A LED display screen operation state analysis system based on multi-source data fusion

Abstract

The application discloses a LED display screen operation state analysis system based on multi-source data fusion, and relates to the technical field of display screen supervision.The multi-parameter acquisition module is arranged to periodically acquire the monitoring values of a plurality of monitoring parameters in the operation process of the target LED display screen, and the fusion analysis module is arranged to periodically perform a screening step on the operation state of the target LED display screen, effectively screen the latest acquired monitoring value of all the monitoring parameters, and re-acquire the monitoring value again at the moment when the next analysis step is performed for the invalid monitoring parameters after the screening, so that the acquired monitoring value is used as the analysis data of the next analysis step.The application solves the problem of the low data reliability in the prior art because the data for state analysis is not effectively checked, effectively removes the invalid data, retains the effective data to form the standard effective analysis data, avoids the interference of the invalid data on the analysis step result, and guarantees the reliability of the analysis step execution result.

Description

Technical Field

[0001] This invention relates to the field of display screen monitoring technology, specifically to an LED display screen operation status analysis system based on multi-source data fusion. Background Technology

[0002] Currently, in the field of LED display operation status monitoring, it is usually necessary to detect and analyze the operating parameters of the screen to determine whether the LED display is working properly. These operating parameters are selected by management personnel according to monitoring needs and mainly include: low-frequency parameters such as average screen brightness, average color temperature, average operating voltage, average operating current, total screen power consumption, average screen temperature, cumulative operating time, dead pixel rate, total number of fault points, brightness attenuation rate, and overall color shift; mid-frequency parameters such as screen voltage fluctuation amplitude, current fluctuation amplitude, brightness uniformity, overall contrast ratio, actual refresh rate, signal packet loss rate, bit error rate, and screen temperature difference; and high-frequency parameters such as instantaneous total current, instantaneous total voltage, voltage overshoot, maximum voltage drop, power supply ripple amplitude, and instantaneous total power consumption. Due to their own structure and working characteristics, LED displays exhibit significant differences in the fault variation patterns of different types of operating parameters: low-frequency parameters tend to change slowly or remain stable over a long period, mid-frequency parameters reflect the overall stability of the screen, while high-frequency parameters change rapidly and are highly random, requiring different acquisition cycles to capture them accurately. In existing technologies, operating parameters are typically collected separately according to their own independent monitoring cycles. When analyzing the operating status of an LED display screen, the monitoring values ​​collected separately according to their independent cycles are directly used. Such data has not undergone validity verification and screening, and it is impossible to determine whether it is reliable and valid. If invalid data is directly used for status assessment, the overall data reliability cannot be guaranteed, making it difficult to form a comprehensive analysis basis that truly reflects the overall operating status of the LED display screen. This can easily lead to problems such as chaotic status judgment, delayed fault location, and insufficient reliability of comprehensive analysis results. In order to solve the above problems, this invention proposes a solution. Summary of the Invention

[0003] The purpose of this invention is to provide an LED display screen operation status analysis system based on multi-source data fusion, in order to solve the problems mentioned in the background art.

[0004] This invention provides an LED display screen operation status analysis system based on multi-source data fusion, comprising: The multi-parameter acquisition module is used to periodically collect the monitoring values ​​of several monitoring parameters during the operation of the target LED display screen and transmit them to the fusion analysis module. The monitoring parameters include three types: low-frequency parameters, medium-frequency parameters and high-frequency parameters. The fusion analysis module is used to store the monitoring value after receiving the monitoring value of any monitoring parameter each time. The fusion analysis module updates and stores the analysis time and the screening time. The fusion analysis module is also used to extract the monitoring value closest to the screening time from the monitoring values ​​stored in its internal storage for each monitoring parameter after the current time reaches the screening time, and to perform a screening step on all the extracted monitoring values ​​to obtain the effective analysis data and invalid parameter set for the target LED display to perform the next analysis step and temporarily store them. The effective analysis data contains several monitoring parameters and their monitoring values, and the invalid parameter set contains several monitoring parameters. The fusion analysis module is also used to perform an analysis step on the operating status of the target LED display screen after the current time is the analysis time. During the execution, the analysis data of the analysis step is generated based on the temporarily stored valid analysis data and invalid parameter set. The comprehensive status score of the target LED display screen in performing the analysis step is calculated based on the monitoring values ​​of all monitoring parameters contained in the analysis data. The execution result of the target LED display screen in performing the analysis step is obtained based on the comprehensive status score.

[0005] Furthermore, the specific content collected and transmitted to the fusion analysis module is as follows: For any monitoring parameter, the multi-parameter acquisition module collects the monitoring value of the monitoring parameter once every preset monitoring period corresponding to the monitoring parameter and transmits it to the fusion analysis module in real time.

[0006] Furthermore, the specific details of performing any screening step are as follows: S11: Label all monitoring parameters of the target LED display screen as A1, A2, ..., Aa, where a is the total number of monitoring parameters selected by the management personnel; S12: Using the formula The effective time factor B1 of the monitoring parameter A1 based on the analysis time is calculated and obtained, where Tnow is the analysis time, Tlast is the acquisition time of the monitoring value of the extracted monitoring parameter A1, and Tbase is the preset effective duration of the monitoring parameter A1. S13: Utilize the formula The effective factor B2 of the working condition based on the analysis time is calculated to obtain the monitoring parameter A1, where C1, C2 and C3 are the temperature coefficient, current coefficient and aging coefficient, respectively. S14: Utilize the formula The historical effective factor of monitoring parameter A1 based on the analysis time is calculated. In the formula, D1 is the average value of all monitoring values ​​of monitoring parameter A1 collected within the time period of backtracking from the analysis time to the preset P1 time period, D2 is the standard deviation of all monitoring values ​​of monitoring parameter A1 collected within the time period, and λ is the preset sensitivity coefficient, λ∈(0,1]. S15: Using the formula Calculate the confidence factor B4 of the monitoring parameter A1 based on the analysis time. In the formula, E1 is the monitoring value of the extracted monitoring parameter A1, that is, the monitoring value of the monitoring parameter A1 from the monitoring values ​​stored in its internal storage after the current time reaches the screening time. S16: Calculate the comprehensive effectiveness F1 of monitoring parameter A1 based on the analysis time using the formula F1=β1×B1+β2×B2+β3×B3+β4×B4, where β1, β2, β3, and β4 are the preset first, second, third, and fourth proportion weights, respectively, and β1+β2+β3+β4=1. S17: Compare F1 and P1. Based on the comparison result, determine whether the monitoring parameter A1 is valid when the target LED display screen performs the next analysis step. If F1 ≥ P1, it is determined that the monitoring parameter A1 is valid when the target LED display screen performs the next analysis step; otherwise, it is determined that the monitoring parameter A1 is invalid when the target LED display screen performs the next analysis step. P1 is the preset validity threshold of the monitoring parameter A1. S18: Following S11 to S17, determine in sequence whether the monitoring parameters A2, A3, ..., Aa are valid when the target LED display screen performs the next analysis step. Based on the determination results, obtain all the monitoring parameters that are determined to be valid and their corresponding extracted monitoring values, and generate valid analysis data for the target LED display screen to perform the next analysis step. Obtain all the monitoring parameters that are determined to be invalid and generate an invalid parameter set for the target LED display screen to perform the next analysis step.

[0007] Furthermore, in S13, the formula for calculating the temperature coefficient C1 is as follows: T1 is the average temperature of the entire target LED display screen, T2 is the maximum allowable operating temperature of the target LED display screen, T3 is the rated minimum operating temperature of the target LED display screen, T4 is the temperature difference of the entire target LED display screen, and T5 is the preset maximum temperature difference of the target LED display screen; α1 and α2 are the preset first and second temperature weights, respectively.

[0008] Furthermore, the formula for calculating the current coefficient C2 in S13 is as follows: I1 is the amplitude of the full-screen current fluctuation of the target LED display screen, I2 is the preset maximum current fluctuation amplitude; I3 is the average working current of the full screen of the target LED display screen, I4 is the rated working current of the target LED display screen; α3 and α4 are the preset first and second current weights in sequence.

[0009] Further, in S13, the calculation formula of the aging coefficient C3 is , T6 is the cumulative running time of the full screen of the target LED display screen, T7 is the rated service life of the target LED display screen, L1 is the brightness attenuation rate of the full screen of the target LED display screen, L2 is the dead pixel rate of the full screen of the target LED display screen; α5, α6, and α7 are the preset first, second, and third aging weights in sequence.

[0010] Further, the specific content of performing any analysis step is as follows: According to each monitoring parameter included in the invalid parameter set for the next analysis step of the target LED display screen temporarily stored, collect its monitoring value at the current moment, and the current moment refers to the starting moment of performing the analysis step; Extract each monitoring parameter and its monitoring value included from the effective analysis data for the next analysis step of the target LED display screen temporarily stored; Generate analysis data for the analysis step according to the monitoring values of all the extracted monitoring parameters and the monitoring values of all the monitoring parameters at the current moment; Calculate and obtain the comprehensive status score S of the target LED display screen for performing the analysis step, and the calculation formula is , where Gi in the formula represents the monitoring value of each monitoring parameter in the analysis data, Hi represents the preset normal value of the corresponding monitoring parameter, and ηi represents the preset scoring weight of the corresponding monitoring parameter in the analysis data, = 1; Compare the sizes of S, P2, and P3. If S ≤ P2, it is determined that the execution result of this analysis step is that the target LED display screen is operating normally. If P2 < S < P3, it is determined that the execution result of this analysis step is that the target display screen is operating abnormally, and an abnormal warning is sent to the management personnel, and the management personnel increase the monitoring frequency. If S ≥ P3, it is determined that the execution result of this analysis step is that the target LED display screen has a running fault, and a fault warning is sent to the management personnel, and the management personnel locate the cause of the fault, where P2 and P3 are the preset first and second state determination thresholds in sequence.

[0011] Further, after the fusion analysis module finishes executing each analysis step and screening step, it recalculates the new analysis moment and screening moment correspondingly, and updates and stores the new analysis moment and screening moment into the fusion analysis module.

[0012] Compared with existing technologies, it has the following advantages: This invention solves the problems of low data reliability and lack of validity verification in existing technologies by setting up a multi-parameter acquisition module to periodically collect monitoring values ​​of several monitoring parameters during the operation of a target LED display screen, and setting up a fusion analysis module to periodically perform a screening step on the operating status of the target LED display screen. During the screening step, the most recently collected monitoring values ​​of all monitoring parameters are screened for validity, and the monitoring values ​​of the screened valid monitoring parameters are used as the analysis data for the next analysis step. For the screened invalid monitoring parameters, they are collected again at the time of the next analysis step, and the collected monitoring values ​​are used as the analysis data for the next analysis step. In this way, it solves the problems of low data reliability and lack of validity verification of status analysis data in existing technologies. By eliminating invalid data and retaining valid data to form standardized valid analysis data, it avoids invalid data from interfering with the analysis results, ensures the reliability of the analysis results, and fundamentally solves the problems of confused status judgment, delayed fault location, and insufficient reliability of comprehensive analysis results. This invention integrates monitoring parameters of different acquisition cycles and types at the same analysis node by real-time supplementation of invalid parameter sets and integration of effective analysis data, forming a complete analysis data system. By setting differentiated scoring weights to calculate a comprehensive status score, it achieves a multi-dimensional comprehensive judgment of the operating status of LED displays, solving the problem that data from different acquisition cycles cannot be integrated and cannot reflect the overall operating status. It can comprehensively and accurately characterize the actual operating status of the display screen and avoid the situation of chaotic status judgment. Attached Figure Description

[0013] Figure 1 This is a system block diagram of the present invention. Detailed Implementation

[0014] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0015] Please see Figure 1 This application provides an LED display screen operation status analysis system based on multi-source data fusion, including a multi-parameter acquisition module and a fusion analysis module; The multi-parameter acquisition module is used to periodically collect the monitoring values ​​of several monitoring parameters during the operation of the target LED display screen and transmit them to the fusion analysis module. Specifically, for any monitoring parameter, the multi-parameter acquisition module collects the monitoring value of the monitoring parameter once every monitoring cycle corresponding to the monitoring parameter and transmits it to the fusion analysis module in real time. The multi-parameter acquisition module pre-stores monitoring cycles corresponding to several monitoring parameters. It should be noted that the monitoring cycle of any monitoring parameter is preset by the administrator according to the type of the monitoring parameter and the fault characteristics; therefore, the monitoring cycle of any monitoring parameter is not exactly the same. The monitoring parameters include three types: low-frequency parameters, medium-frequency parameters, and high-frequency parameters. Each type of monitoring parameter is selected by the management personnel according to its fault characteristics. Among them, low-frequency parameters include, but are not limited to, the average brightness of the whole screen, the average color temperature of the whole screen, the average operating voltage of the whole screen, the average operating current of the whole screen, the total power consumption of the whole screen, the average temperature of the whole screen, the cumulative running time of the whole screen, the dead pixel rate of the whole screen, the total number of fault points, the brightness decay rate of the whole screen, and the overall color shift of the whole screen. It should be noted that the average brightness of the entire screen refers to the average luminous flux emitted per unit area of ​​the LED display under normal display conditions. It is a conventional parameter characterizing the brightness level of an LED display, and the unit is usually cd / m² (nits). The average color temperature of the entire screen refers to the average temperature of the LED display's emission spectrum equivalent to blackbody radiation when displaying a white image. It reflects the overall color temperature characteristics of the display, whether it is cool or warm. The unit is K (Kelvin). The average operating voltage of the entire screen refers to the arithmetic mean of the power supply voltage of the LED display's driving system during stable operation. It reflects the normal operating level of the overall power supply voltage of the display. The average operating current of the entire screen refers to the arithmetic mean of the total input current of the LED display screen under normal lighting and stable display conditions, which is used to characterize the overall load level of the display screen; the total power consumption of the entire screen refers to the total electrical energy consumed by the LED display screen per unit time, which is calculated by combining the operating voltage and operating current, and is a publicly available parameter characterizing the energy consumption of the LED display screen; the average temperature of the entire screen refers to the arithmetic mean of the temperatures of key areas such as the LED display screen body, driver board, and power supply, which reflects the overall thermal operating status of the display screen. The total operating time of the entire screen refers to the total continuous working time of the LED display screen from its first power-on to the present moment. It is a conventional statistical parameter that characterizes the operating time and aging degree of the equipment. The total dead pixel rate of the entire screen refers to the proportion of LED beads and pixels that are faulty, not lit, constantly lit, or have abnormal colors in the LED display screen to the total number of pixels. It is a conventional evaluation indicator of the quality and degree of failure of the LED screen.

[0016] The overall brightness decay rate refers to the percentage decrease in the current actual average brightness of an LED display screen relative to its initial nominal brightness, reflecting the degree of light decay of LED chips after long-term use; the overall color deviation of the LED display screen refers to the overall deviation of the color coordinates of the actual displayed colors of the LED display screen relative to the standard target color coordinates, which is a publicly available parameter characterizing the overall color accuracy of the display screen. Intermediate frequency parameters include, but are not limited to, the amplitude of voltage fluctuation of the entire screen, the amplitude of current fluctuation of the entire screen, the uniformity of brightness of the entire screen, the overall contrast ratio of the entire screen, the actual refresh rate of the entire screen, the packet loss rate of the entire screen, the bit error rate, and the temperature difference of the entire screen. It should be noted that the overall screen voltage fluctuation amplitude refers to the difference between the maximum and minimum values ​​of the LED display screen's operating voltage within a certain period, reflecting the stability of the power supply voltage; the overall screen current fluctuation amplitude refers to the difference between the maximum and minimum values ​​of the LED display screen's operating current within a certain period, used to characterize the stability of the drive current. Brightness uniformity refers to the consistency of brightness in different areas of an LED display screen. It is usually evaluated by the degree of deviation between the brightness of each area and the average brightness. It is a publicly available and universally accepted indicator in the LED display field. Overall contrast ratio refers to the ratio of the brightness of the brightest area to the brightness of the darkest area of ​​the LED display screen. It is a conventional parameter that characterizes the sense of layering and clarity of the displayed image. The actual refresh rate of the entire screen refers to the actual number of times the LED display screen refreshes the entire image per second, reflecting the smoothness of the image display and the stability of the drive control; the signal packet loss rate of the entire screen refers to the proportion of lost or erroneous data frames in the video data or control data transmitted to the LED display screen, which is a common evaluation parameter for signal transmission stability; the temperature difference of the entire screen refers to the difference between the highest temperature area and the lowest temperature area of ​​the LED display screen when it is working, reflecting the uniformity of the screen temperature distribution and the heat dissipation status. High-frequency parameters include, but are not limited to, total instantaneous current of the entire screen, total instantaneous voltage of the entire screen, voltage overshoot of the entire screen, maximum voltage drop of the entire screen, overall amplitude of power ripple of the entire screen, and total instantaneous power consumption of the entire screen. It should be noted that the instantaneous total current of the entire screen refers to the real-time total input current of the LED display at a certain sampling moment, which represents the instantaneous load of the display; the instantaneous total voltage of the entire screen refers to the real-time supply voltage of the LED display at a certain sampling moment, which reflects the instantaneous power supply status; the maximum voltage overshoot of the entire screen refers to the maximum peak value of the instantaneous voltage exceeding the rated voltage when the LED display is powered on, switched, or the load changes, which is a conventional electrical indicator of power supply stability. The maximum voltage drop of the entire screen refers to the maximum valley value of the instantaneous voltage below the rated operating voltage during the operation of the LED display screen, which is used to evaluate the power supply system's anti-disturbance capability; the overall amplitude of the power supply ripple of the entire screen refers to the maximum amplitude of the AC noise component superimposed in the DC power supply of the LED display screen, which is a publicly available electrical parameter characterizing the purity of the power supply output; the total instantaneous power consumption of the entire screen refers to the real-time power consumption of the LED display screen at a certain sampling moment, which is calculated in real time from the instantaneous voltage and instantaneous current, reflecting the instantaneous energy consumption level; The fusion analysis module is used to store the monitoring value after receiving the monitoring value of any monitoring parameter each time. The fusion analysis module updates and stores the analysis time and the screening time. The fusion analysis module is also used to perform an analysis step on the operating status of the target LED display screen after the current time is the analysis time, and recalculate the new analysis time after the analysis step is completed, and update and store the new analysis time into the fusion analysis module. The new analysis time satisfies the following calculation formula: new analysis time = analysis time + preset analysis interval duration. The specific details of performing any one of the analysis steps are as follows: For each monitoring parameter included in the invalid parameter set of the target LED display screen in the temporary storage, collect its monitoring value at the current moment, where the current moment refers to the start time of the next analysis step. Extract each monitoring parameter and its monitoring value from the valid analysis data of the target LED display screen in the temporary storage for the next analysis step; Based on the monitoring values ​​of all the monitoring parameters extracted above and the monitoring values ​​of all the monitoring parameters collected at the current moment, analysis data is generated for the next analysis step. Calculate the overall state score S of the target LED display screen after performing the analysis steps, using the following formula: In the formula, Gi represents the monitored value of each monitoring parameter in the analyzed data, Hi represents the preset normal value of the corresponding monitoring parameter, and ηi represents the preset scoring weight of the corresponding monitoring parameter in the analyzed data, which is set by the management personnel according to the importance of the corresponding monitoring parameter relative to the operation of the target LED display screen. =1. It should be noted that all variables in the above formula are normalized values, and n is the total number of all monitoring values ​​contained in the analysis data. Compare the magnitudes of S, P2, and P3. If S ≤ P2, it is determined that the execution result of this analysis step is that the target LED display operates normally. If P2 < S < P3, it is determined that the execution result of this analysis step is that the target display operates abnormally, and an abnormal warning is sent to the management personnel, who will increase the monitoring frequency. If S ≥ P3, it is determined that the execution result of this analysis step is that the target LED display has a malfunction, and a malfunction warning is sent to the management personnel, who will locate the cause of the malfunction. Here, P2 and P3 are the first and second preset state determination thresholds, respectively. The fusion analysis module is also used to, after the current time reaches the screening time, extract, from the monitoring values stored internally, the one monitoring value with the closest acquisition time to the screening time for each monitoring parameter, and perform a screening step on all the extracted monitoring values to obtain valid analysis data and an invalid parameter set for the target LED display to perform the next analysis step and temporarily store them. The valid analysis data contains several monitoring parameters and their monitoring values, and the invalid parameter set contains several monitoring parameters. After the screening step is completed, recalculate a new screening time and update and store the new screening time in the fusion analysis module. Here, the new screening time satisfies the following calculation formula: new screening time = the screening time + the preset screening interval duration. In this application, the screening interval duration is less than the analysis interval duration, and the screening time is always farther from the current time than the analysis time is from the current time. The execution content of any screening step is as follows: S11: Mark all the monitoring parameters of the target LED display as A1, A2,..., Aa, where a is the total number of monitoring parameters selected by the management personnel. It should be noted here that the total screen cumulative operation time is not involved in the marking. S12: Use the formula , calculate and obtain the time effective factor B1 of the monitoring parameter A1 based on the analysis time. It should be noted here that the time effective factor is defined artificially and is used to characterize the degree of timeliness attenuation of the historical acquisition data of the monitoring parameter over time. In the formula, Tnow is the analysis time, Tlast is the acquisition time of the monitoring value of the monitoring parameter A1 extracted, and Tbase is the preset reference effective duration of the monitoring parameter A1. It should be noted that all variables in the above formula are normalized values. S13: Use the formula The effective factor of the operating condition B2 based on the analysis time is calculated to obtain the monitoring parameter A1. It should be noted that the effective factor of the operating condition is artificially defined and is used to characterize the degree of change in data reliability caused by operating condition factors such as temperature change, current fluctuation, and lamp bead aging during the real-time operation of the target LED display screen. In the formula, C1, C2 and C3 are the temperature coefficient, current coefficient and aging coefficient, respectively. The formula for calculating C1 is as follows: T1 is the average temperature of the entire target LED display screen, calculated by normalizing the extracted monitoring values; T2 is the maximum allowable operating temperature of the target LED display screen; T3 is the rated minimum operating temperature of the target LED display screen; T4 is the temperature difference of the entire target LED display screen, calculated by normalizing the extracted monitoring values; T5 is the preset maximum temperature difference of the target LED display screen; α1 and α2 are the preset first and second temperature weights, respectively, α1+α2=1. It should be noted that all variables in the above formula are normalized values. The formula for calculating C2 is: I1 is the total current fluctuation range of the target LED display screen, calculated by normalizing the corresponding extracted monitoring values; I2 is the preset maximum current fluctuation range; I3 is the average operating current of the target LED display screen, calculated by normalizing the corresponding extracted monitoring values; I4 is the rated operating current of the target LED display screen; α3 and α4 are the preset first and second current weights, respectively, α3+α4=1. It should be noted that all variables in the above formula are normalized values. The formula for calculating C3 is as follows: T6 is the total cumulative operating time of the target LED display screen, calculated by normalizing the extracted monitoring values; T7 is the rated service life of the target LED display screen; L1 is the brightness decay rate of the target LED display screen, calculated by normalizing the extracted monitoring values; L2 is the dead pixel rate of the target LED display screen; α5, α6, and α7 are the preset first, second, and third aging weights, respectively, and α5+α6+α7=1. It should be noted that all variables in the above formula are normalized values. S14: Utilize the formula The historical effective factor of monitoring parameter A1 is calculated based on the analysis time. It should be noted that the historical effective factor is determined by humans and is used to characterize the stability of the monitoring parameter during the historical operation of the target LED display screen. In the formula, D1 is the average value of all monitoring values ​​of monitoring parameter A1 collected within the time period P1, which is the starting point of the analysis time. D2 is the standard deviation of all monitoring values ​​of monitoring parameter A1 collected within the time period. λ is the preset sensitivity coefficient, λ∈(0,1]. It should be noted that for monitoring parameters of type high frequency, λ takes a large value when calculating the historical effective factor. For monitoring parameters of type low frequency, λ takes a small value when calculating the historical effective factor. For monitoring parameters of type medium frequency, λ takes an intermediate value, between the large and small values. It should be noted that all variables in the above formula are normalized values. S15: Using the formula The confidence factor B4 of the monitoring parameter A1 based on the analysis time is calculated. It should be noted that the confidence factor is defined by humans and is used to characterize the degree of deviation between the corresponding monitoring value of the monitoring parameter and the historical monitoring value, and to determine whether it is an abnormal outlier such as a sudden change, spike, overshoot, or drop. In the formula, E1 is the monitoring value of the monitoring parameter A1 extracted, that is, the monitoring value of the monitoring parameter A1 after the current time reaches the screening time, from the monitoring values ​​stored in its internal storage. It should be noted that all variables in the above formula are normalized values. S16: The comprehensive effectiveness F1 of monitoring parameter A1 based on the analysis time is calculated using the formula F1=β1×B1+β2×B2+β3×B3+β4×B4. It should be noted that comprehensive effectiveness is a manually defined term used to characterize the effectiveness of the monitoring values ​​of monitoring parameter A1 collected at the analysis time relative to the analysis steps to be performed. Here, β1, β2, β3, and β4 are preset weights for the first, second, third, and fourth percentages, respectively, and β1+β2+β3+β4=1. In this application, the values ​​of β1+β2+β3+β4 are set based on the differences in the types of monitoring parameters. In one embodiment of the present invention, the monitoring parameters of type low frequency are β1=0.1, β2=0.3, β3=0.4, β4=0.2, and the selection of values ​​focuses on operating conditions and historical stability; the monitoring parameters of type medium frequency are β1=0.2, β2=0.3, β3=0.2, β4=0.3, and the selection of values ​​focuses on balancing various effective factors; the monitoring parameters of type high frequency are β1=0.5, β2=0.2, β3=0.1, β4=0.2, and the selection of values ​​focuses on time effectiveness. It should be noted that all variables in the above formulas are normalized values. S17: Compare F1 and P1. Based on the comparison result, determine whether the monitoring parameter A1 is valid when the target LED display screen performs the next analysis step. If F1 ≥ P1, it is determined that the monitoring parameter A1 is valid when the target LED display screen performs the next analysis step; otherwise, it is determined that the monitoring parameter A1 is invalid when the target LED display screen performs the next analysis step. P1 is the preset validity threshold of the monitoring parameter A1. S18: Determine whether the monitoring parameters A2, A3, ..., Aa are valid when the target LED display screen performs the next analysis step in sequence according to S11 to S17. Based on the determination results, obtain all the monitoring parameters that are determined to be valid and their corresponding extracted monitoring values, and generate valid analysis data for the target LED display screen to perform the next analysis step. Obtain all the monitoring parameters that are determined to be invalid and generate an invalid parameter set for the target LED display screen to perform the next analysis step. It should be noted that a screening step is performed before each analysis step.

[0017] The data in the above formulas are all numerical calculations with dimensions removed. In addition, the contents not described in detail in this specification are all prior art known to those skilled in the art.

[0018] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A system for analyzing the operating status of an LED display screen based on multi-source data fusion, characterized in that, include: The multi-parameter acquisition module is used to periodically collect the monitoring values ​​of several monitoring parameters during the operation of the target LED display screen and transmit them to the fusion analysis module. The monitoring parameters include three types: low-frequency parameters, medium-frequency parameters and high-frequency parameters. The fusion analysis module is used to store the monitoring value each time it receives the monitoring value of any monitoring parameter. The fusion analysis module updates and stores the analysis time and the screening time. The fusion analysis module is also used to extract the monitoring value closest to the screening time from the monitoring values ​​stored in its internal storage for each monitoring parameter after the current time reaches the screening time, and to perform a screening step on all the extracted monitoring values ​​to obtain the effective analysis data and invalid parameter set for the target LED display to perform the next analysis step and temporarily store them. The effective analysis data contains several monitoring parameters and their monitoring values, and the invalid parameter set contains several monitoring parameters. The fusion analysis module is also used to perform an analysis step on the operating status of the target LED display screen after the current time is the analysis time. During the execution, the analysis data of the analysis step is generated based on the temporarily stored valid analysis data and invalid parameter set. The comprehensive status score of the target LED display screen in performing the analysis step is calculated based on the monitoring values ​​of all monitoring parameters contained in the analysis data. The execution result of the target LED display screen in performing the analysis step is obtained based on the comprehensive status score.

2. The LED display screen operation status analysis system based on multi-source data fusion according to claim 1, characterized in that, The specific content collected and transmitted to the fusion analysis module is as follows: For any monitoring parameter, the multi-parameter acquisition module collects the monitoring value of the monitoring parameter once every preset monitoring period corresponding to the monitoring parameter and transmits it to the fusion analysis module in real time.

3. The LED display screen operation status analysis system based on multi-source data fusion according to claim 1, characterized in that, The specific steps for performing any screening step are as follows: S11: Label all monitoring parameters of the target LED display screen as A1, A2, ..., Aa, where a is the total number of monitoring parameters selected by the management personnel; S12: Using the formula The effective time factor B1 of the monitoring parameter A1 based on the analysis time is calculated and obtained, where Tnow is the analysis time, Tlast is the acquisition time of the monitoring value of the extracted monitoring parameter A1, and Tbase is the preset effective duration of the monitoring parameter A1. S13: Utilize the formula The effective factor B2 of the working condition based on the analysis time is calculated to obtain the monitoring parameter A1, where C1, C2 and C3 are the temperature coefficient, current coefficient and aging coefficient, respectively. S14: Utilize the formula The historical effective factor of monitoring parameter A1 based on the analysis time is calculated. In the formula, D1 is the average value of all monitoring values ​​of monitoring parameter A1 collected within the time period of backtracking from the analysis time to the preset P1 time period, D2 is the standard deviation of all monitoring values ​​of monitoring parameter A1 collected within the time period, and λ is the preset sensitivity coefficient, λ∈(0,1]. S15: Using the formula Calculate the confidence factor B4 of the monitoring parameter A1 based on the analysis time. In the formula, E1 is the monitoring value of the extracted monitoring parameter A1, that is, the monitoring value of the monitoring parameter A1 from the monitoring values ​​stored in its internal storage after the current time reaches the screening time. S16: Calculate the comprehensive effectiveness F1 of monitoring parameter A1 based on the analysis time using the formula F1=β1×B1+β2×B2+β3×B3+β4×B4, where β1, β2, β3, and β4 are the preset first, second, third, and fourth proportion weights, respectively, and β1+β2+β3+β4=1. S17: Compare F1 and P1. Based on the comparison result, determine whether the monitoring parameter A1 is valid when the target LED display screen performs the next analysis step. If F1 ≥ P1, it is determined that the monitoring parameter A1 is valid when the target LED display screen performs the next analysis step; otherwise, it is determined that the monitoring parameter A1 is invalid when the target LED display screen performs the next analysis step. P1 is the preset validity threshold of the monitoring parameter A1. S18: Determine in sequence whether the monitoring parameters A2, A3, ..., Aa are valid when the next analysis step is executed on the target LED display screen according to S11 to S17. Based on the determination results, obtain all the determined valid monitoring parameters and their corresponding extracted monitoring values, and generate valid analysis data for the target LED display screen to execute the next analysis step according to them. Obtain all the determined invalid monitoring parameters and generate an invalid parameter set for the target LED display screen to execute the next analysis step according to them.

4. The LED display screen operation status analysis system based on multi-source data fusion according to claim 3, characterized in that, In S13, the formula for calculating the temperature coefficient C1 is: T1 is the average temperature of the entire target LED display screen, T2 is the maximum allowable operating temperature of the target LED display screen, T3 is the rated minimum operating temperature of the target LED display screen, T4 is the temperature difference of the entire target LED display screen, and T5 is the preset maximum temperature difference of the target LED display screen; α1 and α2 are the preset first and second temperature weights, respectively.

5. The LED display screen operation status analysis system based on multi-source data fusion according to claim 3, characterized in that, The formula for calculating the current coefficient C2 in S13 is as follows: I1 is the current fluctuation range of the target LED display screen, I2 is the preset maximum current fluctuation range; I3 is the average operating current of the target LED display screen, I4 is the rated operating current of the target LED display screen; α3 and α4 are the preset first and second current weights, respectively.

6. The LED display screen operation status analysis system based on multi-source data fusion according to claim 3, characterized in that, In S13, the formula for calculating the aging factor C3 is as follows: T6 is the total cumulative operating time of the target LED display screen, T7 is the rated service life of the target LED display screen, L1 is the brightness decay rate of the target LED display screen, and L2 is the dead pixel rate of the target LED display screen; α5, α6, and α7 are the preset first, second, and third aging weights, respectively.

7. The LED display screen operation status analysis system based on multi-source data fusion according to claim 1, characterized in that, The specific content of any execution of the analysis step is as follows: According to each monitoring parameter included in the invalid parameter set for the target LED display screen to execute the next analysis step stored temporarily, collect its monitoring value at the current moment, where the current moment refers to the starting moment of executing the analysis step. Extract each monitoring parameter and its monitoring value included from the valid analysis data for the target LED display screen to execute the next analysis step stored temporarily. Generate analysis data for the analysis step according to the monitoring values of all the extracted monitoring parameters and the monitoring values of all the collected monitoring parameters at the current moment. Calculate the overall state score S of the target LED display screen after performing the analysis steps, using the following formula: In the formula, Gi represents the monitored value of each monitoring parameter in the analyzed data, Hi represents the preset normal value of the corresponding monitoring parameter, and ηi represents the preset scoring weight of the corresponding monitoring parameter in the analyzed data. =1; Compare the magnitudes of S with P2 and P3. If S ≤ P2, determine that the execution result of this analysis step is that the target LED display screen is operating normally. If P2 < S < P3, determine that the execution result of this analysis step is that the target display screen is operating abnormally, send an abnormal warning to the management personnel, and let the management personnel increase the monitoring frequency. If S ≥ P3, determine that the execution result of this analysis step is that the target LED display screen has a malfunction, send a fault warning to the management personnel, and let the management personnel locate the cause of the fault, where P2 and P3 are the preset first and second state determination thresholds in sequence.

8. The LED display screen operation status analysis system based on multi-source data fusion according to claim 1, characterized in that, After each execution of the analysis step and the screening step by the fusion analysis module, recalculate the new analysis moment and screening moment correspondingly, and update and store the new analysis moment and screening moment into the fusion analysis module.

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