A heat dissipation optimization control method and device for an LED display screen

Abstract

The application discloses a heat dissipation optimization control method and device of an LED display screen, and relates to the technical field of LED display, which comprises the following steps: obtaining real-time working information of the LED display screen through dynamic monitoring; reading a predetermined working characteristic factor, performing traversal analysis on the real-time working information, and obtaining a factor parameter set; reading a predetermined factor weight distribution, performing weighted calculation on the factor parameter set, and obtaining a real-time heat dissipation demand coefficient; based on a real-time heat dissipation demand level corresponding to the real-time heat dissipation demand coefficient, calling a target heat dissipation strategy, and performing dynamic heat dissipation control on the LED display screen. The application solves the technical problem that the existing heat dissipation control mode of the LED display screen is fixed, cannot dynamically adapt to a real-time working state, and results in low heat dissipation efficiency and high energy consumption, and achieves the technical effects of intelligently adjusting a heat dissipation strategy, improving heat dissipation efficiency and reducing energy consumption through real-time monitoring of working information and dynamic calculation of heat dissipation demand.

Description

Technical Field

[0001] This invention relates to the field of LED display technology, and more specifically to a method and apparatus for optimizing and controlling the heat dissipation of an LED display screen. Background Technology

[0002] With the widespread application of LED displays in various scenarios, they often generate a large amount of heat when operating at high brightness, for extended periods, and displaying complex content, leading to temperature increases that affect display performance and equipment lifespan. Traditional heat dissipation control methods typically rely on fixed cooling approaches, such as air cooling or liquid cooling systems. These methods may not adequately meet the heat dissipation requirements of the display under different operating conditions, resulting in low heat dissipation efficiency or overheating problems. Furthermore, existing technologies lack precise monitoring and dynamic adjustment of the display's real-time operating status, making it impossible to flexibly adjust heat dissipation strategies based on real-time load and environmental changes. Summary of the Invention

[0003] This application provides a heat dissipation optimization control method and device for LED displays, which solves the technical problem that the existing heat dissipation control mode of LED displays is fixed and cannot dynamically adapt to the real-time working state, resulting in low heat dissipation efficiency and high energy consumption.

[0004] The first aspect of this application provides a method for optimizing and controlling the heat dissipation of an LED display screen. The method includes: dynamically monitoring and obtaining real-time operating information of the LED display screen; reading predetermined operating characteristic factors and performing traversal analysis on the real-time operating information based on the predetermined operating characteristic factors to obtain a set of factor parameters; reading predetermined factor weight allocations and performing weighted calculations on the set of factor parameters in conjunction with the predetermined factor weight allocations to obtain a real-time heat dissipation demand coefficient; retrieving a target heat dissipation strategy from a heat dissipation strategy library based on the real-time heat dissipation demand level corresponding to the real-time heat dissipation demand coefficient; and performing dynamic heat dissipation control on the LED display screen through the target heat dissipation strategy.

[0005] A second aspect of this application provides a heat dissipation optimization control device for an LED display screen. The device includes: a working status monitoring module for dynamically monitoring and obtaining real-time working information of the LED display screen; a working feature acquisition module for reading predetermined working feature factors and performing traversal analysis on the real-time working information based on the predetermined working feature factors to obtain a factor parameter set; a real-time heat dissipation demand calculation module for reading predetermined factor weight allocations and performing weighted calculations on the factor parameter set based on the predetermined factor weight allocations to obtain a real-time heat dissipation demand coefficient; a heat dissipation strategy matching module for retrieving a target heat dissipation strategy from a heat dissipation strategy library based on the real-time heat dissipation demand level corresponding to the real-time heat dissipation demand coefficient; and a dynamic heat dissipation control module for dynamically controlling the heat dissipation of the LED display screen using the target heat dissipation strategy.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0007] This application provides a heat dissipation optimization control method and device for LED displays, relating to the field of LED display technology. By dynamically monitoring the real-time operating information of the LED display, combining predetermined operating characteristic factor analysis and factor weight allocation, a real-time heat dissipation demand coefficient is calculated. Based on this coefficient, a target heat dissipation strategy from a heat dissipation strategy library is retrieved for dynamic heat dissipation control of the LED display, thereby optimizing the heat dissipation effect and adapting to different operating conditions. This solves the technical problem of existing LED display heat dissipation control modes being fixed and unable to dynamically adapt to real-time operating states, resulting in low heat dissipation efficiency and high energy consumption. It achieves the technical effect of improving heat dissipation efficiency and reducing energy consumption by intelligently adjusting the heat dissipation strategy through real-time monitoring of operating information and dynamic calculation of heat dissipation demand. Attached Figure Description

[0008] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0009] Figure 1 A schematic flowchart of a heat dissipation optimization control method for an LED display screen provided in an embodiment of this application;

[0010] Figure 2 This is a schematic diagram of a heat dissipation optimization control device for an LED display screen, provided in an embodiment of this application.

[0011] Explanation of reference numerals in the attached diagram: 11. Working status monitoring module; 12. Working characteristic acquisition module; 13. Real-time heat dissipation demand calculation module; 14. Heat dissipation strategy matching module; 15. Dynamic heat dissipation control module. Detailed Implementation

[0012] This application provides a heat dissipation optimization control method and device for LED displays, which solves the technical problem that the existing heat dissipation control mode of LED displays is fixed and cannot dynamically adapt to the real-time working state, resulting in low heat dissipation efficiency and high energy consumption.

[0013] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0014] It should be noted that the terms "first," "second," etc., in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to such processes, methods, products, or devices.

[0015] Example 1, as Figure 1 As shown, this application provides a heat dissipation optimization control method for an LED display screen, the method comprising:

[0016] P10: Dynamic monitoring obtains real-time operating information of the LED display screen.

[0017] Specifically, dynamic monitoring is a fundamental step in optimizing the heat dissipation control of LED displays. This involves deploying a sensor network inside or around the LED display to collect various operational information in real time, including but not limited to key parameters such as temperature, brightness, current, and voltage. The sensors used can include temperature sensors, light intensity sensors, and current / voltage sensors, enabling high-precision and high-frequency data collection to ensure that the acquired information accurately reflects the real-time operating status of the display.

[0018] Real-time operating information covers all heat dissipation-related parameters during display operation. For example, temperature sensors can accurately measure temperature changes in different areas of the display. Light intensity sensors monitor brightness changes, as higher brightness typically corresponds to greater heat generation. Current and voltage sensors detect current and voltage fluctuations in the display, changes in which also affect the display's heat dissipation requirements.

[0019] To ensure the accurate and complete transmission of sensor-collected data to the control center, the data acquisition system and communication module must work together. The data acquisition system filters, amplifies, and performs analog-to-digital conversion on the sensor signals to ensure data accuracy and integrity. The communication module uses wired or wireless communication technologies, such as Wi-Fi, Bluetooth, or industrial bus, to transmit data quickly and stably to the central processing unit. In practical applications, the frequency of dynamic monitoring can be flexibly adjusted according to the display's usage scenario and heat dissipation requirements. For example, under high-load operation, the monitoring frequency can be appropriately increased to promptly capture rapid changes in key parameters such as temperature; while under low-load operation, the monitoring frequency can be appropriately reduced to save energy.

[0020] By dynamically monitoring the real-time operating information of LED displays, accurate and real-time data support can be provided for subsequent heat dissipation demand analysis and heat dissipation strategy formulation, thereby achieving optimized control of LED display heat dissipation.

[0021] P20: Read the predetermined work characteristic factors, and perform a traversal analysis on the real-time work information based on the predetermined work characteristic factors to obtain the factor parameter set.

[0022] Furthermore, before performing a traversal analysis of the real-time work information based on the predetermined work characteristic factors to obtain the factor parameter set, the predetermined work characteristic factors must first be obtained. In this embodiment, step P20 further includes:

[0023] P21a: Collect thermal characteristic records of similar LED displays; P22a: Extract the first record from the thermal characteristic records of similar displays, and perform collaborative analysis on the first operating information and the first thermal characteristic information in the first record to obtain a first collaborative analysis result; wherein, the first operating information includes operating data of predetermined operating characteristic indicators, wherein the predetermined operating characteristic indicators include at least brightness output, content refresh rate, ambient temperature, grayscale level, color mode, and the proportion of LEDs lit in the display area. The first thermal characteristic information includes indicator data of the predetermined thermal characteristic indicators, wherein the predetermined thermal characteristic indicators include at least heat generation power, thermal resistance, and heat dissipation efficiency. P23a: Take the union of the first relevant operating characteristics in the first collaborative analysis result as the predetermined operating characteristic factor.

[0024] It should be understood that determining predetermined operating characteristic factors and then performing a comprehensive analysis of real-time operating information based on these factors to obtain a set of factor parameters is crucial. Specifically, to determine the predetermined operating characteristic factors, it is first necessary to collect thermal characteristic records of similar LED displays. These records typically originate from operational data of the same model or type of display during actual use, including information such as temperature changes, heat dissipation effects, and operating status. This data can be collected through on-site monitoring equipment or obtained from existing databases. The purpose of collecting these records is to establish a reference model so that operating characteristic factors closely related to heat dissipation requirements can be identified in subsequent analyses.

[0025] Next, a first record is extracted from the collected thermal characteristic records of similar displays, and the first operational information and first thermal characteristic information in this record are analyzed collaboratively. The first operational information includes operational data for predetermined operational characteristic indicators, such as brightness output, content refresh rate, ambient temperature, grayscale level, color mode, and the proportion of LEDs lit in the display area. These indicators reflect the actual operating status of the display and are important factors affecting heat dissipation requirements. The first thermal characteristic information includes indicator data for predetermined thermal characteristic indicators, such as heat generation power, thermal resistance, and heat transfer efficiency. By collaboratively analyzing this operational information and thermal characteristic information, the correlation between them can be identified, i.e., which operational characteristic indicators have a significant impact on heat dissipation requirements.

[0026] Based on the collaborative analysis, the union of the first relevant working characteristics from the first collaborative analysis results is taken as the predetermined working characteristic factors. This means that the working characteristic indicators closely related to heat dissipation requirements, determined through analysis, will be incorporated into the subsequent heat dissipation requirement assessment system. These predetermined working characteristic factors will serve as the basis for subsequent traversal analysis, used to extract parameters related to heat dissipation requirements from real-time working information.

[0027] After obtaining the predetermined operating characteristic factors, real-time operating information can be analyzed traversally based on these factors. Specifically, real-time data, including temperature, brightness, current, and voltage, is acquired by dynamically monitoring the real-time operating information of the LED display screen. This data is collected through a sensor network and data acquisition system and transmitted to the central processing unit. During the traversal analysis, each item of real-time operating information is checked, and key data related to the predetermined operating characteristic factors is extracted. For example, the current brightness value of the display screen is extracted as a parameter for brightness output, the refresh rate of the display screen content is extracted as a parameter for content refresh rate, the temperature of the environment in which the display screen is located is extracted as a parameter for ambient temperature, the grayscale level of the display screen is extracted as a parameter for grayscale level, the color mode of the display screen is extracted as a parameter for color mode, and the proportion of LEDs lit in the display screen is extracted as a parameter for the proportion of LEDs lit in the display area.

[0028] After data extraction, it needs to be processed to ensure its accuracy and usability. Processing may include normalizing brightness output data to a range of 0 to 1; converting the refresh rate data to units consistent with the system settings; filtering ambient temperature data to remove noise; quantizing grayscale data to ensure it falls within a preset grayscale range; encoding color mode data for system recognition; and converting the LED illumination ratio data to a percentage, ensuring it falls within a range of 0 to 100%. Through these processing steps, the extracted data is transformed into standardized parameter values, generating a factor parameter set. This factor parameter set will serve as a crucial basis for subsequent weighted calculations and heat dissipation requirement assessments.

[0029] Furthermore, step P23a in the embodiments of this application also includes:

[0030] P23-1a: Perform a many-to-many correlation analysis on the first working information and the first thermal characteristic information to obtain the first collaborative analysis result; P23-2a: Extract the first analysis result of the first thermal characteristic index from the first collaborative analysis result, wherein the first analysis result includes a first factor set that is significantly related to the first thermal characteristic index, and the first thermal characteristic index refers to any one of the predetermined thermal characteristic indices; P23-3a: Take the union of the first factor set to obtain the first target factor set of the first thermal characteristic index; P23-4a: Construct the predetermined working characteristic factor based on the first target factor set.

[0031] In one possible embodiment of this application, the process of extracting operating characteristic factors closely related to heat dissipation requirements from the first collaborative analysis results and finally determining predetermined operating characteristic factors can be further refined.

[0032] After collecting and collaboratively analyzing thermal characteristic records of similar displays, the first step is to perform a many-to-many correlation analysis between the first operating information and the first thermal characteristic information. This means analyzing not only the relationship between a single operating characteristic indicator and a single thermal characteristic indicator, but also considering the complex interactions between multiple operating characteristic indicators and multiple thermal characteristic indicators to obtain the first collaborative analysis result, which includes the degree of correlation between various operating characteristic indicators and thermal characteristic indicators. This analysis can not only identify the direct relationship between operating information and thermal characteristic indicators, but also reveal potential indirect effects, ensuring that the system can fully understand the combined effect of various factors on heat dissipation requirements.

[0033] Next, a first set of factors significantly correlated with each first thermal characteristic index is extracted from the results of the first collaborative analysis. A first thermal characteristic index refers to any one of the predetermined thermal characteristic indices, such as heat generation power, thermal resistance, or heat dissipation efficiency. For each thermal characteristic index, the analysis results will provide a set of operational characteristic indices significantly correlated with it; these indices constitute the first set of factors. For example, if the analysis finds that brightness output and content refresh rate are significantly correlated with heat generation power, then these two operational characteristic indices will be included in the first factor set of heat generation power.

[0034] Then, the union of the extracted first factor sets is taken to obtain the first target factor set for each first thermal characteristic index. The purpose of this step is to summarize all working characteristic indices that are significantly related to different thermal characteristic indices, forming a more comprehensive factor set. In this way, it can be ensured that all factors that have a significant impact on thermal characteristics are fully considered in practical applications, avoiding the omission of any important factors.

[0035] Finally, predetermined operational characteristic factors are constructed based on the first target factor set. This means that the operational characteristic indicators from the summarized first target factor set are identified as key indicators to be used in subsequent heat dissipation requirement assessments. These predetermined operational characteristic factors will serve as the basis for subsequent heat dissipation requirement assessments, used to extract parameters related to heat dissipation requirements from real-time operational information, thereby providing a basis for the selection and adjustment of heat dissipation strategies.

[0036] P30: Read the predetermined factor weight allocation and perform weighted calculation on the factor parameter set in combination with the predetermined factor weight allocation to obtain the real-time heat dissipation demand coefficient.

[0037] Furthermore, step P30 in this embodiment of the application also includes:

[0038] P31: Traverse the set of factor parameters to obtain the first target parameter set corresponding to the first thermal characteristic index; P32: Perform a coefficient of variation weighted calculation on the first target parameter set to obtain the first index; P33: Calculate the first index in combination with the predetermined factor weight allocation to obtain the real-time heat dissipation demand coefficient; wherein, the predetermined factor weight allocation is a weight allocation determined based on the regression coefficients obtained by regression analysis of the application simulation data of the LED display screen.

[0039] It should be understood that by reading the predetermined factor weight allocation and combining these weights to perform weighted calculations on the factor parameter set, the real-time heat dissipation demand coefficient is finally obtained, ensuring that the heat dissipation demand of the LED display screen under different working conditions can be reasonably predicted and controlled.

[0040] First, it is necessary to traverse the factor parameter set to extract the first target parameter set corresponding to the first thermal characteristic index. The first thermal characteristic index refers to the key thermal characteristic index closely related to heat dissipation requirements identified in the previous analysis, such as heat generation power, thermal resistance, or heat dissipation efficiency. By traversing the factor parameter set, a subset of parameters directly related to these thermal characteristic indices can be selected, providing basic data for subsequent weighted calculations.

[0041] Next, a weighted calculation based on the coefficient of variation (COP) is performed on the first target parameter set to obtain the first index. The COP is a statistic that measures the dispersion of data; by calculating the COP of each parameter, its importance in the heat dissipation requirement can be assessed. Specifically, for each parameter in the first target parameter set, its COP is calculated, and the parameters are weighted according to the COP. A larger COP indicates a greater impact of the parameter's fluctuation on the heat dissipation requirement, and therefore, it is assigned a higher weight in the weighted calculation. In this way, a first index that comprehensively reflects the characteristics of the first target parameter set can be obtained.

[0042] Then, the first index is calculated by combining the predetermined factor weight allocation to obtain the real-time heat dissipation demand coefficient. The predetermined factor weight allocation is determined by regression coefficients obtained from regression analysis of application simulation data of the LED display screen. This means that in determining the weights, not only the coefficient of variation of the parameters is considered, but also the simulation data in actual applications is combined to determine the actual contribution of each parameter to the heat dissipation demand through regression analysis. Regression analysis is a statistical method that can quantify the relationship between various parameters and heat dissipation demand, thus providing a scientific basis for weight allocation. By combining the first index with the predetermined factor weight allocation, the real-time heat dissipation demand coefficient is finally obtained. This coefficient can accurately reflect the degree of heat dissipation demand of the LED display screen under the current working state, providing a basis for the selection of subsequent heat dissipation strategies, ensuring that the temperature of the LED display screen is effectively controlled, and avoiding overheating problems that affect its performance and lifespan.

[0043] P40: Based on the real-time heat dissipation demand level corresponding to the real-time heat dissipation demand coefficient, retrieve the target heat dissipation strategy from the heat dissipation strategy library. The heat dissipation strategy library includes multiple heat dissipation strategies formed by combining one or more predetermined heat dissipation methods, wherein the predetermined heat dissipation methods include air cooling, liquid cooling, heat pipe cooling, and semiconductor refrigeration.

[0044] Furthermore, step P40 in this embodiment of the application also includes:

[0045] P41: Traverse the real-time heat dissipation demand level in the historical heat dissipation records to obtain multiple historical records for processing the real-time heat dissipation demand level; P42: Extract the first historical record from the multiple historical records, wherein the first historical record includes a first historical heat dissipation strategy and a first historical heat dissipation data; P43: Analyze the first historical heat dissipation data to obtain the first historical heat dissipation effect, and sort them in descending order to obtain the historical heat dissipation strategy corresponding to the first historical heat dissipation effect in the descending list, and use it as the target heat dissipation strategy.

[0046] Optionally, based on the real-time heat dissipation demand level corresponding to the real-time heat dissipation demand coefficient, a suitable target heat dissipation strategy can be retrieved from the heat dissipation strategy library to ensure that the LED display screen maintains good heat dissipation performance during operation.

[0047] The heat dissipation strategy library is a pre-built database that stores multiple heat dissipation strategies formed by combinations of one or more predetermined heat dissipation methods. These predetermined heat dissipation methods include air cooling, liquid cooling, heat pipe cooling, and semiconductor refrigeration. Each heat dissipation strategy corresponds to a specific level of heat dissipation requirement, ensuring that a suitable heat dissipation solution can be found under different operating conditions.

[0048] Specifically, the real-time cooling demand level is first traversed through historical cooling records to obtain multiple historical records of handling that demand level. These historical records contain cooling strategies employed in the past under similar demand levels, along with their corresponding cooling performance data. By traversing these records, historical cases matching the current real-time cooling demand level can be found, providing a reference for subsequent cooling strategy selection.

[0049] Next, the first historical record is extracted from multiple historical records. The first historical record includes the first historical cooling strategy and the first historical cooling data. The first historical cooling strategy refers to the specific cooling scheme adopted under a similar level of cooling demand in the past, while the first historical cooling data records the actual cooling effect after the strategy was implemented, such as temperature changes and key indicators like cooling efficiency. By extracting this historical data, past cooling strategies can be evaluated and analyzed.

[0050] Next, the first historical heat dissipation data is analyzed to evaluate its heat dissipation effect. Specifically, by analyzing the first historical heat dissipation data, the first historical heat dissipation effect can be obtained. This effect can be measured by comparing the difference between the actual heat dissipation result and the expected target. Then, the first historical heat dissipation effect is compared with other historical heat dissipation effects and sorted in descending order according to the effectiveness of heat dissipation, forming a descending list. In this list, the historical heat dissipation strategy corresponding to the first historical heat dissipation effect is selected as the target heat dissipation strategy. This means that through the analysis of historical data, the heat dissipation strategy that performed best under similar heat dissipation demand levels in the past has been selected as the solution for the current real-time heat dissipation demand.

[0051] By following the steps described above, a suitable target cooling strategy can be scientifically retrieved from the cooling strategy library. This process not only considers the real-time cooling demand level but also incorporates the analysis of historical cooling records to ensure that the selected cooling strategy is efficient and reliable.

[0052] P50: Dynamically control the heat dissipation of the LED display screen through the target heat dissipation strategy.

[0053] Specifically, after determining the target heat dissipation strategy, dynamic heat dissipation control of the LED display can be implemented. The target heat dissipation strategy is the optimal heat dissipation solution derived in the previous steps by comprehensively considering the real-time heat dissipation demand coefficient, heat dissipation demand level, and historical heat dissipation record analysis. This strategy may include a combination of one or more heat dissipation methods, such as air cooling, liquid cooling, heat pipe cooling, and semiconductor refrigeration, depending on the actual heat dissipation requirements and operating environment of the LED display.

[0054] For example, firstly, based on the target heat dissipation strategy, a suitable heat dissipation method (such as air cooling, liquid cooling, heat pipe cooling, or semiconductor cooling) is selected. For instance, if the current display has high heat dissipation requirements, it can be adjusted to liquid cooling or semiconductor cooling; while under lighter loads and lower heat dissipation requirements, air cooling or heat pipe cooling may be sufficient. This flexible selection of heat dissipation methods can achieve optimal heat dissipation performance under different operating conditions.

[0055] Secondly, the cooling strategy is implemented by adjusting the operating parameters of the heat dissipation equipment. For example, if the target cooling strategy is air cooling, the fan speed or the number of fans activated can be adjusted based on the real-time heat dissipation demand coefficient; if a liquid cooling system is used, the cooling efficiency can be adjusted by controlling the liquid flow rate; and in semiconductor cooling solutions, the workload of the cooling module can be adjusted. By precisely controlling these heat dissipation parameters, the system can ensure stable temperature control of the LED display screen, avoiding performance degradation or hardware damage caused by overheating.

[0056] Furthermore, dynamic heat dissipation control also includes real-time adjustments to the heat dissipation system. When the workload of the display changes (such as changes in the complexity of the displayed content or brightness), the heat dissipation strategy can be adjusted in real time to ensure that it adapts to the new operating conditions. For example, in high-brightness display mode, power consumption and heat dissipation requirements increase, so a more efficient heat dissipation method can be switched; when the displayed content changes or the load decreases, the heat dissipation requirements decrease, so the heat dissipation intensity can be reduced in a timely manner, thereby improving energy efficiency and avoiding excessive consumption.

[0057] By implementing a targeted heat dissipation strategy to control the heat dissipation of LED displays in real time and dynamically, it is ensured that the heat dissipation of the display is always in the best state under various workloads and environmental conditions, thereby effectively extending its service life and improving overall operating efficiency.

[0058] Furthermore, after dynamically controlling the heat dissipation of the LED display screen through the target heat dissipation strategy, step P50 in this embodiment of the application further includes:

[0059] P51a: Construct the target part set of the LED display screen; P52a: Match the first temperature time series corresponding to the first part in the first historical heat dissipation data, wherein the first part refers to any part in the target part set; P53a: Perform regression fitting analysis on the first temperature time series to obtain the first temperature curve; P54a: When the slope of the curve corresponding to the first temperature curve does not meet the predetermined threshold, take the historical heat dissipation strategy corresponding to the second historical heat dissipation effect in the descending sequence list as the backup heat dissipation strategy to replace the target heat dissipation strategy; wherein the normalized result of the curve slope is used as the first historical heat dissipation index of the first part, and weighted to obtain the first historical heat dissipation result.

[0060] In one possible embodiment of this application, further dynamic heat dissipation control includes not only adjusting the operation of the heat dissipation system according to the target heat dissipation strategy, but also detailed monitoring of the target parts of the LED display screen and optimization of the heat dissipation strategy when necessary.

[0061] After implementing dynamic heat dissipation control for the LED display using a targeted heat dissipation strategy, the first step is to establish a target component set based on the LED display's structure and operational requirements. This target component set includes all critical heat dissipation components on the display, which may include display modules, driver circuits, heat sinks, fans, etc. By precisely defining these components, temperature monitoring and heat dissipation control can be performed on specific components in subsequent steps, ensuring uniform and efficient heat dissipation across the entire display.

[0062] Next, the first temperature time series corresponding to the first location is matched with the first historical heat dissipation data. The first location refers to any location within the target location set. The first temperature time series records the temperature changes of that location during the historical heat dissipation process, including the temperature trend and specific values ​​over time. By matching the first temperature time series, the actual temperature performance of that location under the historical heat dissipation strategy can be obtained.

[0063] Then, regression fitting analysis is performed on the first temperature time series to obtain the first temperature curve. Regression fitting analysis is a mathematical method that, by fitting temperature data, obtains a curve that reflects the temperature change trend. This curve can intuitively show the temperature change of the first part during the heat dissipation process, providing a basis for subsequent evaluation of the heat dissipation effect.

[0064] Next, the slope of the first temperature curve is evaluated to determine if it meets a predetermined threshold. The slope reflects the rate of temperature change, i.e., the speed of heat dissipation. If the slope does not meet the predetermined threshold, it indicates that the current target heat dissipation strategy is not effective at that location. In this case, adjustments need to be made. Therefore, if the slope of the first temperature curve does not meet the predetermined threshold, the system will select the strategy corresponding to the second-highest historical heat dissipation effect from the previous historical heat dissipation strategy list as a backup heat dissipation strategy and replace the current target heat dissipation strategy with this backup strategy. The selection of the backup heat dissipation strategy aims to provide a more efficient heat dissipation effect, thereby optimizing the heat dissipation performance of the display.

[0065] Furthermore, the normalized slope of the curve was used as the first historical heat dissipation index for the first part, which quantifies the heat dissipation efficiency of the display screen. By weighting the first historical heat dissipation results, the overall effectiveness of the heat dissipation strategy for that part can be determined, providing valuable data support for further optimization of heat dissipation.

[0066] Following the dynamic heat dissipation control steps outlined above, a detailed analysis and evaluation of the heat dissipation effect is conducted. This not only allows for dynamic adjustment of the heat dissipation strategy based on real-time data but also enables precise monitoring of various components of the LED display screen, promptly identifying and resolving issues of uneven or insufficient heat dissipation. This process achieves adaptive optimization of the heat dissipation strategy, ensuring that the display screen maintains a suitable operating temperature under various workloads, thereby extending equipment lifespan and improving overall performance.

[0067] In summary, the embodiments of this application have at least the following technical effects:

[0068] This application dynamically adjusts the heat dissipation strategy by monitoring the LED display screen's operating information in real time and combining it with predetermined operating characteristic factors and weight allocations, ensuring that the display screen achieves optimal heat dissipation under different operating conditions. By accurately calculating the real-time heat dissipation demand coefficient, the system can more precisely select the most suitable heat dissipation strategy, avoiding excessive or insufficient heat dissipation, thereby improving overall heat dissipation efficiency. Dynamically optimized heat dissipation control can effectively avoid overheating problems, extend the lifespan of the LED display screen, and reduce malfunctions or performance degradation caused by excessive temperature. In addition, it can flexibly adjust the heat dissipation strategy according to the real-time load of the display screen and environmental changes, solving the shortcomings of traditional fixed heat dissipation methods that cannot adapt to changing operating conditions.

[0069] It achieves the technical effect of intelligently adjusting the heat dissipation strategy by monitoring working information in real time and dynamically calculating heat dissipation needs, thereby improving heat dissipation efficiency and reducing energy consumption.

[0070] Example 2, based on the same inventive concept as the heat dissipation optimization control method for an LED display screen in the foregoing examples, such as... Figure 2 As shown, this application provides a heat dissipation optimization control device for LED displays. The device and method embodiments in this application are based on the same inventive concept. The device includes:

[0071] The working status monitoring module 11 is used to dynamically monitor and obtain the real-time working information of the LED display screen.

[0072] The work feature acquisition module 12 is used to read predetermined work feature factors and perform traversal analysis on the real-time work information based on the predetermined work feature factors to obtain a factor parameter set.

[0073] The real-time heat dissipation demand calculation module 13 is used to read the predetermined factor weight allocation and perform weighted calculation on the factor parameter set in combination with the predetermined factor weight allocation to obtain the real-time heat dissipation demand coefficient.

[0074] The heat dissipation strategy matching module 14 is used to retrieve a target heat dissipation strategy from the heat dissipation strategy library based on the real-time heat dissipation demand level corresponding to the real-time heat dissipation demand coefficient. The heat dissipation strategy library includes multiple heat dissipation strategies formed by combining one or more predetermined heat dissipation methods, wherein the predetermined heat dissipation methods include air cooling, liquid cooling, heat pipe cooling, and semiconductor refrigeration.

[0075] The dynamic heat dissipation control module 15 is used to dynamically control the heat dissipation of the LED display screen through the target heat dissipation strategy.

[0076] Furthermore, the working feature acquisition module 12 is also used to perform the following steps:

[0077] Collect thermal characteristic records of similar LED displays; extract the first record from the thermal characteristic records of similar displays, and perform collaborative analysis on the first working information and the first thermal characteristic information in the first record to obtain the first collaborative analysis result; take the union of the first relevant working features in the first collaborative analysis result as the predetermined working feature factor.

[0078] Furthermore, the working feature acquisition module 12 is also used to perform the following steps:

[0079] A many-to-many correlation analysis is performed on the first working information and the first thermal characteristic information to obtain the first collaborative analysis result. A first analysis result of the first thermal characteristic index is extracted from the first collaborative analysis result. The first analysis result includes a first factor set significantly correlated with the first thermal characteristic index, where the first thermal characteristic index refers to any one of the predetermined thermal characteristic indices. The union of the first factor sets is taken to obtain a first target factor set for the first thermal characteristic index. The predetermined working characteristic factors are constructed based on the first target factor set. The first working information includes working data of the predetermined working characteristic index, which includes at least brightness output, content refresh rate, ambient temperature, grayscale level, color mode, and the proportion of LEDs lit in the display area. The first thermal characteristic information includes index data of the predetermined thermal characteristic index, which includes at least heat generation power, thermal resistance, and heat dissipation efficiency.

[0080] Furthermore, the real-time heat dissipation demand calculation module 13 is also used to perform the following steps:

[0081] The first target parameter set corresponding to the first thermal characteristic index is obtained by traversing the set of factor parameters; the first index is obtained by performing a coefficient of variation weighted calculation on the first target parameter set; the first index is calculated in combination with the predetermined factor weight allocation to obtain the real-time heat dissipation demand coefficient; wherein, the predetermined factor weight allocation is a weight allocation determined based on the regression coefficients obtained by regression analysis on the application simulation data of the LED display screen.

[0082] Furthermore, the heat dissipation strategy matching module 14 is also used to perform the following steps:

[0083] The real-time heat dissipation demand level is traversed through historical heat dissipation records to obtain multiple historical records for processing the real-time heat dissipation demand level; the first historical record is extracted from the multiple historical records, wherein the first historical record includes a first historical heat dissipation strategy and a first historical heat dissipation data; the first historical heat dissipation data is analyzed to obtain a first historical heat dissipation effect, and the historical heat dissipation strategy corresponding to the first historical heat dissipation effect in the descending order is obtained and used as the target heat dissipation strategy.

[0084] Furthermore, the dynamic heat dissipation control module 15 is also used to perform the following steps:

[0085] A target part set for the LED display screen is constructed; a first temperature time series corresponding to a first part is matched in the first historical heat dissipation data, wherein the first part refers to any part in the target part set; a regression fitting analysis is performed on the first temperature time series to obtain a first temperature curve; when the slope of the curve corresponding to the first temperature curve does not meet a predetermined threshold, the historical heat dissipation strategy corresponding to the second-ranked historical heat dissipation effect in the descending sequence list is taken as a backup heat dissipation strategy to replace the target heat dissipation strategy; wherein the normalized result of the curve slope is used as the first historical heat dissipation index of the first part, and the first historical heat dissipation result is obtained by weighting.

[0086] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0087] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0088] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application intends to include such modifications and variations.

Claims

1. A method for optimizing and controlling the heat dissipation of an LED display screen, characterized in that, include: Dynamic monitoring obtains real-time operating information of the LED display screen; Read the predetermined work characteristic factors, and perform a traversal analysis on the real-time work information based on the predetermined work characteristic factors to obtain a set of factor parameters; Read the predetermined factor weight allocation, and perform weighted calculation on the factor parameter set in combination with the predetermined factor weight allocation to obtain the real-time heat dissipation demand coefficient; Based on the real-time heat dissipation demand level corresponding to the real-time heat dissipation demand coefficient, the target heat dissipation strategy in the heat dissipation strategy library is retrieved. The LED display screen is dynamically controlled for heat dissipation using the target heat dissipation strategy. Before reading predetermined work characteristic factors and performing a traversal analysis of the real-time work information based on the predetermined work characteristic factors to obtain the factor parameter set, the process includes: Collect thermal characteristic records of similar displays to the LED display screen; Extract the first record from the thermal characteristic records of the same type of display screen, and perform a collaborative analysis on the first working information and the first thermal characteristic information in the first record to obtain the first collaborative analysis result; Take the union of the first relevant work features in the first collaborative analysis results as the predetermined work feature factor; Taking the union of the first relevant work features in the first collaborative analysis results as the predetermined work feature factor, including: A many-to-many correlation analysis is performed on the first working information and the first thermal characteristic information to obtain the first collaborative analysis result; Extract the first analysis result of the first thermal characteristic index from the first collaborative analysis result, wherein the first analysis result includes a first factor set that is significantly related to the first thermal characteristic index, and the first thermal characteristic index refers to any one of the predetermined thermal characteristic indices. The first target factor set of the first thermal characteristic index is obtained by taking the union of the first factor set; The predetermined working characteristic factors are constructed based on the first target factor set; The first working information includes working data of predetermined working characteristic indicators, wherein the predetermined working characteristic indicators include at least brightness output, content refresh rate, ambient temperature, grayscale level, color mode, and the proportion of LEDs lit in the display area; The first thermal characteristic information includes index data of the predetermined thermal characteristic indicators, wherein the predetermined thermal characteristic indicators include at least heating power, thermal resistance, and heat dissipation efficiency.

2. The heat dissipation optimization control method for an LED display screen as described in claim 1, characterized in that, Before reading the predetermined factor weight allocation and performing a weighted calculation on the factor parameter set in conjunction with the predetermined factor weight allocation to obtain the real-time heat dissipation demand coefficient, the process includes: The first target parameter set corresponding to the first thermal characteristic index is obtained by traversing the set of factor parameters. The first index is obtained by weighting the first target parameter set with the coefficient of variation. The real-time heat dissipation demand coefficient is obtained by calculating the first index in combination with the predetermined factor weight allocation. The predetermined factor weight allocation is determined based on the regression coefficients obtained from the regression analysis of the application simulation data of the LED display screen.

3. The heat dissipation optimization control method for an LED display screen as described in claim 1, characterized in that, The heat dissipation strategy library includes multiple heat dissipation strategies formed by combining one or more predetermined heat dissipation methods, wherein the predetermined heat dissipation methods include air cooling, liquid cooling, heat pipe cooling, and semiconductor refrigeration.

4. The heat dissipation optimization control method for an LED display screen as described in claim 1, characterized in that, Based on the real-time heat dissipation demand level corresponding to the real-time heat dissipation demand coefficient, the target heat dissipation strategy in the heat dissipation strategy library is retrieved, including: The real-time heat dissipation demand level is traversed through the historical heat dissipation records to obtain multiple historical records of processing the real-time heat dissipation demand level. Extract the first historical record from the plurality of historical records, wherein the first historical record includes a first historical heat dissipation strategy and a first historical heat dissipation data; The first historical heat dissipation data is analyzed to obtain the first historical heat dissipation effect, and the historical heat dissipation strategy corresponding to the first historical heat dissipation effect in the descending list is obtained by sorting the data in descending order, and this strategy is used as the target heat dissipation strategy.

5. The heat dissipation optimization control method for an LED display screen as described in claim 4, characterized in that, After dynamically controlling the heat dissipation of the LED display screen using the target heat dissipation strategy, the method further includes: Assemble the target part set of the LED display screen; In the first historical heat dissipation data, match the first temperature time sequence corresponding to the first part, wherein the first part refers to any part in the target part set; The first temperature curve is obtained by performing regression fitting analysis on the first temperature time series. When the slope of the curve corresponding to the first temperature curve does not meet the predetermined threshold, the historical heat dissipation strategy corresponding to the second historical heat dissipation effect in the descending sequence list is taken as the backup heat dissipation strategy to replace the target heat dissipation strategy. The normalized result of the curve slope is used as the first historical heat dissipation index of the first part, and the first historical heat dissipation result is obtained by weighting.

6. A heat dissipation optimization control device for an LED display screen, characterized in that, The device includes: A working status monitoring module is used to dynamically monitor and obtain the real-time working information of the LED display screen; A work feature acquisition module is used to read predetermined work feature factors and perform traversal analysis on the real-time work information based on the predetermined work feature factors to obtain a factor parameter set. A real-time heat dissipation demand calculation module is used to read a predetermined factor weight allocation and perform weighted calculation on the factor parameter set in combination with the predetermined factor weight allocation to obtain the real-time heat dissipation demand coefficient. A heat dissipation strategy matching module is used to retrieve a target heat dissipation strategy from the heat dissipation strategy library based on the real-time heat dissipation demand level corresponding to the real-time heat dissipation demand coefficient. A dynamic heat dissipation control module is used to dynamically control the heat dissipation of the LED display screen according to the target heat dissipation strategy. The working feature acquisition module is also used to perform: Collect thermal characteristic records of similar LED displays; extract the first record from the thermal characteristic records of similar displays, and perform a collaborative analysis on the first working information and the first thermal characteristic information in the first record to obtain a first collaborative analysis result; take the union of the first relevant working features in the first collaborative analysis result as the predetermined working feature factor; A many-to-many correlation analysis is performed on the first working information and the first thermal characteristic information to obtain the first collaborative analysis result; a first analysis result of the first thermal characteristic index is extracted from the first collaborative analysis result, wherein the first analysis result includes a first factor set that is significantly related to the first thermal characteristic index, and the first thermal characteristic index refers to any one of the predetermined thermal characteristic indices; the union of the first factor set is taken to obtain a first target factor set of the first thermal characteristic index; the predetermined working characteristic factors are constructed based on the first target factor set; wherein the first working information includes working data of the predetermined working characteristic index, wherein the predetermined working characteristic index includes at least brightness output, content refresh rate, ambient temperature, grayscale level, color mode, and LED illumination ratio in the display area; the first thermal characteristic information includes index data of the predetermined thermal characteristic index, wherein the predetermined thermal characteristic index includes at least heat generation power, thermal resistance, and heat dissipation efficiency.

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