A method for on-site correction of an LED display screen and related apparatus

Abstract

The application discloses an LED display screen on-site correction method and related devices, and relates to the technical field of display, which comprises the following steps: performing preliminary detection on a plurality of LED units, recording initial display parameters of the plurality of LED units; determining target display parameters of an overall screen; performing adjustment calculation on the plurality of LED units to obtain a parameter adjustment scheme of the plurality of LED units; collecting life cycle data of the plurality of LED units and performing analysis to determine predicted residual life of the plurality of LED units under the parameter adjustment scheme respectively; screening a plurality of target LED units with predicted residual life within a preset endurance range; and performing point-by-point correction on the target LED units based on the parameter adjustment scheme. By performing residual life prediction and accurate correction on different batches of LED units, the method realizes reasonable utilization of tail goods LED, makes the display screen present better performance uniformity and longer service life, and improves user experience.

Description

Technical Field

[0001] This application relates to the field of display technology, and in particular to a method and related apparatus for on-site calibration of LED displays. Background Technology

[0002] In the LED display industry, uniformity of display effect and color accuracy are key indicators for measuring product quality. However, leftover LED displays—products accumulated due to inventory buildup or different production cycles—often exhibit variations in brightness and color. In actual sales and use, effectively utilizing these leftover displays while minimizing waste and reducing costs while maintaining display quality has become a pressing issue.

[0003] In order to solve the color difference problem of LED displays, the industry has developed a series of point-by-point calibration technologies. Point-by-point calibration of individual LED cabinets is carried out on the production line to ensure that each cabinet achieves a high degree of uniformity when it leaves the factory; point-by-point calibration of large screens on site is carried out after the LED display is installed, and the entire display is adjusted by selecting a suitable viewing position to ensure the viewing effect in the actual use position.

[0004] However, most point-to-point calibration technologies adjust the physical properties of LED screens without fully considering the lifespan differences between different batches of LED units. Due to the discontinuous manufacturing process, the aging rate and remaining lifespan of leftover LED units often vary. Even if color and brightness consistency is achieved after initial calibration, these calibration effects may gradually diminish over time due to differences in aging rates, leading to inconsistent long-term performance and reducing the overall lifespan of the display and the user experience. Summary of the Invention

[0005] This application provides an on-site calibration method and apparatus for LED displays. By predicting and accurately calibrating the remaining lifespan of LED units in different batches, the method enables the rational utilization of leftover LEDs, resulting in better performance uniformity and a longer lifespan for the display, thus improving the user experience.

[0006] In a first aspect, this application provides an on-site calibration method for an LED display screen, applied to calibration equipment. The method includes: performing preliminary testing on multiple LED units and recording the initial display parameters of the multiple LED units; determining the target display parameters of the entire screen based on a preset display requirement threshold for 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 lifecycle data of the multiple LED units to determine the predicted remaining lifespan of each multiple LED unit under the parameter adjustment scheme; the lifecycle data includes usage time, brightness decay, color shift, and current variation; selecting multiple target LED units whose predicted remaining lifespan is within a preset durability range; and performing point-by-point calibration 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.

[0007] In the above embodiments, the calibration device performs preliminary testing and records initial display parameters of multiple LED units to determine the target display parameters of the entire screen. It then calculates the parameter adjustment scheme for each LED unit and analyzes its remaining lifespan under the adjustment scheme using the LED unit's lifespan data. From this analysis, target LED units with remaining lifespans within an acceptable range are selected. Finally, these target LED units undergo precise point-by-point calibration to ensure the target LED display achieves the expected display effect. This method fully considers the performance and lifespan differences between different batches of LED units, achieves reasonable utilization of remaining LEDs through remaining lifespan prediction, avoids unnecessary losses that may result from over-calibration, and ensures long-term stable display performance of the screen.

[0008] In conjunction with some embodiments of the first aspect, in some embodiments, adjustment calculations are performed on multiple LED units to obtain parameter adjustment schemes for multiple LED units from initial display parameters to target display parameters. Specifically, this includes: 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 inversely calculate the driving current adjustment amount required for the LED unit to reach the target display parameters based on the light attenuation degree of the LED unit, the initial display parameters, and the target display parameters, as the parameter adjustment scheme for the LED unit.

[0009] In the above embodiments, the calibration device establishes a light attenuation model for each LED unit, calculates the degree of light attenuation, and then obtains a drive current adjustment scheme that meets the target parameters through recursive inverse calculation. This calculation method can accurately assess the aging condition and calibration requirements of each LED unit, which is conducive to obtaining a precise and feasible parameter adjustment scheme, thereby guiding subsequent accurate calibration.

[0010] In conjunction with some embodiments of the first aspect, in some embodiments, lifecycle data of multiple LED units are collected and analyzed to determine the predicted remaining lifespan of multiple LED units under parameter adjustment schemes. Specifically, this includes: reading lifecycle data of each LED unit, including manufacturing time, transportation time, storage time, and usage time, and establishing a lifecycle database; statistically analyzing the average failure rate curves of LED units from different batches; calculating the predicted failure probability distribution of the LED unit using a two-parameter Weibull distribution model based on the LED unit's lifecycle data, batch, and parameter adjustment scheme; and calculating the predicted remaining lifespan 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 embodiments, the calibration device calculates the remaining service life by establishing a lifecycle database, combining it with a two-parameter Weibull distribution model to calculate the failure probability distribution, and considering the average failure rate curve. This prediction method fully utilizes the lifecycle data of LED units and employs scientific and systematic statistical analysis methods, enabling accurate assessment of the remaining service life of different batches of LED units, providing a reliable basis for their effective subsequent utilization.

[0012] In conjunction 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: calculating the average predicted remaining lifetime of the target LED display based on the predicted remaining lifetime of the target LED unit; determining whether the average predicted remaining lifetime is lower than a preset expected threshold; if the average predicted remaining lifetime is lower than the preset threshold, then automatically generating multiple LED unit layout schemes using a genetic algorithm based on the predicted remaining lifetime; scoring the multiple LED unit layout schemes based on a preset evaluation model of uniformity and heat dissipation performance to obtain a scoring result; and selecting the layout scheme with the highest scoring result as the final layout scheme of the target LED display.

[0013] In the above embodiments, the calibration device calculates the average predicted remaining lifespan of the target LED display screen to determine whether it is below the expected threshold. If it is too low, a genetic algorithm is used to generate multiple layout schemes, and these layout schemes are scored based on an evaluation model to select the optimal scheme. This approach fully utilizes the predicted lifespan of each LED unit in the early stages, enabling dynamic detection of the overall health of the display screen and further extending its lifespan based on the initial calibration. Simultaneously, the multiple optional layouts generated by the genetic algorithm and the scoring and selection by the evaluation model make layout optimization more intelligent and comprehensive.

[0014] In conjunction 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: using a surface fitting algorithm, based on the preset actual content playback data of the target LED display screen, simulating and predicting the position distribution of the future key content areas, and obtaining the predicted content key area distribution surface; calculating the gradient direction and gradient magnitude of the content key area distribution surface, and determining the boundary of the content key area; traversing the position coordinates of all LED units, determining the LED units in the content key area as the center LED units, and the LED units in the remaining areas as the edge LED units; sorting the multiple target LED units from high to low according to the predicted remaining lifespan, and dividing the center LED units and edge LED units according to the sorting result.

[0015] In the above embodiments, the calibration device can predict the hot zone distribution of the displayed content, distinguish between the central area and the edge area, and allocate LED units in descending order of predicted lifespan, placing LED units with longer lifespans in the hot zones of the content. This layout method enables the LED units in key areas of the display screen to be properly protected and utilized, avoiding premature aging in these areas and extending the stable period of the display effect.

[0016] In conjunction with some embodiments of the first aspect, in some embodiments, after the step of performing point-by-point correction on the target LED units 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; correcting the predicted remaining lifetime of multiple target LED units based on the temperature model and the illuminance model to obtain the corrected lifetime distribution result; and replanning the layout of multiple target LED units on the target LED display screen according to the corrected lifetime distribution result.

[0017] In the above embodiments, the calibration device can detect and collect environmental parameters of the display screen in real time, such as temperature distribution, illuminance distribution, and usage frequency. Based on temperature and illuminance models, it corrects the predicted remaining lifespan of each LED unit, obtaining a revised lifespan distribution. Then, based on the revised lifespan distribution, the layout of each LED unit on the display screen is replanned. This technical solution fully considers the actual impact of the usage environment on the lifespan of LED units, and can adjust the layout scheme in real time according to environmental changes, making the utilization of LED units more rational and efficient, thereby achieving long-term stability of the display effect.

[0018] In conjunction with some embodiments of the first aspect, in some embodiments, the layout of multiple target LED units on the target LED display screen is replanned based on the corrected lifetime distribution results. Specifically, this includes: 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, obtaining a priority sorting result; determining the key areas of the display content based on the usage scenario of the target LED display screen, and counting the number of LED units in each area; allocating LED units sequentially according to the priority sorting result based on the LED unit quantity requirements of the key areas of the display content; and using a greedy algorithm to optimize the positional distribution of LED units in each area while meeting the allocation requirements, so that LED units with similar predicted lifetimes in the same area are placed in adjacent positions, obtaining the final layout scheme.

[0019] In the above embodiments, the technical process of the correction device replanning the layout based on the corrected lifetime distribution results includes reading the corrected lifetime of each LED unit, iteratively sorting them to obtain priorities, determining key areas and LED quantity requirements based on the display content, and then allocating LED units to each area according to priority. Simultaneously, a greedy algorithm is used to further optimize the LED position distribution within each area, placing LED units with similar lifetimes adjacent to each other. In this way, while meeting the display content requirements, the lifespan of each LED unit can be maximized.

[0020] Secondly, embodiments of this application provide a calibration device, which includes: a preliminary testing module for performing preliminary testing 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 overall 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 a parameter adjustment scheme for the multiple LED units from the initial display parameters to the target display parameters; a lifetime prediction module for collecting and analyzing the life cycle data of the multiple LED units to determine the predicted remaining lifetime of the multiple 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 for screening out multiple target LED units whose predicted remaining lifetime is within a preset durability range; and a unit calibration module for performing point-by-point calibration 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] Thirdly, embodiments of this application provide a calibration device, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program code, the computer program code including computer instructions, and the one or more processors call the computer instructions to cause the calibration device to perform the method described in the first aspect and any possible implementation thereof.

[0022] Fourthly, embodiments of this application provide a computer program product containing instructions that, when the computer program product is run on a calibration device, cause the calibration device to perform the method described in the first aspect and any possible implementation thereof.

[0023] Fifthly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a calibration device, cause the calibration device to perform the method described in the first aspect and any possible implementation thereof.

[0024] Understandably, 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 this application. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in 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:

[0026] 1. By conducting preliminary testing and recording of initial display parameters for multiple LED units, determining the target display parameters for the entire screen, calculating the parameter adjustment scheme for each LED unit, and analyzing the remaining lifespan of the LED units under the adjustment scheme based on their lifespan data, target LED units with acceptable remaining lifespans are selected. Finally, these target LED units are precisely calibrated point by point to ensure that the target LED display achieves the expected display effect. Therefore, it can fully consider the performance and lifespan differences between different batches of LED units. By predicting the remaining lifespan, it achieves the rational utilization of surplus LEDs, avoids unnecessary losses that may be caused by overcalibration, and ensures the long-term stable display performance of the display. It effectively solves the problem of shortened display lifespan caused by the failure to consider batch differences and remaining lifespan in existing technologies, thereby realizing the effective reuse of surplus LEDs and extending the lifespan of the display.

[0027] 2. By reading the lifecycle data of each LED unit, including manufacturing time, transportation time, storage time, and usage time, and establishing a lifecycle database, combining it with a two-parameter Weibull distribution model to calculate the failure probability distribution, and considering the average failure rate curve, the remaining service life can be calculated. Therefore, the lifecycle data of the LED units can be fully utilized. A scientific and systematic statistical analysis method is adopted to accurately assess 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 prediction of the remaining service life of LED units caused by insufficient consideration of lifecycle data in existing technologies, and thus achieves accurate prediction of the remaining service life of different batches of LED units.

[0028] 3. By collecting actual environmental parameters of the target LED display screen, including temperature distribution, illuminance distribution, and usage frequency, and correcting the predicted remaining lifespan of each LED unit based on temperature and illuminance models, a new lifespan distribution result is obtained. Then, the layout of each LED unit on the display screen is replanned based on the corrected lifespan distribution result. Therefore, the actual impact of the usage environment on the lifespan of the LED unit can be fully considered, and the layout scheme can be adjusted in real time according to environmental changes, making the utilization of LED units more reasonable and efficient. This achieves long-term stability of the display effect and effectively solves the problem of unreasonable layout schemes caused by the failure to consider the impact of usage environment changes on LED units in existing technologies. Thus, a dynamic adjustment LED unit layout scheme based on the usage environment is realized. Attached Figure Description

[0029] Figure 1 This is a flowchart illustrating an on-site calibration method for an LED display screen in an embodiment of this application.

[0030] Figure 2 This is another flowchart illustrating the on-site calibration method for LED displays in this application embodiment;

[0031] Figure 3 This is a schematic diagram of a functional module structure of the calibration device in an embodiment of this application;

[0032] Figure 4 This is a schematic diagram of the physical device structure of the calibration equipment in the embodiments of this application. Detailed Implementation

[0033] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification of this application, the singular expressions “a,” “an,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0034] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0035] To facilitate understanding, the application scenarios of the embodiments of this application are described below.

[0036] A sports stadium needs to purchase an ultra-large curved LED display screen for broadcasting live sports events and spectator interaction. However, due to a limited budget, they need to control costs. Therefore, they decided to purchase surplus LED displays from different suppliers and splice them together. However, these LED units, due to different production batches, have variations in brightness and color temperature. Directly splicing them together would result in noticeable unevenness across the entire display, severely impacting the display quality. How to effectively plan and utilize these surplus LEDs to achieve a uniform display effect while ensuring cost control is a pressing issue for the sports stadium operator.

[0037] In related technologies, the uniformity of LED displays can be improved by performing point-by-point calibration on the LED display production line or at the installation site. However, these point-by-point calibration methods do not take into account the differences in lifespan between different batches of LED units.

[0038] The following describes a scenario where on-site calibration methods for LED displays are used in conjunction with relevant technologies.

[0039] The stadium operator initially planned to increase the driving current of the LED units to achieve the same brightness and color temperature across different batches. However, in actual use, it was found that due to the different aging rates of the LED units from different batches, even if a uniform effect was initially achieved, differences in display performance still appeared after prolonged use due to the different aging rates of the LED units, making it impossible to truly achieve long-term stable display uniformity.

[0040] The LED display screen field calibration method in this application embodiment, by predicting the remaining service life of LED units in different batches, allows for precise adjustment of display parameters for LED units with similar service lives. This not only effectively utilizes leftover LEDs to achieve short-term uniformity of display effects, but also takes into account the differences in service life caused by batch differences, ensuring long-term display stability.

[0041] The following describes a scenario where the on-site calibration method for LED displays described in this application was used.

[0042] Later, the stadium operator adopted the LED display screen on-site calibration solution proposed in this application. They predicted the lifespan of LED units from different batches, calculated the remaining lifespan of each LED unit, and then fine-tuned the parameters to achieve a uniform display effect for LED units with similar remaining lifespans. This approach not only utilized surplus LEDs but also considered the different aging rates caused by batch variations, ensuring the display screen's stability after long-term use.

[0043] As can be seen, by adopting the method in the embodiments of this application, while achieving display uniformity, it can also effectively solve the problem of lifespan differences between different batches of LED units, thereby realizing the efficient utilization of leftover LEDs and improving the long-term stability of the display screen.

[0044] To facilitate understanding, the method provided in this implementation will be described in detail below, using the above scenario as an example. Please refer to [link / reference]. Figure 1 This is a flowchart illustrating an on-site calibration method for an LED display screen in an embodiment of this application.

[0045] S101. Perform preliminary testing on multiple LED units and record the initial display parameters of the multiple LED units.

[0046] The calibration equipment performs preliminary testing on multiple LED units, recording their initial display parameters. Specifically, the equipment uses a built-in image sensor to acquire image information of the LED units under test in their initial state, and combines this with a spectrometer to measure the initial color coordinates, brightness parameters, etc., of each LED unit. These measured initial parameters are then recorded to establish an initial parameter database for each LED unit, which may include parameters such as LED batch information, manufacturing date, LED model and specifications, initial brightness, initial color temperature, and initial color difference. These parameters lay the foundation for subsequent determination of display target parameters and calibration calculations. For example, if a significant brightness deviation is detected between different batches of LED units, the subsequent target brightness setting needs to consider the differences between batches, using a method of setting target brightness by region. After this step is completed, the calibration equipment has obtained the initial performance parameters of each LED unit.

[0047] S102. Based on the preset display requirement threshold of the finished LED display screen, determine the target display parameters of the overall screen.

[0048] The calibration equipment determines the target display parameters of the entire screen based on the preset display requirement thresholds of the finished LED display. After obtaining the initial parameters of each LED unit, the calibration equipment needs to determine the overall screen's performance target parameters after calibration, based on the display's usage requirements and expected display effect indicators. These target parameters may include target brightness, target color temperature, and target uniformity. The setting of these target parameters requires reference to the display product's specifications, which typically specify performance thresholds the display must achieve, such as a minimum color difference or a standard deviation for brightness uniformity within a certain range. The calibration equipment reads these display requirement thresholds from the product specifications as the basis for setting the target parameters. Furthermore, if the initial parameters of different batches of LED units deviate significantly, the target parameters can be set in a zoned manner. For example, in cases of uneven brightness, a higher target brightness value can be set for the initial group of bright LED units. The proper setting of the target parameters is crucial for subsequent calibration calculations and the final result.

[0049] S103. Perform adjustment calculations on multiple LED units to obtain parameter adjustment schemes for multiple LED units from initial display parameters to target display parameters.

[0050] The calibration equipment performs adjustment calculations on multiple LED units to obtain parameter adjustment schemes for each unit from its initial display parameters to the target display parameters. After determining the target display parameters for the entire screen, the calibration equipment needs to obtain the driving scheme required for each LED unit to adjust from its current initial parameters to the target parameters. This scheme may include adjusting the magnitude of the LED drive current, adjusting the PWM duty cycle, etc. The calculation method typically requires establishing a light attenuation model, considering the influence of current magnitude, usage time, and temperature factors on LED light attenuation, and then combining the initial parameters, target parameters, and light attenuation model, using a recursive algorithm to calculate the drive current or PWM scheme that meets the target parameters. This yields the parameter fine-tuning scheme for each LED unit, which guides subsequent precise calibration, adjusting the LED units from their initial state to the target state, and achieving the target display effect for the entire screen.

[0051] It should be noted that the light decay model is a light emission decay trend model established for LED units. It comprehensively considers the impact of factors such as driving current, usage time, and temperature on the LED's luminous efficacy. By simulating the LED's usage environment and aging process, it establishes a model relating these factors to the amount of light emission decay. This model can take LED usage parameters as input and simulate and predict the degree of light emission decay of the output LED. The purpose of establishing this model is to evaluate the light emission decay trend of LEDs and provide a basis for subsequent dimming correction.

[0052] S104. Collect and analyze the lifecycle data of multiple LED units, and determine the predicted remaining lifespan of each LED unit under the parameter adjustment scheme.

[0053] The calibration equipment collects and analyzes lifecycle data from multiple LED units to determine their predicted remaining lifespan under different parameter adjustment schemes. The equipment needs to consider performance aging differences between batches of LED units due to variations in manufacturing time. To this end, it collects complete lifecycle data for each LED unit from factory to field use, including manufacturing date, transportation time, storage time, and usage time, establishing a lifecycle database. It also needs to statistically analyze the average failure rate curves of different batches of LEDs. Based on this, and using a two-parameter Weibull distribution model, the predicted failure probability of each LED under the parameter adjustment scheme, i.e., the predicted remaining lifespan, can be calculated. This requires comprehensive consideration of lifecycle data, batch type, and the accelerated aging effect of the parameter adjustment scheme on the LED. This allows for a thorough prediction of the remaining lifespan across different batches, providing a basis for subsequent LED selection and use.

[0054] It should be noted that the two-parameter Weibull distribution model is a statistical distribution model for predicting the failure probability of LEDs. It simultaneously considers the LED's usage time and the average failure rate curve of its batch. It can take the LED's lifecycle data and the batch failure rate curve as input, and output the failure probability distribution of that individual LED over its future lifespan—that is, a lifespan distribution model. This model can reflect the impact of batch differences on the individual LED failure rate, and is used to accurately predict the failure probability of LEDs.

[0055] S105. Select multiple target LED units whose predicted remaining lifespan is within the preset durability range.

[0056] The calibration equipment will select multiple target LED units whose predicted remaining lifespan is within a preset durability range. Based on the prediction in the previous step, the calibration equipment can obtain the remaining lifespan distribution for each LED after parameter adjustment. Then, according to project usage requirements, a lifespan threshold range can be preset, for example, allowing for continued use for another 1-2 years. LEDs with predicted lifespans exceeding this threshold range are selected as target LED units. Because these LEDs, after parameter adjustment, still meet usage requirements in terms of remaining lifespan, they are suitable for calibration. LEDs expected to quickly become unusable can be directly discarded to avoid over-calibration. In this way, through the prediction, analysis, and selection of remaining lifespan, the use of LEDs becomes more rational and efficient.

[0057] S106. Based on the parameter adjustment scheme, the target LED units are calibrated 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.

[0058] The calibration equipment performs point-by-point calibration on the target LED units based on a parameter adjustment scheme, enabling the target LED display to achieve 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 LED parameter adjustment scheme. This may require adjusting the LED's drive current or PWM duty cycle, using a controller or driver chip to adjust the parameters one by one until the LED unit meets 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 previous calculations and analysis, performing targeted calibration, avoiding over-adjustment, and ensuring calibration efficiency.

[0059] In the above embodiment, by predicting the remaining lifespan of each LED unit, LED units with similar lifespans are fine-tuned to achieve a uniform display effect. In practical applications, the influence of the usage environment, such as temperature and humidity, can be further considered to establish an environmental impact model, dynamically assess and correct the remaining lifespan of each LED unit, thereby more accurately planning the use of LED units.

[0060] The following provides supplementary information regarding the scenario in this embodiment.

[0061] After implementing this solution, the sports venue operator also established an environmental impact model based on actual environmental data, such as temperature, humidity, and usage frequency. This model dynamically assessed and adjusted the remaining lifespan of each LED unit, and optimized the layout of the LED units accordingly, placing LEDs with similar lifespans adjacent to each other. This further improves the stability of the display effect and maximizes the lifespan of the display screen.

[0062] It should be noted that the environmental impact model considers the influence of the operating environment on LEDs. It establishes a model of the relationship between environmental factors and LED lifespan by collecting environmental parameters such as temperature, humidity, and illuminance. This model can take the environmental parameters of the LED as input and output the degree of influence of environmental factors on the LED's lifespan. The purpose of establishing this model is to assess the impact of the environment on the LED's lifespan after its use and to perform subsequent corrections and optimizations.

[0063] In light of the above scenarios, the method provided in this implementation will now be described in more detail. Please refer to [link / reference]. Figure 2 This is another flowchart illustrating the on-site calibration method for LED displays in this application.

[0064] S201. Perform preliminary testing on multiple LED units and record the initial display parameters of the multiple LED units.

[0065] Referring to step S101, the calibration device will perform preliminary testing on multiple LED units and record the initial display parameters of the multiple LED units.

[0066] S202. Based on the preset display requirement threshold of the finished LED display screen, determine the target display parameters of the overall screen.

[0067] Referring to step S102, the calibration device will determine the target display parameters for the entire screen.

[0068] S203. Perform adjustment calculations on multiple LED units to obtain parameter adjustment schemes for multiple LED units from initial display parameters to target display parameters.

[0069] Referring to step S103, the calibration equipment will calculate the parameter adjustment scheme.

[0070] In some embodiments, the calibration device establishes a light attenuation model for each LED unit; then uses the light attenuation model to calculate the light attenuation level of the LED unit; based on the light attenuation level of the LED unit, the initial display parameters, and the target display parameters, a recursive algorithm is used to calculate the amount of drive current adjustment required for the LED unit to reach the target display parameters, which is then used as the parameter adjustment scheme for the LED unit.

[0071] Specifically, firstly, the calibration equipment establishes a light decay model for each LED unit. During long-term use, the luminous efficacy of LEDs gradually decreases due to factors such as current driving and temperature. To assess the light decay of each LED, a light decay model needs to be established for each LED unit. This model considers various factors affecting light decay and simulates the light decay process of the LED.

[0072] Then, the light decay model comprehensively considers the effects of current magnitude, usage time, and temperature on LED light emission. The magnitude of the driving current directly affects the operating state of the LED chip; usage time leads to aging of the internal structure of the material; high temperature accelerates the decay rate of the LED. The light decay model needs to incorporate these important factors to establish a relationship model between current, time, temperature, and light decay.

[0073] Next, the calibration equipment calculates the light attenuation level of each LED unit based on the light attenuation model. By inputting the specific operating environment parameters of each LED into the light attenuation model, the light attenuation level of that LED up to the current moment can be simulated and calculated. The light attenuation level will vary significantly between LEDs from different batches and in different locations.

[0074] The calibration device then acquires the initial display parameters and target display parameters for each LED. The initial parameters are derived from preliminary test results, while the target parameters are preset based on display requirements.

[0075] Finally, the calibration equipment employs a recursive algorithm to calculate, in reverse, the required adjustment amount of the driving current to meet the target parameters based on the light attenuation level and the initial target parameters. This serves as the parameter adjustment scheme for the LED. The recursive algorithm can derive the driving parameters required to meet the target parameters from the light attenuation model. This calculation method can accurately provide an adjustment scheme for each LED unit, providing a basis for subsequent precise calibration.

[0076] S204. Read the lifecycle data of each LED unit, including manufacturing time, transportation time, storage time, and usage time, and establish a lifecycle database.

[0077] The calibration equipment reads lifecycle data for each LED unit, including manufacturing date, transportation time, storage time, and usage time, to build a lifecycle database. The calibration equipment needs to collect complete lifecycle information for each LED unit from manufacturing to the field, which is crucial for determining the aging status of the LEDs. For example, it can parse the manufacturing date from the LED's ID identifier; calculate transportation time from logistics information; obtain storage records from the warehousing system and calculate storage time; and analyze the usage time from usage information. This lifecycle data is built into a database, providing fundamental data support for subsequent loss analysis. Due to differences in manufacturing time and storage conditions, the lifecycle information of different batches of LEDs will vary significantly.

[0078] S205. Statistically analyze the average failure rate curves of LED units from different batches.

[0079] The calibration equipment statistically analyzes the average failure rate curves of different batches of LED units. After acquiring the lifecycle data for each LED unit, the calibration equipment needs to statistically analyze the failure rate curve model for different batches of LEDs. This can be done by training the model based on historical operating data to obtain the trend of the average failure rate of different batches of LEDs over time. These failure rate curves can reflect the reliability differences between batches, providing an important basis for predicting the failure rate of individual LEDs. For example, if the average failure rate curve of a certain batch of LEDs is steeper, it indicates that the reliability of this batch of LEDs is poor and the quality problems are more serious.

[0080] It should be noted that the failure rate curve model is a model of the average failure rate trend of LEDs in the same batch. It finds the average trend curve of LED failure rate over time by statistically analyzing a large amount of historical operating data of that batch of LEDs. This model reflects the reliability differences between different batches of LEDs and can provide a basis for predicting the failure rate of individual LEDs.

[0081] S206. Based on the LED unit's lifecycle data, batch number, and parameter adjustment scheme, calculate the predicted failure probability distribution of the LED unit using a two-parameter Weibull distribution model.

[0082] The calibration equipment calculates the predicted failure probability distribution of an LED unit using a two-parameter Weibull distribution model, based on the LED unit's lifecycle data, batch number, and parameter adjustment scheme. After obtaining the lifecycle data and average failure rate curve, the future failure probability distribution of an individual LED can be calculated. This calculation uses a two-parameter Weibull distribution model, simultaneously considering the LED's usage time and the failure rate curve corresponding to its batch, thus simulating and predicting the LED's failure probability distribution over its future lifespan—its lifespan distribution. This provides mathematical model support for subsequent lifespan analysis.

[0083] S207. Combine the predicted failure probability distribution, the average failure rate curve, and the used time of the LED unit to calculate the predicted remaining service life of the LED unit.

[0084] The calibration equipment combines the predicted failure probability distribution, the average failure rate curve, and the used time of the LED unit to calculate the predicted remaining lifespan of the LED unit. 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 can be calculated. When the cumulative probability reaches a threshold, the predicted remaining lifespan of the LED can be estimated. This prediction value comprehensively considers both the failure probability distribution and the average failure rate curve, enabling a relatively accurate prediction of the remaining lifespan of an individual LED.

[0085] It should be noted that the failure probability distribution model is a calculation model for the failure probability of an individual LED based on a statistical distribution algorithm. It can calculate the cumulative distribution function of the failure probability of an LED over its future service life based on the predicted lifetime distribution results. This model can assess the failure probability of a single LED and predict the timing of LED failure.

[0086] S208. Select multiple target LED units whose predicted remaining lifespan is within a preset durability range.

[0087] Referring to step S105, the calibration device will select multiple target LED units.

[0088] S209. Based on the parameter adjustment scheme, the target LED units are calibrated 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.

[0089] Referring to step S106, the calibration device will perform point-by-point calibration on the target LED unit.

[0090] In some embodiments, the calibration device calculates the average predicted remaining lifetime of the target LED display based on the predicted remaining lifetime of the target LED units; determines whether the average predicted remaining lifetime is lower than a preset expected threshold; if the average predicted remaining lifetime is lower than the preset threshold, it automatically generates multiple LED unit layout schemes using a genetic algorithm based on the predicted remaining lifetime; scores the multiple LED unit layout schemes based on a preset evaluation model for uniformity and heat dissipation performance, and obtains a scoring result; and selects the layout scheme with the highest scoring result as the final layout scheme of the target LED display.

[0091] It should be noted that the evaluation model is a comprehensive scoring model for LED unit layout schemes. It considers various influencing factors, such as layout uniformity, heat distribution, and density, and establishes a scoring system to score each layout scheme. The model can take different layout schemes as input and output the quality scores of these schemes to select the superior layout scheme.

[0092] Specifically, firstly, the calibration equipment calculates the average predicted remaining lifespan of the target LED display based on the predicted remaining lifespan of the target LED units. After parameter calibration 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 can be statistically analyzed to calculate the average predicted remaining lifespan of the display. This reflects the overall lifespan of the display. For example, if the calculated average lifespan is only one year, it indicates that the display is generally in a relatively aged state and requires further processing.

[0093] The calibration device then determines whether the average predicted remaining lifespan is lower than a preset expected threshold. After calculating the average predicted lifespan, it needs to be compared with the preset expected lifespan threshold to determine if it is too low. This threshold can be set according to the project's usage requirements, for example, to 2 years. If the calculated result is lower than this threshold, it indicates that the overall health of the display screen is poor, and its lifespan is unlikely to meet the requirements.

[0094] Next, if the average lifetime is below a threshold, the calibration device will automatically generate multiple LED unit layout schemes using a genetic algorithm based on the predicted lifetime data of each LED unit. For cases with low lifetimes, optimization can be achieved by changing the layout of the LED units. The device will apply a genetic algorithm to generate multiple different layout schemes, each containing different layout patterns of LED units. The genetic algorithm can quickly converge to obtain multiple candidate layout schemes of varying quality through operations such as selection, crossover, and mutation.

[0095] The calibration equipment then scores each layout scheme based on a pre-set evaluation model. This model considers multiple factors, such as layout uniformity and inter-cell heat dissipation, to provide a comprehensive score for each candidate scheme. This allows for the evaluation of the quality of each layout scheme from multiple perspectives.

[0096] In some embodiments, the calibration device employs a surface fitting algorithm to simulate and predict the future location distribution of key content areas based on preset actual content playback data of the target LED display, thereby obtaining a predicted content key area distribution surface; calculates the gradient direction and gradient magnitude of the content key area distribution surface to determine the boundaries of the content key areas; traverses the position coordinates of all LED units to determine the LED units in the content key areas as center LED units and the LED units in the remaining areas as edge LED units; sorts multiple target LED units from high to low according to their predicted remaining lifespan, and divides the center LED units and edge LED units according to the sorting results.

[0097] Specifically, firstly, the calibration equipment employs a surface fitting algorithm. Based on preset actual content playback data of the target LED display screen, it simulates and predicts the future location distribution of key content areas, obtaining a predicted content key area distribution surface. In actual use, the layout of displayed content is not fixed, and different areas will have hotspot distributions. To evaluate these hotspot areas, the equipment calls the surface fitting algorithm, inputs preset actual content playback data, predicts the two-dimensional coordinate distribution of key content areas, and ultimately simulates a content key area distribution surface.

[0098] Then, the calibration device calculates the gradient direction and magnitude of the distribution surface of the content-focused areas to determine the boundaries of these areas. Based on the predicted distribution surface, gradient vectors can be calculated on the surface. The gradient direction represents the diffusion direction of the content-focused areas, and the gradient magnitude represents the degree of content focus. The boundary range of the content-focused areas can be determined based on the changes in gradient magnitude.

[0099] Next, the calibration device iterates through the position coordinates of all LED units, identifying the LED units in the key content areas as center LED units and the LED units in the remaining areas as edge LED units. It then compares the coordinates of each LED on the display screen with the boundary of the key content area to determine whether each LED belongs to the center or edge area, thus classifying it accordingly.

[0100] Then, the calibration equipment sorts the multiple target LED units from highest to lowest according to their predicted remaining lifespan, and divides them into center LED units and edge LED units based on the sorting results. That is, LEDs with longer lifespans are prioritized for placement in key content areas, while LEDs with shorter lifespans are placed in non-critical areas, so that limited LED resources are allocated rationally.

[0101] Finally, by evaluating the display content area and sorting the LED units, the calibration device can use LED units with longer lifespans in areas where the display content is more concentrated, extending the lifespan of critical areas of the display screen and avoiding localized degradation of display quality.

[0102] S210. Collect actual environmental parameters of the target LED display screen, including temperature distribution, illuminance distribution, and usage frequency.

[0103] The calibration equipment collects actual environmental parameters of the target LED display, including temperature distribution, illuminance distribution, and usage frequency. After the initial calibration of the LED units, changes in the actual usage environment may affect the performance and lifespan of the LED units. Therefore, the calibration equipment also needs to monitor the usage environment in real time as a basis for subsequent optimization. Specifically, it collects temperature distribution data within the display area to monitor changes in the thermal environment during operation; it collects ambient light intensity distribution to determine if photoaging occurs; and it statistically analyzes usage frequency parameters to assess the impact of workload on the LEDs. These actual environmental parameters can be obtained through temperature sensors, photoresistors, usage logs, etc., to assess the comprehensive impact of the usage environment on the LEDs.

[0104] S211. Based on the temperature model and the illuminance model, the predicted remaining lifetime of multiple target LED units is corrected to obtain the corrected lifetime distribution results.

[0105] The calibration equipment uses temperature and illuminance models to correct the predicted remaining lifetime of multiple target LED units, resulting in a revised lifetime distribution. By collecting environmental parameter data and combining it with pre-established temperature and illuminance influence models, the impact of the environment on LED lifetime can be assessed, correcting previous predictions that only considered batch variations. For example, prolonged exposure to high temperatures may shorten LED lifetime, while long-term exposure to strong light will accelerate LED aging. The calibration equipment can adjust the predicted lifetime of each LED unit based on environmental parameters, making the assessment more accurate. Ultimately, a new predicted lifetime distribution that comprehensively considers the impact of the usage environment can be obtained.

[0106] It's important to note that the temperature model establishes the relationship between LED operating temperature and luminous decay. It collects LED operating temperature data, analyzes the impact of high temperatures on LED luminous efficacy, and derives a correlation model between temperature and luminous decay. This model takes the LED's operating temperature as input and predicts the luminous decay at high temperatures, thus assessing the impact of temperature on LED lifespan. The illuminance model, on the other hand, correlates LED illuminance with luminous decay. It establishes a correlation model between illuminance levels and the decrease in LED luminous efficacy by testing luminous decay data under different illuminance levels. This model takes ambient illuminance as input and outputs the expected luminous decay of the LED at that illuminance level, thus evaluating the impact of ambient light on LEDs.

[0107] S212. Based on the corrected lifetime distribution results, replan the layout of multiple target LED units on the target LED display screen.

[0108] The calibration equipment re-plans the layout of multiple target LED units on the target LED display screen based on the corrected lifetime distribution results. After obtaining the new lifetime distribution data after environmental impact correction, the LED layout on the display screen can be re-planned to better utilize the value of each LED. For example, LEDs with longer expected lifetimes can be placed in key areas of the displayed content, while those with shorter lifetimes can be placed in non-critical areas. Alternatively, LEDs within the same area can be made to have units with similar lifetimes, ensuring a relatively consistent aging trend among the LEDs within the area. This not only makes rational use of each LED unit but also ensures balanced display across areas. This re-layout process can be implemented through various sorting and allocation algorithms to achieve the optimal balance between display effect and utilization efficiency.

[0109] In some embodiments, the calibration device reads the corrected predicted remaining lifetime data of each target LED unit; it uses an iterative sorting algorithm to sort all target LED units from high to low according to the corrected predicted remaining lifetime, and obtains a priority sorting result; it determines the key areas of the displayed content based on the usage scenario of the target LED display and counts the number of LED units in each area; it allocates LED units sequentially according to the priority sorting result based on the LED unit quantity requirements of the key areas of the displayed content; and it uses a greedy algorithm to optimize the positional distribution of LED units in each area while meeting the allocation requirements, so that LED units with similar predicted lifetimes in the same area are placed in adjacent positions, thus obtaining the final layout scheme.

[0110] Specifically, firstly, the calibration equipment reads the corrected predicted remaining lifetime data for each target LED unit. After considering the impact of the usage environment, each LED unit has a corrected predicted lifetime value. The calibration equipment needs to read this new round of lifetime data to provide a basis for subsequent planning.

[0111] Then, the calibration device uses an iterative sorting algorithm to sort all target LED units from highest to lowest predicted lifetime, obtaining a priority ranking result. The iterative sorting algorithm can quickly and efficiently sort the lifetime values ​​of a large number of LED units and assign a priority to each LED unit. The ranking result reflects the importance of each LED.

[0112] Next, the calibration equipment will determine the key areas of the displayed content based on the target LED display screen's usage scenario and count the number of LED units in each area. Different usage scenarios, such as advertising screens and monitoring screens, have different key content areas. After determining the key areas, the number of LED units required for each area can be calculated.

[0113] Then, the calibration device will allocate LEDs sequentially according to priority based on the required number of LED units in key areas of the displayed content. LEDs with the highest lifespan priority will be allocated to key areas first, until the required number of LEDs in those areas is met; then, they will be sequentially added to other non-critical areas to complete the allocation of all LEDs.

[0114] Finally, the calibration equipment employs 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 within the same area are placed adjacent to each other. This maintains a consistent aging trend among LEDs within the same area, preventing premature local decay. Through iterative sorting, sequential allocation, and greedy algorithm optimization, the layout of LED units can be rationally planned to maximize the utilization value of LEDs.

[0115] In this embodiment, by performing preliminary testing and recording of initial display parameters for multiple LED units, determining the target display parameters for the entire screen, calculating the parameter adjustment scheme for each LED unit, and analyzing the remaining lifespan of the LED units under the adjustment scheme based on their lifespan data, target LED units with acceptable remaining lifespans are selected. Finally, these target LED units are precisely calibrated point by point to ensure that the target LED display achieves the expected display effect. Therefore, it can fully consider the performance and lifespan differences between different batches of LED units, and achieve reasonable utilization of surplus LEDs through remaining lifespan prediction. It avoids unnecessary losses that may be caused by overcalibration, ensures the long-term stable display performance of the display, and effectively solves the problem of shortened display lifespan caused by not considering batch differences and remaining lifespan in the prior art. Thus, it realizes the effective reuse of surplus LEDs and the extension of display lifespan.

[0116] The calibration device in the embodiments of this application is described below from a module perspective. Please refer to... Figure 3 This is a schematic diagram of a functional module structure of the calibration device in an embodiment of this application.

[0117] The calibration device includes:

[0118] The preliminary testing module 301 is used to perform preliminary testing on multiple LED units and record the initial display parameters of the multiple LED units;

[0119] The target determination module 302 is used to determine the target display parameters of the entire screen based on the preset display requirement threshold of the finished LED display screen;

[0120] The scheme determination module 303 is used to perform adjustment calculations on multiple LED units to obtain parameter adjustment schemes for multiple LED units from initial display parameters to target display parameters;

[0121] The lifetime prediction module 304 is used to collect and analyze the lifetime data of multiple LED units to determine the predicted remaining lifetime of each LED unit under the parameter adjustment scheme. The lifetime data includes usage time, brightness decay, color shift, and current change.

[0122] The unit screening module 305 is used to screen out multiple target LED units whose predicted remaining lifespan is within a preset durability range.

[0123] The unit calibration module 306 is used to perform point-by-point calibration on the target LED unit based on the parameter adjustment scheme, so that the display parameters of the target LED display screen composed of multiple target LED units reach the target display parameters.

[0124] In some embodiments, the scheme determination module 303 specifically includes:

[0125] The model building unit is used to build a light attenuation model for each LED unit.

[0126] The attenuation calculation unit is used to calculate the degree of light attenuation of the LED unit using a light attenuation model.

[0127] The parameter determination unit is used to calculate the amount of drive current adjustment required for the LED unit to reach the target display parameters by using a recursive algorithm based on the light attenuation degree of the LED unit, the initial display parameters and the target display parameters, and to use this as the parameter adjustment scheme for the LED unit.

[0128] In some embodiments, the lifetime prediction module 304 specifically includes:

[0129] The data reading unit is used to read the lifecycle data of each LED unit, including manufacturing time, transportation time, storage time, and usage time, and to establish a lifecycle database.

[0130] The fault statistics unit is used to calculate the average failure rate curve of LED units from different batches.

[0131] The probability calculation unit is used to calculate the predicted failure probability distribution of the LED unit based on the LED unit's life cycle data, batch, and parameter adjustment scheme, using a two-parameter Weibull distribution model.

[0132] The lifespan prediction unit is used to calculate the predicted remaining lifespan of the LED unit by combining the predicted failure probability distribution, the average failure rate curve, and the used time of the LED unit.

[0133] In some embodiments, the calibration device further includes:

[0134] The lifetime integration module is used to calculate the average predicted remaining lifetime of the target LED display based on the predicted remaining lifetime of the target LED unit.

[0135] The life assessment module is used to determine whether the average predicted remaining lifespan is lower than a preset expected threshold.

[0136] The scheme generation module is used to automatically generate multiple LED unit layout schemes based on the predicted remaining lifetime when the average predicted remaining lifetime is lower than a preset threshold.

[0137] The scheme scoring module is used to score multiple LED unit layout schemes based on a preset evaluation model for uniformity and heat dissipation performance, and obtain the scoring results.

[0138] The scheme selection module is used to select the layout scheme with the highest score as the final layout scheme for the target LED display screen.

[0139] In some embodiments, the calibration device further includes:

[0140] The region determination module is used to simulate and predict the location distribution of key content areas in the future based on the preset actual content playback data of the target LED display screen using a surface fitting algorithm, and obtain the predicted content key area distribution surface.

[0141] The boundary determination module is used to calculate the gradient direction and gradient magnitude of the surface on which the key content areas are distributed, and to determine the boundaries of the key content areas.

[0142] 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;

[0143] The unit partitioning module is used to sort multiple target LED units from high to low according to their predicted remaining lifetime, and to divide the center LED units and edge LED units according to the sorting results.

[0144] In some embodiments, the calibration device further includes:

[0145] The environmental acquisition module is used to collect actual environmental parameters of the target LED display screen, including temperature distribution, illuminance distribution, and usage frequency.

[0146] The lifetime correction module is used to correct the predicted remaining lifetime of multiple target LED units based on the temperature model and the illuminance model, and obtain the corrected lifetime distribution results.

[0147] The layout reset module is used to replan the layout of multiple target LED units on the target LED display based on the corrected lifetime distribution results.

[0148] In some embodiments, the calibration device further includes:

[0149] The data acquisition module is used to read the corrected predicted remaining lifetime data for each target LED unit;

[0150] The unit sorting module is used to sort all target LED units from high to low according to the corrected predicted remaining lifetime using an iterative sorting algorithm to obtain the priority sorting result;

[0151] The LED statistics module is used to determine the key areas of the displayed content based on the usage scenario of the target LED display screen, and to count the number of LED units in each area.

[0152] The unit allocation module is used to allocate LED units sequentially according to priority sorting results based on the required number of LED units in key areas of the displayed content.

[0153] The distribution determination module is used to optimize the position distribution of LED units in each region using a greedy algorithm, under the premise of meeting the allocation requirements, so that LED units with similar predicted lifetimes in the same region are placed in adjacent positions, thus obtaining the final layout scheme.

[0154] The above description of the calibration device in the embodiments of this application is from the perspective of modular functional entities. The following description is from the perspective of hardware processing. Please refer to [link to relevant documentation]. Figure 4 This is a schematic diagram of the physical device structure of the calibration equipment in the embodiments of this application.

[0155] It should be noted that, Figure 4 The structure of the calibration device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of the present invention.

[0156] like Figure 4 As shown, the calibration device includes a Central Processing Unit (CPU) 401, which can perform various appropriate actions and processes based on a program stored in Read-Only Memory (ROM) 402 or a program loaded from storage portion 408 into Random Access Memory (RAM) 403, such as performing the methods described in the above embodiments. Various programs and data required for system operation are also stored in RAM 403. The CPU 401, ROM 402, and RAM 403 are interconnected via bus 404. An Input / Output (I / O) interface 405 is also connected to bus 404.

[0157] The following components are connected to I / O interface 405: input section 406 including a camera, spectrometer, push-button switch, etc.; output section 407 including a liquid crystal display (LCD) and indicator lights, audio, etc.; storage section 408 including a hard disk, etc.; and communication section 409 including a network interface card such as a LAN (Local Area Network) card, modem, etc. Communication section 409 performs communication processing via a network such as the Internet. Drive 410 is also connected to I / O interface 405 as needed. Removable media 411, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 410 as needed so that computer programs read from it can be installed into storage section 408 as needed.

[0158] 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 containing computer programs for performing the methods shown 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 medium 411. When the computer program is executed by central processing unit (CPU) 401, it performs the various functions defined in the present invention.

[0159] It should be noted that the computer-readable medium shown in the embodiments of the present invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can 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 a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, 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, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium can 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 can include a data signal propagated in baseband or as part of a carrier wave, wherein a computer-readable computer program is carried. The transmitted data signal can take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof.

[0160] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0161] Specifically, the calibration device in this embodiment includes a processor and a memory. The memory stores a computer program, and when the computer program is executed by the processor, it implements the on-site calibration method for LED displays provided in the above embodiment.

[0162] In another aspect, the present invention also provides a computer-readable storage medium, which may be included in the calibration device described in the above embodiments; or it may exist independently and not assembled into the calibration device. The storage medium carries one or more computer programs that, when executed by a processor of the calibration device, cause the calibration device to implement the LED display screen on-site calibration method provided in the above embodiments.

[0163] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

[0164] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as meaning "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is interpreted as meaning "if determining...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

[0165] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. This computer program product includes one or more computer instructions. When these computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this 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, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive), etc.

[0166] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above 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 calibration equipment, characterized in that, The method includes: Perform preliminary testing on multiple LED units and record the initial display parameters of the multiple LED units; Based on the preset display requirement threshold of the finished LED display screen, the target display parameters of the overall screen are determined; Adjustment calculations are performed 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; The process involves collecting and analyzing the lifecycle data of multiple LED units to determine their predicted remaining lifespan under the parameter adjustment scheme. The lifecycle data includes usage time, brightness decay, color shift, and current variation. Specifically, this process includes: reading lifecycle data for each LED unit, including manufacturing time, transportation time, storage time, and usage time, and establishing a lifecycle database; statistically analyzing the average failure rate curves of LED units from different batches; calculating the predicted failure probability distribution of the LED unit using a two-parameter Weibull distribution model based on its lifecycle data, batch number, and parameter adjustment scheme; and combining the predicted failure probability distribution, the average failure rate curve, and the used time of the LED unit to calculate its predicted remaining lifespan. Multiple target LED units whose predicted remaining lifespan is within a preset durability range are selected; Based on the parameter adjustment scheme, the target LED units are 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 step of adjusting and calculating 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 specifically includes: A light attenuation model is established for each LED unit; The light attenuation level of the LED unit is calculated using the light attenuation model. Based on the light attenuation level of the LED unit, the initial display parameters, and the target display parameters, a recursive algorithm is used to calculate in reverse the amount of drive current adjustment required for the LED unit to reach the target display parameters, which serves as the parameter adjustment scheme for the LED unit.

3. The method according to claim 1, characterized in that, After the step of performing point-by-point calibration on the target LED unit based on the parameter adjustment scheme, the method further includes: Based on the predicted remaining lifetime of the target LED unit, calculate the average predicted remaining lifetime of the target LED display screen; Determine whether the average predicted remaining lifespan is lower than a preset expected threshold. If the average predicted remaining lifetime is lower than the preset expected threshold, then based on the predicted remaining lifetime, a genetic algorithm is used to automatically generate multiple LED unit layout schemes. Based on a preset evaluation model for uniformity and heat dissipation performance, the layout schemes of the multiple LED units are scored to obtain the scoring results. The layout scheme with the highest score is selected as the final layout scheme for the target LED display screen.

4. The method according to claim 1, characterized in that, After the step of performing point-by-point calibration 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, the location distribution of key content areas in the future is simulated and predicted to obtain the predicted content key area distribution surface; Calculate the gradient direction and gradient magnitude of the surface on which the content focus area is distributed, and determine the boundary of the content focus area; 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 edge LED units; The target LED units are sorted from highest to lowest according to their predicted remaining lifetime, and the center LED unit and the edge LED units are divided according to the sorting results.

5. The method according to claim 3, characterized in that, After the step of performing point-by-point calibration on the target LED unit based on the parameter adjustment scheme, the method further includes: Collect actual environmental parameters of the target LED display screen, including temperature distribution, illuminance distribution, and usage frequency; Based on the temperature model and the illuminance model, the predicted remaining lifetime of the multiple target LED units is corrected to obtain the corrected lifetime distribution results. Based on the revised lifetime distribution results, the final layout scheme of the plurality of target LED units on the target LED display screen is replanned.

6. The method according to claim 5, characterized in that, The step of replanning the final layout scheme of the plurality of target LED units on the target LED display screen based on the corrected lifetime distribution results specifically includes: Read the corrected predicted remaining lifetime data for 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 lifetime, and the priority sorting result is obtained. Based on the usage scenario of the target LED display screen, determine the key areas for displaying its content, and count the number of LED units in each area; Based on the LED unit quantity requirements of the key areas of the displayed content, they are allocated sequentially according to the priority sorting results. A greedy algorithm is used to optimize the positional distribution of LED units in each region while meeting the allocation requirements, so that LED units with similar predicted remaining lifespans in the same region are placed in adjacent positions, thus obtaining the final layout scheme.

7. A calibration device, characterized in that, include: The preliminary testing module is used to perform preliminary testing on multiple LED units and record the initial display parameters of the multiple LED units; The target determination module is used to determine the target display parameters of the entire screen based on the preset display requirement threshold of the finished LED display screen; The scheme determination module is used to perform adjustment calculations 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; The lifespan prediction module is used to collect and analyze the lifespan data of the multiple LED units to determine the predicted remaining lifespan of each LED unit under the parameter adjustment scheme. The lifespan data includes usage time, brightness decay, color shift, and current variation. Specifically, collecting and analyzing the lifespan data of the multiple LED units to determine the predicted remaining lifespan of each LED unit under the parameter adjustment scheme includes: reading the lifespan data of each LED unit, including manufacturing time, transportation time, storage time, and usage time, and establishing a lifespan database; statistically analyzing the average failure rate curves of LED units from different batches; calculating the predicted failure probability distribution of the LED unit using a two-parameter Weibull distribution model based on the lifespan data, batch, and parameter adjustment scheme; and calculating the predicted remaining lifespan of the LED unit by combining the predicted failure probability distribution, the average failure rate curve, and the usage time of the LED unit. The unit filtering module is used to filter out multiple target LED units whose predicted remaining lifespan is within a preset durability range; The unit calibration module is used to perform point-by-point calibration on the target LED unit 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.

8. A calibration device, characterized in that, include: One or more processors and memory; The memory is coupled to the one or more processors, the memory being used to store computer program code, the computer program code including computer instructions, the one or more processors invoking the computer instructions to cause the calibration device to perform the method as described in any one of claims 1-6.

9. A computer-readable storage medium comprising instructions, characterized in that, When the instruction is executed on the calibration device, the calibration device performs the method as described in any one of claims 1-6.

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