is scanned by using an infrared thermal imager to obtain a two-dimensional distribution map of the LCD panel area temperature; The temperature difference between adjacent areas of the two-dimensional temperature distribution diagram of the LCD panel area is calculated to generate temperature gradient data of adjacent areas; the balance of the panel surface temperature of the LCD panel display interface is evaluated based on the temperature gradient data of adjacent areas to generate extreme temperature distribution data of the LCD panel.

7. The liquid crystal panel aging test method according to claim 4, characterized in that: Step S23 includes the following steps: Step S231: acquiring steady-state temperature data of the liquid crystal panel display interface through the extreme temperature distribution data of the liquid crystal panel to obtain a steady-state test temperature of the liquid crystal panel display interface; discretizing the panel space region of the liquid crystal panel display interface according to the steady-state test temperature of the liquid crystal panel display interface to generate a panel space discretization region; Step S232: performing heat diffusion simulation on the panel space discretization area to generate panel area heat diffusion simulation temperature data; performing temperature contour map conversion on the panel area heat diffusion simulation temperature data to generate panel area surface temperature contour map; Step S233: Based on the heat conduction equation, the heat diffusion time of the panel area surface temperature contour map is estimated to obtain the panel surface heat diffusion time; wherein the heat conduction equation and the heat diffusion time estimation formula are as follows: In the formula, It is expressed as a heat conduction equation, α is the thermal diffusion coefficient of the material, is the Laplace operator of temperature, T is the temperature, t is the time, t steady It is represented as the heat diffusion time on the panel surface, and L is the length scale of the panel area; Step S234: Identify the heat diffusion area of ​​the LCD panel display interface according to the panel surface heat diffusion time and the panel area surface temperature contour map to generate heat diffusion area identification data; perform heat load concentration area analysis on the heat diffusion area identification data to generate LCD panel display heat diffusion data.

8. The liquid crystal panel aging test method according to claim 1, characterized in that: Step S3 includes the following steps: Step S31: collecting historical evaluation data of the liquid crystal panel display aging evaluation data and the liquid crystal panel thermal management aging evaluation data to obtain liquid crystal panel aging evaluation historical data; dividing the liquid crystal panel aging evaluation historical data into data sets to generate a model training set and a model test set; Step S32: training the model training set by a recurrent neural network algorithm to generate a pre-model for evaluating the aging state of a liquid crystal panel; optimizing and iterating the pre-model for evaluating the aging state of a liquid crystal panel by using a model test set, thereby generating a liquid crystal panel aging state evaluation model; Step S33: importing the first order test results of the liquid crystal panel and the second order test results of the liquid crystal panel into the liquid crystal panel aging state evaluation model to perform aging state evaluation, and generate liquid crystal panel global aging state evaluation data; Step S34: Perform independent panel area aging difference evaluation on the LCD panel according to the LCD panel aging status evaluation data to generate panel area aging local difference evaluation data; visualize the aging data of the LCD panel global aging status evaluation data and the panel area aging local difference evaluation data to perform the LCD panel aging test evaluation operation.

9. The liquid crystal panel aging test method according to claim 8, characterized in that: Based on the LCD panel aging status assessment data, the independent difference assessment of the panel area aging of the LCD panel includes: According to the aging status evaluation data of the liquid crystal panel, the liquid crystal panel is divided into four corners to generate the four corner division areas of the liquid crystal panel; the division corner points of the four corner division areas of the liquid crystal panel are confirmed to obtain the division corner points of the four corner areas; Connecting adjacent corner points of the four corner area division corner points to obtain an adjacent corner point connection area, and marking it as a liquid crystal panel edge division area; The core area of ​​the LCD panel is divided by the edge division area of ​​the LCD panel to generate the core division area of ​​the LCD panel; the global aging status assessment data of the LCD panel is evaluated by using the four corner division areas of the LCD panel, the edge division areas of the LCD panel and the core division areas of the LCD panel to perform independent difference evaluation of panel area aging to generate local difference evaluation data of panel area aging.

10. A liquid crystal panel aging test system, characterized in that: Used to perform the LCD panel aging test method according to claim 1, the LCD panel aging test system comprises: A display aging test module is used to obtain a liquid crystal panel display interface; perform dynamic image display on the liquid crystal panel display interface to generate a liquid crystal panel dynamic image display interface; perform a liquid crystal panel dynamic image display aging test on the liquid crystal panel dynamic image display interface based on a preset running display time to generate a first-order test result of the liquid crystal panel; perform a display aging evaluation on the liquid crystal panel display change analysis data based on the first-order test result of the liquid crystal panel to generate a liquid crystal panel display aging evaluation data; The temperature change cycle test module is used to perform a temperature and humidity cycle change test on the LCD panel display interface according to the first order test results of the LCD panel, and generate the second order test results of the LCD panel; perform a thermal management evaluation on the second order test results of the LCD panel, and generate thermal management aging evaluation data of the LCD panel; The comprehensive aging assessment module is used to perform model training on the display aging assessment data of the LCD panel and the thermal management aging assessment data of the LCD panel to generate an aging status assessment model for the LCD panel; import the first-order test results of the LCD panel and the second-order test results of the LCD panel into the LCD panel aging status assessment model to perform aging status assessment and generate global aging status assessment data for the LCD panel; perform independent difference assessment on the aging of the LCD panel in the panel area according to the aging status assessment data of the LCD panel to generate local difference assessment data on the aging of the panel area; and perform aging data visualization on the global aging status assessment data of the LCD panel and the local difference assessment data on the aging of the panel area to perform LCD panel aging test assessment operations.

Images