Display screen energy-saving control optimization system

Abstract

The invention relates to the technical field of display screen energy-saving optimization, and discloses a display screen energy-saving control optimization system, which comprises an analysis module used for dividing a display screen into a plurality of monitoring areas, collecting historical operation parameters of the plurality of monitoring areas, carrying out correlation analysis, and determining characteristic operation parameters according to a correlation analysis result; the calculation module is used for acquiring real-time characteristic operation parameters of the plurality of monitoring areas, performing clustering analysis to obtain a plurality of real-time characteristic operation parameter sequences, and calculating an energy consumption loss evaluation value of each real-time characteristic operation parameter sequence based on a preset application demand and the real-time environment parameters; and the optimization module is used for judging whether the corresponding real-time characteristic operation parameters are optimized or not according to the energy consumption loss evaluation value, if yes, an optimization strategy is generated, an energy-saving control instruction is issued, and the energy-saving efficiency and accuracy of the display screen are improved.

Description

Technical Field

[0001] This application relates to the technical field of energy-saving optimization of display screens, and particularly to an energy-saving control optimization system for display screens. Background Art

[0002] Currently, display screens have been widely used in various display fields, but they also have obvious disadvantages, such as high power consumption and reduced lifespan of the display screen due to heat generation during long-term operation. Therefore, it is necessary to conduct in-depth research on the field of energy-saving control of display screens.

[0003] In the prior art, energy-saving control of display screens mainly relies on manual adjustment of brightness and operating modes. However, relying solely on manual adjustment not only results in low energy-saving efficiency but also cannot guarantee control accuracy. Therefore, there is an urgent need for an energy-saving control optimization system for display screens that can comprehensively reflect the energy consumption losses of various operating parameters, formulate reasonable energy-saving control optimization strategies, and improve energy-saving efficiency and accuracy. Summary of the Invention

[0004] To solve the above technical problems, this application provides an energy-saving control optimization system for display screens. By determining characteristic operating parameters and constructing several real-time characteristic operating parameter sequences, calculating the energy consumption loss evaluation value of each real-time characteristic operating parameter sequence, and judging whether to optimize the corresponding real-time characteristic operating parameter based on the energy consumption loss evaluation value, if so, generating an optimization strategy and issuing an energy-saving control instruction, thereby improving the energy-saving efficiency and accuracy of the display screen.

[0005] In some embodiments of this application, an energy-saving control optimization system for display screens is provided, including: An analysis module for dividing the display screen into several monitoring areas, collecting historical operating parameters of the several monitoring areas, and performing correlation analysis, and determining characteristic operating parameters according to the correlation analysis results; A calculation module for obtaining real-time characteristic operating parameters of the several monitoring areas, performing clustering analysis to obtain several real-time characteristic operating parameter sequences, and calculating the energy consumption loss evaluation value of each real-time characteristic operating parameter sequence based on preset application requirements and real-time environmental parameters; An optimization module for judging whether to optimize the corresponding real-time characteristic operating parameter according to the energy consumption loss evaluation value, and if so, generating an optimization strategy and issuing an energy-saving control instruction.

[0006] In some embodiments of this application, determining characteristic operating parameters according to the correlation analysis results includes: Presetting energy-saving evaluation indicators and other evaluation indicators for the display screen in advance; Calculating the influence degree of other evaluation indicators on the energy-saving evaluation indicators; Set the energy-saving evaluation index as the target evaluation index, set other evaluation indexes with an influence degree greater than the preset influence degree threshold as secondary evaluation indexes, and set the weight coefficient of each secondary evaluation index; Obtain the historical monitoring logs of each monitoring area, and generate the historical evaluation values of the target evaluation index and several secondary evaluation indexes; Extract the historical operation parameters from each historical monitoring log, construct a time reference line based on the historical monitoring duration of the historical monitoring log, and set the acquisition time nodes according to the preset time interval; Collect the historical operation parameters and the corresponding historical evaluation values according to the acquisition time nodes and map them to the corresponding time reference lines to obtain a parameter-evaluation value change curve graph; Analyze each parameter-evaluation value change curve graph, and obtain the target correlation degree and several secondary correlation degrees between the corresponding historical operation parameters in each historical monitoring log and the target evaluation index and several secondary evaluation indexes according to the analysis results; Set the evaluation index with a correlation degree greater than the preset correlation degree threshold as the correlation evaluation index of the corresponding historical operation parameter; Generate the comprehensive correlation degree of the corresponding historical operation parameter according to the target correlation degree and several secondary correlation degrees of the same historical operation parameter in different historical monitoring logs; Set the historical operation parameter with a comprehensive correlation degree greater than the comprehensive correlation degree threshold as the characteristic operation parameter.

[0007] In some embodiments of the present application, generating the comprehensive correlation degree of the corresponding historical operation parameter according to the target correlation degree and several secondary correlation degrees of the same historical operation parameter in different historical monitoring logs includes: Compare the several target correlation degrees of the same historical operation parameter in different historical monitoring logs and the several secondary correlation degrees of multiple secondary evaluation indexes to obtain the first quantity with the target correlation degree greater than the preset first correlation degree threshold, several target correlation degree differences, the second quantity with the secondary correlation degree greater than the preset second correlation degree threshold, and the corresponding several secondary correlation degree differences; Generate the credibility of the target evaluation index according to the first quantity, and generate the credibility of the corresponding secondary evaluation index according to the second quantity; Generate the comprehensive correlation degree of the corresponding historical operation parameter according to the first quantity, several target correlation degree differences, the second quantity, several secondary correlation degree differences, and the corresponding weight coefficient; The calculation formula of the comprehensive correlation degree is: ; where G is the comprehensive correlation degree, a1 is the first weight coefficient, k1 is the credibility of the target evaluation index, n1 is the first quantity, is the difference in the degree of association for the i1-th target, and a2 is the second weight coefficient. is the credibility of the j-th secondary evaluation index. is the difference in the i2-th secondary degree of association of the j-th secondary evaluation index, n2j is the second quantity of the j-th secondary evaluation index, and m is the number of secondary evaluation indexes. is the weight coefficient of the j-th secondary evaluation index.

[0008] In some embodiments of the present application, based on preset application requirements and real-time environmental parameters, the energy consumption loss evaluation value of each real-time feature operation parameter sequence is calculated, including: Obtain the real-time feature operation parameters of each monitoring area, perform data cleaning and standardization processing on the real-time feature operation parameters to obtain the processed real-time feature operation parameters. Perform clustering analysis on the processed real-time feature operation parameters of different monitoring areas to obtain several real-time feature operation parameter sequences. Perform energy consumption conversion on each real-time feature operation parameter in the same real-time feature operation parameter sequence to obtain the corresponding energy consumption sequence, and the energy consumption sequence includes several real-time energy consumptions. Generate the standard parameter threshold of each feature operation parameter based on the preset application requirements and real-time environmental parameters, and perform energy consumption conversion to obtain the corresponding standard energy consumption. Divide the energy consumption sequence of the corresponding real-time feature operation parameter sequence according to the standard energy consumption to obtain the first energy consumption set, the second energy consumption set, and the third energy consumption set of the corresponding real-time feature operation parameter sequence. Calculate the energy consumption loss evaluation value of the corresponding real-time feature operation parameter sequence according to the first energy consumption set, the second energy consumption set, and the third energy consumption set.

[0009] In some embodiments of the present application, obtaining the first energy consumption set, the second energy consumption set, and the third energy consumption set of the corresponding real-time feature operation parameter sequence includes: Compare the standard energy consumption with several real-time energy consumptions in the energy consumption sequence of the corresponding real-time feature operation parameter sequence. If the real-time energy consumption is less than the standard energy consumption, divide the real-time energy consumption into the low energy consumption set. If the real-time energy consumption is equal to the standard energy consumption, divide the real-time energy consumption into the medium energy consumption set. If the real-time energy consumption is greater than the standard energy consumption, divide the real-time energy consumption into the high energy consumption set. Calculate the mean and standard deviation of the low energy consumption set, the medium energy consumption set, and the high energy consumption set respectively. Set the first critical interval, the second critical interval, and the third critical interval according to the mean and standard deviation. Extract the real-time energy consumption in the first critical interval from the low energy consumption set and construct the first energy consumption set; Extract the real-time energy consumption in the second critical interval from the medium energy consumption set and construct the second energy consumption interval; Extract the real-time energy consumption in the third critical interval from the high energy consumption set and construct the third energy consumption interval.

[0010] In some embodiments of the present application, calculate the energy consumption loss evaluation value of the corresponding real-time characteristic operation parameter sequence according to the first energy consumption set, the second energy consumption set, and the third energy consumption set, including: Calculate the first set quantity, the second set quantity, and the third set quantity of the first energy consumption set, the second energy consumption set, and the third energy consumption set; Set the selection coefficient according to the set quantity relationship of the first set quantity, the second set quantity, and the third set quantity; The calculation formula of the energy consumption loss evaluation value is: ; Wherein, H is the energy consumption loss evaluation value, is the selection coefficient, h1 is the first energy consumption loss conversion coefficient, h2 is the second energy consumption loss conversion coefficient, b1 is the weight coefficient of the first energy consumption set, b2 is the weight coefficient of the third energy consumption set, z1 is the first set quantity, z2 is the third set quantity, is the s1-th real-time energy consumption in the first energy consumption set, q0 is the corresponding standard energy consumption, is the s2-th real-time energy consumption in the third energy consumption set.

[0011] In some embodiments of the present application, set the selection coefficient according to the set quantity relationship of the first set quantity, the second set quantity, and the third set quantity, including: Preset the first preset selection coefficient interval, the second preset selection coefficient interval, and the third preset selection coefficient interval; When the first set quantity is greater than the second set quantity and the first set quantity is greater than the third set quantity, set the selection coefficient to be in the first preset selection coefficient interval; When the second set quantity is greater than the first set quantity and the second set quantity is greater than the third set quantity, set the selection coefficient to be in the second preset selection coefficient interval; When the third set quantity is greater than the second set quantity and the third set quantity is greater than the first set quantity, set the selection coefficient to be in the third preset selection coefficient interval.

[0012] In some embodiments of the present application, determine whether to optimize the corresponding real-time characteristic operation parameter according to the energy consumption loss evaluation value, including: Preset the preset energy consumption loss evaluation value threshold; When the evaluation value of energy consumption loss is less than the preset threshold value of the evaluation value of energy consumption loss, it is determined that the corresponding real-time characteristic operation parameters are not optimized; When the evaluation value of energy consumption loss is greater than the preset threshold value of the evaluation value of energy consumption loss, it is determined that the corresponding real-time characteristic operation parameters are optimized.

[0013] In some embodiments of the present application, an optimization strategy is generated, including: According to a number of real-time energy consumptions in the third energy consumption set corresponding to the real-time characteristic operation parameters to be optimized and the corresponding standard energy consumption, a number of real-time energy consumption differences are obtained; Based on a number of real-time energy consumption differences, preset application requirements, and real-time environmental parameters as matching conditions, a number of preset optimization strategies with a matching similarity greater than the preset similarity threshold are screened out from the preset optimization strategy reference library; Map the real-time energy consumption difference to the corresponding preset optimization strategy to obtain an energy consumption difference - optimization strategy mapping table for the real-time characteristic operation parameters to be optimized; Obtain the optimization evaluation coefficient of each preset optimization strategy in the energy consumption difference - optimization strategy mapping table, and calculate the comprehensive optimization evaluation coefficient of the corresponding preset optimization strategy in combination with the difference similarity; Set the preset optimization strategy with the largest comprehensive optimization evaluation coefficient as the optimization strategy for the corresponding real-time characteristic operation parameters to be optimized.

[0014] In some embodiments of the present application, a number of energy-saving control instructions are generated according to the optimization strategy of the real-time characteristic operation parameters to be optimized; Determine whether there is a conflict between a number of energy-saving control instructions. If there is a conflict, set the issuing order of the corresponding energy-saving control instructions according to the weight coefficient of the corresponding real-time characteristic operation parameters. If not, directly issue the energy-saving control instructions.

[0015] An energy-saving control optimization system for a display screen according to an embodiment of the present application, compared with the prior art, has the beneficial effects that: By determining the characteristic operation parameters and constructing a number of real-time characteristic operation parameter sequences, calculating the evaluation value of energy consumption loss of each real-time characteristic operation parameter sequence, and determining whether to optimize the corresponding real-time characteristic operation parameters according to the evaluation value of energy consumption loss. If so, an optimization strategy is generated and an energy-saving control instruction is issued, improving the energy-saving efficiency and accuracy of the display screen. Description of the Drawings

[0016] Figure 1 It is a schematic diagram of an energy-saving control optimization system for a display screen in an embodiment of the present application. Detailed Embodiments

[0017] The specific embodiments of the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following embodiments are used to illustrate the present application, but are not used to limit the scope of the present application.

[0018] In the description of the present application, it should be understood that the orientation or positional relationship indicated by the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present application.

[0019] The terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present application, unless otherwise stated, the meaning of "plurality" is two or more.

[0020] In the description of the present application, it should be noted that unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense. For example, it may be a fixed connection, a detachable connection, or an integral connection; it may be a mechanical connection or an electrical connection; it may be directly connected or indirectly connected through an intermediate medium, and it may be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to specific circumstances.

[0021] As Figure 1 shown, an energy-saving control optimization system for a display screen according to an embodiment of the present application includes: An analysis module, configured to divide the display screen into several monitoring areas, collect historical operation parameters of the several monitoring areas, and perform correlation analysis, and determine characteristic operation parameters according to the correlation analysis results; A calculation module, configured to obtain real-time characteristic operation parameters of the several monitoring areas, perform clustering analysis, obtain several real-time characteristic operation parameter sequences, and calculate an energy consumption loss evaluation value for each real-time characteristic operation parameter sequence based on a preset application requirement and real-time environmental parameters; An optimization module, configured to determine whether to optimize the corresponding real-time characteristic operation parameters according to the energy consumption loss evaluation value. If so, generate an optimization strategy and issue an energy-saving control instruction.

[0022] In this embodiment, a number of real-time feature operation parameter sequences are constructed based on the real-time feature operation parameters of the same category in different monitoring areas. The categories include display screen brightness, refresh rate, dynamic effect, heat dissipation efficiency, etc.

[0023] In some embodiments of the present application, determining the feature operation parameters according to the correlation analysis results includes: Presetting the energy-saving evaluation index and other evaluation indexes of the display screen; Calculating the influence degree of other evaluation indexes on the energy-saving evaluation index; Setting the energy-saving evaluation index as the target evaluation index, setting other evaluation indexes with an influence degree greater than the preset influence degree threshold as secondary evaluation indexes, and setting the weight coefficient of each secondary evaluation index; Obtaining the historical monitoring logs of each monitoring area, and generating the historical evaluation values of the target evaluation index and a number of secondary evaluation indexes; Extracting the historical operation parameters in each historical monitoring log, constructing a time reference line based on the historical monitoring duration of the historical monitoring log, and setting the acquisition time nodes according to the preset time interval; Collecting the historical operation parameters and the corresponding historical evaluation values according to the acquisition time nodes and mapping them to the corresponding time reference lines to obtain a parameter-evaluation value change curve graph; Analyzing each parameter-evaluation value change curve graph, and obtaining the target correlation degree and a number of secondary correlation degrees between the corresponding historical operation parameters in each historical monitoring log and the target evaluation index and a number of secondary evaluation indexes according to the analysis results; Setting the evaluation index with a correlation degree greater than the preset correlation degree threshold as the correlation evaluation index of the corresponding historical operation parameter; Generating the comprehensive correlation degree of the corresponding historical operation parameter according to the target correlation degree and a number of secondary correlation degrees of the same historical operation parameter in different historical monitoring logs; Setting the historical operation parameters with a comprehensive correlation degree greater than the comprehensive correlation degree threshold as the feature operation parameters.

[0024] In this embodiment, the change curves of the same historical operation parameter in the same parameter-evaluation value change curve graph are compared and analyzed with the change curves of the historical evaluation values of the target evaluation index and a number of secondary evaluation indexes. If the historical evaluation value changes with the change of the historical operation parameter, the greater the correlation degree, and vice versa, the smaller the correlation degree.

[0025] In this embodiment, the comprehensive correlation degree is used to comprehensively evaluate the correlation between each historical operating parameter and the target evaluation index as well as several secondary evaluation indexes. Based on the comprehensive correlation degree, the characteristic operating parameters are accurately screened, laying a foundation for constructing the real-time characteristic operating parameter sequence and calculating the energy consumption loss evaluation value later, reducing the amount of data analysis and processing, and improving the calculation accuracy of the energy consumption loss evaluation value, so as to formulate a reasonable optimization strategy, achieve the energy-saving control of the display screen, and improve the energy-saving efficiency.

[0026] In some embodiments of the present application, the comprehensive correlation degree of the corresponding historical operating parameter is generated according to the target correlation degree and several secondary correlation degrees of the same historical operating parameter in different historical monitoring logs, including: Compare several target correlation degrees of the same historical operating parameter in different historical monitoring logs and several secondary correlation degrees of multiple secondary evaluation indexes to obtain the first quantity with the target correlation degree greater than the preset first correlation degree threshold, several target correlation degree differences, the second quantity with the secondary correlation degree greater than the preset second correlation degree threshold, and the corresponding several secondary correlation degree differences; Generate the credibility of the target evaluation index according to the first quantity, and generate the credibility of the corresponding secondary evaluation index according to the second quantity; Generate the comprehensive correlation degree of the corresponding historical operating parameter according to the first quantity, several target correlation degree differences, the second quantity, several secondary correlation degree differences, and the corresponding weight coefficients; The calculation formula of the comprehensive correlation degree is: ; Wherein, G is the comprehensive correlation degree, a1 is the first weight coefficient, k1 is the credibility of the target evaluation index, n1 is the first quantity, is the i1-th target correlation degree difference, a2 is the second weight coefficient, is the credibility of the j-th secondary evaluation index, is the i2-th secondary correlation degree difference of the j-th secondary evaluation index, n2j is the second quantity of the j-th secondary evaluation index, m is the number of secondary evaluation indexes, is the weight coefficient of the j-th secondary evaluation index.

[0027] In this embodiment, the credibility refers to the ratio of the first quantity or the second quantity to the number of historical monitoring logs. The larger the ratio, the greater the credibility, and vice versa.

[0028] In some embodiments of the present application, based on the preset application requirements and real-time environmental parameters, calculate the energy consumption loss evaluation value of each real-time characteristic operating parameter sequence, including: Obtain the real-time characteristic operation parameters of each monitoring area, perform data cleaning and standardization processing on the real-time characteristic operation parameters to obtain the processed real-time characteristic operation parameters; Perform clustering analysis on the processed real-time characteristic operation parameters of different monitoring areas to obtain several real-time characteristic operation parameter sequences; Perform energy consumption conversion on each real-time characteristic operation parameter in the same real-time characteristic operation parameter sequence to obtain the corresponding energy consumption sequence, and the energy consumption sequence includes several real-time energy consumptions; Generate the standard parameter thresholds of each characteristic operation parameter based on the preset application requirements and real-time environmental parameters, and perform energy consumption conversion to obtain the corresponding standard energy consumption; Divide the energy consumption sequence of the corresponding real-time characteristic operation parameter sequence according to the standard energy consumption to obtain the first energy consumption set, the second energy consumption set, and the third energy consumption set of the corresponding real-time characteristic operation parameter sequence; Calculate the energy consumption loss evaluation value of the corresponding real-time characteristic operation parameter sequence according to the first energy consumption set, the second energy consumption set, and the third energy consumption set.

[0029] In this embodiment, the standard parameter threshold refers to the minimum operation parameter of the corresponding characteristic operation parameter under the current environmental conditions and meeting the application requirements, and perform energy consumption conversion to obtain the standard energy consumption, that is, the lowest energy consumption.

[0030] In this embodiment, each characteristic operation parameter has a specific formula for energy consumption conversion, which is set in advance and will not be elaborated here.

[0031] In this embodiment, by performing energy consumption conversion on each real-time characteristic operation parameter sequence to obtain an energy consumption sequence, where each real-time characteristic operation parameter corresponds to the corresponding real-time energy consumption, and dividing the energy consumption sequence to obtain the first energy consumption set, the second energy consumption set, and the third energy consumption set, it lays a foundation for calculating the energy consumption loss evaluation value of each real-time characteristic operation parameter sequence later and improves the calculation accuracy of the energy consumption loss evaluation value.

[0032] In some embodiments of the present application, obtaining the first energy consumption set, the second energy consumption set, and the third energy consumption set of the corresponding real-time characteristic operation parameter sequence includes: Compare the standard energy consumption with several real-time energy consumptions in the energy consumption sequence of the corresponding real-time characteristic operation parameter sequence. If the real-time energy consumption is less than the standard energy consumption, divide the real-time energy consumption into the low energy consumption set; If the real-time energy consumption is equal to the standard energy consumption, divide the real-time energy consumption into the medium energy consumption set; If the real-time energy consumption is greater than the standard energy consumption, divide the real-time energy consumption into the high energy consumption set; Calculate the mean and standard deviation of the low energy consumption set, the medium energy consumption set, and the high energy consumption set respectively; Set the first critical interval, the second critical interval, and the third critical interval according to the mean and the standard deviation; Extract the real-time energy consumption within the first critical interval from the low energy consumption set, and construct the first energy consumption set; Extract the real-time energy consumption within the second critical interval from the medium energy consumption set, and construct the second energy consumption interval; Extract the real-time energy consumption within the third critical interval from the high energy consumption set, and construct the third energy consumption interval.

[0033] In this embodiment, perform subtraction and addition according to the mean and the standard deviation, and use the values after subtraction and the values after addition as boundary points to obtain the first critical interval of the low energy consumption set, the second critical interval of the medium energy consumption set, and the third critical interval of the high energy consumption set.

[0034] In some embodiments of the present application, calculate the energy consumption loss evaluation value of the corresponding real-time characteristic operation parameter sequence according to the first energy consumption set, the second energy consumption set, and the third energy consumption set, including: Calculate the first set quantity, the second set quantity, and the third set quantity of the first energy consumption set, the second energy consumption set, and the third energy consumption set; Set the selection coefficient according to the set quantity relationship of the first set quantity, the second set quantity, and the third set quantity; The calculation formula of the energy consumption loss evaluation value is: ; Where H is the energy consumption loss evaluation value, is the selection coefficient, h1 is the first energy consumption loss conversion coefficient, h2 is the second energy consumption loss conversion coefficient, b1 is the weight coefficient of the first energy consumption set, b2 is the weight coefficient of the third energy consumption set, z1 is the first set quantity, z2 is the third set quantity, is the s1-th real-time energy consumption in the first energy consumption set, q0 is the corresponding standard energy consumption, is the s2-th real-time energy consumption in the third energy consumption set.

[0035] In this embodiment, the first energy consumption loss conversion coefficient and the second energy consumption loss conversion coefficient respectively refer to converting the real-time energy consumption difference in the first energy consumption set and the third energy consumption set into a value with the same dimension as the energy consumption loss evaluation value. The real-time energy consumption differences in the first energy consumption set are all negative numbers. When the real-time energy consumption difference is smaller, the converted energy consumption loss evaluation value is smaller. The real-time energy consumption differences in the third energy consumption set are all positive numbers. When the real-time energy consumption difference is larger, the converted energy consumption loss evaluation value is larger.

[0036] In this embodiment, by selecting a coefficient and calculating an energy consumption loss evaluation value based on the real-time energy consumption difference, the accurate calculation of the energy consumption loss evaluation value for each real-time characteristic operating parameter is realized, reflecting the actual energy consumption situation of each real-time characteristic operating parameter, and ensuring the accuracy and optimization efficiency of subsequent energy-saving control optimization.

[0037] In some embodiments of the present application, the selection coefficient is set according to the set quantity relationship among the first set quantity, the second set quantity, and the third set quantity, including: A first preset selection coefficient interval, a second preset selection coefficient interval, and a third preset selection coefficient interval are preset in advance; When the first set quantity is greater than the second set quantity and the first set quantity is greater than the third set quantity, the selection coefficient is set to be within the first preset selection coefficient interval; When the second set quantity is greater than the first set quantity and the second set quantity is greater than the third set quantity, the selection coefficient is set to be within the second preset selection coefficient interval; When the third set quantity is greater than the second set quantity and the third set quantity is greater than the first set quantity, the selection coefficient is set to be within the third preset selection coefficient interval.

[0038] In this embodiment, the first preset selection coefficient interval is (0.7, 0.85), the second preset selection coefficient interval is (0.85, 1.15), and the third preset selection coefficient interval is (1.15, 1.3).

[0039] In this embodiment, when the first set quantity is greater than the second set quantity and the first set quantity is greater than the third set quantity, if the second set quantity is greater than the third set quantity, the selection coefficient approaches 0.7, and if the third set quantity is greater than the second set quantity, the selection coefficient approaches 0.85. When the second set quantity is greater than the first set quantity and the second set quantity is greater than the third set quantity, when the first set quantity is greater than the third set quantity, the selection coefficient approaches 0.85, and when the first set quantity is less than the third set quantity, the selection coefficient approaches 1.15. When the third set quantity is greater than the second set quantity and the third set quantity is greater than the first set quantity, when the second set quantity is less than the first set quantity, the selection coefficient approaches 1.15, and when the second set quantity is greater than the first set quantity, the selection coefficient approaches 1.3. The accurate value of the selection coefficient is selected according to the actual situation.

[0040] In this embodiment, the corresponding selection coefficient is selected through the set quantity relationship, thereby improving the accuracy of the energy consumption loss evaluation value, realizing the accurate adjustment of the energy consumption loss evaluation value, and ensuring the accuracy of subsequent energy-saving control optimization.

[0041] In some embodiments of the present application, determining whether to optimize the corresponding real-time feature operating parameters according to the energy consumption loss evaluation value includes: Presetting a threshold value of the preset energy consumption loss evaluation value; When the energy consumption loss evaluation value is less than the threshold value of the preset energy consumption loss evaluation value, it is determined not to optimize the corresponding real-time feature operating parameters; When the energy consumption loss evaluation value is greater than the threshold value of the preset energy consumption loss evaluation value, it is determined to optimize the corresponding real-time feature operating parameters.

[0042] In this embodiment, the threshold value of the preset energy consumption loss evaluation value is the maximum energy consumption loss evaluation value of each feature operating parameter under the current preset application requirements and environmental conditions, which is set in advance.

[0043] In some embodiments of the present application, generating an optimization strategy includes: Obtaining a number of real-time energy consumption differences based on a number of real-time energy consumptions in the third energy consumption set corresponding to the real-time feature operating parameters to be optimized and the corresponding standard energy consumption; Based on the number of real-time energy consumption differences, the preset application requirements, and the real-time environmental parameters as matching conditions, screening out a number of preset optimization strategies from the preset optimization strategy reference library whose matching similarity is greater than the preset similarity threshold; Mapping the real-time energy consumption differences to the corresponding preset optimization strategies to obtain an energy consumption difference - optimization strategy mapping table for the real-time feature operating parameters to be optimized; Obtaining the optimization evaluation coefficient of each preset optimization strategy in the energy consumption difference - optimization strategy mapping table, and calculating the comprehensive optimization evaluation coefficient of the corresponding preset optimization strategy in combination with the difference similarity; Setting the preset optimization strategy with the largest comprehensive optimization evaluation coefficient as the optimization strategy for the corresponding real-time feature operating parameters to be optimized.

[0044] In this embodiment, the optimization evaluation coefficient refers to the optimization cost, optimization difficulty, optimization success probability, etc. when the preset optimization strategy optimizes the corresponding feature operating parameters. The larger the optimization evaluation coefficient, the better the application effect of the corresponding preset optimization strategy.

[0045] In this embodiment, when the difference similarity is larger and the optimization evaluation coefficient is larger, the comprehensive optimization evaluation coefficient of the corresponding preset optimization strategy is larger, and vice versa.

[0046] In this embodiment, the preset optimization strategy reference library is constructed according to the historical optimization logs, and the real-time energy consumption difference is obtained by subtracting the corresponding standard energy consumption from the real-time energy consumption.

[0047] In this embodiment, the matching similarity is calculated based on the difference similarity between the reference energy consumption difference and the real-time energy consumption difference of the corresponding feature operation parameters, the demand similarity between the reference application requirements and the preset application requirements, and the environment similarity between the reference environment parameters and the real-time environment parameters. When the difference similarity, the demand similarity, and the environment similarity are larger, the corresponding matching similarity is larger; otherwise, it is smaller.

[0048] In this embodiment, by calculating the comprehensive optimization evaluation coefficient of each preset optimization strategy, the optimization strategy for each real-time feature operation parameter to be optimized is selected, so that the application effect of the optimization strategy is the best, and the energy-saving control optimization effect of each real-time feature operation parameter to be optimized is improved.

[0049] In some embodiments of the present application, issuing an energy-saving control instruction includes: Generating a number of energy-saving control instructions according to the optimization strategy of the real-time feature operation parameter to be optimized; Judging whether there is a conflict between the number of energy-saving control instructions. If there is a conflict, set the issuing order of the corresponding energy-saving control instructions according to the weight coefficient of the corresponding real-time feature operation parameter. If there is no conflict, directly issue the energy-saving control instructions.

[0050] In this embodiment, the conflict of the energy-saving control instruction means that there is a conflict in the control target, timing, or control strategy of the energy-saving control instruction. If there is a conflict, set the weight coefficient according to the comprehensive correlation degree of the real-time feature operation parameter with the conflict. The greater the comprehensive correlation degree, the greater the weight coefficient; otherwise, it is smaller.

[0051] In this embodiment, by screening out the real-time feature operation parameters to be optimized and setting the corresponding optimization strategies, a number of energy-saving control instructions are generated and conflict analysis is performed, so as to ensure the issuing efficiency and application effect of the energy-saving control instructions, and improve the energy-saving control optimization efficiency of the display screen.

[0052] The above are only the preferred embodiments of the present application. It should be noted that for those of ordinary skill in the art, without departing from the technical principle of the present application, several improvements and replacements can be made, and these improvements and replacements should also be regarded as the protection scope of the present application.

Claims

1. An energy-saving control optimization system for a display screen, characterized in that, Including: An analysis module, configured to divide a display screen into a plurality of monitoring areas, collect historical operation parameters of the plurality of monitoring areas, perform correlation analysis, and determine characteristic operation parameters according to the correlation analysis results; A calculation module, configured to obtain real-time characteristic operation parameters of the plurality of monitoring areas, perform clustering analysis to obtain a plurality of real-time characteristic operation parameter sequences, and calculate an energy consumption loss evaluation value for each real-time characteristic operation parameter sequence based on a preset application requirement and real-time environment parameters; An optimization module, configured to determine whether to optimize the corresponding real-time characteristic operation parameters according to the energy consumption loss evaluation value, and if so, generate an optimization strategy and issue an energy-saving control instruction.

2. The energy-saving control optimization system for a display screen according to claim 1, wherein Determining characteristic operation parameters according to the correlation analysis results includes: Presetting an energy-saving evaluation index and other evaluation indexes of the display screen; Calculating the influence degree of other evaluation indexes on the energy-saving evaluation index; Setting the energy-saving evaluation index as the target evaluation index, setting other evaluation indexes with an influence degree greater than a preset influence degree threshold as secondary evaluation indexes, and setting a weight coefficient for each secondary evaluation index; Obtaining historical monitoring logs of each monitoring area, and generating historical evaluation values of the target evaluation index and a plurality of secondary evaluation indexes; Extracting historical operation parameters from each historical monitoring log, constructing a time reference line based on the historical monitoring duration of the historical monitoring log, and setting collection time nodes according to a preset time interval; Collecting historical operation parameters and corresponding historical evaluation values according to the collection time nodes and mapping them to the corresponding time reference lines to obtain a parameter-evaluation value change curve graph; Analyzing each parameter-evaluation value change curve graph, and obtaining the target correlation degree and a plurality of secondary correlation degrees between the corresponding historical operation parameters in each historical monitoring log and the target evaluation index and a plurality of secondary evaluation indexes according to the analysis results; Setting an evaluation index with a correlation degree greater than a preset correlation degree threshold as the correlation evaluation index of the corresponding historical operation parameter; Generating a comprehensive correlation degree of the corresponding historical operation parameter according to the target correlation degree and a plurality of secondary correlation degrees of the same historical operation parameter in different historical monitoring logs; Setting historical operation parameters with a comprehensive correlation degree greater than a comprehensive correlation degree threshold as characteristic operation parameters.

3. The energy-saving control optimization system for a display screen according to claim 2, characterized in that Generating a comprehensive correlation degree of the corresponding historical operation parameter according to the target correlation degree and a plurality of secondary correlation degrees of the same historical operation parameter in different historical monitoring logs, including: Comparing a plurality of target correlation degrees of the same historical operation parameter in different historical monitoring logs and a plurality of secondary correlation degrees of a plurality of secondary evaluation indexes to obtain a first quantity with a target correlation degree greater than a preset first correlation degree threshold, a plurality of target correlation degree differences, a second quantity with a secondary correlation degree greater than a preset second correlation degree threshold, and corresponding plurality of secondary correlation degree differences; Generating a credibility of the target evaluation index according to the first quantity, and generating a credibility of the corresponding secondary evaluation index according to the second quantity; Generating a comprehensive correlation degree of the corresponding historical operation parameter according to the first quantity, a plurality of target correlation degree differences, the second quantity, a plurality of secondary correlation degree differences, and corresponding weight coefficients; The calculation formula of the comprehensive correlation degree is: ； Among them, G is the comprehensive correlation degree, a1 is the first weight coefficient, k1 is the credibility of the target evaluation index, and n1 is the first quantity. is the difference in the target correlation degree of the i1-th one, and a2 is the second weight coefficient. is the credibility of the j-th secondary evaluation index. is the difference in the i2-th secondary correlation degree of the j-th secondary evaluation index, n2j is the second quantity of the j-th secondary evaluation index, and m is the number of secondary evaluation indexes. is the weight coefficient of the j-th secondary evaluation index.

4. The display screen energy-saving control optimization system according to claim 3, wherein, Calculate the energy consumption loss evaluation value of each real-time feature operation parameter sequence based on preset application requirements and real-time environment parameters, including: Obtain the real-time feature operation parameters of each monitoring area, perform data cleaning and standardization processing on the real-time feature operation parameters to obtain the processed real-time feature operation parameters; Perform clustering analysis on the processed real-time feature operation parameters of different monitoring areas to obtain several real-time feature operation parameter sequences; Perform energy consumption conversion on each real-time feature operation parameter in the same real-time feature operation parameter sequence to obtain the corresponding energy consumption sequence, and the energy consumption sequence includes several real-time energy consumptions; Generate the standard parameter threshold of each feature operation parameter based on preset application requirements and real-time environment parameters, and perform energy consumption conversion to obtain the corresponding standard energy consumption; Divide the energy consumption sequence of the corresponding real-time feature operation parameter sequence according to the standard energy consumption to obtain the first energy consumption set, the second energy consumption set and the third energy consumption set of the corresponding real-time feature operation parameter sequence; Calculate the energy consumption loss evaluation value of the corresponding real-time feature operation parameter sequence according to the first energy consumption set, the second energy consumption set and the third energy consumption set.

5. The energy-saving control optimization system for a display screen according to claim 4, characterized in that, Obtain the first energy consumption set, the second energy consumption set and the third energy consumption set of the corresponding real-time feature operation parameter sequence, including: Compare the standard energy consumption with several real-time energy consumptions in the energy consumption sequence of the corresponding real-time feature operation parameter sequence. If the real-time energy consumption is less than the standard energy consumption, divide the real-time energy consumption into the low energy consumption set; If the real-time energy consumption is equal to the standard energy consumption, divide the real-time energy consumption into the medium energy consumption set; If the real-time energy consumption is greater than the standard energy consumption, divide the real-time energy consumption into the high energy consumption set; Calculate the mean and standard deviation of the low energy consumption set, the medium energy consumption set and the high energy consumption set respectively; Set the first critical interval, the second critical interval and the third critical interval according to the mean and standard deviation; Extract the real-time energy consumptions in the first critical interval in the low energy consumption set and construct the first energy consumption set; Extract the real-time energy consumptions in the second critical interval in the medium energy consumption set and construct the second energy consumption interval; Extract the real-time energy consumptions in the third critical interval in the high energy consumption set and construct the third energy consumption interval.

6. The display screen energy-saving control optimization system according to claim 5, characterized in that, Calculate the energy consumption loss evaluation value of the corresponding real-time feature operation parameter sequence according to the first energy consumption set, the second energy consumption set and the third energy consumption set, including: Calculate the first set quantity, the second set quantity and the third set quantity of the first energy consumption set, the second energy consumption set and the third energy consumption set; Set the selection coefficient according to the set quantity relationship of the first set quantity, the second set quantity and the third set quantity; The calculation formula of the energy consumption loss evaluation value is: ； Among them, H is the evaluation value of energy consumption loss, is the selection coefficient, h1 is the first energy consumption loss conversion coefficient, h2 is the second energy consumption loss conversion coefficient, b1 is the weight coefficient of the first energy consumption set, b2 is the weight coefficient of the third energy consumption set, z1 is the number of the first set, z2 is the number of the third set, is the s1-th real-time energy consumption in the first energy consumption set, q0 is the corresponding standard energy consumption, is the s2-th real-time energy consumption in the third energy consumption set.

7. The display screen energy-saving control optimization system according to claim 6, wherein, Set the selection coefficient according to the set quantity relationship of the first set quantity, the second set quantity and the third set quantity, including: Preset the first preset selection coefficient interval, the second preset selection coefficient interval and the third preset selection coefficient interval; When the first set quantity is greater than the second set quantity and the first set quantity is greater than the third set quantity, set the selection coefficient to be in the first preset selection coefficient interval; When the quantity of the second set is greater than that of the first set and greater than that of the third set, set the selection coefficient to be within the second preset selection coefficient range; When the quantity of the third set is greater than that of the second set and greater than that of the first set, set the selection coefficient to be within the third preset selection coefficient range.

8. The energy-saving control optimization system for a display screen according to claim 7, characterized in that, Judge whether to optimize the corresponding real-time characteristic operating parameters according to the energy consumption loss evaluation value, including: Preset a threshold value of the preset energy consumption loss evaluation value in advance; When the energy consumption loss evaluation value is less than the threshold value of the preset energy consumption loss evaluation value, judge not to optimize the corresponding real-time characteristic operating parameters; When the energy consumption loss evaluation value is greater than the threshold value of the preset energy consumption loss evaluation value, judge to optimize the corresponding real-time characteristic operating parameters.

9. The energy-saving control optimization system for a display screen according to claim 8, wherein Generate an optimization strategy, including: Obtain a number of real-time energy consumption differences according to a number of real-time energy consumptions in the third energy consumption set corresponding to the real-time characteristic operating parameters to be optimized and the corresponding standard energy consumption; Based on the number of real-time energy consumption differences, the preset application requirements, and the real-time environmental parameters as matching conditions, screen out a number of preset optimization strategies from the preset optimization strategy reference library whose matching similarity is greater than the preset similarity threshold; Map the real-time energy consumption differences to the corresponding preset optimization strategies to obtain an energy consumption difference - optimization strategy mapping table for the real-time characteristic operating parameters to be optimized; Obtain the optimization evaluation coefficient of each preset optimization strategy in the energy consumption difference - optimization strategy mapping table, and calculate the comprehensive optimization evaluation coefficient of the corresponding preset optimization strategy in combination with the difference similarity; Set the preset optimization strategy with the largest comprehensive optimization evaluation coefficient as the optimization strategy for the corresponding real-time characteristic operating parameters to be optimized.

10. The display screen energy-saving control optimization system according to claim 9, characterized in that, Issue an energy-saving control instruction, including: Generate a number of energy-saving control instructions according to the optimization strategy of the real-time characteristic operating parameters to be optimized; Judge whether there is a conflict between the number of energy-saving control instructions. If there is, set the issuing order of the corresponding energy-saving control instructions according to the weight coefficient of the corresponding real-time characteristic operating parameters. If not, directly issue the energy-saving control instructions.

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