LED display screen field correction method and related device

Abstract

The invention discloses an LED display screen field correction method and a related device, and relates to the technical field of display, and the method comprises the steps: carrying out the preliminary detection of a plurality of LED units, and recording the initial display parameters of the plurality of LED units; determining a target display parameter of the whole screen; adjusting and calculating the plurality of LED units to obtain a parameter adjusting scheme of the plurality of LED units; collecting life cycle data of the plurality of LED units and analyzing the life cycle data, and respectively determining predicted residual life of the plurality of LED units under the parameter adjustment scheme; screening out a plurality of target LED units of which the predicted residual life is within a preset durability range; and performing point-by-point correction on the target LED unit based on the parameter adjustment scheme. By implementing the method, residual life prediction and accurate correction are performed on different batches of LED units, so that reasonable utilization of the tail LEDs is realized, a display screen shows better performance uniformity and longer service life, and user experience is improved.

Description

Technical Field

[0001] The present application relates to the field of display technology, and in particular to an on-site calibration method for an LED display screen and related devices. Background Art

[0002] In the LED display industry, display uniformity and color fidelity are key indicators of product quality. However, leftover LED displays—those left over from inventory or production cycles—often exhibit variations in brightness and color. Effectively utilizing these leftovers, minimizing waste and reducing costs while maintaining display quality, has become a pressing issue in actual sales and use.

[0003] To address color differences in LED displays, the industry has developed a series of point-by-point calibration technologies. Point-by-point calibration of individual LED cabinets is performed on the production line to ensure a high degree of uniformity for each cabinet before shipment. On-site point-by-point calibration of large-screen displays occurs after the LED display is installed, selecting a suitable viewing position to calibrate the entire display to ensure optimal viewing quality at the actual viewing location.

[0004] However, most relevant point-by-point calibration technologies adjust the physical properties of LED screens without fully accounting for the lifespan variations between different batches of LED units. Due to the discontinuous manufacturing timelines of leftover LED units, component aging and remaining lifespans often vary. Even if color and brightness consistency is achieved after initial calibration, these corrections may be lost over time due to differences in aging rates, leading to divergent results over long-term use, reducing the overall lifespan of the display and the user experience. Summary of the Invention

[0005] The present application provides an on-site calibration method and device for an LED display screen. By predicting the remaining life and accurately calibrating LED units from different batches, the rational utilization of leftover LEDs is achieved, so that the display screen exhibits better performance uniformity and longer service life, thereby improving the user experience.

[0006] In the first aspect, the present application provides an on-site calibration method for an LED display screen, which is applied to a calibration device, and the method includes: performing preliminary detection on multiple LED units and recording the initial display parameters of the multiple LED units; determining the target display parameters of the overall screen based on a preset display requirement threshold of the finished LED display screen; performing adjustment calculations on the multiple LED units to obtain a parameter adjustment scheme for the multiple LED units from the initial display parameters to the target display parameters; collecting and analyzing the life cycle data of the multiple LED units, and determining the predicted remaining life of the multiple LED units under the parameter adjustment scheme; the life cycle data includes usage time, brightness attenuation, color shift, and current change; screening out multiple target LED units whose predicted remaining life is within a preset durability range; based on the parameter adjustment scheme, performing point-by-point calibration on the target LED units so that the display parameters of the target LED display screen composed of the multiple target LED units reach the target display parameters.

[0007] In the above embodiment, the calibration device performs preliminary testing on multiple LED units and records the initial display parameters to determine the target display parameters for the entire screen. It then calculates the parameter adjustment plan for each LED unit and analyzes the remaining lifespan of the LED units under the adjustment plan in combination with their lifecycle data. The device then selects target LED units with a remaining lifespan within an acceptable range and then performs precise point-by-point calibration on these target LED units to achieve the desired display effect for the target LED display. This method fully considers the performance and lifespan differences between different batches of LED units. By predicting the remaining lifespan, it achieves the rational utilization of unsold LEDs, avoids unnecessary losses that may result from over-calibration, and ensures the long-term stable display performance of the display.

[0008] In combination with some embodiments of the first aspect, in some embodiments, adjustment calculations are performed on multiple LED units to obtain parameter adjustment schemes for the multiple LED units from initial display parameters to target display parameters, specifically including: establishing a light attenuation model for each LED unit; using the light attenuation model to calculate the light attenuation degree of the LED unit; and using a recursive algorithm to reversely calculate, based on the light attenuation degree of the LED unit, the initial display parameters, and the target display parameters, to obtain the driving current adjustment amount required for the LED unit to reach the target display parameters, as the parameter adjustment scheme for the LED unit.

[0009] In the above embodiment, the calibration device establishes a light attenuation model for each LED unit, calculates the degree of light attenuation, and then uses recursive inverse calculation to determine a drive current adjustment solution that meets the target parameters. This calculation method accurately assesses the aging condition and calibration requirements of each LED unit, facilitating the development of precise and feasible parameter adjustment solutions, thereby guiding subsequent precise calibration.

[0010] In combination with some embodiments of the first aspect, in some embodiments, life cycle data of multiple LED units are collected and analyzed to determine the predicted remaining lifespan of the multiple LED units under the parameter adjustment scheme, specifically including: reading the life cycle data of each LED unit, including the factory time, transportation time, storage time, and usage time, and establishing a life cycle database; statistically analyzing the average failure rate curves of LED units from different batches; using a two-parameter Weibull distribution model to calculate the predicted failure probability distribution of the LED unit based on the life cycle data of the LED unit, the batch to which it belongs, and the parameter adjustment scheme; and calculating the predicted remaining service life of the LED unit by combining the predicted failure probability distribution, the average failure rate curve, and the usage time of the LED unit.

[0011] In the above-mentioned embodiment, the calibration device establishes a lifecycle database, combines it with a two-parameter Weibull distribution model to calculate the failure probability distribution, and considers the average failure rate curve to calculate the remaining useful life. This prediction method fully utilizes the lifecycle data of LED units and employs a scientific and systematic statistical analysis method to accurately estimate the remaining useful life of different batches of LED units, providing a reliable basis for their subsequent effective utilization.

[0012] In combination with some embodiments of the first aspect, in some embodiments, after the step of performing point-by-point correction on the target LED unit based on the parameter adjustment scheme, the method also includes: calculating the average predicted remaining life of the target LED display screen based on the predicted remaining life of the target LED unit; determining whether the average predicted remaining life is lower than a preset expected threshold; if the average predicted remaining life is lower than the preset threshold, automatically generating multiple LED unit layout schemes based on the predicted remaining life using a genetic algorithm; scoring the multiple LED unit layout schemes based on a preset evaluation model combining uniformity and heat dissipation performance to obtain scoring results; and selecting the layout scheme with the highest scoring result as the final layout scheme of the target LED display screen.

[0013] In the above-mentioned embodiment, the calibration device calculates the average predicted remaining lifespan of the target LED display and determines whether it falls below a desired threshold. If so, a genetic algorithm is used to generate multiple layout options. These options are then scored based on an evaluation model to select the optimal one. This approach leverages the initial lifespan predictions for each LED unit, dynamically monitoring the overall health of the display and further extending its lifespan beyond the initial calibration. Furthermore, the multiple layout options generated by the genetic algorithm and the scoring and screening by the evaluation model make layout optimization more intelligent and comprehensive.

[0014] In combination with some embodiments of the first aspect, in some embodiments, after the step of performing point-by-point correction on the target LED unit based on the parameter adjustment scheme, the method also includes: using a surface fitting algorithm to simulate and predict the position distribution of future content key areas based on the preset actual content playback data of the target LED display screen, and obtain a predicted content key area distribution surface; calculating the gradient direction and gradient magnitude of the content key area distribution surface to determine the boundary of the content key area; traversing the position coordinates of all LED units to determine that the LED unit in the content key area is the central LED unit, and the LED units in the remaining area are edge LED units; sorting multiple target LED units from high to low according to the predicted remaining lifespan, and dividing the central LED units and edge LED units according to the sorting results.

[0015] In the above embodiment, the calibration device predicts the distribution of hotspots within the display content, distinguishing between central and peripheral areas. It then allocates LED units in descending order of predicted lifespan, placing LED units with longer lifespans within the content hotspots. This layout ensures optimal protection and utilization of LED units in key areas of the display, preventing premature aging in these areas and extending the display's stable performance.

[0016] In combination with some embodiments of the first aspect, in some embodiments, after the step of performing point-by-point correction on the target LED unit based on the parameter adjustment scheme, the method further includes: collecting actual usage environment parameters of the target LED display screen, including temperature distribution, illuminance distribution, and usage frequency; based on the temperature model and the illuminance model, correcting the predicted remaining life of multiple target LED units to obtain a corrected life distribution result; and re-planning the layout of multiple target LED units on the target LED display screen based on the corrected life distribution result.

[0017] In the above-described embodiment, the calibration device is capable of real-time detection and collection of display screen environmental parameters, such as temperature distribution, illuminance distribution, and frequency of use. Based on the temperature and illuminance models, the predicted remaining lifespan of each LED unit is corrected, resulting in a revised lifespan distribution. The layout of the LED units on the display screen is then replanned based on this revised lifespan distribution. This technical solution fully considers the actual impact of the operating environment on the lifespan of LED units and can adjust the layout plan in real time based on environmental changes, making the utilization of LED units more efficient and effective, thereby achieving long-term stability in the display effect.

[0018] In combination with some embodiments of the first aspect, in some embodiments, the layout of multiple target LED units on the target LED display screen is re-planned based on the corrected lifetime distribution results, specifically including: reading the corrected predicted remaining lifetime data of each target LED unit; using an iterative sorting algorithm to sort all target LED units from high to low according to the corrected predicted remaining lifetime to obtain a priority sorting result; determining the key areas of the display content according to the usage scenario of the target LED display screen, and counting the number of LED units in each area; based on the number requirements of the LED units in the key areas of the display content, sequentially allocating them according to the priority sorting results; using a greedy algorithm, on the premise of meeting the allocation requirements, optimizing the position distribution of the LED units in each area, so that LED units with similar predicted lifetimes in the same area are in adjacent positions, to obtain the final layout plan.

[0019] In the above-mentioned embodiment, the calibration device replans the layout based on the corrected lifetime distribution results. The technical process includes reading the corrected lifetime of each LED unit, iteratively sorting to determine the priority, determining the key areas and LED quantity requirements based on the display content, and then allocating the LED units to each area in order of priority. Furthermore, a greedy algorithm is used to further optimize the distribution of LED positions within the area, placing LED units with similar lifetimes adjacent to each other. In this way, the service life of each LED unit can be maximized while meeting the display content requirements.

[0020] In a second aspect, an embodiment of the present application provides a correction device, which includes: a preliminary test module for performing preliminary detection on multiple LED units and recording the initial display parameters of the multiple LED units; a target determination module for determining the target display parameters of the entire screen based on a preset display requirement threshold of the finished LED display screen; a scheme determination module for performing adjustment calculations on the multiple LED units to obtain parameter adjustment schemes for the multiple LED units from the initial display parameters to the target display parameters; a life prediction module for collecting and analyzing the life cycle data of the multiple LED units, and determining the predicted remaining life of the multiple LED units under the parameter adjustment scheme; the life cycle data includes usage time, brightness attenuation, color shift and current change; a unit screening module for screening out multiple target LED units whose predicted remaining life is within a preset durability range; a unit adjustment module for performing point-by-point correction on the target LED units based on the parameter adjustment scheme, so that the display parameters of the target LED display screen composed of the multiple target LED units reach the target display parameters.

[0021] In a third aspect, an embodiment of the present application provides a correction device, comprising: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the correction device to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer program product comprising instructions, which, when the computer program product is run on a correction device, enables the correction device to execute the method described in the first aspect and any possible implementation of the first aspect.

[0023] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium comprising instructions, which, when executed on a correction device, enables the correction device to execute the method described in the first aspect and any possible implementation of the first aspect.

[0024] It is understandable that the calibration devices provided in the second and third aspects, the computer program product provided in the fourth aspect, and the computer storage medium provided in the fifth aspect are all used to execute the methods provided in the embodiments of the present application. Therefore, the beneficial effects that can be achieved can be referenced to the beneficial effects of the corresponding methods and will not be repeated here.

[0025] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: 1. By conducting preliminary inspections on multiple LED units and recording initial display parameters, determining the target display parameters of the entire screen, and calculating the parameter adjustment plan for each LED unit, the remaining lifespan of the LED unit under the adjustment plan is analyzed in combination with the life cycle data of the LED unit, and the target LED units with a remaining lifespan within an acceptable range are screened out. Finally, these target LED units are accurately corrected point by point to achieve the expected display effect for the target LED display. Therefore, the performance and lifespan differences between LED units in different batches can be fully considered, and the reasonable utilization of the leftover LEDs is achieved through the remaining lifespan prediction, thus avoiding unnecessary losses that may be caused by over-correction, ensuring the long-term stable display performance of the display, and effectively solving the problem of shortened display service life due to the failure to consider batch differences and remaining lifespan in the existing technology, thereby achieving the effective reuse of leftover LEDs and extending the service life of the display.

[0026] 2. By reading the life cycle data of each LED unit, including the factory time, transportation time, storage time, and usage time, and establishing a life cycle database, the two-parameter Weibull distribution model is used to calculate the failure probability distribution, and the average failure rate curve is taken into account to calculate the remaining service life. Therefore, the life cycle data of the LED unit can be fully utilized. A scientific and systematic statistical analysis method is adopted to accurately evaluate the remaining service life of different batches of LED units, providing a reliable basis for subsequent effective utilization. This effectively solves the problem of inaccurate estimation of the remaining service life of LED units due to insufficient consideration of life cycle data in the existing technology, and thus realizes accurate prediction of the remaining service life of different batches of LED units.

[0027] 3. Due to the adoption of the collection of actual usage environment parameters of the target LED display including temperature distribution, illumination distribution, and usage frequency, the predicted remaining life of each LED unit is corrected based on the temperature model and illumination model to obtain a corrected new life distribution result, and then the layout of each LED unit on the display is replanned according to the corrected life distribution result. Therefore, the actual impact of the usage environment on the life of the LED unit can be fully considered, and the layout plan can be adjusted in real time according to environmental changes, so that the utilization of the LED unit is more reasonable and efficient, thereby achieving long-term stability of the display effect, and effectively solving the problem of unreasonable layout plan caused by not considering the impact of the usage environment changes on the LED unit in the existing technology, thereby realizing the LED unit layout plan dynamically adjusted based on the usage environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a flow chart of the on-site calibration method for an LED display screen according to an embodiment of the present application; Figure 2 This is another flow chart of the on-site calibration method for an LED display screen according to an embodiment of the present application; Figure 3 This is a schematic diagram of a functional module structure of a correction device in an embodiment of the present application; Figure 4 This is a schematic diagram of the physical device structure of the correction device in the embodiment of the present application. DETAILED DESCRIPTION

[0029] The terms used in the following examples of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification of the present application, the singular expressions "a", "an", "above", "the", and "this" are intended to include plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations of one or more of the listed items.

[0030] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood to imply or suggest relative importance or implicitly indicate the number of the technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of this application, unless otherwise specified, "plurality" means two or more.

[0031] For ease of understanding, the application scenarios of the embodiments of the present application are introduced below.

[0032] A sports stadium needed to purchase an ultra-large curved LED display to broadcast live game content and provide interactive audience information. However, due to a limited budget and the need to control costs, they decided to combine remaining stock LED displays from different suppliers. However, these LED units, due to different production batches, exhibited variations in brightness and color temperature. Directly combining these units would result in noticeable unevenness across the entire display, severely impacting the visual quality. The stadium operator urgently needed to address the issue of how to effectively utilize these remaining stock LED displays while ensuring cost control and achieving a uniform display quality.

[0033] In the related art, the display uniformity of LED displays can be improved by performing point-by-point calibration on the production line or at the installation site. However, these point-by-point calibration methods do not take into account the differences in service life between different batches of LED units.

[0034] The following describes a scenario where the on-site calibration method for an LED display screen in the related art is used.

[0035] The stadium operator initially planned to achieve the same brightness and color temperature across different batches of LED units by increasing the drive current. However, in actual use, they discovered that due to the varying degrees of aging of LED units across batches, even if initially adjusted to achieve uniformity, the varying aging rates of the LED units over time led to variations in display quality, making it impossible to achieve truly stable, long-term display uniformity.

[0036] By adopting the on-site calibration method for LED display screens in the embodiment of the present application, the remaining service life of LED units from different batches is predicted, and the display parameters of LED units with similar service life are accurately adjusted. This can not only effectively utilize the leftover LEDs and achieve short-term uniformity of the display effect, but also take into account the service life differences caused by batch differences, thereby ensuring long-term display stability.

[0037] The following describes the scenarios in which the on-site calibration method for LED displays in this application is used.

[0038] Later, the stadium operator adopted the on-site calibration solution for LED displays proposed in this application. This solution predicted the lifespan of LED units from different batches, calculated the remaining useful life of each unit, and then fine-tuned parameters to achieve a uniform display effect for units with similar remaining lifespans. This approach not only utilized leftover LEDs but also accounted for the varying aging rates caused by batch differences, ensuring the display's stability over extended periods of use.

[0039] It can be seen that by adopting the method in the embodiment of the present application, while achieving display uniformity, it can also effectively solve the problem of life span differences of LED units in different batches, thereby achieving efficient utilization of leftover LEDs and improving the long-term stability of the display screen.

[0040] For ease of understanding, the following describes the process of the method provided by this implementation in combination with the above scenario. Figure 1 , which is a flow chart of the on-site calibration method for an LED display screen in an embodiment of the present application.

[0041] S101 , performing preliminary detection on multiple LED units and recording initial display parameters of the multiple LED units.

[0042] The calibration equipment will perform preliminary inspections on multiple LED units and record the initial display parameters of the multiple LED units. Specifically, the calibration equipment will use a built-in image sensor to capture image information of the multiple LED units to be inspected in their initial state, and use a spectrometer to measure the initial color coordinates, brightness parameters, and other parameters of each LED unit. These initial parameters are then recorded to establish an initial parameter database for each LED unit, which may include parameters such as LED batch information, production date, LED model specifications, initial brightness, initial color temperature, and initial color difference. These parameters will lay the foundation for subsequent display target parameter determination and calibration calculations. For example, if a large brightness deviation is detected between different batches of LED units, the subsequent target brightness setting will need to take into account the differences between the different batches and adopt a regional target brightness setting method. After this step is completed, the calibration equipment has obtained the initial performance parameters of each LED unit.

[0043] S102: Determine target display parameters of the entire screen based on a preset display requirement threshold of the finished LED display screen.

[0044] The calibration equipment determines the target display parameters for the entire screen based on the preset display requirement thresholds of the finished LED display. After obtaining the initial parameters for each LED unit, the calibration equipment determines the target performance parameters for the entire screen after calibration, based on the display's usage requirements and the expected display performance indicators. These target parameters may include target brightness, target color temperature, and target uniformity. Setting these target parameters requires reference to the display product specifications, which generally specify the performance thresholds to be achieved, such as the color difference threshold to be less than or the brightness uniformity standard deviation to be within a certain range. The calibration equipment reads the display requirement thresholds from these product specifications and uses them as the basis for setting the target parameters. Furthermore, if the initial parameters of LED units vary significantly across batches, the target parameters can be set in a zoned manner. For example, to address uneven brightness, a higher target brightness value can be set for the group of initially bright LED units. Properly setting target parameters is crucial for subsequent calibration calculations and effectiveness.

[0045] S103 , performing adjustment calculations on the multiple LED units to obtain parameter adjustment schemes for the multiple LED units from initial display parameters to target display parameters.

[0046] The calibration equipment will perform adjustment calculations on multiple LED units to obtain parameter adjustment schemes for multiple LED units from initial display parameters to target display parameters. After determining the target display parameters of the entire screen, the calibration equipment needs to obtain the driving scheme required for each LED unit to adjust from the current initial parameters to the target parameters. This scheme may include adjustments to the size of the LED driving current, adjustments to the PWM duty cycle, etc. The calculation method usually requires the establishment of a light attenuation model, considering the effects of current size, usage time, and temperature factors on LED light attenuation, and then combining the initial parameters, target parameters, and the light attenuation model, using a recursive algorithm to reversely calculate and obtain the driving current or PWM scheme that meets the target parameters. In this way, parameter fine-tuning schemes for each LED unit can be obtained. These schemes guide subsequent precise calibrations, so that the LED units are adjusted from the initial state to the target state, achieving the target display effect of the entire screen.

[0047] It's important to note that the light attenuation model is a model of the luminous decay trend of LED units. It comprehensively considers the impact of factors such as drive current, operating time, and temperature on the LED's luminous performance. By simulating the LED's operating environment and aging, it establishes a relationship between these factors and the amount of luminous decay. This model accepts LED operating parameters as input and simulates and predicts the output LED's light decay. The purpose of this model is to assess the LED's luminous decay trend and provide a basis for subsequent dimming corrections.

[0048] S104 : Collect and analyze life cycle data of multiple LED units to determine predicted remaining lifespans of the multiple LED units under the parameter adjustment scheme.

[0049] The calibration equipment collects and analyzes lifecycle data from multiple LED units to determine the predicted remaining lifespan under the parameter adjustment scheme. This calibration equipment needs to account for performance aging variations among different batches of LED units due to differences in manufacturing time. To this end, the equipment collects complete lifecycle data for each LED unit, from factory to field use, including production date, transportation duration, storage duration, and usage time, to establish a lifecycle database. Statistical analysis is also performed on the average failure rate curves for different LED batches. Based on this data, a two-parameter Weibull distribution model is used to calculate the predicted failure probability (RLL) for each LED under the parameter adjustment scheme, i.e., the predicted RLL. This approach comprehensively considers factors such as lifecycle data, batch number, and the impact of the parameter adjustment scheme on accelerated aging of the LEDs. This allows for a comprehensive assessment of the RLL across batches, providing a basis for subsequent LED selection and use.

[0050] It's important to note that the two-parameter Weibull distribution model is a statistical distribution model for predicting LED failure probability. It takes into account both the LED's lifetime and the average failure rate curve of its batch. It accepts LED lifecycle data and a batch failure rate curve as input and outputs the failure probability distribution of that individual LED over its future lifetime, known as the lifetime distribution model. This model can reflect the impact of batch variations on the failure rate of individual LEDs and can be used to accurately predict LED failure probability.

[0051] S105 , screening out a plurality of target LED units whose predicted remaining lifespans are within a preset durability range.

[0052] The calibration equipment will select multiple target LED units whose predicted remaining lifespans are within a preset durability range. Based on the predictions from the previous step, the calibration equipment can determine the corresponding remaining lifespan distribution for each LED after parameter adjustment. Then, a threshold range for lifespans can be preset based on the project's usage requirements, such as a range of 1-2 years of continued use. LEDs with predicted lifespans greater than this threshold range are selected as target LED units. This is because after parameter adjustment, the remaining lifespans of these LEDs still meet usage requirements and are therefore suitable for calibration. LEDs predicted to soon wear out and become scrapped can be directly eliminated and no longer used to avoid over-calibration. In this way, through the prediction, analysis, and screening of remaining lifespans, LED usage becomes more rational and efficient.

[0053] S106 , based on the parameter adjustment scheme, calibrate the target LED unit point by point, so that the display parameters of the target LED display screen composed of multiple target LED units reach the target display parameters.

[0054] Based on the parameter adjustment plan, the calibration equipment will perform point-by-point calibration on the target LED units, ensuring that the target LED display screen achieves the target display effect. After obtaining the target LED units, the calibration equipment will perform precise point-by-point calibration on these selected LEDs according to the previously determined parameter adjustment plans for each LED. This may require adjusting the LED drive current or PWM duty cycle, and adjusting the parameters individually through the controller or driver chip until the LED units meet the target parameter requirements, such as target brightness and target color temperature. After point-by-point calibration, the screen composed of the target LED units can achieve the overall target display effect, and the calibration is complete. This process fully utilizes the results of the previous calculations and analysis to perform targeted calibration, avoid over-adjustment, and ensure calibration efficiency.

[0055] In the above embodiment, by predicting the remaining life of each LED unit, fine-tuning is performed on LED units with similar lifespans to achieve a uniform display effect. In practical applications, the impact of the operating environment, such as temperature and humidity, can be further considered. An environmental impact model can be established to dynamically assess and correct the remaining life of each LED unit, thereby more accurately planning the use of LED units.

[0056] The following is a supplement to the scenario of this embodiment.

[0057] After implementing this solution, stadium operators also combined actual environmental data, such as temperature, humidity, and frequency of use, to build an environmental impact model. This model dynamically assessed and corrected the remaining life of each LED unit, and optimized the layout of LED units accordingly, placing LEDs with similar lifespans adjacent to each other. This further improved the stability of the display and maximized the lifespan of the display.

[0058] It's important to note that the environmental impact model considers the effects of the operating environment on LEDs. It collects data on environmental parameters such as temperature, humidity, and illumination to establish a relationship between these factors and LED lifespan. This model accepts the LED's environmental parameters as input and outputs the degree of impact of these factors on LED lifespan. The purpose of this model is to assess the impact of environmental factors on LED lifespan after use and to facilitate subsequent correction and optimization.

[0059] After combining the above scenarios, the following is a more detailed description of the process of the method provided by this implementation. Figure 2 , is another flow chart of the on-site calibration method for an LED display screen in an embodiment of the present application.

[0060] S201: Perform preliminary detection on multiple LED units and record initial display parameters of the multiple LED units.

[0061] Referring to step S101 , the calibration device performs preliminary detection on the plurality of LED units and records the initial display parameters of the plurality of LED units.

[0062] S202: Determine target display parameters of the entire screen based on a preset display requirement threshold of the finished LED display screen.

[0063] Referring to step S102 , the calibration device determines target display parameters of the entire screen.

[0064] S203 , performing adjustment calculations on the multiple LED units to obtain parameter adjustment schemes for the multiple LED units from initial display parameters to target display parameters.

[0065] Referring to step S103 , the calibration device calculates and obtains a parameter adjustment solution.

[0066] In some embodiments, the calibration device establishes a light attenuation model for each LED unit; and then uses the light attenuation model to calculate the light attenuation degree of the LED unit; based on the light attenuation degree of the LED unit, the initial display parameters and the target display parameters, a recursive algorithm is used to reversely calculate the driving current adjustment amount required for the LED unit to achieve the target display parameters, as a parameter adjustment solution for the LED unit.

[0067] Specifically, the calibration equipment first creates a light attenuation model for each LED unit. Over long-term use, LEDs gradually lose their luminous effectiveness due to factors such as current driving and temperature. To assess the light attenuation of each LED, a light attenuation model is created for each unit. This model considers various factors that influence light attenuation and simulates the LED's light attenuation process.

[0068] The light decay model then comprehensively considers the effects of current, age, and temperature on LED luminescence. The driving current directly affects the operating state of the LED chip; age causes aging of the internal material structure; and high temperatures accelerate the decay of the LED. The light decay model incorporates these important factors to establish the relationship between current, age, temperature, and light decay.

[0069] Next, the calibration equipment calculates the light attenuation of each LED unit based on a light attenuation model. By inputting the specific operating environment parameters of each LED into the light attenuation model, the light attenuation of that LED at that moment can be simulated and calculated. The light attenuation of LEDs from different batches and locations can vary significantly.

[0070] The calibration equipment then obtains the initial and target display parameters for each LED. The initial parameters are derived from the preliminary test results, while the target parameters are preset based on the display requirements.

[0071] Finally, the calibration equipment uses a recursive algorithm to reverse-calculate the drive current adjustment required to meet the target parameters based on the light attenuation level and the initial target parameters. This algorithm then uses the recursive algorithm to calculate the required drive current adjustment required to meet the target parameters. This calculation method accurately provides an adjustment plan for each LED unit, providing a basis for subsequent precise calibration.

[0072] S204: Read the life cycle data of each LED unit, including the factory time, transportation time, storage time, and usage time, and establish a life cycle database.

[0073] The calibration equipment reads the lifecycle data of each LED unit, including its manufacturing date, transportation time, storage time, and usage time, to build a lifecycle database. This data is collected from the complete lifecycle of each LED unit, from the factory to the field. This information is crucial for determining the LED's aging condition. For example, the manufacturing date can be determined from the LED's ID identifier; transportation time can be calculated from logistics information; storage time can be calculated from storage records obtained from the warehousing system; and usage time can be analyzed from usage information. This lifecycle data is then compiled into a database, providing the foundation for subsequent wear and tear analysis. Lifecycle information can vary significantly between batches of LEDs due to differences in manufacturing time and storage conditions.

[0074] S205 , calculating average failure rate curves of LED units from different batches.

[0075] The calibration equipment calculates the average failure rate curves for different batches of LED units. After acquiring the lifecycle data for each LED unit, the calibration equipment then analyzes the failure rate curve models for each batch of LEDs. This model is trained based on historical operating data to determine the average failure rate trends of different batches of LEDs over time. These failure rate curves reflect reliability differences between batches and provide an important basis for predicting the failure rate of individual LEDs. For example, a steeper average failure rate curve for a batch of LEDs indicates poor reliability and more serious quality issues.

[0076] It's important to note that the failure rate curve model is a model that tracks the average failure rate trends of LEDs within a batch. It statistically analyzes a large amount of historical operating data from that batch of LEDs to find the average trend curve of LED failure rates over time. This model reflects the reliability differences between batches of LEDs and can provide a basis for predicting the failure rates of individual LEDs.

[0077] S206 , calculating the predicted failure probability distribution of the LED unit using a two-parameter Weibull distribution model based on the life cycle data, the batch to which the LED unit belongs, and the parameter adjustment plan.

[0078] The calibration equipment uses a two-parameter Weibull distribution model to calculate the predicted failure probability distribution of each LED unit based on the unit's lifecycle data, batch, and parameter adjustment plan. After obtaining the lifecycle data and the average failure rate curve, the future failure probability distribution of each individual LED can be calculated. This calculation uses a two-parameter Weibull distribution model, taking into account the LED's age and the corresponding failure rate curve for its batch. This model can then simulate and predict the failure probability distribution of the LED over its future service life, known as its lifetime distribution. This provides the mathematical model for the next step in lifetime analysis.

[0079] S207 , calculating the predicted remaining service life of the LED unit by combining the predicted failure probability distribution, the average failure rate curve, and the usage time of the LED unit.

[0080] The calibration equipment calculates the predicted remaining useful life of the LED unit by combining the predicted failure probability distribution, the average failure rate curve, and the LED unit's age. Based on the failure probability distribution model obtained in the previous step, the cumulative distribution function of the failure probability of the LED over time is calculated. When the cumulative probability reaches a threshold, the predicted remaining useful life of the LED is estimated. This prediction, which comprehensively considers both the failure probability distribution and the average failure rate curve, provides a relatively accurate prediction of the remaining useful life of an individual LED.

[0081] It should be noted that the failure probability distribution model calculates the failure probability of individual LEDs based on a statistical distribution algorithm. Based on the predicted lifetime distribution of an LED, it calculates the cumulative distribution function of the failure probability of that LED over its future lifespan. This model can assess the failure probability of a single LED and predict when LED failures will occur.

[0082] S208 , screening out a plurality of target LED units whose predicted remaining lifespans are within a preset durability range.

[0083] Referring to step S105 , the calibration device screens out a plurality of target LED units.

[0084] S209 , based on the parameter adjustment scheme, calibrate the target LED unit point by point, so that the display parameters of the target LED display screen composed of multiple target LED units reach the target display parameters.

[0085] Referring to step S106 , the calibration device calibrates the target LED unit point by point.

[0086] In some embodiments, the correction device calculates the average predicted remaining life of the target LED display based on the predicted remaining life of the target LED unit; determines whether the average predicted remaining life is lower than a preset expected threshold; if the average predicted remaining life is lower than the preset threshold, a genetic algorithm is used to automatically generate multiple LED unit layout schemes based on the predicted remaining life; based on a preset evaluation model that combines uniformity and heat dissipation performance, the multiple LED unit layout schemes are scored to obtain scoring results; and the layout scheme with the highest scoring result is selected as the final layout scheme of the target LED display.

[0087] It's important to note that the evaluation model comprehensively scores LED unit layout options. It considers various factors, such as layout uniformity, thermal distribution, and density, and establishes a scoring system to assign a score to each layout option. The model accepts different layout options as input and outputs quality scores for each, which are then used to select the best layout options.

[0088] Specifically, the calibration equipment first calculates the average predicted remaining lifespan of the target LED display based on the predicted remaining lifespan of the target LED units. After calibrating the parameters of each LED unit, the equipment obtains the predicted remaining lifespan data for each LED unit. To assess the overall health of the display, the predicted lifespan values ​​of all LED units are tallied and the average predicted remaining lifespan of the display is calculated. This provides an indication of the overall service life of the display. For example, if the calculated average lifespan is only one year, the display is generally in a relatively aged state and requires further processing.

[0089] The calibration device then determines whether the average predicted remaining lifespan is below a preset threshold. After calculating the average predicted lifespan, it is compared with a preset threshold to determine if it is too low. This threshold can be set based on project requirements, for example, to 2 years. If the calculated result is below this threshold, the display's overall health is poor and its lifespan will not meet the required requirements.

[0090] Next, if the average lifetime falls below a threshold, the calibration device automatically generates multiple LED unit layout plans using a genetic algorithm based on the predicted lifetime data for each LED unit. For situations where lifetimes are too low, optimization can be achieved by changing the layout of the LED units. The device then applies the genetic algorithm to generate multiple different layout plans, each containing a different layout pattern for the LED units. Through operations such as selection, crossover, and mutation, the genetic algorithm quickly converges to produce multiple candidate layout plans of varying quality.

[0091] The calibration equipment then scores each layout solution based on a pre-set evaluation model. This model considers multiple factors, such as layout uniformity and inter-unit heat dissipation, to comprehensively evaluate each candidate solution. This allows the quality of each layout solution to be measured from multiple perspectives.

[0092] In some embodiments, the correction device will use a surface fitting algorithm to simulate and predict the position distribution of future content key areas based on the preset actual content playback data of the target LED display screen, and obtain a predicted content key area distribution surface; calculate the gradient direction and gradient magnitude of the content key area distribution surface to determine the boundary of the content key area; traverse the position coordinates of all LED units, determine that the LED unit in the content key area is the center LED unit, and the LED units in the remaining area are edge LED units; sort multiple target LED units from high to low according to the predicted remaining lifespan, and divide them into center LED units and edge LED units according to the sorting results.

[0093] Specifically, the calibration device first uses a surface fitting algorithm to simulate and predict the future location distribution of key content areas based on the preset actual content playback data of the target LED display, thereby generating a predicted distribution surface for key content areas. In actual use, the layout of displayed content on a display is not fixed, with hotspots distributed across different areas. To evaluate these hotspots, the device uses a surface fitting algorithm, inputs the preset actual content playback data, and predicts the two-dimensional coordinate distribution of key content areas, ultimately simulating a distribution surface for key content areas.

[0094] The calibration device then calculates the gradient direction and magnitude of the distribution surface of the key content area to determine the boundaries of the key content area. Based on the predicted distribution surface, the gradient vector on the surface is calculated. The gradient direction represents the diffusion direction of the key content area, and the gradient magnitude represents the degree of content emphasis. Based on the changes in the gradient magnitude, the boundaries of the key content area are determined.

[0095] Next, the calibration device traverses the coordinates of all LED units, identifying those in the content-focused area as center LED units and those in the remaining areas as edge LED units. The device compares the coordinates of each LED on the display screen with the boundaries of the content-focused area to determine whether each LED belongs to the center or edge area, and then classifies it.

[0096] The calibration equipment then sorts the target LED units by predicted remaining lifespan from high to low, and uses this ranking to assign them to central and peripheral LED units. This means that LEDs with longer lifespans are prioritized for placement in key areas, while those with shorter lifespans are placed in less critical areas, effectively allocating limited LED resources.

[0097] Finally, by evaluating the display content area and sorting the LED units, the calibration equipment can enable LED units with longer lifespans to be used in areas where the display content is more concentrated, extending the service life of key areas of the display and avoiding localized degradation of display quality.

[0098] S210 , collecting actual usage environment parameters of the target LED display screen including temperature distribution, illumination distribution, and usage frequency.

[0099] The calibration equipment will collect the actual usage environment parameters of the target LED display, including temperature distribution, illumination distribution, and usage frequency. After completing the initial calibration of the LED unit, the performance and life of the LED unit may be affected due to changes in the actual usage environment. Therefore, the calibration equipment also needs to monitor the usage environment in real time as a basis for subsequent optimization. Specifically, it will collect temperature distribution data within the display area to monitor changes in the thermal environment during operation; collect the distribution of ambient light intensity to determine whether light aging has occurred; and count usage frequency parameters to analyze the impact of workload on LEDs. The collection of these actual environmental parameters can be obtained through temperature sensors, photoresistors, usage logs, etc., and is used to evaluate the comprehensive impact of the usage environment on LEDs.

[0100] S211 , based on the temperature model and the illumination model, correct the predicted remaining lifetimes of the plurality of target LED units to obtain a corrected lifetime distribution result.

[0101] The calibration equipment then modifies the predicted remaining lifespan of multiple target LED units based on temperature and illumination models, producing a revised lifetime distribution. By combining the collected environmental parameter data with pre-established temperature and illumination models, it assesses the environmental impact of LED lifespan and corrects previous predictions that only account for batch variations. For example, prolonged exposure to high temperatures can shorten LED lifespan, while prolonged exposure to strong light can accelerate LED aging. The calibration equipment then adjusts the predicted lifetime of each LED unit based on environmental parameters, further refining the assessment. Ultimately, a new predicted lifetime distribution is generated that comprehensively considers the impact of the operating environment.

[0102] It's important to note that the temperature model establishes a relationship between LED operating temperature and luminous attenuation. It collects LED operating temperature data and analyzes the impact of high temperature on the LED's luminous performance, generating a correlation model between temperature and luminous attenuation. This model accepts the LED's operating temperature as input and predicts the LED's luminous attenuation at high temperatures, useful for assessing the impact of temperature on LED lifespan. The illumination model correlates the LED's illumination with luminous attenuation. By testing LED luminous attenuation data under different illumination levels, it establishes a correlation model between illumination level and LED luminous performance degradation. This model accepts ambient light as input and outputs the expected luminous attenuation of the LED at that level, useful for assessing the impact of ambient light on the LED.

[0103] S212: Re-plan the layout of the target LED units on the target LED display screen according to the corrected lifetime distribution result.

[0104] Based on the corrected lifetime distribution results, the calibration equipment replans the layout of multiple target LED units on the target LED display. After obtaining the new lifetime distribution data, corrected for environmental impacts, the LED layout on the display can be replanned to maximize the value of each LED. For example, LEDs with expected longer lifespans can be placed in key areas of the display, while those with shorter lifespans can be placed in non-critical areas. Alternatively, LEDs within the same area can be configured with units of similar lifespans, resulting in relatively consistent aging trends within the area. This not only optimizes the utilization of each LED unit but also ensures a balanced display across all areas. This re-layout process can be implemented using a variety of sorting and allocation algorithms to achieve the optimal balance between display quality and efficiency.

[0105] In some embodiments, the correction device reads the corrected predicted remaining life data of each target LED unit; uses an iterative sorting algorithm to sort all target LED units from high to low according to the corrected predicted remaining life to obtain a priority sorting result; determines the key areas of the display content based on the usage scenario of the target LED display screen, and counts the number of LED units in each area; based on the number requirements of the key areas of the display content, sequentially allocates them according to the priority sorting results; uses a greedy algorithm to optimize the position distribution of LED units in each area, while meeting the allocation requirements, so that LED units with similar predicted lifespans in the same area are in adjacent positions, thereby obtaining a final layout plan.

[0106] Specifically, the calibration equipment first reads the revised predicted remaining lifespan data for each target LED unit. After accounting for the impact of the operating environment, each LED unit has a revised predicted lifespan value. The calibration equipment needs to read this new round of lifespan data to provide a basis for subsequent planning.

[0107] The calibration equipment then uses an iterative sorting algorithm to prioritize all target LED units based on their predicted lifespans, from highest to lowest. This algorithm can quickly and efficiently sort the lifespans of a large number of LED units and assign a priority to each unit. The resulting ranking reflects the importance of each LED.

[0108] Next, the calibration equipment determines the key display areas based on the target LED display's usage scenario and counts the number of LED units in each area. Different usage scenarios, such as advertising screens and surveillance screens, require different key content areas. Once the key areas are determined, the number of LED units required for each area can be counted.

[0109] The calibration equipment then allocates LED units based on the required number of LED units in the key display areas, sorted by priority. LED units with the highest lifespan priority are allocated to the key areas until the required number of LEDs in the key areas is met. Other non-critical areas are then allocated in order, completing the allocation of all LEDs.

[0110] Finally, the calibration equipment uses a greedy algorithm to optimize the positional distribution of LED units within each area, while meeting allocation requirements. This ensures that LED units with similar lifespans are placed adjacent to each other within the same area. This ensures consistent aging trends for LEDs within the same area, preventing premature degradation in some areas. Through iterative sorting, sequential allocation, and greedy algorithm optimization, the layout of LED units can be rationally planned to maximize the value of LEDs.

[0111] In the embodiment of the present application, a preliminary detection of multiple LED units and recording of initial display parameters are adopted to determine the target display parameters of the entire screen, calculate the parameter adjustment scheme of each LED unit, and analyze the remaining life under the adjustment scheme in combination with the life cycle data of the LED unit, thereby screening out target LED units with remaining life within an acceptable range, and finally performing precise point-by-point correction on these target LED units to enable the target LED display screen to achieve the expected display effect. Therefore, the performance and life differences between LED units of different batches can be fully considered, and the reasonable utilization of the leftover LEDs is achieved through the remaining life prediction, thereby avoiding unnecessary losses that may be caused by over-correction, ensuring the long-term stable display performance of the display screen, and effectively solving the problem of shortened display service life due to the failure to consider batch differences and remaining life in the prior art, thereby achieving effective reuse of leftover LEDs and extending the service life of the display screen.

[0112] The following describes the calibration device in the embodiment of the present application from the perspective of modules. Figure 3 , is a schematic diagram of the functional module structure of the correction device in an embodiment of the present application.

[0113] The calibration equipment includes: A preliminary test module 301 is used to perform preliminary testing on the multiple LED units and record the initial display parameters of the multiple LED units; A target determination module 302 is configured to determine target display parameters of the entire screen based on a preset display requirement threshold of the finished LED display screen; A solution determination module 303 is used to perform adjustment calculations on the multiple LED units to obtain parameter adjustment solutions for the multiple LED units from initial display parameters to target display parameters; Life prediction module 304, configured to collect and analyze life cycle data of multiple LED units to determine the predicted remaining life of each of the multiple LED units under a parameter adjustment scheme; life cycle data includes usage time, brightness decay, color shift, and current change; The unit screening module 305 is used to screen out a plurality of target LED units whose predicted remaining lifespan is within a preset durability range; The unit adjustment module 306 is used to calibrate the target LED unit point by point based on the parameter adjustment solution, so that the display parameters of the target LED display screen composed of multiple target LED units reach the target display parameters.

[0114] In some embodiments, the solution determination module 303 specifically includes: A model building unit, used for building a light attenuation model for each LED unit; an attenuation calculation unit, for calculating the light attenuation degree of the LED unit using a light attenuation model; The parameter determination unit is used to reversely calculate the driving current adjustment amount required for the LED unit to achieve the target display parameters using a recursive algorithm based on the light attenuation degree, initial display parameters and target display parameters of the LED unit, as a parameter adjustment scheme for the LED unit.

[0115] In some embodiments, the lifespan prediction module 304 specifically includes: A data reading unit is used to read the life cycle data of each LED unit, including the factory time, transportation time, storage time, and usage time, and establish a life cycle database; Fault statistics unit, used to calculate the average failure rate curve of LED units in different batches; A probability calculation unit is used to calculate the predicted failure probability distribution of the LED unit using a two-parameter Weibull distribution model based on the life cycle data, the batch to which the LED unit belongs, and the parameter adjustment plan; The life prediction unit is used to calculate the predicted remaining service life of the LED unit by combining the predicted failure probability distribution, the average failure rate curve and the usage time of the LED unit.

[0116] In some embodiments, the calibration device further comprises: A lifespan synthesis module is used to calculate the average predicted remaining lifespan of a target LED display based on the predicted remaining lifespan of the target LED units; Life assessment module, used to determine whether the average predicted remaining life is lower than the preset expected threshold; A solution generation module is used to automatically generate multiple LED unit layout solutions using a genetic algorithm based on the predicted remaining life when the average predicted remaining life is lower than a preset threshold; A scheme scoring module is used to score multiple LED unit layout schemes based on a preset evaluation model combining uniformity and heat dissipation performance to obtain scoring results; The scheme selection module is used to select the layout scheme with the highest scoring result as the final layout scheme of the target LED display screen.

[0117] In some embodiments, the calibration device further comprises: The area determination module is used to use a surface fitting algorithm to simulate and predict the position distribution of future content key areas based on the preset actual content playback data of the target LED display screen, and obtain a predicted content key area distribution surface; A boundary determination module is used to calculate the gradient direction and gradient magnitude of the distribution surface of the content key area and determine the boundary of the content key area; The unit statistics module is used to traverse the position coordinates of all LED units, determine the LED units in the key content area as the center LED units, and the LED units in the remaining areas as the edge LED units; The unit division module is used to sort multiple target LED units from high to low according to the predicted remaining life, and divide them into central LED units and edge LED units according to the sorting results.

[0118] In some embodiments, the calibration device further comprises: Environmental acquisition module, used to collect the actual environmental parameters of the target LED display including temperature distribution, illumination distribution, and usage frequency; A life correction module is used to correct the predicted remaining life of multiple target LED units based on the temperature model and the illumination model to obtain a corrected life distribution result; The layout resetting module is used to re-plan the layout of multiple target LED units on the target LED display screen according to the corrected lifetime distribution result.

[0119] In some embodiments, the calibration device further comprises: A data acquisition module, configured to read the corrected predicted remaining life data of each target LED unit; A unit sorting module is used to sort all target LED units from high to low according to the corrected predicted remaining life using an iterative sorting algorithm to obtain a priority sorting result; The LED statistics module is used to determine the key display areas based on the usage scenario of the target LED display and count the number of LED units in each area; A unit allocation module is used to allocate the LED units in order according to the priority sorting results based on the number requirements of the key areas of the display content; The distribution determination module is used to optimize the position distribution of LED units in each area by using a greedy algorithm, while meeting the allocation requirements, so that LED units with similar predicted lifespans in the same area are placed in adjacent positions, thereby obtaining the final layout plan.

[0120] The correction device in the embodiment of the present application is described above from the perspective of modular functional entities. The correction device in the embodiment of the present application is described below from the perspective of hardware processing. Figure 4 , is a schematic diagram of the physical device structure of the correction device in the embodiment of the present application.

[0121] It should be noted that Figure 4 The structure of the correction device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0122] like Figure 4 As shown, the calibration device includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes, such as the methods described in the above embodiments, based on programs stored in a read-only memory (ROM) 402 or programs loaded from a storage unit 408 into a random access memory (RAM) 403. RAM 403 also stores various programs and data required for system operation. CPU 401, ROM 402, and RAM 403 are interconnected via a bus 404. An input / output (I / O) interface 405 is also connected to bus 404.

[0123] The following components are connected to the I / O interface 405: an input section 406 including a camera, a spectrometer, and pushbutton switches; an output section 407 including a liquid crystal display (LCD), indicator lights, and speakers; a storage section 408 including a hard disk; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card or a modem. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. Removable media 411, such as magnetic disks, optical disks, magneto-optical disks, and semiconductor memories, are installed in the drive 410 as needed, allowing computer programs read from these media to be installed in the storage section 408 as needed.

[0124] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for executing the methods illustrated in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 409 and / or installed from removable media 411. When executed by central processing unit (CPU) 401, the computer program performs the various functions defined in the present invention.

[0125] It should be noted that the computer-readable medium described in the embodiments of the present invention may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium may include a data signal transmitted in baseband or as part of a carrier wave, which carries a computer-readable computer program. Such a propagated data signal may take any of a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof.

[0126] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the boxes can also occur in an order different from that marked in the accompanying drawings. For example, two boxes shown in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or can be implemented using a combination of dedicated hardware and computer instructions.

[0127] Specifically, the calibration device of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, the on-site calibration method for the LED display screen provided in the above embodiment is implemented.

[0128] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the calibration device described in the above embodiments, or may exist independently and not be incorporated into the calibration device. The storage medium carries one or more computer programs, which, when executed by a processor of the calibration device, enable the calibration device to implement the on-site calibration method for an LED display screen provided in the above embodiments.

[0129] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0130] As used in the above embodiments, the term “when” may be interpreted to mean “if” or “after” or “in response to determining that” or “in response to detecting that”, depending on the context. Similarly, the phrases “upon determining that” or “if (stated condition or event) is detected” may be interpreted to mean “if determining that” or “in response to determining that” or “upon detecting (stated condition or event)” or “in response to detecting (stated condition or event)”, depending on the context.

[0131] In the above embodiments, all or part of the embodiments can be implemented using software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from a website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media. The available medium can be a magnetic medium (e.g., a floppy disk, hard disk, tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive).

[0132] Those skilled in the art will appreciate that all or part of the process steps in the above-described method embodiments can be implemented by a computer program instructing the relevant hardware. The program can be stored in a computer-readable storage medium, and when executed, the program can include the process steps in the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A method for on-site calibration of an LED display screen, applied to a calibration device, characterized in that: The method comprises: Performing preliminary detection on a plurality of LED units and recording initial display parameters of the plurality of LED units; Determine the target display parameters of the entire screen based on the preset display demand threshold of the finished LED display; Performing adjustment calculation on the multiple LED units to obtain a parameter adjustment scheme for the multiple LED units from the initial display parameters to the target display parameters; Collecting and analyzing life cycle data of the plurality of LED units to respectively determine the predicted remaining lifespan of the plurality of LED units under the parameter adjustment scheme; the life cycle data including usage time, brightness attenuation, color shift, and current change; Screening out a plurality of target LED units whose predicted remaining lifespan is within a preset durability range; Based on the parameter adjustment scheme, the target LED unit is calibrated point by point, so that the display parameters of the target LED display screen composed of the multiple target LED units reach the target display parameters.

2. The method according to claim 1, characterized in that: The adjusting calculation of the plurality of LED units to obtain a parameter adjustment scheme of the plurality of LED units from the initial display parameters to the target display parameters specifically includes: Establish a light attenuation model for each LED unit; Calculate the light attenuation degree of the LED unit using the light attenuation model; According to the light attenuation degree of the LED unit, the initial display parameters and the target display parameters, a recursive algorithm is used to reversely calculate the driving current adjustment amount required for the LED unit to achieve the target display parameters as a parameter adjustment scheme for the LED unit.

3. The method according to claim 1, characterized in that: The collecting and analyzing the life cycle data of the plurality of LED units to respectively determine the predicted remaining lifespan of the plurality of LED units under the parameter adjustment scheme specifically includes: Read the life cycle data of each LED unit, including the factory time, transportation time, storage time, and usage time, and establish a life cycle database; Statistical average failure rate curves of different batches of LED units; According to the life cycle data of the LED unit, the batch to which it belongs and the parameter adjustment scheme, a two-parameter Weibull distribution model is used to calculate the predicted failure probability distribution of the LED unit; The predicted remaining service life of the LED unit is calculated by combining the predicted failure probability distribution, the average failure rate curve, and the used time of the LED unit.

4. The method according to claim 1, characterized in that: After the step of performing point-by-point correction on the target LED unit based on the parameter adjustment scheme, the method further includes: Based on the predicted remaining life of the target LED unit, calculating the average predicted remaining life of the target LED display screen; Determining whether the average predicted remaining life is lower than a preset expected threshold; If the average predicted remaining life is lower than a preset threshold, automatically generating multiple LED unit layout schemes using a genetic algorithm based on the predicted remaining life; Based on a preset evaluation model combining uniformity and heat dissipation performance, scoring the plurality of LED unit layout schemes to obtain a scoring result; The layout scheme with the highest scoring result is selected as the final layout scheme of the target LED display screen.

5. The method according to claim 1, characterized in that After the step of performing point-by-point correction on the target LED unit based on the parameter adjustment scheme, the method further includes: Using a surface fitting algorithm, based on the preset actual content playback data of the target LED display screen, simulate and predict the position distribution of future content key areas to obtain a predicted content key area distribution surface; Calculating the gradient direction and gradient magnitude of the distribution surface of the content key area to determine the boundary of the content key area; Traversing the position coordinates of all LED units, determining the LED units in the content focus area as the central LED units, and the LED units in the remaining areas as the edge LED units; The plurality of target LED units are sorted from high to low according to the predicted remaining lifespan, and the central LED unit and the edge LED unit are divided according to the sorting result.

6. The method according to claim 1, characterized in that After the step of performing point-by-point correction on the target LED unit based on the parameter adjustment scheme, the method further includes: Collecting actual usage environment parameters of the target LED display including temperature distribution, illumination distribution, and usage frequency; Based on the temperature model and the illumination model, the predicted remaining lifespan of the plurality of target LED units is corrected to obtain a corrected lifespan distribution result; According to the corrected lifetime distribution result, the layout of the plurality of target LED units on the target LED display screen is replanned.

7. The method according to claim 6, characterized in that The re-planning the layout of the plurality of target LED units on the target LED display screen according to the corrected lifetime distribution result specifically includes: Reading the corrected predicted remaining life data of each target LED unit; An iterative sorting algorithm is used to sort all target LED units from high to low according to the corrected predicted remaining lifespan to obtain a priority sorting result; According to the usage scenario of the target LED display screen, determine the key areas of the display content, and count the number of LED units in each area; Based on the requirement of the number of LED units in the key area of ​​the display content, sequentially allocate according to the priority sorting result; A greedy algorithm is used to optimize the position distribution of LED units in each area while meeting the allocation requirements, so that LED units with similar predicted lifespans in the same area are placed in adjacent positions, and the final layout plan is obtained.

8. A calibration device, characterized in that: include: A preliminary test module, used to perform preliminary testing on a plurality of LED units and record initial display parameters of the plurality of LED units; A target determination module, used to determine the target display parameters of the entire screen based on the preset display demand threshold of the finished LED display screen; A scheme determination module, used for performing adjustment calculation on the plurality of LED units to obtain a parameter adjustment scheme for the plurality of LED units from the initial display parameters to the target display parameters; A life prediction module, used to collect and analyze life cycle data of the plurality of LED units, and respectively determine the predicted remaining life of the plurality of LED units under the parameter adjustment scheme; the life cycle data includes usage time, brightness decay, color shift, and current change; A unit screening module, used to screen out a plurality of target LED units whose predicted remaining lifespan is within a preset durability range; The unit adjustment module is used to calibrate the target LED unit point by point based on the parameter adjustment scheme, so that the display parameters of the target LED display screen composed of the multiple target LED units reach the target display parameters.

9. A calibration device, characterized in that: include: one or more processors and memory; The memory is coupled to the one or more processors, and the memory is used to store computer program codes, wherein the computer program codes include computer instructions, and the one or more processors call the computer instructions to enable the correction device to perform the method according to any one of claims 1 to 7.

10. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on a correction device, the correction device is caused to execute the method according to any one of claims 1 to 7.

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