Energy-saving control method and system for COB display screen module

Abstract

The invention relates to the technical field of energy-saving control, in particular to an energy-saving control method and system for a COB display screen module, and the method comprises the steps: obtaining a real-time operation data sequence of the COB display screen module, the real-time operation data sequence comprising dynamic parameters of a pixel driving region and a power management module; feature extraction is carried out on the real-time operation data sequence, pixel energy consumption features and power supply load features are obtained, the pixel energy consumption features comprise brightness distribution and current density, and the power supply load features comprise voltage fluctuation and power loss. According to the method, the pixel energy consumption characteristics and the power supply load characteristics of the display screen can be accurately analyzed by acquiring the real-time operation data and extracting the characteristics, and the data-driven energy-saving optimization not only considers static parameters such as the brightness and the power loss of the display screen, but also improves the energy-saving performance of the display screen. The energy consumption distribution of the display area and the power module is determined by generating the dynamic energy-saving state parameters, and the energy efficiency change of the system can be monitored in real time and adjusted in time in combination with the efficiency parameters.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy-saving control, in particular to an energy-saving control method and system for a COB display module. BACKGROUND

[0002] With the wide application of display technology, especially COB display screens, especially in advertising screens, televisions, mobile phones, computers and other devices, the energy consumption of display screens has become a significant factor. COB display screens are widely used in various high-end display products due to their high brightness, high definition, wide viewing angle and other advantages. However, the display requirements of high brightness and high resolution often result in high power consumption, especially during long-term use. Therefore, how to effectively reduce the energy consumption of the display screen and ensure its efficient operation has become a problem to be solved.

[0003] Currently, the working environment and use scenarios of each display screen are quite different, such as the brightness of the display area, the working time, etc. Therefore, the use of traditional energy-saving control methods cannot accurately meet various different needs. Although the current display screen technology has some optimization in energy saving, most traditional technologies only stop at control based on static parameters (such as brightness, power, etc.). SUMMARY

[0004] To achieve the above-mentioned purpose, the present application provides the following technical scheme: an energy-saving control method for a COB display module, comprising: obtaining a real-time running data sequence of the COB display module, wherein the real-time running data sequence includes dynamic parameters of a pixel driving area and a power management module; performing feature extraction on the real-time running data sequence to obtain pixel energy consumption features and power load features, wherein the pixel energy consumption features include brightness distribution and current density, and the power load features include voltage fluctuation and power loss; based on the pixel energy consumption features and the power load features, determining the energy consumption distribution of the pixel driving area and the efficiency parameters of the power management module, and generating dynamic energy-saving state parameters; performing multi-dimensional abnormality recognition on the dynamic energy-saving state parameters according to a predefined energy efficiency level standard, and determining high energy consumption area types and energy-saving potential levels; based on the high energy consumption area types and energy-saving potential levels, generating a modular energy-saving control strategy, wherein the modular energy-saving control strategy includes area adjustment parameters, power optimization schemes and effect prediction curves.

[0005] Preferably, the feature extraction on the real-time running data sequence to obtain the pixel energy consumption features and the power load features comprises: Sampling key parameters from the real-time operation data sequence to obtain an operation static data set of at least one COB display screen module; Dividing a feature dimension of each of the module operation static data sets to obtain a pixel driving candidate area and a power supply monitoring candidate area; Performing multi-scale energy consumption analysis on the pixel driving candidate area based on a deep learning network to determine the brightness distribution and the current density and generate the pixel energy consumption feature; Performing parameter inversion on the power supply monitoring candidate area to obtain the voltage fluctuation and the power loss and generate the power supply load feature.

[0006] Preferably, dividing a feature dimension of each of the module operation static data sets to obtain a pixel driving candidate area and a power supply monitoring candidate area comprises: Performing parameter standardization processing on the module operation static data set to enhance the distinguishability of the pixel driving parameter and the power supply management parameter to obtain the module operation static data after standardization processing; Extracting a sample area with a parameter fluctuation exceeding a preset fluctuation threshold from the module operation static data after standardization processing by a clustering algorithm to generate an initial candidate area set; Performing feature correlation analysis on the initial candidate area set to merge candidate areas with similar parameter change trends and adjacent spatial positions to generate a merged candidate area set; According to a preset pixel driving parameter range and a power supply parameter range, screening candidate areas from the merged candidate area set to obtain a preliminarily screened candidate area set; Performing noise filtering processing on the preliminarily screened candidate area set to generate the final pixel driving candidate area and the power supply monitoring candidate area.

[0007] Preferably, based on the pixel energy consumption feature and the power supply load feature, determining the energy consumption distribution of the pixel driving area and the efficiency parameter of the power supply management module to generate a dynamic energy-saving state parameter comprises: According to the brightness distribution in the pixel energy consumption feature, calculating the energy consumption proportion and the brightness redundancy of different display areas to generate the energy consumption distribution; Based on the voltage fluctuation in the power supply load feature, determining the correlation between the power conversion efficiency and the load rate to generate the efficiency parameter; Fusing the energy consumption distribution and the efficiency parameter to determine the energy consumption coupling coefficient of the pixel driving area and the power module; According to the energy consumption coupling coefficient, generating quantitative indexes of the regional current regulation threshold, the power voltage correction amount and the dynamic power consumption upper limit; Matching the quantitative indexes with a preset energy efficiency model to output the dynamic energy-saving state parameter.

[0008] Preferably, based on the voltage fluctuation in the power supply load characteristics, the correlation between the power conversion efficiency and the load rate is determined, and the efficiency parameter is generated, including: The voltage fluctuation value and the load rate data corresponding to the adjacent time stamps in the power supply load characteristics are extracted, the voltage value of the previous time stamp is matched with the load rate of the next time stamp, and a voltage-load correlation pair is generated; According to the numerical change of the voltage-load correlation pair, the deviation amount of the real-time value and the theoretical value of the power conversion efficiency is calculated, and the efficiency deviation coefficient is generated; Based on the change rate of the efficiency deviation coefficient at consecutive time stamps, the efficiency decay rate is calculated, the time point at which the decay rate exceeds the preset rate threshold is marked as an efficiency mutation point, the distribution frequency of the efficiency mutation point in the power supply operation cycle is counted, and the efficiency stability index is generated according to the ratio of the distribution frequency to the rate threshold; The efficiency deviation coefficient, the efficiency mutation point distribution frequency and the efficiency stability index are normalized and fused to generate an efficiency parameter set; According to the power loss data in the power supply load characteristics, the pre-defined power supply type attribute library is matched, and the efficiency compensation coefficient of the corresponding power supply type is extracted; The efficiency deviation coefficient in the efficiency parameter set is multiplied by the efficiency compensation coefficient to generate an efficiency correction index, and according to the time sequence change trend of the efficiency correction index, the index difference between adjacent time stamps is compared with the pre-defined efficiency decay threshold to generate an efficiency parameter dynamic abnormal flag bit; The efficiency parameter set, the efficiency correction index and the efficiency parameter dynamic abnormal flag bit are time-series superimposed to form an efficiency parameter trend graph with time stamp markers, and based on the parameter change direction of consecutive time stamps in the efficiency parameter trend graph, an efficiency optimization direction prediction trajectory is generated; According to the correlation degree between the efficiency optimization direction prediction trajectory and the pixel energy consumption distribution, the dynamic weight coefficient of the efficiency parameter is adjusted to generate a final efficiency parameter set.

[0009] Preferably, the energy consumption distribution and the efficiency parameter are fused to determine the energy consumption coupling coefficient of the pixel driving area and the power supply module, including: According to the energy consumption proportion of each display area in the energy consumption distribution, the current change curve of the high energy consumption area at consecutive time stamps is extracted; Based on the correlation between the power conversion efficiency and the load rate in the efficiency parameter, the efficiency decay coefficient of the power supply module at the corresponding time stamp is extracted; The current change curve and the efficiency decay coefficient are time-synchronized and calibrated to generate a synchronized energy consumption-efficiency mapping relationship; According to the synchronized energy consumption-efficiency mapping relationship, a current threshold point corresponding to an efficiency decay peak value is located in the current change curve, and an influence weight of a high energy consumption area on power supply efficiency is calculated based on the current threshold point; According to the influence weight and the spatial distribution of the efficiency decay coefficient, an energy consumption conduction path of each display area and the power supply module is determined; According to the intensity change and direction consistency of the energy consumption conduction path at consecutive time stamps, the energy consumption coupling coefficient is generated, wherein the numerical size of the energy consumption coupling coefficient represents the energy consumption correlation closeness.

[0010] Preferably, according to the energy consumption coupling coefficient, a quantitative index of a regional current regulation threshold, a power supply voltage correction amount and a dynamic power consumption upper limit is generated, including: Extract the distribution characteristics of the energy consumption coupling coefficient, mark the continuous area of the energy consumption coupling coefficient exceeding the preset coupling threshold as a strong correlation core area, divide the analysis unit in the strong correlation core area, and count the consistency proportion of the energy consumption conduction direction in each analysis unit. The analysis unit with a consistency proportion exceeding a preset proportion threshold is merged into a high-efficiency energy-saving zone; Based on the product of the coverage area of the high-efficiency energy-saving zone and the energy consumption coupling coefficient, a current regulation initial threshold at each time stamp is generated, according to the brightness distribution in the pixel energy consumption characteristics, a pre-defined brightness-current correspondence table is matched, the current regulation initial threshold is weighted and corrected with the brightness redundancy to generate a regional current regulation threshold; Extract the stability margin corresponding to the power supply voltage fluctuation in the power supply load characteristics, calculate the decay proportion of the stability margin and the coupling value in the same area of the energy consumption coupling coefficient, and determine the dynamic evaluation of the power supply voltage correction amount according to the decay proportion and the pre-defined voltage regulation curve; Based on the strong correlation core area duration of each time stamp in the energy consumption coupling coefficient, the proportion of the strong correlation core area in the total running time is counted to generate an energy consumption proportion initial value, and the credibility weight of the power consumption proportion initial value is adjusted according to the power loss data in the power supply load characteristics to generate a dynamic power consumption upper limit; Align the regional current regulation threshold, power supply voltage correction amount and dynamic power consumption upper limit according to the time stamp to generate a quantitative index time sequence matrix, and match a pre-defined energy-saving mode feature library according to the fluctuation amplitude of each index in the quantitative index time sequence matrix to generate a current regulation safety interval, a voltage correction precision threshold and a power consumption upper limit dynamic range; Based on the safety interval, the precision threshold and the dynamic range, the quantitative index time sequence matrix is segmented and labeled to generate a quantitative index set with energy-saving level labels.

[0011] Preferably, according to the predefined energy efficiency level standard, the dynamic energy-saving state parameters are subjected to multi-dimensional anomaly recognition to determine the high energy consumption area type and the energy-saving potential level, including: extracting the time sequence characteristic array of the area current value, power supply efficiency and power consumption upper limit in the dynamic energy-saving state parameters; According to the predefined energy efficiency level standard, the time sequence characteristic array is divided into analysis window segments matching the current running mode; The average value of the area current in each analysis window segment is subjected to ratio operation with the current reference value in the energy efficiency level standard to generate a current exceeding coefficient; Synchronously, the minimum value of the power supply efficiency in the analysis window segment is subjected to difference comparison with the efficiency threshold value in the energy efficiency level standard to generate an efficiency deficiency flag bit; The fluctuation amplitude of the power consumption upper limit is subjected to deviation calculation with the power consumption stability threshold value in the energy efficiency level standard to generate a power consumption fluctuation proportion value; The current exceeding coefficient, efficiency deficiency flag bit and power consumption fluctuation proportion value are input into a pre-trained energy-saving decision model, wherein the energy-saving decision model includes a first decision layer, a second decision layer and a third decision layer, the first decision layer judges whether the current exceeding coefficient exceeds an energy-saving critical value, the second decision layer generates a power supply aging index according to the trigger number of the efficiency deficiency flag bit, and the third decision layer generates a region anomaly mode based on the power consumption fluctuation proportion value and the energy consumption distribution characteristic; Based on the recognition result output by the energy-saving decision model, the corresponding high energy consumption area type label is determined, wherein the high energy consumption area type label includes at least one of pixel overload, power supply inefficiency and coupling loss; Real-time acquisition of the brightness distribution change amount in the pixel energy consumption feature, when a region with no significant change in brightness but continuous rise in current is detected, an implicit performance energy consumption signal is generated; The implicit performance energy consumption signal is fused with the high energy consumption area type label, if there is an overlapping interval in the time stamp, the energy-saving potential level of the corresponding region is promoted by one level.

[0012] Preferably, based on the high energy consumption area type and the energy-saving potential level, a modular energy-saving control strategy is generated, including: According to the pixel coordinates corresponding to the high energy consumption area type and the power supply interface position, the regulation area is located in the real-time running data sequence to generate a parameter adjustment curve and a text description matching the energy-saving potential level; Based on the optimization priority corresponding to the energy-saving potential level, a multi-level energy-saving trigger signal is generated; According to the high energy consumption area type, current regulation rules and power optimization parameters in the pre-defined energy saving scheme library are matched, wherein, the pixel overload type generates current attenuation gradient and brightness compensation coefficient, the power inefficiency type generates voltage fine-tuning curve and load balancing instruction, the coupling loss type generates area isolation parameter and energy consumption shunting path.

[0013] An energy saving control system of a COB display screen module, which is suitable for the energy saving control method of the COB display screen module, comprises: A data acquisition module is configured to acquire a real-time running data sequence of the COB display screen module, wherein the real-time running data sequence comprises dynamic parameters of a pixel driving area and a power management module. A feature extraction module is configured to perform feature extraction on the real-time running data sequence to obtain pixel energy consumption features and power load features, wherein the pixel energy consumption features comprise brightness distribution and current density, and the power load features comprise voltage fluctuation and power loss. An efficiency calculation module is configured to determine energy consumption distribution of the pixel driving area and efficiency parameters of the power management module based on the pixel energy consumption features and the power load features, and generate dynamic energy saving state parameters. An energy saving matching module is configured to perform multi-dimensional abnormality recognition on the dynamic energy saving state parameters according to pre-defined energy efficiency level standards, and determine high energy consumption area types and energy saving potential levels. An energy saving control module is configured to generate a modular energy saving control strategy based on the high energy consumption area types and the energy saving potential levels, wherein the modular energy saving control strategy comprises area adjustment parameters, power optimization schemes and effect prediction curves.

[0014] Compared with the prior art, the present application has the following advantages: (1) The present application can accurately analyze the pixel energy consumption features and the power load features of the display screen by acquiring real-time running data and performing feature extraction, and the data-driven energy saving optimization not only considers static parameters such as display screen brightness and power loss, but also realizes dynamic energy efficiency adjustment through deep learning and other technologies. This can optimize energy consumption in real time according to actual use conditions, and can generate dynamic energy saving state parameters to determine the energy consumption distribution of the display area and the power module, and can monitor the change of system energy efficiency in real time and adjust in time, and can generate energy efficiency coupling coefficients, further improving the accuracy of energy efficiency adjustment. (2) The application can accurately locate the high-energy consumption area of the display screen through multi-dimensional anomaly recognition, and adjust the energy consumption of different areas according to the energy saving potential level, which helps to identify potential energy saving space and avoid ineffective energy consumption. Through the analysis of the high-energy consumption area type and the energy saving potential level, a modular energy saving control strategy is generated. This strategy not only considers the current regulation, brightness compensation and power optimization scheme of the area, but also can customize energy saving measures according to the characteristics of different areas, so as to realize accurate energy saving control (3) The system can more efficiently adjust the power supply and display screen through current regulation, safety interval, precision threshold and other quantitative indicators, which not only reduces power consumption, but also prolongs the service life of the system and improves the stability of power management. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 It is a step flow diagram of the overall method in an embodiment of the application. Figure 2 It is a system architecture diagram of the overall system in an embodiment of the application.

[0016] In the figure: 1, data acquisition module; 2, feature extraction module; 3, efficiency calculation module; 4, energy saving matching module; 5, energy saving control module. DETAILED DESCRIPTION

[0017] The technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, not all. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the application.

[0018] Embodiment one, please refer to Figure 1 The application provides a technical solution: an energy saving control method for a COB display screen module, comprising: S1, obtaining a real-time running data sequence of the COB display screen module, wherein the real-time running data sequence includes dynamic parameters of the pixel driving area and the power management module; S2, performing feature extraction on the real-time running data sequence to obtain pixel energy consumption features and power load features, wherein the pixel energy consumption features include brightness distribution and current density, and the power load features include voltage fluctuation and power loss; S3, determining the energy consumption distribution of the pixel driving area and the efficiency parameters of the power management module based on the pixel energy consumption features and the power load features, and generating dynamic energy saving state parameters; S4. Multi-dimensional anomaly recognition is performed on the dynamic energy-saving state parameters according to the predefined energy efficiency level standard, to determine the high energy consumption area type and the energy-saving potential level; S5. A modular energy-saving control strategy is generated based on the high energy consumption area type and the energy-saving potential level, wherein the modular energy-saving control strategy includes area adjustment parameters, power supply optimization scheme and effect prediction curve.

[0019] It should be noted that real-time data of the COB display module during operation is collected, including: pixel driving area: the working state of pixels in different areas of the display screen; power management module: a module that controls voltage, current, etc.; for example: assuming that a large COB display screen is used, real-time data records the brightness, color change, power consumption, etc. of different areas of the display screen, especially the areas with high brightness (such as advertising areas) and the efficiency of power management; from the collected real-time data, two important features are extracted: pixel energy consumption feature related to brightness distribution and current density, which refers to the power consumption of each pixel on the display screen; power load feature related to voltage fluctuation and power loss, which represents the load state of the power module; for example: if a part of the display screen is particularly bright and the displayed content has a large area of pure white, the pixel energy consumption of those areas will be higher; and if the voltage fluctuation of the power module is too large, it also indicates that the power supply may be overloaded, resulting in low efficiency; according to the pixel energy consumption feature and the power load feature, the energy consumption distribution of different areas of the display screen and the efficiency of the power management module are calculated; for example: through analysis, it can be found that the middle area of the display screen (such as the billboard part) has high energy consumption, while the edge area has low energy consumption; the power management module may be working under high load, resulting in low efficiency; according to the predefined energy efficiency level standard, it is identified which areas have excessive energy consumption, the high energy consumption areas are determined, and the energy-saving potential level is given; for example: if it is found that some areas (such as white advertising areas) consume too much energy, and these areas do not need high brightness, these areas are identified as “high energy consumption areas” and their energy-saving potential is evaluated; based on the high energy consumption area type and the energy-saving potential level, an energy-saving control strategy is developed; the control strategy includes: area adjustment: adjusting the brightness or color of certain areas of the display screen to reduce energy consumption; power optimization: optimizing voltage, current, etc. according to the efficiency of the power module; effect prediction: predicting the energy-saving effect after optimization; for example: if the high energy consumption area is mainly the white advertising area, the brightness of these areas can be reduced, or the color of the display can be adjusted without affecting the visual effect to reduce energy consumption; at the same time, the voltage of the power module is optimized to improve its efficiency and reduce power loss.

[0020] In an optional embodiment, feature extraction is performed on the real-time running data sequence to obtain pixel energy consumption features and power load features, including: sampling key parameters from a real-time running data sequence to obtain a running static data set of at least one COB display screen module; dividing a feature dimension for each module running static data set to obtain a pixel driving candidate area and a power supply monitoring candidate area; performing multi-scale energy consumption analysis on the pixel driving candidate area based on a deep learning network to determine luminance distribution and current density and generate pixel energy consumption features; performing parameter inversion on the power supply monitoring candidate area to obtain voltage fluctuation and power loss and generate power supply load features.

[0021] It should be noted that the real-time running data of the COB display screen module is sampled for key parameters; these data include the pixel driving state and the power management state of the display screen; through these data, a "running static data set" can be obtained, which is actually a set of static data collected from the module running process; for example: assuming that there is a COB display screen module, the luminance, color and current distribution of each pixel are collected in real time, and the voltage and current data of the power module are also collected; the feature dimension of the static data set of each module is divided to obtain two candidate areas: the pixel driving candidate area: the energy consumption area generated by the pixel driving in the display screen; the power supply monitoring candidate area: the area related to the power management module, focusing on voltage fluctuation and power loss; for example: for example, some areas of the display screen (such as the pure white background part) may need high brightness, and the pixel driving of these areas will consume more electric energy, so they will be divided into the pixel driving candidate area; the power module may have voltage fluctuation when controlling these areas, so the data related to power management will become the power supply monitoring candidate area; the pixel driving candidate area is analyzed by a deep learning model for multi-scale energy consumption; specifically, the energy consumption is analyzed according to different luminance distribution and current density; through the deep learning network, the energy consumption features of each area can be accurately identified to generate pixel energy consumption features, including luminance distribution and current density; for example: assuming that a certain area of the display screen (such as the advertisement part) has a high brightness, the deep learning model will analyze the energy consumption features of this area to obtain its luminance distribution and current density, thereby identifying the energy consumption of the area; the parameter inversion of the power supply monitoring candidate area obtains the features of voltage fluctuation and power loss; this step is to analyze whether the power module is running under high load, and the parameter inversion of voltage fluctuation and power loss can reveal the efficiency of the power supply; for example: for example, the voltage fluctuation of the power module may be large when adjusting the area with high brightness of the display screen, and the deep learning algorithm can infer the efficiency of the power module through these fluctuations to generate power load features.

[0022] In an optional embodiment, dividing a feature dimension for each module running static data set to obtain a pixel driving candidate area and a power supply monitoring candidate area comprises: Parameter standardization is performed on the module running static data set, the discrimination of the pixel driving parameters and the power management parameters is enhanced, and the module running static data after the standardization is obtained; A sample region with a parameter fluctuation exceeding a preset fluctuation threshold is extracted from the module running static data after the standardization through a clustering algorithm, and an initial candidate region set is generated; Feature correlation analysis is performed on the initial candidate region set, candidate regions with similar parameter change trends and adjacent spatial positions are merged, and a merged candidate region set is generated; According to a preset pixel driving parameter range and a power parameter range, candidate regions are screened from the merged candidate region set, and a preliminary screened candidate region set is obtained; Noise filtering is performed on the preliminary screened candidate region set, and final pixel driving candidate regions and power monitoring candidate regions are generated.

[0023] It should be noted that the static data set of the display screen module is processed and divided into pixel driving candidate areas and power supply monitoring candidate areas; the goal here is to extract the characteristics of different areas from the overall data, corresponding to the pixel energy consumption and power supply load of the display screen; for example: assuming that a display screen, the energy consumption of each pixel and the load information of the power supply are recorded; by dividing the characteristics, the screen can be divided into multiple candidate areas; for example, some display areas may become pixel driving candidate areas due to high brightness; some areas with large voltage fluctuations may be marked as power supply monitoring candidate areas; during the standardization process, all parameters will be calculated by standardization to ensure that they are compared within the same range; through this processing, the distinction between pixel driving parameters and power management parameters will be enhanced, facilitating subsequent analysis and optimization; for example: if the pixel brightness value range of a region is 0 to 255, and the voltage fluctuation range of another region is -5 to 5 volts, direct comparison of these two data may not be meaningful; through standardization processing, the range of the two parameters is adjusted to the same scale, facilitating subsequent comparison and optimization; next, the standardized data is analyzed using a clustering algorithm to find areas where parameter fluctuations exceed a pre-set threshold, and a preliminary candidate area set is generated; the goal of this stage is to identify areas that may have energy-saving potential; for example: if the pixel brightness fluctuation of some areas is too large (such as some over-bright advertisements), and the power load of other areas changes dramatically, the system will extract these areas as candidate areas, which may mean that these areas have high energy consumption and are worth optimizing; through feature correlation analysis, the system will merge candidate areas that have similar parameter change trends and are adjacent in space; this can reduce computational complexity while focusing on energy-saving optimization in specific areas; for example: if the brightness fluctuation and power fluctuation of two display areas are similar and they are close together on the screen, the system will merge these two areas into one for processing instead of processing them separately; after merging, the system will further filter out the most potential candidate areas according to the pre-set pixel driving parameter range and power parameter range; the purpose of this filtering is to concentrate on optimizing areas that truly need energy saving; the selected areas are the optimization targets; areas with good energy efficiency that do not need optimization are excluded; finally, through noise filtering processing, areas affected by interference or abnormal data are removed, ensuring that the final selected candidate areas are reliable and have optimization potential; for example: if the power data of a region is affected by external interference (such as transient voltage fluctuations), the system will filter out these abnormal data to ensure that it does not affect the energy-saving optimization effect.

[0024] In an optional embodiment, based on the pixel energy consumption characteristics and the power load characteristics, the energy consumption distribution of the pixel driving area and the efficiency parameters of the power management module are determined, and dynamic energy-saving state parameters are generated, including: According to the brightness distribution in the pixel energy consumption characteristics, the energy consumption proportion and the brightness redundancy of different display areas are calculated to generate an energy consumption distribution; Based on the voltage fluctuation in the power supply load characteristics, the correlation between the power conversion efficiency and the load rate is determined to generate an efficiency parameter; Fusing the energy consumption distribution and the efficiency parameter, the energy consumption coupling coefficient of the pixel driving area and the power module is determined; According to the energy consumption coupling coefficient, the quantitative indicators of the regional current regulation threshold, the power voltage correction amount and the dynamic power consumption upper limit are generated; The quantitative indicators are matched with the preset energy efficiency model to output the dynamic energy-saving state parameters.

[0025] It should be noted that according to different regions of the display screen, the brightness information of the region is extracted; the higher the brightness of the display region, the more the pixel energy consumption will increase; by counting the brightness of each region, the energy consumption proportion of each region is determined; some display regions may have excessive brightness (for example, white background, or regions that do not require too high brightness), and the redundancy of these regions is high; the energy consumption redundancy of these regions is calculated; for example: assuming that there is an advertisement region on the screen, and the advertisement uses an excessively bright background color, these parts will consume more energy; by calculating the brightness redundancy of the advertisement region, the energy consumption proportion of the region can be obtained, thereby providing a basis for subsequent energy-saving adjustment; according to the load rate and voltage fluctuation of the power supply, the conversion efficiency of the power supply is calculated; generally, the higher the load rate of the power supply, the greater the voltage fluctuation, and the efficiency may decrease; by establishing the correlation between voltage and load rate, the efficiency parameter of the power supply can be calculated; for example: assuming that the power supply voltage has a large fluctuation at a certain moment, and the load rate is high; according to the power supply load characteristics, the conversion efficiency of the power supply and the possible efficiency deviation can be calculated; compare the deviation between the theoretical efficiency and the actual efficiency to calculate the decay rate of the efficiency; when the decay rate exceeds the preset threshold, it is marked as an "efficiency mutation point", and the frequency is counted; efficiency mutation point: the moment when the efficiency changes greatly or abnormally; efficiency stability index: by calculating the change trend of the efficiency, the stability of the power supply is obtained; for example: if the efficiency of the power supply suddenly decreases at a certain moment, and the decay rate is higher than the preset value, then the moment will be marked as an "efficiency mutation point"; by analyzing the distribution of these mutation points, the stability of the power supply efficiency can be obtained; normalize the efficiency deviation, efficiency mutation point, efficiency stability and other parameters in the power supply load characteristics to form a comprehensive efficiency parameter set; by matching with the predefined power supply type attribute library, the corresponding efficiency compensation coefficient is obtained to compensate the efficiency of the power supply; for example: if a power supply has efficiency decay when the load is high, find the efficiency compensation coefficient that adapts to this type of power supply through the power supply type attribute library, and use it to correct its efficiency performance; multiply the efficiency compensation coefficient by the efficiency deviation coefficient to generate an efficiency correction index; if the change of the efficiency correction index exceeds the set threshold, a dynamic abnormal flag bit is generated to prompt that the power supply efficiency is abnormal; for example: when the power supply efficiency suddenly decreases and exceeds the predetermined decay threshold, the efficiency correction index will prompt that an abnormality occurs, and the dynamic abnormal flag bit will be set to 1, indicating that the system has an efficiency abnormality; by fusing pixel energy consumption distribution, efficiency parameter set, efficiency correction index, etc., a comprehensive energy-saving state parameter is generated; according to the trend chart of the efficiency parameter, the direction of power supply efficiency optimization is predicted, and the energy-saving strategy is dynamically adjusted according to the correlation of the pixel energy consumption distribution; for example: if the brightness of a certain region is too high and the power supply efficiency decays, the system will automatically adjust the adjustment threshold of the power supply voltage and the region current to reduce the energy consumption.

[0026] In an optional embodiment, based on the voltage fluctuation in the power load characteristics, the correlation between the power conversion efficiency and the load rate is determined, and the efficiency parameter is generated, including: The voltage fluctuation value and the load rate data corresponding to the adjacent time stamps in the power load characteristics are extracted, and the voltage value of the previous time stamp is matched with the load rate of the next time stamp to generate a voltage-load correlation pair; According to the numerical change of the voltage-load correlation pair, the deviation amount of the real-time value and the theoretical value of the power conversion efficiency is calculated, and the efficiency deviation coefficient is generated; Based on the change rate of the efficiency deviation coefficient at consecutive time stamps, the efficiency decay rate is calculated, the time point where the decay rate exceeds the preset rate threshold is marked as the efficiency mutation point, the distribution frequency of the efficiency mutation point in the power operation cycle is counted, and the efficiency stability index is generated according to the ratio of the distribution frequency to the rate threshold; The efficiency deviation coefficient, the efficiency mutation point distribution frequency and the efficiency stability index are normalized and fused to generate the efficiency parameter set; According to the power loss data in the power load characteristics, the pre-defined power type attribute library is matched, and the efficiency compensation coefficient of the corresponding power type is extracted; The efficiency deviation coefficient and the efficiency compensation coefficient in the efficiency parameter set are multiplied to generate the efficiency correction index, and according to the time sequence change trend of the efficiency correction index, the index difference value of adjacent time stamps is compared with the pre-defined efficiency decay threshold to generate the efficiency parameter dynamic abnormal flag bit; The efficiency parameter set, the efficiency correction index and the efficiency parameter dynamic abnormal flag bit are time-series superimposed to form an efficiency parameter trend graph with time stamp markers, and based on the parameter change direction of consecutive time stamps in the efficiency parameter trend graph, an efficiency optimization direction prediction trajectory is generated; According to the correlation degree between the efficiency optimization direction prediction trajectory and the pixel energy consumption distribution, the dynamic weight coefficient of the efficiency parameter is adjusted to generate the final efficiency parameter set.

[0027] It is necessary to note that the voltage fluctuation and load rate data of adjacent time stamps are extracted from the power load characteristic data; then, the voltage value of the previous time stamp is associated with the load rate of the next time stamp to generate a voltage-load association pair; this is to capture the relationship between voltage fluctuation and load change; for example: assuming that the voltage is 5 volts at time stamp T1, and the load rate is 80% at time stamp T2; the system will match the data of these two time points to form a voltage-load association pair (5V, 80%); by analyzing these association pairs, the response of the power load to voltage fluctuation can be understood; then, according to the numerical change of the voltage-load association pair, the deviation between the actual conversion efficiency of the power supply and the theoretical value is calculated to obtain the efficiency deviation coefficient; this coefficient reflects the degree of deviation of the power conversion efficiency; for example: assuming that theoretically, when the voltage is 5 volts and the load rate is 80%, the conversion efficiency of the power supply should be 85%; but the actual measurement result shows that the efficiency is 80%; then, the efficiency deviation coefficient is: efficiency deviation coefficient = 85% - 80% = 5% efficiency deviation coefficient = 85% - 80% = 5%; by analyzing the change rate of the efficiency deviation coefficient under consecutive time stamps, the decay rate of the power efficiency can be calculated; if the decay rate exceeds the preset threshold, the system will mark this time point as an "efficiency mutation point"; the efficiency mutation point refers to the abnormal rapid change of the power efficiency; for example: assuming that the efficiency deviation coefficient decreases from 5% to 15% during the T1 to T2 period, the efficiency decay rate is 10%; if the preset threshold is 5%, the efficiency change in this period will be marked as an efficiency mutation point; the distribution frequency of all efficiency mutation points is counted, and the efficiency stability index is generated according to the ratio of the distribution frequency to the decay rate threshold; this index is used to measure the stability of the power supply efficiency during operation; for example: if there are 10 efficiency mutation points in a power supply operation cycle, and the frequency of these mutation points is high, the stability index is low, indicating that the power efficiency is unstable; the efficiency deviation coefficient, efficiency mutation point distribution frequency, and efficiency stability index are normalized and fused to form a new efficiency parameter set; this set is used to comprehensively reflect the change trend of the power efficiency; for example: assuming that the efficiency deviation coefficient is 5%, the efficiency mutation point frequency is 0.2, and the stability index is 0.7, after normalization processing, a comprehensive efficiency parameter set is formed; for example, the final efficiency parameter set may be {5%, 0.2, 0.7}; according to the power loss data in the power load characteristics, match the pre-defined power type attribute library to extract the efficiency compensation coefficient related to the power type; this is to provide different optimization compensation schemes for different types of power supplies; for example: assuming that the power loss of a certain power supply is 50W, the system queries the power type library to find that the compensation coefficient of this power supply is 1.2; this compensation coefficient indicates that the efficiency of this power supply needs to be optimized by 1.2 times of correction; multiply the efficiency deviation coefficient in the efficiency parameter set with the efficiency compensation coefficient to generate an efficiency correction index; according to the time sequence change trend of the efficiency correction index, compare the index difference value of adjacent time stamps with the pre-defined efficiency attenuation threshold to generate a dynamic abnormal flag bit; for example: if the efficiency correction index is 1.0 at T1 and the correction index is 0.8 at T2, the index change is -0.2; if the pre-set efficiency attenuation threshold is 0.1, the system will be marked as abnormal; by superimposing the efficiency parameter set, the efficiency correction index and the dynamic abnormal flag bit, a power efficiency parameter trend graph with time stamp marking is generated; then, based on the change direction of these data, a power efficiency optimization direction prediction trajectory is generated; for example: assuming that the efficiency correction index gradually rises in the past few time stamps, the system can predict the improvement trend of future power efficiency and indicate which adjustment measures should be taken by the system to improve the efficiency; according to the correlation degree between the power efficiency optimization direction prediction trajectory and the pixel energy consumption distribution, the weight coefficient of the efficiency parameter is dynamically adjusted, and finally an optimized efficiency parameter set is generated; this set will be used by the power management system for actual optimization adjustment; for example: if the system predicts that the future power efficiency will continue to decline, and the energy consumption of some pixel areas is high, the system may adjust the efficiency parameter weight to optimize power distribution and energy saving effect.

[0028] In an optional embodiment, the energy consumption distribution and the efficiency parameter are fused to determine the energy consumption coupling coefficient of the pixel driving area and the power module, comprising: According to the energy consumption proportion of each display area in the energy consumption distribution, the current change curve of the high energy consumption area at the continuous time stamp is extracted; Based on the correlation between the power conversion efficiency and the load rate in the efficiency parameter, the efficiency attenuation coefficient of the power module at the corresponding time stamp is extracted; The current change curve and the efficiency attenuation coefficient are time-synchronized and calibrated to generate a synchronized energy consumption-efficiency mapping relationship; According to the synchronized energy consumption-efficiency mapping relationship, the current threshold point corresponding to the efficiency attenuation peak value is located in the current change curve, and the influence weight of the high energy consumption area on the power efficiency is calculated based on the current threshold point; According to the spatial distribution of the influence weight and the efficiency attenuation coefficient, the energy consumption conduction path of each display area and the power module is determined; According to the consistency of the intensity change and the direction of the energy consumption conduction path at the continuous time stamp, the energy consumption coupling coefficient is generated, wherein the numerical size of the energy consumption coupling coefficient represents the close degree of energy consumption correlation.

[0029] It needs to be noted that find out which area in the display system has the highest energy consumption; for example, assuming there is a display screen divided into multiple areas, such as the top, middle and bottom; analyze the energy consumption of each area, and then select the area with the highest energy consumption for detailed analysis; the efficiency of the power supply will fluctuate with the change of the load; the efficiency of the power supply at different time points needs to be recorded; for example, when the load of different areas of the display screen increases, the power supply may become less efficient; align the current change curve in the first step with the power supply efficiency attenuation coefficient in the second step to form a "energy consumption and efficiency" relationship diagram; in this way, it can be seen how the change of current affects the efficiency of the power supply; for example: the current change and the power supply efficiency attenuation coefficient can be sorted in chronological order to see that at a certain time point, when the current is large, the efficiency of the power supply may decrease significantly; next, find out the maximum value of the power supply efficiency attenuation, that is, the time point of the "efficiency attenuation peak"; this is usually related to the peak of a certain current; for example: assuming that the power supply efficiency attenuation reaches 10% at T3, and at this time, the current reaches 2.5 amperes, then 2.5 amperes is the threshold point of the current; calculate the size of the influence of the high-energy consumption area on the power supply efficiency; the greater the current fluctuation, the more obvious the attenuation of the power supply efficiency, the greater the influence of this area on the power supply; for example: assuming that it is found that the current change of a certain area is large, and the area has a greater impact on the power supply efficiency, so it is assigned a higher weight, such as 0.4; analyze how the display area affects the power supply efficiency through current change; it needs to be known which display area change has the greatest impact on which power supply module; the degree of influence between each area and the power supply module is called "energy consumption conduction path"; according to the strength and consistency of the energy consumption conduction path, calculate the "coupling coefficient" between each area and the power supply module; the higher the coupling coefficient, the greater the impact of the energy consumption of the display area on the power supply efficiency.

[0030] In an optional embodiment, according to the energy consumption coupling coefficient, the quantitative indicators of the regional current regulation threshold, the power supply voltage correction amount and the dynamic power consumption upper limit are generated, including: Extract the distribution characteristics of the energy consumption coupling coefficient, mark the continuous area of the energy consumption coupling coefficient exceeding the preset coupling threshold as a strong correlation core area, divide the analysis unit in the strong correlation core area, and count the consistency proportion of the energy consumption conduction direction in each analysis unit. The analysis unit with a consistency proportion exceeding a preset proportion threshold is merged into a high-efficiency energy-saving zone. Based on the product of the coverage area of the high-efficiency energy-saving zone and the energy consumption coupling coefficient, generate the current regulation initial threshold at each timestamp, match the predefined brightness-current correspondence table according to the brightness distribution in the pixel energy consumption characteristics, weight and correct the current regulation initial threshold and the brightness redundancy to generate the regional current regulation threshold; The stable margin corresponding to the power supply voltage fluctuation in the power supply load feature is extracted, the decay ratio of the same region coupling value in the stable margin and the energy consumption coupling coefficient is calculated, and the dynamic evaluation of the power supply voltage correction amount is determined according to the decay ratio and a predefined voltage adjustment curve; Based on the strong correlation core area duration of each timestamp in the energy consumption coupling coefficient, the proportion of the strong correlation core area in the total running duration is counted, the initial value of the energy consumption proportion is generated, and the credibility weight of the initial value of the energy consumption proportion is adjusted according to the power loss data in the power supply load feature, and the dynamic power consumption upper limit is generated; Align the regional current regulation threshold, the power supply voltage correction amount and the dynamic power consumption upper limit according to the timestamp, generate a quantitative index time sequence matrix, and match a predefined energy saving mode feature library according to the fluctuation amplitude of each index in the quantitative index time sequence matrix, generate a current regulation safety interval, a voltage correction precision threshold and a power consumption upper limit dynamic range; Based on the safety interval, the precision threshold and the dynamic range, the quantitative index time sequence matrix is segmented and labeled to generate a quantitative index set with energy saving level markers.

[0031] It should be noted that the area with high energy consumption coupling coefficient in the display system is found; this coefficient represents the relationship between the energy consumption change of the display area and the power efficiency change; according to these coupling coefficients, some areas are found, which are closely related to the change of the energy consumption and the change of the power efficiency; the strong correlation core area is divided into multiple small analysis units, and the proportion of the consistent energy consumption conduction direction in each analysis unit is counted; if the consistency exceeds the preset threshold (for example, 80%), then this analysis unit can be merged into a high-efficiency energy-saving zone; for example: in the top area, divide it into 5 small units, and find that the consistency of the energy consumption conduction direction of 3 units exceeds 80%, so the 3 units will form a high-efficiency energy-saving zone; based on the product of the coverage area of the high-efficiency energy-saving zone and the energy consumption coupling coefficient, an initial threshold of current regulation can be initially set; then, according to the brightness distribution of the display area, the relationship between brightness and current is matched, and the threshold is further adjusted; according to the load characteristics of the power supply, the voltage fluctuation of the power supply is monitored; when the voltage fluctuation is found to be large, the stability margin can be calculated, and the power supply voltage can be adjusted according to the energy consumption coupling coefficient to maintain system stability; for example: assuming that the power supply voltage fluctuates greatly at some time points, the stability margin of the power supply is calculated to be 10%; based on the stability margin and the coupling coefficient, the power supply voltage correction amount is adjusted to ensure that the power supply can maintain stable output under high load; according to the duration of the strong correlation core area, the proportion of the total running time is counted, and the credibility weight of the power consumption proportion is adjusted in combination with the power loss characteristics of the power supply, and finally the dynamic power consumption upper limit is generated; the current regulation threshold, the power supply voltage correction amount and the dynamic power consumption upper limit generated before are aligned according to the time stamp to form a time sequence matrix; by analyzing the fluctuation amplitude of each index in the matrix, it can be judged whether the system is in energy-saving mode, and according to the pre-defined energy-saving mode feature library, the current regulation safety interval, the voltage correction precision threshold and the dynamic range of the power consumption upper limit are generated; finally, based on the current regulation safety interval, the voltage correction precision threshold and the dynamic range of the power consumption upper limit, the quantification index time sequence matrix is segmented and labeled to generate a quantification index set with energy-saving levels; this set can help evaluate the energy efficiency of the display system under different working conditions.

[0032] In an optional embodiment, multi-dimensional abnormal identification is performed on the dynamic energy-saving state parameters according to the pre-defined energy efficiency level standard, to determine the high energy consumption area type and the energy-saving potential level, including: extracting the time sequence feature array of the area current value, the power supply efficiency and the power consumption upper limit in the dynamic energy-saving state parameters; according to the pre-defined energy efficiency level standard, the time sequence feature array is divided into analysis window segments matched with the current running mode; the average value of the area current in each analysis window segment is subjected to ratio operation with the current reference value in the energy efficiency level standard to generate a current over-standard coefficient; The power efficiency minimum value in the analysis window segment is compared with the efficiency threshold in the energy efficiency grade standard to generate an efficiency deficiency flag bit; The fluctuation range of the power consumption upper limit is calculated with the power consumption stability threshold in the energy efficiency grade standard to generate a power consumption fluctuation proportion value; The current exceeding coefficient, the efficiency deficiency flag bit, and the power consumption fluctuation proportion value are input into a pre-trained energy-saving decision model, wherein the energy-saving decision model includes a first decision layer, a second decision layer, and a third decision layer, the first decision layer judges whether the current exceeding coefficient exceeds an energy-saving critical value, the second decision layer generates a power supply aging index according to the triggering number of the efficiency deficiency flag bit, and the third decision layer generates a regional abnormal pattern based on the power consumption fluctuation proportion value and the energy consumption distribution characteristics; Based on the recognition result output by the energy-saving decision model, a corresponding high-energy-consumption region type label is determined, wherein the high-energy-consumption region type label includes at least one of pixel overload, power inefficiency, and coupling loss; The brightness distribution change amount in the pixel energy consumption feature is obtained in real time, and when a region where the brightness has no significant change but the current continuously rises is detected, a hidden performance energy consumption signal is generated; The hidden performance energy consumption signal and the high-energy-consumption region type label are fused, and if there is an overlapping interval in the time stamp, the energy-saving potential level of the corresponding region is improved by one level.

[0033] It should be noted that the time series data is extracted from the dynamic energy saving state parameters of the system, mainly including the changes of regional current value, power efficiency and power consumption upper limit; these data can help understand the energy efficiency status of the system at different time points; for example: assuming that the system current value changes from 0.8 ampere to 1.2 ampere, the power efficiency decreases from 90% to 85%, and the power consumption upper limit fluctuates from 5 watts to 6 watts in a certain period of time; these data constitute the time series feature array; according to the pre-defined energy efficiency level standard, the time series feature array is divided into multiple analysis window segments, each segment represents a running mode or a specific time period; for example, the fluctuation of current value, power efficiency and the like in different time periods may reflect different working states of the system; in each analysis window segment, the mean value of the regional current is calculated, and the mean value is compared with the current reference value in the energy efficiency level standard; if the current exceeds the predetermined range, a "current exceeding coefficient" is generated; for example: assuming that the mean value of the regional current of a certain analysis window is 1.5 ampere, and the current reference value of the region in the energy efficiency level standard is 1.0 ampere, then the current exceeding coefficient is 1.5 / 1.0 = 1.5, indicating that the current exceeds 50%; the minimum value of the power efficiency in the analysis window segment is calculated, and compared with the efficiency threshold value in the energy efficiency level standard; if the power efficiency is lower than the threshold value, a "low efficiency flag" is generated; for example: if the minimum value of the power efficiency of a certain window is 82%, and the standard threshold value is 85%, a low efficiency flag will be generated, indicating that the power efficiency is low; the fluctuation range of the power consumption upper limit is calculated, and the deviation is calculated with the power consumption stability threshold value in the energy efficiency level standard; if the fluctuation range is large, a "power consumption fluctuation proportion value" is generated; for example: assuming that the power consumption upper limit fluctuates from 5 watts to 6 watts in a certain period of time, the fluctuation range is 1 watt, and the standard stability threshold value is 0.5 watt, then the power consumption fluctuation proportion value is 1 watt / 0.5 watt = 2, indicating that the power consumption fluctuation exceeds the standard limit; the current exceeding coefficient, low efficiency flag and power consumption fluctuation proportion value are input into the pre-trained energy saving decision model; assuming that in a certain time window, the current exceeding coefficient is 1.5, the efficiency insufficient flag bit triggers twice, and the power consumption fluctuation ratio value is 2; the decision model can determine whether the region needs to be optimized according to these indicators; the output result of the energy-saving decision model is used to determine whether the region belongs to a high-energy-consumption type; the high-energy-consumption region type includes: pixel overload, which refers to that the display pixels of a certain region exceed the normal power consumption range; power inefficiency, which refers to that the power supply efficiency is low, resulting in more energy waste; coupling loss, which refers to that the energy efficiency is reduced due to the strong coupling relationship between different parts of the system; the brightness distribution change of the pixels is monitored in real time; if the brightness of a certain region does not change significantly, but the current continues to rise, a "hidden energy consumption signal" is generated; this means that there is a hidden energy consumption problem in the region, which may be a display driving or power management problem; if the hidden energy consumption signal and the high-energy-consumption region label overlap in the same time period, the energy-saving potential level of the region can be improved; that is, if the current rises and the region has been marked as a high-energy-consumption region, the energy-saving potential level of the region can be improved to prioritize the optimization of the region; for example: if the current of a certain region rises and the region has been marked as "power inefficiency", and a hidden energy consumption signal is generated at this time, the energy-saving potential level of the region may be improved, so as to enter a higher priority optimization region.

[0034] In an optional embodiment, based on the high-energy-consumption region type and the energy-saving potential level, a modular energy-saving control strategy is generated, including: According to the pixel coordinates and the power supply interface position corresponding to the high-energy-consumption region type, the regulation region is located in the real-time running data sequence, and the parameter adjustment curve and the text description matched with the energy-saving potential level are generated; Based on the optimization priority corresponding to the energy-saving potential level, a multi-level energy-saving trigger signal is generated; According to the current adjustment rule and the power supply optimization parameter matched in the pre-defined energy-saving scheme library according to the high-energy-consumption region type, the current attenuation gradient and the brightness compensation coefficient are generated for the pixel overload type, the voltage fine-tuning curve and the load balancing instruction are generated for the power inefficiency type, and the region isolation parameter and the energy consumption shunting path are generated for the coupling loss type.

[0035] It should be noted that according to different high energy consumption area types, the system will first identify and locate the area that needs to be regulated, including pixel coordinates and power interface positions; this process is carried out through information in the real-time data sequence; for example: assuming that there is a display device, where a certain area displays excessive brightness, causing excessive current consumption, the system extracts the pixel coordinates and power interface positions of the area, locates the area that needs to be regulated, and formulates corresponding optimization strategies according to its energy saving potential; the energy saving potential level will affect the priority of the adjustment strategy, and generate the corresponding adjustment curve and explanation; this is based on the energy consumption potential of the area to adjust the power consumption performance of the device, ensuring that high-potential areas are prioritized for optimization; according to the energy saving potential level, multi-level energy saving trigger signals are designed; these signals reflect the energy saving measures that need to be taken in different areas, such as current adjustment, voltage fine-tuning, etc.; for example: in a power inefficient area, the system will generate multi-level signals according to its energy saving potential level, indicating different degrees of optimization measures, such as slight voltage adjustment or more intense load balancing operations; different high energy consumption area types correspond to different energy saving scheme libraries, and the rules in the library will be used to adjust the current and power; for example, pixel overload type areas will use current attenuation and brightness compensation; power inefficient type may need voltage fine-tuning and load balancing; for example: pixel overload type: if a display area consumes too much current due to pixel overload, the system will use current attenuation rules to reduce the current of the area, and adjust the brightness compensation coefficient as needed to maintain the display effect while reducing energy consumption; power inefficient type: if the power efficiency is low, the system will generate a voltage fine-tuning curve to optimize the output of the power supply and reduce waste; coupling loss usually refers to the energy loss caused by the interaction of energy between different parts of the system; for this type of high energy consumption area, the system will generate area isolation parameters and energy consumption shunt paths to reduce losses; for example: assuming that in a multi-layer circuit system, the coupling of power supplies in different parts causes energy waste, the system can identify this type of coupling loss and design energy shunt paths to reduce losses.

[0036] Embodiment two, please refer to Figure 2 The present application provides a technical solution: an energy saving control system for a COB display module, which is applicable to the energy saving control method of the COB display module, comprising: A data acquisition module 1 is used to obtain the real-time running data sequence of the COB display module, wherein the real-time running data sequence includes dynamic parameters of the pixel driving area and the power management module; A feature extraction module 2 is used to extract features from the real-time running data sequence to obtain pixel energy consumption features and power load features, wherein the pixel energy consumption features include brightness distribution and current density, and the power load features include voltage fluctuation and power loss; An efficiency calculation module 3 is configured to determine the energy consumption distribution of the pixel driving area and the efficiency parameter of the power management module based on the pixel energy consumption feature and the power load feature, and generate a dynamic energy-saving state parameter; An energy-saving matching module 4 is configured to perform multi-dimensional anomaly identification on the dynamic energy-saving state parameter according to a predefined energy efficiency level standard, and determine the high energy consumption area type and the energy-saving potential level. An energy-saving control module 5 is configured to generate a modular energy-saving control strategy based on the high energy consumption area type and the energy-saving potential level, wherein the modular energy-saving control strategy includes an area adjustment parameter, a power optimization scheme and an effect prediction curve.

[0037] The embodiments of the present application are described in detail above with reference to the drawings, but the present application is not limited thereto, and various changes can be made within the knowledge of those skilled in the art without departing from the spirit of the present application.

Claims

1. A method for energy-saving control of a COB display module, characterized in that: include: Acquire a real-time operating data sequence of the COB display screen module, wherein the real-time operating data sequence includes dynamic parameters of the pixel driving area and the power management module; Extracting features from the real-time operation data sequence to obtain pixel energy consumption features and power load features, wherein the pixel energy consumption features include brightness distribution and current density, and the power load features include voltage fluctuation and power loss; Based on the pixel energy consumption characteristics and the power load characteristics, determining the energy consumption distribution of the pixel driving area and the efficiency parameters of the power management module, and generating dynamic energy-saving state parameters; According to the predefined energy efficiency grade standard, the dynamic energy-saving state parameters are subjected to multi-dimensional anomaly identification to determine the type of high energy consumption area and the energy-saving potential grade; Based on the high energy consumption area type and energy saving potential level, a modular energy saving control strategy is generated, wherein the modular energy saving control strategy includes regional adjustment parameters, power supply optimization scheme and effect prediction curve.

2. The energy-saving control method of a COB display screen module according to claim 1, characterized in that: Extracting features from the real-time operation data sequence to obtain pixel energy consumption features and power load features includes: Sampling key parameters of the real-time operation data sequence to obtain an operation static data set of at least one COB display module; Performing feature dimension division on the static data set of each module operation to obtain a pixel driving candidate area and a power monitoring candidate area; Performing multi-scale energy consumption analysis on the pixel drive candidate area based on a deep learning network, determining the brightness distribution and current density, and generating the pixel energy consumption characteristics; Parameter inversion is performed on the candidate power supply monitoring area to obtain the voltage fluctuation and power loss, and generate the power supply load characteristics.

3. The energy-saving control method of a COB display screen module according to claim 2, characterized in that: The static data set of each module is divided into feature dimensions to obtain pixel drive candidate areas and power monitoring candidate areas, including: Performing parameter standardization on the module operation static data set to enhance the distinction between pixel drive parameters and power management parameters, thereby obtaining standardized module operation static data; Extracting sample areas where parameter fluctuations exceed a preset fluctuation threshold from the standardized module operation static data using a clustering algorithm to generate an initial candidate area set; Performing feature association analysis on the initial candidate area set, merging candidate areas with similar parameter change trends and adjacent spatial positions to generate a merged candidate area set; Filtering candidate areas from the merged candidate area set according to a preset pixel driving parameter range and a power supply parameter range to obtain a preliminarily filtered candidate area set; Noise filtering is performed on the candidate area set after the preliminary screening to generate final pixel driving candidate areas and power supply monitoring candidate areas.

4. The energy-saving control method of a COB display screen module according to claim 3, characterized in that: Based on the pixel energy consumption characteristics and the power load characteristics, determining the energy consumption distribution of the pixel driving area and the efficiency parameter of the power management module, and generating a dynamic energy-saving state parameter, including: Calculating energy consumption proportions and brightness redundancy of different display areas based on the brightness distribution in the pixel energy consumption characteristics to generate the energy consumption distribution; Determining a correlation between power conversion efficiency and load rate based on voltage fluctuations in the power load characteristics, and generating the efficiency parameter; Combining the energy consumption distribution and the efficiency parameter to determine the energy consumption coupling coefficient between the pixel driving area and the power module; Generating quantitative indicators of a regional current regulation threshold, a power supply voltage correction amount, and a dynamic power consumption upper limit based on the energy consumption coupling coefficient; The quantitative index is matched with a preset energy efficiency model, and the dynamic energy-saving state parameter is output.

5. The energy-saving control method of a COB display screen module according to claim 4, characterized in that: Determining a correlation between power conversion efficiency and load rate based on voltage fluctuations in the power load characteristics, and generating the efficiency parameter, includes: Extracting voltage fluctuation values ​​and load rate data corresponding to adjacent timestamps in the power load feature, correlating and matching the voltage value of the previous timestamp with the load rate of the next timestamp to generate a voltage-load correlation pair; Calculating the deviation between the real-time value and the theoretical value of the power conversion efficiency based on the value change of the voltage-load association pair to generate an efficiency deviation coefficient; Based on the rate of change of the efficiency deviation coefficient at consecutive timestamps, the efficiency decay rate is calculated, the time point when the decay rate exceeds a preset rate threshold is marked as an efficiency mutation point, the distribution frequency of the efficiency mutation point within the power supply operation cycle is counted, and the efficiency stability index is generated according to the ratio of the distribution frequency to the rate threshold; Normalizing and fusing the efficiency deviation coefficient, the efficiency mutation point distribution frequency, and the efficiency stability index to generate an efficiency parameter set; According to the power loss data in the power load characteristics, a predefined power type attribute library is matched to extract the efficiency compensation coefficient of the corresponding power type; Performing a product operation on the efficiency deviation coefficient in the efficiency parameter set and the efficiency compensation coefficient to generate an efficiency correction index; comparing the exponential difference between adjacent timestamps with a predefined efficiency attenuation threshold based on the temporal variation trend of the efficiency correction index to generate an efficiency parameter dynamic abnormality flag; The efficiency parameter set, efficiency correction index and efficiency parameter dynamic abnormality flag are superimposed in time series to form an efficiency parameter trend graph with a timestamp, and based on the parameter change direction of consecutive timestamps in the efficiency parameter trend graph, a power supply efficiency optimization direction prediction trajectory is generated; According to the correlation degree between the efficiency optimization direction prediction trajectory and the pixel energy consumption distribution, the dynamic weight coefficient of the efficiency parameter is adjusted to generate a final efficiency parameter set.

6. The energy-saving control method of a COB display screen module according to claim 5, characterized in that: Combining the energy consumption distribution and the efficiency parameter to determine the energy consumption coupling coefficient between the pixel driving area and the power module includes: Extracting the current change curve of the high energy consumption area under continuous time stamps according to the energy consumption proportion of each display area in the energy consumption distribution; Extracting the efficiency attenuation coefficient of the power module at the corresponding timestamp based on the correlation between the power conversion efficiency and the load rate in the efficiency parameter; Performing time synchronization calibration on the current change curve and the efficiency attenuation coefficient to generate a synchronized energy consumption-efficiency mapping relationship; According to the synchronized energy consumption-efficiency mapping relationship, locating a current threshold point corresponding to an efficiency decay peak in the current change curve, and calculating an influence weight of a high energy consumption area on power supply efficiency based on the current threshold point; determining an energy consumption conduction path between each display area and a power module according to the spatial distribution of the influence weight and the efficiency attenuation coefficient; The energy consumption coupling coefficient is generated according to the intensity change and direction consistency of the energy consumption conduction path at continuous time stamps, wherein the numerical value of the energy consumption coupling coefficient represents the degree of energy consumption correlation.

7. The energy-saving control method of a COB display screen module according to claim 6, characterized in that: According to the energy consumption coupling coefficient, quantitative indicators of the regional current regulation threshold, power supply voltage correction amount and dynamic power consumption upper limit are generated, including: Extracting the distribution characteristics of the energy consumption coupling coefficient, marking the continuous area where the energy consumption coupling coefficient exceeds a preset coupling threshold as a strong correlation core area, dividing the analysis unit within the strong correlation core area, counting the energy consumption conduction direction consistency ratio within each analysis unit, and merging the analysis units whose consistency ratio exceeds a preset ratio threshold into a high-efficiency energy-saving zone; Based on the product of the coverage area of ​​the high-efficiency energy-saving belt and the energy consumption coupling coefficient, an initial current regulation threshold value at each time stamp is generated; according to the brightness distribution in the pixel energy consumption characteristics, a predefined brightness-current correspondence table is matched, and the initial current regulation threshold value and the brightness redundancy are weightedly corrected to generate a regional current regulation threshold value; Extracting a stability margin corresponding to power supply voltage fluctuations in the power supply load characteristics, calculating an attenuation ratio between the stability margin and a coupling value in the same region of the energy consumption coupling coefficient, and determining a dynamic estimate of the power supply voltage correction amount based on the attenuation ratio and a predefined voltage regulation curve; Based on the duration of the strongly correlated core area of ​​each time stamp in the energy consumption coupling coefficient, the proportion of the strongly correlated core area in the total operating time is counted to generate an initial value of the power consumption proportion, and according to the power loss data in the power load characteristics, the credibility weight of the initial value of the power consumption proportion is adjusted to generate a dynamic power consumption upper limit; The regional current regulation threshold, power supply voltage correction amount, and dynamic power consumption upper limit are aligned according to timestamps to generate a quantitative indicator timing matrix, and according to the fluctuation amplitude of each indicator in the quantitative indicator timing matrix, a predefined energy-saving mode feature library is matched to generate a current regulation safety interval, a voltage correction accuracy threshold, and a power consumption upper limit dynamic range; Based on the safety interval, accuracy threshold and dynamic range, the quantitative indicator time series matrix is ​​segmented and labeled to generate a set of quantitative indicators with energy-saving level marks.

8. The energy-saving control method of a COB display screen module according to claim 7, characterized in that: According to the predefined energy efficiency grade standard, the dynamic energy-saving state parameters are subjected to multi-dimensional anomaly identification to determine the type of high energy consumption area and the energy-saving potential level, including: Extracting a time series feature array of regional current value, power efficiency and power consumption upper limit from the dynamic energy-saving state parameters; According to the predefined energy efficiency grade standard, the timing feature array is divided into analysis window segments matching the current operating mode; Performing a ratio operation on the regional current mean value within each analysis window segment and the current reference value in the energy efficiency grade standard to generate a current exceeding standard coefficient; Synchronously comparing the difference between the minimum power efficiency value within the analysis window segment and the efficiency threshold value in the energy efficiency grade standard to generate an efficiency deficiency flag; Calculate the deviation between the fluctuation amplitude of the power consumption upper limit and the power consumption stability threshold in the energy efficiency grade standard to generate a power consumption fluctuation ratio value; Inputting the current exceeding coefficient, the efficiency insufficient flag, and the power consumption fluctuation ratio into a pre-trained energy-saving decision model, wherein the energy-saving decision model includes a first decision layer, a second decision layer, and a third decision layer, wherein the first decision layer determines whether the current exceeding coefficient exceeds the energy-saving critical value, the second decision layer generates a power supply aging index according to the number of times the efficiency insufficient flag is triggered, and the third decision layer generates a regional abnormality pattern based on the power consumption fluctuation ratio and energy consumption distribution characteristics; Determining a corresponding high-energy-consumption area type label based on the recognition result output by the energy-saving decision model, wherein the high-energy-consumption area type label includes at least one of pixel overload, power inefficiency, and coupling loss; Acquire the brightness distribution change in the pixel energy consumption characteristics in real time, and generate a latent energy consumption signal when detecting an area where the brightness does not change significantly but the current continues to rise; The implicit energy consumption signal is fused with the high energy consumption area type label. If there is an overlapping interval between the two in terms of timestamps, the energy saving potential level of the corresponding area is increased by one level.

9. The energy-saving control method of a COB display screen module according to claim 8, characterized in that: Based on the type of high energy consumption area and the energy saving potential level, a modular energy saving control strategy is generated, including: Locating the control area in the real-time operation data sequence based on the pixel coordinates and power interface position corresponding to the high energy consumption area type, and generating a parameter adjustment curve and text description matching the energy saving potential level; generating a multi-level energy-saving trigger signal based on the optimization priority corresponding to the energy-saving potential level; The current regulation rules and power optimization parameters in the predefined energy-saving solution library are matched according to the high-energy consumption area type, wherein the pixel overload type generates a current attenuation gradient and a brightness compensation coefficient, the power inefficiency type generates a voltage fine-tuning curve and a load balancing instruction, and the coupling loss type generates a regional isolation parameter and an energy consumption diversion path.

10. An energy-saving control system for a COB display screen module, which is applicable to the energy-saving control method for a COB display screen module according to any one of claims 1 to 9, characterized in that: include: A data acquisition module is used to obtain a real-time operating data sequence of the COB display module, wherein the real-time operating data sequence includes dynamic parameters of the pixel drive area and the power management module; a feature extraction module, configured to extract features from the real-time operation data sequence to obtain pixel energy consumption features and power load features, wherein the pixel energy consumption features include brightness distribution and current density, and the power load features include voltage fluctuation and power loss; an efficiency calculation module, configured to determine the energy consumption distribution of the pixel driving area and the efficiency parameter of the power management module based on the pixel energy consumption characteristics and the power load characteristics, and generate a dynamic energy-saving state parameter; An energy-saving matching module is used to perform multi-dimensional anomaly identification on the dynamic energy-saving state parameters according to predefined energy efficiency grade standards, and determine the type of high energy consumption area and energy-saving potential level; The energy-saving control module is used to generate a modular energy-saving control strategy based on the high-energy-consuming area type and energy-saving potential level, wherein the modular energy-saving control strategy includes regional adjustment parameters, power supply optimization scheme and effect prediction curve.

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