A remote monitoring and management platform based on 2M line

Abstract

The application belongs to the technical field of line remote monitoring, and particularly relates to a 2M line remote monitoring and management platform, which comprises a front-end acquisition device, a data analysis module, a judgment module and an adjustment prediction module. The front-end acquisition device is used for collecting line operation data, obtaining a data missing coefficient value by analyzing the line operation data, and obtaining a data state signal according to the data missing coefficient value. The data analysis module is used for establishing a line operation data field null value number and a time coordinate system based on a data complete signal, dividing an analysis period into a plurality of acquisition time periods by setting the analysis period, obtaining a slope difference value and a floating value in the analysis period, and calculating a field null value change value through the slope difference value and the floating value. The field null value change value can reflect the influence degree of line output transmission, the influence degree of line data transmission on the actual use process is judged, and corresponding processing measures are made in combination with the influence degree.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of line remote monitoring, and particularly relates to a 2M line remote monitoring and management platform. BACKGROUND

[0002] The 2M line remote monitoring and management platform is a comprehensive system integrating network communication, video processing, data storage and remote management functions. This platform is usually applied to scenarios requiring remote monitoring and management, such as the army, enterprises, schools, etc., wherein the 2M line (i.e. a line with a bandwidth of 2 Mbps) serves as the basis for data transmission, ensuring the real-time and stability of monitoring data.

[0003] The traditional monitoring system has problems such as slow transmission speed and large data volume. In the process of line transmission, the data transmission quality cannot be judged, and the data integrity can only be judged by simple threshold comparison through the number of field null values. For some data meeting the threshold judgment, the data transmission quality is easily affected due to different degrees of influence of the number of field null values, which affects normal use.

[0004] Therefore, the application provides a 2M line remote monitoring and management platform. SUMMARY

[0005] In order to make up for the deficiencies of the prior art and solve at least one technical problem proposed in the background.

[0006] The technical scheme adopted by the application to solve the technical problems is: the 2M line remote monitoring and management platform comprises

[0007] a front-end acquisition device, which is used to acquire line operation data, analyze the line operation data to obtain a data loss coefficient value, and obtain a data state signal according to the data loss coefficient value; wherein the data state signal comprises a data integrity signal and a data loss signal;

[0008] The data analysis module establishes a line operation data field null value quantity and time coordinate system based on the data integrity signal, takes the field null value quantity of the line operation data as the Y axis and takes time as the X axis, sets a first data field null value quantity threshold and a second data field null value quantity threshold, the first data field null value quantity threshold is smaller than the second data field null value quantity threshold, and the first data field null value quantity threshold and the second data field null value quantity threshold are marked in the line operation data field null value quantity and time coordinate system, thereby obtaining two straight lines parallel to the X axis; an area below the first data field null value quantity threshold line is marked as a high-quality area, an area between the first data field null value quantity threshold line and the second data field null value quantity threshold line is marked as an adjustment area, and an area above the second data field null value quantity threshold line is marked as a dangerous area;

[0009] The judgment module obtains the line operation data of the current period, performs judgment, and generates a control signal; the control signal includes a line sustainable operation signal and a control analysis signal;

[0010] The adjustment prediction module, after obtaining the control analysis signal, sets an analysis period, divides the analysis period into a plurality of collection periods, and obtains a field null value change value; the change value is used to judge the influence degree of the line output transmission, and the power transmission line is adjusted according to the influence degree.

[0011] Preferably, a data missing coefficient value is obtained by analyzing the line operation data, specifically:

[0012] The line operation time period is divided into a plurality of time subunits, the line operation data field of each subunit is obtained, the null value quantity of the data field of each subunit is obtained through SQL query, and the null value quantity of the data field of each subunit is compared with a subunit null value quantity threshold:

[0013] If the null value quantity of the data field of the subunit is greater than the subunit null value quantity threshold, it indicates that the null value quantity of the data field of the subunit exceeds the standard, a data null value number abnormal signal is generated, and the subunit is marked as a data abnormal subunit;

[0014] Conversely, if the null value quantity of the data field of the subunit is less than or equal to the subunit null value quantity threshold, it indicates that the null value quantity of the data field of the subunit meets the standard, a data null value number normal signal is generated, and the subunit is marked as a data normal subunit;

[0015] Preferably, based on the data null value number abnormal signal, a ratio of the null value quantity of the data abnormal subunit to the corresponding subunit character total number is obtained, which is denoted as an abnormal null value ratio; the abnormal null value ratio of each subunit is subjected to variance calculation to obtain an abnormal ratio fluctuation value;

[0016] Obtaining the maximum value and the minimum value of the null value number in all sub-units, and calculating the difference between the maximum value and the minimum value of the control number to obtain a null value deviation value;

[0017] Multiplying the null value number variance value of the line with the null value deviation value to obtain a data loss coefficient value.

[0018] Preferably, a data state signal is obtained according to the data loss coefficient value, specifically:

[0019] Comparing the data loss coefficient value with a data loss coefficient threshold value;

[0020] If the data loss coefficient value is greater than or equal to the data loss coefficient threshold value, it indicates that the null value number of the data abnormal sub-unit changes greatly in the line operation time period, and complete information data transmission cannot be performed in the line operation time period, and a data loss signal is generated;

[0021] If the data loss coefficient value is less than the data loss coefficient threshold value, it indicates that the null value number of the data abnormal sub-unit changes less in the line operation time period, and complete information data transmission can be performed in the line operation time period, and a data integrity signal is generated.

[0022] Preferably, line operation data of a current period is obtained, and a control signal is generated by judging, specifically:

[0023] Obtaining the field null value number of the line operation data of the current period, and substituting the field null value number into the line operation data field null value number and time coordinate system;

[0024] If the field null value number of the line operation data of the current period is in the high-quality zone, a line sustainable operation signal is generated;

[0025] If the field null value number of the line operation data of the current period is in the adjustment zone, a control analysis signal is generated;

[0026] If the field null value number of the line operation data of the current period is in the danger zone, a fault signal is generated.

[0027] Preferably, the field null value number of the line operation data of all collection periods in the analysis period is taken as Y-axis coordinate data, and the end moment of the collection period is taken as X-axis coordinate data, which are taken as coordinate points input into the line operation data field null value number and time coordinate system to obtain a line operation data curve;

[0028] Calculating the difference between the field null value number of the line operation data of the current period and the field null value number of the line operation data of the analysis period start period, and calculating the ratio between the obtained difference value and the time interval between the current period and the analysis period start period to obtain a slope difference value XLC.

[0029] The difference between the number of nulls of all collection periods in the analysis period and the collection period null number threshold is obtained, and all the differences are calculated by the variance formula to obtain the floating value FDZ.

[0030] Preferably, the slope difference XLC and the floating value FDZ are substituted into the formula BHZ=XLC×a1+FDZ×a2 to obtain the field null change value BHZ, wherein a1 and a2 are both preset proportion coefficients, and a1+a2=1, a1 is the influence degree coefficient of the slope difference XLC on the field null change value BHZ, and a2 is the influence degree coefficient of the floating value FDZ on the field null change value BHZ.

[0031] Preferably, the influence degree of the field null change value on the line output transmission is judged, specifically:

[0032] The field null change value BHZ is calculated by the difference value with the field null change value threshold to obtain the null change difference value KBC, and the null change difference value KBC is compared with the preset null change difference value YKC:

[0033] If the null change difference value KBC is greater than or equal to the preset null change difference value YKC, it indicates that the field null change value exceeds the standard, and a large influence degree signal is generated;

[0034] If the null change difference value KBC is less than the preset null change difference value YKC, it indicates that the field null change value does not exceed the standard, indicating a small influence degree signal.

[0035] Preferably, the line is adjusted according to the influence degree, specifically:

[0036] After receiving the large influence degree signal, the alarm is controlled to issue an alarm, indicating that the line transmission effect in the analysis period affects the actual use, and immediate stop maintenance is required;

[0037] After receiving the small influence degree signal, the line is predicted to judge the length of time that the line can continue to be used.

[0038] Preferably, the length of time that the line can continue to be used is judged, specifically:

[0039] All rising trend curve segments and falling trend curve segments in the line operation data curve are obtained, the Y-axis coordinate data of all coordinate points in each rising trend curve segment is summed to obtain a rising total value, the Y-axis coordinate data of all coordinate points in each falling trend curve segment is summed to obtain a falling total value, the difference between the rising total value and the falling total value is obtained as a growth value ZZ;

[0040] The total time of the analysis period is ST, and the formula is used to obtain the growth rate value ZV;

[0041] The field null value quantity KS of the current period of the line is obtained, and the second data field null value quantity threshold DEY is obtained through the formula The line can continue to use duration CXT is obtained.

[0042] The beneficial effects of the present application are as follows:

[0043] 1. The 2M line remote monitoring and management platform disclosed by the present application, in a specific embodiment, divides the analysis period into a plurality of collection periods by setting the analysis period, obtains the slope difference value and the floating value in the analysis period, and calculates the field null value change value through the slope difference value and the floating value; the field null value change value can reflect the influence degree on the line output transmission, judge the influence degree of the line data transmission on the actual use process, and make corresponding processing measures in combination with the influence degree.

[0044] 2. The 2M line remote monitoring and management platform disclosed by the present application, when the adjustment prediction module receives a large influence degree signal or a data missing signal, it indicates that the line transmission data cannot be normally used and needs to be immediately stopped for maintenance; and after receiving a small influence degree signal, it indicates that the line can continue to be used, but the line sustainable use time needs to be predicted to judge whether the remaining transmission work can be completed, if the line sustainable use time can complete the transmission work, the line does not need to be immediately stopped for maintenance, and the maintenance can be performed after the work is completed, which can ensure the work efficiency without affecting the actual use. BRIEF DESCRIPTION OF DRAWINGS

[0045] The present application will be further described below with reference to the accompanying drawings.

[0046] Figure 1 is a system flowchart of the first embodiment of the present application;

[0047] Figure 2 is a field null value change value acquisition flowchart in the second embodiment of the present application. DETAILED DESCRIPTION

[0048] In order to make the technical means, creative features, purposes and effects realized by the present application easy to understand, the present application will be further described below with reference to the specific embodiments.

[0049] Embodiment one

[0050] As shown in Figure 1 , the 2M line remote monitoring and management platform disclosed by the present application embodiment comprises a front-end collection device, a data analysis module, a judgment module and an adjustment prediction module.

[0051] The front-end acquisition device is used to acquire line operation data, a data missing coefficient value is obtained by analyzing the line operation data, and a data state signal is obtained according to the data missing coefficient value; wherein the data state signal comprises a data completeness signal and a data missing signal;

[0052] The data analysis module, based on the data completeness signal, establishes a line operation data field null value number and time coordinate system, takes the field null value number of the line operation data as the Y axis, takes time as the X axis, sets a first data field null value number threshold and a second data field null value number threshold, and the first data field null value number threshold is less than the second data field null value number threshold, and marks the first data field null value number threshold and the second data field null value number threshold in the line operation data field null value number and time coordinate system to obtain two straight lines parallel to the X axis; mark the area below the first data field null value number threshold line as a high-quality area, the area between the first data field null value number threshold line and the second data field null value number threshold line as an adjustment area, and the area above the second data field null value number threshold line as a dangerous area;

[0053] The judgment module acquires line operation data of the current period, judges, and generates a control signal; the control signal comprises a line sustainable operation signal and a control analysis signal;

[0054] The adjustment prediction module, after obtaining the control analysis signal, sets an analysis period, divides the analysis period into a plurality of acquisition periods, and acquires a field null value change value; according to the change value, judges the influence degree of the line output transmission, and adjusts the power transmission line according to the influence degree.

[0055] The data missing coefficient value is obtained by analyzing the line operation data, specifically:

[0056] The line operation time period is divided into a plurality of time subunits, the line operation data field of each subunit is acquired, the null value number of the data field of each subunit is queried through SQL, and the null value number of the data field of each subunit is compared with the subunit null value number threshold:

[0057] If the null value number of the data field of the subunit is greater than the subunit null value number threshold, it indicates that the null value number of the data field of the subunit exceeds the standard, a data null value number abnormal signal is generated, and the subunit is marked as a data abnormal subunit;

[0058] Conversely, if the null value number of the data field of the subunit is less than or equal to the subunit null value number threshold, it indicates that the null value number of the data field of the subunit meets the standard, a data null value number normal signal is generated, and the subunit is marked as a data normal subunit;

[0059] Based on the data null number abnormal signal, the ratio of the null number of the data abnormal subunit to the total number of characters of the corresponding subunit is obtained, denoted as an abnormal null value ratio; the abnormal null value ratio of each subunit is subjected to variance calculation to obtain an abnormal ratio fluctuation value;

[0060] The maximum and minimum values of the null number in all subunits are obtained, and the difference between the maximum and minimum values of the null number is calculated to obtain a null deviation value;

[0061] The null number variance value of the line is multiplied by the null deviation value to obtain a data loss coefficient value.

[0062] In one specific embodiment, SQL is a standard programming language for managing and operating a relational database system; using SQL can perform various operations on the database, such as querying, updating, deleting, and inserting numbers, and through SQL, the null number of the data field of each subunit can be queried, the subunit null number threshold is set according to actual experience, and the actual query value is compared with the subunit null number threshold, when the actual query value is greater than the subunit null number threshold, a data null number abnormal signal is generated, and the subunit is marked as a data abnormal subunit, when the null number of the data field of the subunit is less than or equal to the subunit null number threshold, a data null number normal signal is generated, and the subunit is marked as a data normal subunit; the variance value of the abnormal null value ratio of all data abnormal subunits is obtained to obtain an abnormal ratio fluctuation value, the abnormal null value ratio is the ratio of the null number of the data abnormal subunit to the total number of characters of the corresponding subunit, and the abnormal ratio fluctuation value reflects the fluctuation size of the abnormal null value ratio, the larger the abnormal ratio fluctuation value, the greater the null number size change fluctuation of the data abnormal subunit in the line operation period, and the more unstable the signal transmission.

[0063] According to the data loss coefficient value, a data state signal is obtained, specifically:

[0064] The data loss coefficient value is compared with a data loss coefficient threshold value;

[0065] If the data loss coefficient value is greater than or equal to the data loss coefficient threshold value, it indicates that the null number of the data abnormal subunit changes greatly in the line operation period, and complete information data transmission cannot be performed in the line operation period, a data loss signal is generated;

[0066] If the data loss coefficient value is less than the data loss coefficient threshold value, it indicates that the null number of the data abnormal subunit changes less in the line operation period, and complete information data transmission can be performed in the line operation period, a data integrity signal is generated.

[0067] It should be noted that the data loss coefficient threshold value represents the maximum value of data loss that the line can withstand to realize normal data transmission, which can be set according to historical experience; the data loss signal indicates that the number of null values of the data abnormality subunit changes greatly in the line operation time period, and complete information data transmission cannot be performed in the line operation time period; and the data integrity signal indicates that although the line exists data loss when transmitting signals, it can still transmit the basic framework content, for example, audio data transmission. The data integrity signal indicates that a small amount of data is missing, but only the voice is missing when playing a part, which can affect the information receiving degree of the listener, but the audio can still be played normally, and the data loss signal in this embodiment indicates that the audio cannot be normally played, and the listener cannot receive the audio information at all.

[0068] Embodiment two

[0069] As shown in Figure 2 , the line operation data of the current period is obtained, judged, and a control signal is generated, specifically:

[0070] The field null value number of the line operation data of the current period is obtained, and the field null value number is substituted into the line operation data field null value number and time coordinate system;

[0071] If the field null value number of the line operation data of the current period is in the high-quality area, a line sustainable working signal is generated;

[0072] If the field null value number of the line operation data of the current period is in the adjustment area, a control analysis signal is generated;

[0073] If the field null value number of the line operation data of the current period is in the danger area, a fault signal is generated.

[0074] It should be noted that the high-quality area is located in the current period field null value, which will not affect the line transmission effect, and the data transmission quality is good; the adjustment area is located between the first data field null value number threshold value straight line and the second data field null value number threshold value straight line, indicating that the field null value number in the current period needs to be further analyzed and determined to determine whether the line transmission data affects the actual use effect, whether to continue to work or to stop maintenance, and a control analysis signal is needed; the danger area indicates that the current period field null value is more, which affects the normal use, and the actual use effect is poor, and the line needs to be stopped for maintenance immediately.

[0075] The field null value number of the line operation data of all collection periods in the analysis period is taken as the Y-axis coordinate data, and the end time of the collection period is taken as the X-axis coordinate data, which is input into the line operation data field null value number and time coordinate system as coordinate points, to obtain the line operation data curve;

[0076] The difference between the number of null values of the field of the line operation data of the current period and the number of null values of the field of the line operation data of the analysis period starting period is calculated, and the obtained difference is divided by the time interval between the current period and the analysis period starting period to obtain a slope difference XLC;

[0077] The difference between the number of null values of all collection periods in the analysis period and the collection period null value threshold is obtained, and all the differences are calculated by a variance formula to obtain a floating value FDZ.

[0078] The slope difference XLC and the floating value FDZ are substituted into the formula BHZ=XLC×a1+FDZ×a2 to obtain a field null value change value BHZ, wherein a1 and a2 are both preset proportion coefficients, and a1+a2=1, a1 is a degree of influence coefficient of the slope difference XLC on the field null value change value BHZ, and a2 is a degree of influence coefficient of the floating value FDZ on the field null value change value BHZ.

[0079] In one specific embodiment, the slope difference XLC is the difference between the number of null values of the field of the line operation data of the current period and the number of null values of the field of the line operation data of the analysis period starting period, and is further divided by the time interval, which can reflect whether the line operation data curve is in an upward trend or a downward trend from the starting time to the current time, and can reflect the change degree of the number of null values of the field of the line operation data of the current period and the number of null values of the field of the line operation data of the analysis period starting period. The floating value FDZ is the difference between the number of null values of all collection periods in the analysis period and the collection period null value threshold, and is obtained by calculating the variance of all the differences. The field null value change value BHZ is calculated according to the degree of influence coefficients of the slope difference XLC and the floating value FDZ. The greater the field null value change value BHZ, the greater the change degree of the line operation data curve in the analysis period, and the greater the degree of influence on the line output transmission.

[0080] The collection period null value threshold is set according to historical experience.

[0081] It should be noted that by setting the analysis period, the analysis period is divided into a plurality of collection periods, the slope difference XLC and the floating value FDZ in the analysis period are obtained, and the field null value change value BHZ is calculated by the slope difference XLC and the floating value FDZ. The field null value change value BHZ can reflect the degree of influence on the line output transmission.

[0082] According to the field null value change value, the degree of influence on the line output transmission is judged, specifically:

[0083] The difference between the field null value change value BHZ and the field null value change value threshold is calculated to obtain a null value change difference KBC, and the null value change difference KBC is compared with a preset null value change difference YKC:

[0084] If the empty variation value KBC is greater than or equal to the preset empty variation value YKC, it indicates that the field empty value change value exceeds the standard, and a large impact signal is generated.

[0085] If the empty variation value KBC is less than the preset empty variation value YKC, it indicates that the field empty value change value does not exceed the standard, indicating a small impact signal.

[0086] It should be noted that the large impact signal is obtained by the empty variation value KBC greater than or equal to the preset empty variation value YKC. The large impact signal represents that although the line can transmit data, and the transmitted data can also analyze the data complete signal, but the actual use of the data has a large impact, for example, the voice quality may be poor, the video may have distortion and other phenomena, which affect the actual use. The small impact signal is obtained by the empty variation value KBC being less than the preset empty variation value YKC, and the actual use has little impact and can continue to work normally. The field empty value change value can intelligently distinguish the impact degree of the actual use in the line transmission, improve the use experience, and ensure the data transmission quality.

[0087] The field empty value change value threshold and the preset empty variation value YKC are preset values, which are set artificially according to historical experience.

[0088] Embodiment three

[0089] According to the impact degree, the line is adjusted, specifically:

[0090] After receiving the large impact signal, the alarm is controlled to issue an alarm, indicating that the line transmission effect in the analysis period affects the actual use, and needs to be stopped for maintenance immediately.

[0091] After receiving the small impact signal, the line is predicted to determine the length of time the line can continue to be used.

[0092] It should be noted that the adjustment prediction module receives the large impact signal or the data missing signal, which indicates that the line transmission data cannot be normally used, and needs to be stopped for maintenance immediately. After receiving the small impact signal, it indicates that the line can continue to be used, but the sustainable use time of the line needs to be predicted to determine whether the remaining transmission work can be completed. If the line can be used for a sustainable time, it can not be necessary to stop the line for maintenance immediately, and the line can be maintained after the work is completed, to ensure the work efficiency.

[0093] The length of time the line can continue to be used is determined, specifically:

[0094] Obtain all rising trend curve segments and falling trend curve segments in the line operation data curve, sum all Y-axis coordinate data of all coordinate points in each rising trend curve segment to obtain a rising total value, sum all Y-axis coordinate data of all coordinate points in each falling trend curve segment to obtain a falling total value, obtain a difference value between the rising total value and the falling total value as a growth value ZZ;

[0095] Obtain a total time ST of the analysis period, and obtain a growth rate value ZV by using a formula

[0096] Obtain a field null value number KS of the line current period and a second data field null value number threshold DEY, and obtain a line continued use time length CXT by using a formula

[0097] It should be noted that the growth value ZZ is a difference value between a rising total value obtained by summing all Y-axis coordinate data of all coordinate points in each rising trend curve segment and a falling total value obtained by summing all Y-axis coordinate data of all coordinate points in each falling trend curve segment, and represents a whole growth value of the field null value data in the analysis period. The growth value is divided by the total time ST of the analysis period to obtain the growth rate value ZV. The difference value between the field null value number KS of the line current period and the second data field null value number threshold DEY is divided by the growth rate value ZV to obtain a time when the character null value number grows to the second data field null value number threshold. In combination with the line working residual time, it can be analyzed that the line needs to be immediately stopped for maintenance, and the working efficiency is ensured without affecting the actual use.

[0098] The basic principles, main features and advantages of the present application are shown and described above. It should be understood by those skilled in the art that the present application is not limited by the above embodiments, and the above embodiments and descriptions in the specification are only to illustrate the principles of the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the present application. The scope of protection of the present application is defined by the appended claims and their equivalents.​​

Claims

1. A remote monitoring and management platform based on a 2M line, characterized in that: include A front-end acquisition device is used to acquire line operation data, analyze the line operation data to obtain a data missing coefficient value, and obtain a data status signal based on the data missing coefficient value; wherein, the data status signal includes a data integrity signal and a data missing signal; The data analysis module, based on the data integrity signal, establishes a coordinate system for the number of null values ​​in the line operation data fields and time. The number of null values ​​in the line operation data fields is used as the Y-axis, and time as the X-axis. A first threshold and a second threshold for the number of null values ​​in the data fields are set, with the first threshold being less than the second threshold. These two thresholds are then marked on the coordinate system, resulting in two straight lines parallel to the X-axis. The area below the first threshold line is marked as a high-quality zone, the area between the first and second threshold lines is marked as an adjustment zone, and the area above the second threshold line is marked as a danger zone. The judgment module acquires the line operation data for the current time period, makes a judgment, and generates a control signal; the control signal includes a line continuous operation signal and a control analysis signal; The prediction module is adjusted by setting an analysis period after receiving the control analysis signal. The analysis period is divided into several acquisition periods. The difference between the number of null values ​​in the field of the line operation data in the current period and the number of null values ​​in the field of the line operation data at the beginning of the analysis period is calculated. The obtained difference is then compared with the time interval between the current period and the beginning of the analysis period to obtain the slope difference. The difference between the number of null values ​​in all acquisition periods within the analysis period and the threshold number of null values ​​in each acquisition period is obtained. All differences are calculated using the variance formula to obtain the floating value. The change value of the field null value is calculated using the slope difference and the floating value. The degree of impact on the line output transmission is determined based on the change value of the field null value, and the transmission line is adjusted accordingly.

2. The remote monitoring and management platform based on a 2M line according to claim 1, characterized in that: The data missing coefficient value was obtained by analyzing the line operation data, specifically: The line operation time period is divided into several time sub-units. The line operation data fields of each sub-unit are obtained. The number of null values ​​in the data fields of each sub-unit is queried using SQL. The number of null values ​​in the data fields of each sub-unit is compared with the null value threshold of the sub-unit. If the number of null values ​​in the data field of a sub-unit exceeds the threshold for the number of null values ​​in the sub-unit, it indicates that the number of null values ​​in the data field of the sub-unit exceeds the limit, generating an abnormal signal for the number of null values ​​and marking the sub-unit as a data abnormal sub-unit. Conversely, if the number of null values ​​in the data field of a sub-unit is less than or equal to the threshold for the number of null values ​​in the sub-unit, it indicates that the number of null values ​​in the data field of that sub-unit meets the standard, a normal null value signal is generated, and the sub-unit is marked as a normal data sub-unit.

3. The remote monitoring and management platform based on a 2M line according to claim 2, characterized in that: Based on the abnormal signal of the number of null values ​​in the data, the ratio of the number of null values ​​in the abnormal data sub-unit to the total number of characters in the corresponding sub-unit is obtained and recorded as the abnormal null value ratio; the variance of the abnormal null value ratio of each sub-unit is calculated to obtain the abnormal fluctuation value. Obtain the maximum and minimum number of empty values ​​in all sub-units, calculate the difference between the maximum number of empty values ​​and the minimum number of control values, and obtain the empty value deviation value. The missing data coefficient is obtained by multiplying the variance of the number of missing data in the line by the missing data deviation.

4. The remote monitoring and management platform based on a 2M line according to claim 3, characterized in that: The data status signal is obtained based on the missing data coefficient value, specifically: Compare the missing data coefficient value with the missing data coefficient threshold; If the data missing coefficient value is greater than or equal to the data missing coefficient threshold, it indicates that the number of missing values ​​in the abnormal data sub-unit changes significantly during the line operation period, and complete information data cannot be transmitted during the line operation period, thus generating a data missing signal. If the data missing coefficient value is less than the data missing coefficient threshold, it indicates that the number of missing values ​​in the abnormal data sub-units changes little during the line operation period, and that complete information data can be transmitted and a complete data signal can be generated during the line operation period.

5. The remote monitoring and management platform based on a 2M line according to claim 1, characterized in that: Obtain the line operation data for the current time period, make judgments, and generate control signals, specifically: Get the number of null values ​​in the field of the line operation data for the current time period, and substitute the number of null values ​​into the line operation data field null value and time coordinate system; If the number of null values ​​in the field of the line operation data for the current time period is in the high-quality zone, a signal for continuous line operation will be generated. If the number of null values ​​in the field of the line operation data for the current time period is in the adjustment zone, a control analysis signal will be generated. A fault signal is generated if the number of null values ​​in a field of the line operation data for the current time period is in the danger zone.

6. The remote monitoring and management platform based on a 2M line according to claim 1, characterized in that: The number of null values ​​in the field of the line operation data for all collection periods within the analysis period is used as the Y-axis coordinate data, and the end time of the collection period is used as the X-axis coordinate data. These coordinate points are then input into the line operation data field null value number and time coordinate system to obtain the line operation data curve.

7. A remote monitoring and management platform based on a 2M line according to claim 6, characterized in that: Substitute the slope difference XLC and the floating value FDZ into the formula The field null value change value BHZ is obtained, where a1 and a2 are both preset proportional coefficients, and a1+a2=1. a1 is the influence coefficient of the slope difference XLC on the field null value change value BHZ, and a2 is the influence coefficient of the floating value FDZ on the field null value change value BHZ.

8. A remote monitoring and management platform based on a 2M line according to claim 7, characterized in that: The impact on line output transmission is determined based on the change in the field null value BHZ. Specifically: The difference between the field null value change value BHZ and the field null value change threshold is calculated to obtain the null value change difference value KBC. The null value change difference value KBC is then compared with the preset null value change difference value YKC. If the null value KBC is greater than or equal to the preset null value YKC, it indicates that the field null value change exceeds the standard, generating a signal with a large impact. If the null value variation KBC is less than the preset null value variation YKC, it indicates that the field null value variation value has not exceeded the standard, indicating that the impact is small.

9. A remote monitoring and management platform based on a 2M line according to claim 8, characterized in that: The routes will be adjusted according to the degree of impact, specifically as follows: Upon receiving a signal indicating a significant impact, the control alarm will sound, indicating that the line transmission performance within the analysis period is affecting actual use and requires immediate shutdown and maintenance. After receiving a signal with a small impact, the system predicts the line's continued usability and determines how long it can be used.

10. A remote monitoring and management platform based on a 2M line according to claim 9, characterized in that: The remaining usable time of the line is determined as follows: Obtain all upward and downward trend curve segments in the line operation data curve. Sum the Y-axis coordinate data of all coordinate points in each upward trend curve segment to obtain the total upward value. Sum the Y-axis coordinate data of all coordinate points in each downward trend curve segment to obtain the total downward value. Obtain the difference between the total upward value and the total downward value as the growth value ZZ. The total time of the analysis period is obtained as ST, using the formula. The growth rate value ZV is obtained; Obtain the number of null values ​​in the current data field KS and the threshold number of null values ​​in the second data field DEY for the current time period of the line, using the formula The remaining usable time for the line is CXT.

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