Multifunctional signboard and monitoring data processing method

Abstract

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

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of data processing, and particularly relates to a multifunctional signboard and a monitoring data processing method. BACKGROUND

[0002] In order to improve the intuitiveness of fault display processing, the prior art scheme sets a mechanical fault indicator to directly realize fault display processing. Specifically, the fault indicator is directly connected with the connection point in the invention patent application CN201610912215.X "Memory alloy spring fault indicator for detecting power transmission line connection point", without considering the influence of the surrounding environment on the measurement of the temperature of the power transmission line connection point, improving the detection accuracy and the simplicity of the structure, and further improving the safety of high-altitude operation. However, the following technical problems exist:

[0003] The mechanical fault indicator can only identify a single line fault type, and cannot remotely transmit fault data to the monitoring platform, so that the reliability of the management of the line operation fault cannot meet the requirements.

[0004] In view of the above technical problems, the present application provides a multifunctional signboard and a monitoring data processing method. SUMMARY

[0005] To achieve the purpose of the present application, the present application adopts the following technical solutions:

[0006] According to one aspect of the present application, a monitoring data processing method is provided.

[0007] A monitoring data processing method, specifically comprising:

[0008] S1 determines similar weather dates based on the weather data of the current date, and determines the power supply reliability coefficient of the current date within a preset interval based on the power generation data of the new energy power supply device of the signboard in the similar weather dates and the power consumption of the collected data of the signboard, and then enters the next step;

[0009] S2 determines the abnormal probability of the occurrence of line faults corresponding to different monitoring functions in a specific time period according to the analysis result of the weather data of the specific time period of the current date, and when the abnormal probability of the occurrence of line faults corresponding to the monitoring functions in the specific time period meets the requirements, the next step is entered;

[0010] S3 takes the specific period as a reference period, and takes a period before the reference period in the current date as a history period, determines the fault state of the line fault corresponding to the monitoring function according to the analysis result of the monitoring data corresponding to the monitoring function in the history period, and uploads the monitoring data corresponding to the monitoring function in the specific period to the monitoring platform when the fault state of the line fault corresponding to the monitoring function meets the requirement.

[0011] S4 determines whether the monitoring data corresponding to the monitoring function needs to be processed by the indicator according to the analysis result of the monitoring data corresponding to the monitoring function in the monitoring platform in the specific period.

[0012] The beneficial effects of the present application are:

[0013] According to the power generation data of the new energy power supply device of the indicator in the similar weather date and the power consumption of the collected data of the indicator, it is determined whether the power supply reliability coefficient of the current date is in the preset interval, thereby avoiding the technical problem of large power consumption of the indicator caused by insufficient power generation data of the new energy power supply device in the current date, improving the operation reliability of the indicator, and meeting the data processing demand of the monitoring data.

[0014] According to the analysis result of the monitoring data corresponding to the monitoring function in the monitoring platform, it is determined whether the monitoring data corresponding to the monitoring function needs to be processed by the indicator in the specific period, thereby realizing the determination of the data analysis processing mode of the monitoring function from the angle of the abnormal situation of the monitoring data, ensuring the data processing efficiency of the abnormal monitoring data, and avoiding the occurrence of the technical problem of unreliable power consumption caused by using the indicator for data analysis processing.

[0015] Further technical solutions are that the similar weather date is a historical date whose different dimension weather data deviates from the current date within a preset weather deviation range.

[0016] Further technical solutions are that the weather data includes temperature, humidity, wind speed, rainfall and snowfall.

[0017] Further technical solutions are that the new energy power supply device includes a wind power generation device and a photovoltaic power generation device.

[0018] Further technical solutions are that the determination method of the power supply reliability coefficient of the current date is:

[0019] The power generation data of the new energy power supply device of the indicator in different similar weather dates is determined as the basis.

[0020] Determine a power supply reliable date in the similar weather dates by using the power generation amount and the power consumption amount of the collected data of the signboard.

[0021] Determine a power supply reliable coefficient of the current date by a proportion of the number of the power supply reliable dates in the similar weather dates.

[0022] Further technical solutions are that the power supply reliable date is a similar weather date in which the power generation amount and the power consumption amount of the collected data of the signboard are within a preset power deviation range.

[0023] Further technical solutions are that the power supply reliable coefficient of the current date is within a range of 0 to 1, and the greater the power supply reliable coefficient of the current date is, the higher the power supply reliability of the current date is.

[0024] Further technical solutions are that it is determined whether the monitoring data corresponding to the monitoring function needs to be analyzed and processed by using the signboard in a specific period, and the determination specifically includes:

[0025] Determine a time at which the monitoring data corresponding to the monitoring function is within a preset abnormal data interval according to an analysis result of the monitoring data corresponding to the monitoring function, and take the time as an abnormal data time;

[0026] Determine whether the monitoring data corresponding to the monitoring function needs to be analyzed and processed by using the signboard in a specific period according to a number of abnormal data times within a preset period.

[0027] Further technical solutions are that when the number of abnormal data times within the preset period is greater than a preset abnormal time number threshold, it is determined that the monitoring data corresponding to the monitoring function needs to be analyzed and processed by using the signboard in a specific period.

[0028] In a second aspect, the application provides a multifunctional signboard applied to the monitoring data processing method, and specifically includes:

[0029] a data collection module, a monitoring data transmission module, and a data analysis module.

[0030] The data collection module is responsible for collecting and processing the monitoring data of a line.

[0031] The monitoring data transmission module is responsible for transmitting the collected monitoring data to a monitoring platform and receiving an analysis result of the monitoring data of the monitoring platform.

[0032] The data analysis module is responsible for analyzing and processing the monitoring data.

[0033] Other features and advantages will be set forth in the descriptions that follow, and in part will be apparent from the description, or can be learned by practice of the application. The purposes and other advantages of the application will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

[0034] To make the above objectives, features and advantages of the present application more obvious and easy to understand, the following preferred embodiments are specifically described below with reference to the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0035] The above and other features and advantages of the present application will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings in which:

[0036] Figure 1 is a flowchart of a method for monitoring data processing;

[0037] Figure 2 is a flowchart of a method for determining the power supply reliability coefficient of the current date;

[0038] Figure 3 is a flowchart of a method for determining the abnormal probability of the occurrence of a line fault corresponding to a monitoring function;

[0039] Figure 4 is a flowchart of determining that the fault state of a line fault corresponding to a monitoring function meets the requirements;

[0040] Figure 5 is a frame diagram of a multifunctional signboard. DETAILED DESCRIPTION

[0041] In order for those skilled in the art to better understand the technical solutions in the specification, the technical solutions in the specification will be clearly and completely described below in conjunction with the drawings in the specification. Obviously, the described embodiments are only some of the embodiments of the specification, not all. Based on the embodiments of the specification, all other embodiments obtained by those skilled in the art without creative labor should fall within the scope of protection of the specification.

[0042] For the sake of understanding, the following will be described by way of example 1 and example 2. EMBODIMENTS

[0043] To solve the above problems, according to one aspect of the present application, as shown in Figure 1 According to one aspect of the present application, a method for monitoring data processing is provided, specifically comprising:

[0044] S1 determines a similar weather date according to weather data of the current date, and determines a power supply reliability coefficient of the current date in a preset interval based on power generation data of a new energy power supply device of a sign in the similar weather date and power consumption of collected data of the sign, and enters the next step when the power supply reliability coefficient of the current date is in the preset interval;

[0045] Further, the similar weather date is a historical date with a deviation of different dimensions of weather data of the current date within a preset weather deviation range.

[0046] Specifically, the weather data includes temperature, humidity, wind speed, rainfall and snowfall.

[0047] It should be noted that the new energy power supply device includes a wind power generation device and a photovoltaic power generation device.

[0048] It can be understood that, as shown in the figure, Figure 2 the method for determining the power supply reliability coefficient of the current date is:

[0049] determining power generation in different similar weather dates based on power generation data of a new energy power supply device of a sign in the different similar weather dates;

[0050] determining a power supply reliable date in the similar weather date by using the power generation and power consumption of collected data of the sign;

[0051] determining the power supply reliability coefficient of the current date by using a quantity ratio of the power supply reliable date in the similar weather date.

[0052] Further, the power supply reliable date is a similar weather date with power generation and power consumption of collected data of the sign within a preset power deviation range.

[0053] It can be understood that, the power supply reliability coefficient of the current date is within a range of 0 to 1, wherein the greater the power supply reliability coefficient of the current date, the higher the power supply reliability degree of the current date.

[0054] Specifically, when the power supply reliability coefficient of the current date is not within the preset interval, it is further needed to determine whether the power supply reliability coefficient of the current date is greater than a 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, different monitoring data corresponding to different monitoring functions in different time periods of the current date are all analyzed and processed by using the sign, and when the power supply reliability coefficient of the current date is less than the preset power supply reliability coefficient threshold, different monitoring data corresponding to different monitoring functions in different time periods of the current date are all analyzed and processed by using a monitoring platform.

[0055] In another embodiment, the method for determining the power supply reliability coefficient of the current date is:

[0056] Based on the power generation data of the new energy power supply device of the sign in different similar weather dates, the power generation in different similar weather dates is determined, and the power generation reference value is determined according to the average value of the power generation in different similar weather dates;

[0057] When the power generation reference value is greater than the power consumption of the collected data of the sign, the monitoring data corresponding to different monitoring functions in different time periods in the current date are all analyzed and processed by the sign;

[0058] When the power generation reference value is less than the power consumption of the collected data of the sign:

[0059] When the deviation of 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 in the current date are all analyzed and processed by the monitoring platform;

[0060] When the deviation of the power generation reference value and the power consumption of the collected data of the sign is within the preset deviation range:

[0061] When there is no power supply reliable date in 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 in the current date are all analyzed and processed by the monitoring platform;

[0062] When there is a power supply reliable date in the similar weather dates:

[0063] When the number ratio of the power supply reliable dates in the similar weather dates is greater than the preset date number ratio threshold, the monitoring data corresponding to different monitoring functions in different time periods in the current date are all analyzed and processed by the sign;

[0064] When the number ratio is not greater than the preset date number ratio threshold:

[0065] The similar weather dates in which the power consumption of the collected data of the sign is greater than the power generation and the deviation of the power consumption and the power generation is not within the preset deviation range interval are regarded as power generation deviation dates, and when the number of the power generation deviation dates does not meet the requirement, the monitoring data corresponding to different monitoring functions in different time periods in the current date are all analyzed and processed by the monitoring platform;

[0066] When the number of the power generation deviation dates meets the requirement:

[0067] The power supply reliability coefficient of the current date is determined by using a preset mapping function according to the deviation rate of the power consumption and the power generation of different similar weather dates.

[0068] S2, according to the analysis result of the weather data of the specific period of the current date, determines the abnormal probability of the line fault corresponding to the monitoring function in the specific period, and when the abnormal probability of the line fault corresponding to the monitoring function in the specific period meets the requirement, the next step is entered.

[0069] Further, the monitoring function includes temperature sensing, inclination sensing, line image acquisition, line waveform recording, and Beidou positioning.

[0070] Specifically, as shown in Figure 3 The method for determining the abnormal probability of the line fault corresponding to the monitoring function is as follows:

[0071] According to the analysis result of the weather data of the specific period of the current date, a historical period with a deviation amount of the weather data within a preset weather deviation amount range is determined as a similar historical period.

[0072] The line fault corresponding to the monitoring function is taken as a matching line fault, and the similar historical period in which the matching line fault occurs is taken as a fault period.

[0073] The abnormal probability of the line fault corresponding to the monitoring function is determined based on the proportion of the number of the fault periods in the similar historical periods.

[0074] 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 by using a signboard.

[0075] In another embodiment, the method for determining the abnormal probability of the line fault corresponding to the monitoring function is as follows:

[0076] According to the analysis result of the weather data of the specific period of the current date, a historical period with a deviation amount of the weather data within a preset weather deviation amount range is determined as a similar historical period, and the line fault corresponding to the monitoring function is taken as a matching line fault.

[0077] When the matching line fault occurs in the similar historical period:

[0078] obtaining the number of occurrences of the matching line fault in the similar historical period, when the number of occurrences of the matching line fault in the similar historical period is greater than the preset number of occurrences, it is determined that the abnormal probability of the line fault corresponding to the monitoring function does not meet the requirements;

[0079] 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 has occurred is taken as a fault period, when the proportion of the number of the fault period in the similar historical period is greater than the preset proportion of the number, it is determined that the abnormal probability of the line fault corresponding to the monitoring function does not meet the requirements;

[0080] When the proportion of the number of the fault period in the similar historical period is not greater than the preset proportion of the number:

[0081] The number of occurrences of the matching line fault in different fault periods is used to determine the fault period in which the number of occurrences is greater than the preset number threshold, and it is taken as a screening fault period, when the number of the screening fault period is greater than the preset screening period number, it is determined that the abnormal probability of the line fault corresponding to the monitoring function does not meet the requirements;

[0082] When the number of the screening fault period is not greater than the preset screening period number:

[0083] The proportion of the number 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.

[0084] Further, 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, specifically including:

[0085] The ratio of the number of occurrences of the matching line fault in the similar historical period to the fault period is used to determine the frequent occurrence coefficient, and the abnormal probability of the line fault corresponding to the monitoring function is determined according to the frequent occurrence coefficient, the weight of the proportion of the number of the fault period in the similar historical period and the proportion of the number of the fault period in the similar historical period.

[0086] S3 takes the specific period as a reference period, and takes the period before the reference period in the current date as a historical period, and determines the fault state of the line fault corresponding to the monitoring function according to the analysis result of the monitoring data corresponding to the monitoring function in the historical period, when the fault state of the line fault corresponding to the monitoring function meets the requirements, the monitoring data corresponding to the monitoring function in the specific period is uploaded to the monitoring platform;

[0087] Specifically, as Figure 4As shown, determining whether the fault state of the line fault corresponding to the monitoring function meets the requirement, specifically comprising:

[0088] According to the analysis result of the monitoring data corresponding to the monitoring function in the historical period, determining the time point of the monitoring data corresponding to the monitoring function in the historical period within the preset abnormal data interval, and taking it as an abnormal data time point;

[0089] According to the number of abnormal data time points in different historical periods, determining the total number of abnormal data time points;

[0090] Determine whether the fault state of the line fault corresponding to the monitoring function meets the requirement through the total number of abnormal data time points.

[0091] Further, when the total number of abnormal data time points is greater than the preset time point number, it is determined that the fault state of the line fault corresponding to the monitoring function does not meet the requirement.

[0092] It should be noted that when the fault state 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 by a signboard.

[0093] It can be understood that determining whether the fault state of the line fault corresponding to the monitoring function meets the requirement, specifically comprising:

[0094] S31 According to the analysis result of the monitoring data corresponding to the monitoring function in the historical period, determining the time point of the monitoring data corresponding to the monitoring function in the historical period within the preset abnormal data interval, and taking it as an abnormal data time point;

[0095] S32 According to the number of abnormal data time points in different historical periods, determining the abnormal coefficient of different historical periods according to the preset mapping function;

[0096] S33 Determine the fault state abnormal coefficient of the line fault corresponding to the monitoring function through the abnormal coefficient of different historical periods, and determine whether the fault state of the line fault corresponding to the monitoring function meets the requirement by using the fault state abnormal coefficient.

[0097] Further, the fault state abnormal coefficient is determined according to the average value of the abnormal coefficient of different historical periods.

[0098] Specifically, when the fault state abnormal coefficient is greater than the preset abnormal coefficient threshold, it is determined that the fault state of the line fault corresponding to the monitoring function does not meet the requirement.

[0099] Optionally, the above step S31 includes the following contents:

[0100] S311 determines, according to the analysis result of the monitoring data corresponding to the monitoring function in the historical period, that the fault state of the line fault corresponding to the monitoring function meets the requirement when there is no time point in the historical period in which the monitoring data corresponding to the monitoring function is in the preset abnormal data interval, and turns to step S312 when there is a time point in which the monitoring data corresponding to the monitoring function is in the preset abnormal data interval.

[0101] S312 takes the time point in which the monitoring data corresponding to the monitoring function is in the preset abnormal data as an abnormal data time point, determines that the fault state of the line fault corresponding to the monitoring function does not meet the requirement when the number of abnormal data time points in the historical period does not meet the requirement, and turns to step S313 when the number of abnormal data time points in the historical period meets the requirement.

[0102] S313 determines a data time point number proportion according to the ratio of the number of abnormal data time points to the number of historical periods, turns to step S32 when the data time point number proportion is greater than a preset time point number proportion, and determines that the fault state of the line fault corresponding to the monitoring function meets the requirement when the data time point number proportion is not greater than the preset time point number proportion.

[0103] Optionally, the step S32 includes the following contents.

[0104] S321 obtains the historical periods in which there are abnormal data time points and takes them as data abnormal periods, turns to step S322 when the number of data abnormal periods is less than a preset abnormal period number threshold, and turns to step S323 when the number of data abnormal periods is not less than the preset abnormal period number threshold.

[0105] S322 determines that the fault state of the line fault corresponding to the monitoring function meets the requirement when the number of abnormal data time points in different data abnormal periods is in a preset time point number interval, and turns to step S323 when there is a data abnormal period in which the number of abnormal data time points is not in the preset time point number interval.

[0106] S323 determines an abnormal coefficient of different historical periods according to the number of abnormal data time points in different historical periods according to a preset mapping function, determines that the fault state of the line fault corresponding to the monitoring function does not meet the requirement when the number of historical periods in which the abnormal coefficient does not meet the requirement does not meet the requirement, and turns to step S33 when the number of historical periods in which the abnormal coefficient does not meet the requirement meets the requirement.

[0107] S4 determines whether the monitoring data corresponding to the monitoring function needs to be analyzed and processed by the indicator in a specific period according to the analysis result of the monitoring data corresponding to the monitoring function in the monitoring platform.

[0108] It is understandable that determining whether the monitoring data corresponding to the monitoring function needs to be analyzed and processed using the indicator during a specific time period includes:

[0109] Based on the analysis results 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 take it as the abnormal data time.

[0110] Based on the number of abnormal data moments within a preset time period, it is determined whether it is necessary to perform data analysis and processing on the monitoring data corresponding to the monitoring function using the indicator in a specific time period.

[0111] Furthermore, when the number of abnormal data moments within a preset time period exceeds a preset threshold for the number of abnormal moments, it is determined that the monitoring data corresponding to the monitoring function needs to be analyzed and processed using the indicator in a specific time period. Example

[0112] Secondly, such as Figure 5 As shown, the present invention provides a multifunctional signboard applied to the above-mentioned monitoring data processing method, specifically including:

[0113] Data acquisition module, monitoring and data transmission module, data analysis module;

[0114] The data acquisition module is responsible for collecting and processing the monitoring data of the line.

[0115] 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.

[0116] The data analysis module is responsible for performing data analysis and processing using the monitoring data.

[0117] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments of apparatus, devices, and non-volatile computer storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0118] The above-described embodiments of the application have special structure and can achieve the desired results. Other embodiments can have different structures and achieve the same results. The purpose of the above-described embodiments is to illustrate the principles of the application and not to limit the scope of the application. The scope of the application is defined by the claims and their equivalents. Other embodiments are within the scope of the claims.

[0119] The above description is merely illustrative of the embodiments of the present application and is not intended to limit the scope of the present application. Various modifications can be made by those skilled in the art based upon the teachings disclosed herein. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present application shall fall within the scope of the claims of the present application.

Claims

1. A monitoring data processing method, characterized in that, Specifically, it includes: Based on the weather data of the current date, similar weather dates are determined. Based on the power generation data of the new energy power supply device on the sign in the similar weather dates and the power consumption of the data collected by the sign, if the power supply reliability coefficient of the current date is within the preset range, proceed to the next step. Based on the analysis results of weather data for a specific time period of the current date, determine the abnormal probability of line faults occurring for different monitoring functions during the specific time period. When the abnormal probability of line faults occurring for the monitoring functions during the specific time period meets the requirements, proceed to the next step. The specific time period is used as the base time period, and the time periods before the base time period in the current date are used as historical time periods. Based on the analysis results of the monitoring data corresponding to the monitoring function in the historical time period, when it is determined that the fault status of the line fault corresponding to the monitoring function meets the requirements, the monitoring data corresponding to the monitoring function in the specific time period is uploaded to the monitoring platform. Based on 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 the sign to perform data analysis and processing on the monitoring data corresponding to the monitoring function during a specific time period. The method for determining the power supply reliability coefficient for the current date is as follows: Based on the power generation data of the new energy power supply devices on different similar weather days, the power generation on different similar weather days is determined; Using the power generation and the power consumption data collected from the signpost, reliable power supply dates among the similar weather dates are determined; The power supply reliability coefficient for the current date is determined by the proportion of such reliable power supply dates among similar weather dates.

2. The monitoring data processing method as described in claim 1, characterized in that, The similar weather dates are historical dates whose deviations from the current date's weather data in different dimensions are all within a preset weather deviation range.

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

4. The monitoring data processing method as described in claim 1, characterized in that, The new energy power supply equipment includes wind power generation equipment and photovoltaic power generation equipment.

5. The monitoring data processing method as described in claim 1, characterized in that, The reliable power supply date is a similar weather date when the power generation and the power consumption data collected by the indicator are within a preset power deviation range.

6. The monitoring data processing method as described in 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 will be analyzed and processed using the indicator. 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 will be analyzed and processed using the monitoring platform.

7. The monitoring data processing method as described in claim 1, characterized in that, Determining whether it is necessary to perform data analysis and processing on the monitoring data corresponding to the monitoring function using the indicator during a specific time period includes: Based on the analysis results 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 take it as the abnormal data time. Based on the number of abnormal data moments within a preset time period, it is determined whether the monitoring data corresponding to the monitoring function needs to be analyzed and processed using the indicator in a specific time period.

8. The monitoring data processing method as described in claim 7, characterized in that, When the number of abnormal data moments within a preset time period exceeds a preset threshold for the number of abnormal moments, it is determined that the monitoring data corresponding to the monitoring function needs to be analyzed and processed using the indicator in a specific time period.

9. A multi-functional signboard, applied to the monitoring data processing method according to any one of claims 1-8, characterized in that, Specifically, it includes: Data acquisition module, monitoring and 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 the monitoring data.

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