Multifunctional signboard and monitoring data processing method

Abstract

The invention provides a multifunctional signboard and a monitoring data processing method, and belongs to the technical field of data processing, and the method specifically comprises the steps: taking a specific time period as a reference time period when the abnormal probability of a line fault corresponding to a monitoring function meets a requirement in the specific time period; and taking a time period before the reference time period in the current date as a historical time period, and uploading the monitoring data corresponding to the monitoring function in a specific time period to the monitoring platform when determining that the fault state of the line fault corresponding to the monitoring function meets the requirement according to the analysis result of the monitoring data corresponding to the monitoring function in the historical time period. According to the analysis result of the monitoring data corresponding to the monitoring function in the monitoring platform, whether the monitoring data corresponding to the monitoring function needs to be subjected to data analysis processing by using the indication board in the specific time period is determined, so that the real-time performance of data processing is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of data processing, and in particular relates to a multifunctional identification plate and a monitoring data processing method. Background Art

[0002] In order to improve the intuitiveness of fault display processing, the prior art solution can intuitively realize fault display processing by setting a mechanical fault indicator. Specifically, in the invention patent application CN201610912215.X "A memory alloy spring fault indicator for detecting a power transmission line connection point", the fault indicator is directly connected to the connection point, without considering the influence of the surrounding environment on the temperature of the transmission line connection point, thereby improving the accuracy of detection, and the structure is simple and easy to install, thereby improving the safety of high-altitude operations. However, there are the following technical problems: Mechanical fault indicators can often only identify a single type of line fault and are unable to remotely transmit fault data to a monitoring platform, making it difficult to meet the reliability requirements for line operation fault management.

[0003] In response to the above technical problems, the present application specifically provides a multifunctional signboard and a monitoring data processing method. Summary of the invention

[0004] To achieve the purpose of the present invention, the present invention adopts the following technical solutions: According to one aspect of the present invention, a monitoring data processing method is provided.

[0005] A monitoring data processing method specifically comprises: S1 determines similar weather dates based on the weather data of the current date, and proceeds to the next step when it is determined that the power supply reliability coefficient of the current date is within a preset range based on the power generation data of the new energy power supply device of the signboard on the similar weather date and the power consumption of the collected data of the signboard; S2 determines the abnormal probability of line faults corresponding to different monitoring functions in the specific period according to the analysis result of the weather data in the specific period of the current date, and when the abnormal probability of line faults corresponding to the monitoring functions in the specific period meets the requirements, proceeds to the next step; S3 takes the specific period as the reference period, and takes the period before the reference period in the current date as the historical period, and when it is determined that the fault state of the line fault corresponding to the monitoring function meets the requirements based on the analysis results of the monitoring data corresponding to the monitoring function in the historical period, uploads the monitoring data corresponding to the monitoring function in the specific period to the monitoring platform; S4 determines whether it is necessary to use the signboard to perform data analysis and processing on the monitoring data corresponding to the monitoring function in a specific time period based on the analysis results of the monitoring data corresponding to the monitoring function in the monitoring platform.

[0006] The beneficial effects of the present invention are: Based on the power generation data of the new energy power supply device of the sign on similar weather dates and the power consumption of the collected data of the sign, it is determined whether the power supply reliability coefficient of the current date is within the preset range, thereby avoiding the technical problem of high power consumption of the sign caused by using the sign for data processing due to insufficient power generation data of the new energy power supply device on the current date, thereby improving the operating reliability of the sign and meeting the data processing needs of monitoring data.

[0007] According to the analysis results of the monitoring data corresponding to the monitoring function in the monitoring platform, it is determined whether it is necessary to use signboards to perform data analysis and processing on the monitoring data corresponding to the monitoring function during a specific period of time, thereby realizing the determination of the method of performing data analysis and processing on the monitoring function from the perspective of abnormal conditions of the monitoring data, which not only ensures the efficiency of data processing of abnormal monitoring data, but also avoids the emergence of technical problems such as unreliable power consumption caused by the use of signboards for data analysis and processing.

[0008] A further technical solution is that the similar weather date is a historical date whose deviations from the weather data of different dimensions of the current date are all within a preset weather deviation range.

[0009] A further technical solution is that the weather data includes temperature, humidity, wind speed, rainfall and snowfall.

[0010] A further technical solution is that the new energy power supply device includes a wind power generation device and a photovoltaic power generation device.

[0011] A further technical solution is that the method for determining the power supply reliability coefficient on the current date is: Based on the power generation data of the new energy power supply device of the indicator on different similar weather dates, the power generation on different similar weather dates is determined; Determine a reliable power supply date among the similar weather dates by using the power generation and the power consumption of the collected data of the sign; The power supply reliability coefficient of the current date is determined by the proportion of the power supply reliability dates in the similar weather dates.

[0012] A further technical solution is that the reliable power supply date is a similar weather date when the power generation and the power consumption of the collected data of the sign are within a preset power deviation range.

[0013] A further technical solution is that the power supply reliability coefficient of the current date has a value range between 0 and 1, wherein the larger the power supply reliability coefficient of the current date is, the higher the power supply reliability of the current date is.

[0014] A further technical solution is to determine whether it is necessary to use the signboard to perform data analysis and processing on the monitoring data corresponding to the monitoring function in a specific period of time, specifically including: Based on the analysis result of the monitoring data corresponding to the monitoring function, determine the time when the monitoring data corresponding to the monitoring function is within the preset abnormal data interval, and use it as the abnormal data time; It is determined according to the number of abnormal data moments within a preset time period whether it is necessary to use the indicator sign to perform data analysis and processing on the monitoring data corresponding to the monitoring function in a specific time period.

[0015] A further technical solution is that when the number of abnormal data moments within a preset time period is greater than a preset abnormal moment number threshold, it is determined that the monitoring data corresponding to the monitoring function needs to be analyzed and processed using the signboard in a specific time period.

[0016] In a second aspect, the present invention provides a multifunctional sign, which is applied to the above-mentioned monitoring data processing method, specifically comprising: Data acquisition module, monitoring data transmission module, data analysis module; The data acquisition module is responsible for collecting and processing the monitoring data of the line; The monitoring data transmission module is responsible for transmitting the collected monitoring data to the monitoring platform and receiving the analysis results of the monitoring data from the monitoring platform; The data analysis module is responsible for performing data analysis and processing using monitoring data.

[0017] Other features and advantages will be described in the following description, and partly become apparent from the description, or understood by practicing the invention. The purpose and other advantages of the invention are realized and obtained by the structures particularly pointed out in the description and the drawings.

[0018] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

[0020] Figure 1is a flow chart of a monitoring data processing method; Figure 2 is a flow chart of a method for determining a power supply reliability factor on a current date; Figure 3 It is a flow chart of a method for determining the abnormal probability of occurrence of a line fault corresponding to a monitoring function; Figure 4 It is a flow chart for determining that the fault state of the line fault corresponding to the monitoring function meets the requirements; Figure 5 It is a frame diagram of a multifunctional sign. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0022] For ease of understanding, the scheme will be described below through Example 1 and Example 2. Example

[0023] To solve the above problems, according to one aspect of the present invention, Figure 1 According to one aspect of the present invention, a monitoring data processing method is provided, which specifically includes: S1 determines similar weather dates based on the weather data of the current date, and proceeds to the next step when it is determined that the power supply reliability coefficient of the current date is within a preset range based on the power generation data of the new energy power supply device of the signboard on the similar weather date and the power consumption of the collected data of the signboard; Furthermore, the similar weather date is a historical date whose deviations from the weather data of different dimensions of the current date are all within a preset weather deviation range.

[0024] Specifically, the weather data includes temperature, humidity, wind speed, rainfall and snowfall.

[0025] It should be noted that the new energy power supply device includes a wind power generation device and a photovoltaic power generation device.

[0026] It is understandable that if Figure 2 As shown, the method for determining the power supply reliability coefficient of the current date is: Based on the power generation data of the new energy power supply device of the indicator on different similar weather dates, the power generation on different similar weather dates is determined; Determine a reliable power supply date among the similar weather dates by using the power generation and the power consumption of the collected data of the sign; The power supply reliability coefficient of the current date is determined by the proportion of the power supply reliability dates in the similar weather dates.

[0027] Furthermore, the reliable power supply date is a similar weather date when the power generation and the power consumption of the collected data of the sign are within a preset power deviation range.

[0028] It can be understood that the value range of the power supply reliability coefficient of the current date is between 0 and 1, wherein the larger the power supply reliability coefficient of the current date is, the higher the power supply reliability of the current date is.

[0029] Specifically, when the power supply reliability coefficient of the current date is not within the preset range, it is also necessary to determine whether the power supply reliability coefficient of the current date is greater than the preset power supply reliability coefficient threshold. When the power supply reliability coefficient of the current date is not less than the preset power supply reliability coefficient threshold, the monitoring data corresponding to different monitoring functions in different time periods of the current date are all processed by using signboards for data analysis. When the power supply reliability coefficient of the current date is less than the preset power supply reliability coefficient threshold, the monitoring data corresponding to different monitoring functions in different time periods of the current date are all processed by using the monitoring platform for data analysis.

[0030] In another embodiment, the method for determining the power supply reliability coefficient on the current date is: Based on the power generation data of the new energy power supply device of the indicator on different similar weather dates, the power generation on different similar weather dates is determined, and the power generation benchmark value is determined according to the average value of the power generation on different similar weather dates; When the power generation reference value is greater than the power consumption of the data collected by the sign, the monitoring data corresponding to different monitoring functions in different time periods of the current date are analyzed and processed using the sign; When the power generation reference value is less than the power consumption of the collected data of the sign: When the deviation between the power generation reference value and the power consumption of the collected data of the sign is not within the preset deviation range, the monitoring data corresponding to different monitoring functions in different time periods of the current date are all analyzed and processed by the monitoring platform; When the deviation between the power generation reference value and the power consumption of the collected data of the sign is within a preset deviation range: When it is determined that there is no reliable power supply date among the similar weather dates by using the power generation and the power consumption of the collected data of the sign, the monitoring data corresponding to different monitoring functions in different time periods of the current date are analyzed and processed by the monitoring platform; When there is a reliable power supply date among the similar weather dates: Obtain the proportion of the number of the power supply reliability date in the similar weather date. When the proportion is greater than the preset date proportion threshold, the monitoring data corresponding to different monitoring functions in different time periods of the current date are analyzed and processed using indicator signs; When the quantity ratio is not greater than the preset date quantity ratio threshold: The similar weather dates when the power consumption of the collected data of the sign is greater than the power generation and the deviation between the power consumption and the power generation is not within the preset deviation range are used as power generation deviation dates. When the number of power generation deviation dates does not meet the requirements, the monitoring data corresponding to different monitoring functions in different time periods of the current date are all analyzed and processed using the monitoring platform; When the number of power generation deviation dates meets the requirement: The power supply reliability coefficient of the current date is determined by using the deviation rate of power consumption and power generation on different similar weather dates using a preset mapping function.

[0031] S2 determines the abnormal probability of line faults corresponding to different monitoring functions in the specific period according to the analysis result of the weather data in the specific period of the current date, and when the abnormal probability of line faults corresponding to the monitoring functions in the specific period meets the requirements, proceeds to the next step; Furthermore, the monitoring functions include temperature sensing, tilt sensing, line image acquisition, line waveform recording, and Beidou positioning.

[0032] Specifically, Figure 3 As shown, the method for determining the abnormal probability of the line fault corresponding to the monitoring function is: Based on the analysis result of the weather data of a specific period of the current date, determine the historical period whose deviation from the weather data of the specific period is within a preset weather deviation range, and use it as a similar historical period; The line fault corresponding to the monitoring function is regarded as a matching line fault, and a similar historical period in which the matching line fault occurred is regarded as a fault period; The abnormal probability of occurrence of the line fault corresponding to the monitoring function is determined based on the proportion of the fault time period in the similar historical time period.

[0033] Specifically, when the abnormal probability of the line fault corresponding to the monitoring function does not meet the requirement, the monitoring data corresponding to the monitoring function is analyzed and processed using the indicator board.

[0034] In another embodiment, the method for determining the abnormal probability of the line fault corresponding to the monitoring function is: Based on the analysis result of the weather data of a specific period of the current date, determine the historical period whose deviation from the weather data of the specific period is within the preset weather deviation range, and use it as the similar historical period, and use the line fault corresponding to the monitoring function as the matching line fault. When no matching line fault occurs in the similar historical period, it is determined that the abnormal probability of the line fault corresponding to the monitoring function does not meet the requirement. When a matching line failure has occurred in the similar historical period: Obtaining the number of occurrences of the matching line fault in the similar historical period, and when the number of occurrences of the matching line fault in the similar historical period is greater than a preset number of occurrences, determining that the abnormal probability of the line fault corresponding to the monitoring function does not meet the requirement; When the number of occurrences of the matching line fault in the similar historical period is not greater than the preset number of occurrences: the similar historical period in which the matching line fault occurred is taken as the fault period, and when the proportion of the number of the fault period in the similar historical period is greater than the preset proportion, it is determined that the abnormal probability of the line fault corresponding to the monitoring function does not meet the requirement; When the proportion of the fault period in the similar historical period is not greater than the preset proportion: Determine the fault time period whose occurrence number is greater than a preset number threshold value according to the occurrence number of the matching line fault in different fault time periods, and use it as the screening fault time period. When the number of the screening fault time periods is greater than the preset screening time period number, it is determined that the abnormal probability of the line fault corresponding to the monitoring function does not meet the requirement; When the number of the screening failure periods is not greater than the preset number of screening periods: The proportion of the fault period in the similar historical period is obtained, and the abnormal probability of the line fault corresponding to the monitoring function is determined in combination with the number of occurrences of the matching line fault in the similar historical period.

[0035] Further, the abnormal probability of occurrence of the line fault corresponding to the monitoring function is determined in combination with the number of occurrences of the matching line fault in the similar historical period, specifically including: The frequency coefficient of occurrence is determined by using the ratio of the number of occurrences of the matching line fault in the similar historical period to the fault period, and the abnormal probability of the line fault corresponding to the monitoring function is determined according to the frequency coefficient of occurrence and the weight of the proportion of the fault period in the similar historical period.

[0036] S3 takes the specific period as the reference period, and takes the period before the reference period in the current date as the historical period, and when it is determined that the fault state of the line fault corresponding to the monitoring function meets the requirements based on the analysis results of the monitoring data corresponding to the monitoring function in the historical period, uploads the monitoring data corresponding to the monitoring function in the specific period to the monitoring platform; Specifically, Figure 4 As shown, determining that the fault state of the line fault corresponding to the monitoring function meets the requirements specifically includes: Based on the analysis results of the monitoring data corresponding to the monitoring function in the historical period, determine the time when the monitoring data corresponding to the monitoring function in the historical period is within the preset abnormal data interval, and use it as the abnormal data time; Determine the total number of abnormal data moments according to the number of abnormal data moments in different historical periods; Whether the fault state of the line fault corresponding to the monitoring function meets the requirement is determined by the total number of the abnormal data moments.

[0037] Further, when the total number of abnormal data moments is greater than the preset number of moments, it is determined that the fault state of the line fault corresponding to the monitoring function does not meet the requirement.

[0038] It should be noted that when the fault state of the line fault corresponding to the monitoring function does not meet the requirements, the monitoring data corresponding to the monitoring function is analyzed and processed using an indicator board.

[0039] It can be understood that determining that the fault state of the line fault corresponding to the monitoring function meets the requirements specifically includes: S31 determines the moment when the monitoring data corresponding to the monitoring function in the historical period is within a preset abnormal data interval based on the analysis result of the monitoring data corresponding to the monitoring function in the historical period, and uses it as the abnormal data moment; S32 determines the abnormal coefficients of different historical periods according to the number of abnormal data moments in different historical periods according to a preset mapping function; S33 determines the fault state abnormality coefficient of the line fault corresponding to the monitoring function through the abnormality coefficients of different historical time periods, and uses the fault state abnormality coefficient to determine whether the fault state of the line fault corresponding to the monitoring function meets the requirements.

[0040] Furthermore, the fault state abnormality coefficient is determined according to an average value of abnormality coefficients in different historical time periods.

[0041] Specifically, when the fault state abnormality coefficient is greater than a preset abnormality coefficient threshold, it is determined that the fault state of the line fault corresponding to the monitoring function does not meet the requirement.

[0042] Optionally, the above step S31 includes the following contents: S311 determines that the fault state of the line fault corresponding to the monitoring function meets the requirement based on the analysis result of the monitoring data corresponding to the monitoring function in the historical period. If the monitoring data corresponding to the monitoring function does not exist in the historical period and is within the preset abnormal data interval, the process proceeds to step S312. S312: taking the moment of the monitoring data corresponding to the monitoring function within the preset abnormal data as the abnormal data moment; when the number of abnormal data moments in the historical period does not meet the requirement, determining that the fault state of the line fault corresponding to the monitoring function does not meet the requirement; when the number of abnormal data moments in the historical period meets the requirement, proceeding to step S313; S313 determines the proportion of data moments according to the ratio of the number of abnormal data moments to the number of historical time periods. When the proportion of data moments is greater than the proportion of preset moments, the process goes to step S32. When the proportion of data moments is not greater than the proportion of preset moments, it is determined that the fault state of the line fault corresponding to the monitoring function meets the requirements.

[0043] Optionally, the above step S32 includes the following contents: S321 obtains the historical period with abnormal data moments and uses it as the data abnormal period. When the number of the data abnormal period is less than the preset abnormal period number threshold, the process proceeds to step S322. When the number of the data abnormal period is not less than the preset abnormal period number threshold, the process proceeds to step S323. S322: when the number of abnormal data moments in different data abnormal time periods is within the preset time number interval, it is determined that the fault state of the line fault corresponding to the monitoring function meets the requirement; when there is a data abnormal time period in which the number of abnormal data moments is not within the preset time number interval, the process proceeds to step S323; S323 determines the abnormal coefficients of different historical time periods according to the number of abnormal data moments in different historical time periods and the preset mapping function. When the number of historical time periods that do not meet the requirements and the abnormal coefficients do not meet the requirements, it is determined that the fault state of the line fault corresponding to the monitoring function does not meet the requirements. When the number of historical time periods that do not meet the requirements and the abnormal coefficients do meet the requirements, proceed to step S33.

[0044] S4 determines whether it is necessary to use the signboard to perform data analysis and processing on the monitoring data corresponding to the monitoring function in a specific time period based on the analysis results of the monitoring data corresponding to the monitoring function in the monitoring platform.

[0045] It is understandable that determining whether it is necessary to use the signboard to perform data analysis on the monitoring data corresponding to the monitoring function during a specific period of time specifically includes: Based on the analysis result of the monitoring data corresponding to the monitoring function, determine the time when the monitoring data corresponding to the monitoring function is within the preset abnormal data interval, and use it as the abnormal data time; It is determined according to the number of abnormal data moments within a preset time period whether it is necessary to use the indicator sign to perform data analysis and processing on the monitoring data corresponding to the monitoring function in a specific time period.

[0046] Furthermore, when the number of abnormal data moments within a preset time period is greater than a preset abnormal moment number threshold, it is determined that the monitoring data corresponding to the monitoring function needs to be analyzed and processed using the signboard in a specific time period. Example

[0047] Second, as Figure 5 As shown, the present invention provides a multifunctional sign, which is applied to the above-mentioned monitoring data processing method, specifically comprising: Data acquisition module, monitoring data transmission module, data analysis module; The data acquisition module is responsible for collecting and processing the monitoring data of the line; The monitoring data transmission module is responsible for transmitting the collected monitoring data to the monitoring platform and receiving the analysis results of the monitoring data from the monitoring platform; The data analysis module is responsible for performing data analysis and processing using monitoring data.

[0048] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0049] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0050] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A monitoring data processing method, characterized in that: Specifically include: Determine similar weather dates based on the weather data of the current date, and proceed to the next step when it is determined that the power supply reliability coefficient of the current date is within a preset range based on the power generation data of the new energy power supply device of the signboard on the similar weather date and the power consumption of the collected data of the signboard; According to the analysis result of the weather data in the specific period of the current date, the abnormal probability of line faults corresponding to different monitoring functions in the specific period is determined, and when the abnormal probability of line faults corresponding to the monitoring functions in the specific period meets the requirements, the next step is entered; The specific period is taken as the reference period, and the period before the reference period in the current date is taken as the historical period. When it is determined that the fault state of the line fault corresponding to the monitoring function meets the requirements based on the analysis results of the monitoring data corresponding to the monitoring function in the historical period, the monitoring data corresponding to the monitoring function in the specific period is uploaded to the monitoring platform; According to the analysis result of the monitoring data corresponding to the monitoring function in the monitoring platform, it is determined whether it is necessary to use the signboard to perform data analysis and processing on the monitoring data corresponding to the monitoring function in a specific time period.

2. A monitoring data processing method according to claim 1, characterized in that: The similar weather date is a historical date whose deviations of weather data in different dimensions from the current date are all within a preset weather deviation range.

3. A monitoring data processing method as claimed in claim 2, characterized in that: The weather data includes temperature, humidity, wind speed, rainfall, and snowfall.

4. A monitoring data processing method according to claim 1, characterized in that: The new energy power supply device includes a wind power generation device and a photovoltaic power generation device.

5. A monitoring data processing method according to claim 1, characterized in that: The method for determining the power supply reliability coefficient of the current date is: Based on the power generation data of the new energy power supply device of the indicator on different similar weather dates, the power generation on different similar weather dates is determined; Determine a reliable power supply date among the similar weather dates by using the power generation and the power consumption of the collected data of the sign; The power supply reliability coefficient of the current date is determined by the proportion of the power supply reliability dates in the similar weather dates.

6. A monitoring data processing method according to claim 1, characterized in that: The reliable power supply date is a similar weather date when the power generation and the power consumption of the collected data of the sign are within a preset power deviation range.

7. A monitoring data processing method according to claim 1, characterized in that: When the power supply reliability coefficient of the current date is not within the preset range, it is also necessary to determine whether the power supply reliability coefficient of the current date is greater than the preset power supply reliability coefficient threshold. When the power supply reliability coefficient of the current date is not less than the preset power supply reliability coefficient threshold, the monitoring data corresponding to different monitoring functions in different time periods of the current date are all processed using signboards for data analysis. When the power supply reliability coefficient of the current date is less than the preset power supply reliability coefficient threshold, the monitoring data corresponding to different monitoring functions in different time periods of the current date are all processed using the monitoring platform for data analysis.

8. A monitoring data processing method as claimed in claim 1, characterized in that: Determining whether it is necessary to use the signboard to perform data analysis and processing on the monitoring data corresponding to the monitoring function during a specific period of time specifically includes: Based on the analysis result of the monitoring data corresponding to the monitoring function, determine the time when the monitoring data corresponding to the monitoring function is within the preset abnormal data interval, and use it as the abnormal data time; It is determined according to the number of abnormal data moments within a preset time period whether it is necessary to use the indicator sign to perform data analysis and processing on the monitoring data corresponding to the monitoring function in a specific time period.

9. A monitoring data processing method according to claim 8, characterized in that: When the number of abnormal data moments within a preset time period is greater than a preset abnormal moment number threshold, it is determined that the monitoring data corresponding to the monitoring function needs to be analyzed and processed using the signboard in a specific time period.

10. A multifunctional identification plate, applied to a monitoring data processing method according to any one of claims 1 to 9, characterized in that: Specifically include: Data acquisition module, monitoring data transmission module, data analysis module; The data acquisition module is responsible for collecting and processing the monitoring data of the line; The monitoring data transmission module is responsible for transmitting the collected monitoring data to the monitoring platform and receiving the analysis results of the monitoring data from the monitoring platform; The data analysis module is responsible for performing data analysis and processing using monitoring data.

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