Remote monitoring and management platform based on 2M line

Abstract

The invention belongs to the technical field of line remote monitoring, and particularly relates to a remote monitoring and management platform based on a 2M line, which comprises front-end acquisition equipment, a data analysis module, a judgment module and an adjustment prediction module, analyzing the line operation data to obtain a data missing coefficient value, 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 time coordinate system based on the data complete signal, setting an analysis period, dividing the analysis period into a plurality of acquisition time periods, 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 on line output transmission, the influence degree of line data transmission on the actual use process is judged, and corresponding processing measures are taken in combination with the influence degree.

Description

Technical Field

[0001] The invention belongs to the technical field of line remote monitoring, in particular to a 2M line-based remote monitoring and management platform. Background Art

[0002] The remote monitoring and management platform based on 2M lines is a comprehensive system that integrates network communication, video processing, data storage and remote management functions. This platform is usually used in scenarios that require remote monitoring and management, such as the military, enterprises, schools, etc., where the 2M line (i.e., the line with 2Mbps bandwidth) is used as the basis for data transmission to ensure the real-time and stability of monitoring data.

[0003] Traditional monitoring systems have problems such as slow transmission speed and large data volume. During line transmission, it is impossible to judge the quality of data transmission. The integrity of the data can only be judged through a simple threshold comparison based on the number of empty field values. For some data that meet the threshold judgment, the number of empty field values ​​has different degrees of influence, which can easily lead to poor data transmission quality and affect normal use.

[0004] To this end, the present invention provides a remote monitoring and management platform based on a 2M line. Summary of the invention

[0005] In order to make up for the deficiencies of the prior art, at least one technical problem raised in the background technology is solved.

[0006] The technical solution adopted by the present invention to solve the technical problem is: the 2M line-based remote monitoring and management platform described in the present invention includes:

[0007] A front-end acquisition device, the front-end acquisition device is used to collect line operation data, obtain a data missing coefficient value by analyzing the line operation data, and obtain a data status signal according to the data missing coefficient value; wherein the data status signal includes a data complete signal and a data missing 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 line operation data field null value quantity as the Y axis and the time as the X axis, sets a first data field null value quantity threshold and a second data field null value quantity threshold, and the first data field null value quantity threshold is less than the second data field null value quantity threshold, and marks the first data field null value quantity threshold and the second data field null value quantity threshold in the line operation data field null value quantity and time coordinate system to obtain two straight lines parallel to the X axis; marks the area below the first data field null value quantity threshold straight line as a high-quality area, marks the area between the first data field null value quantity threshold straight line and the second data field null value quantity threshold straight line as an adjustment area, and marks the area above the second data field null value quantity threshold straight line as a danger zone;

[0009] A judgment module, which obtains the line operation data of the current period, makes a 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 sets the analysis period after obtaining the regulation analysis signal, divides the analysis period into several collection periods, and obtains the change value of the field null value; judges the degree of influence on the line output transmission according to the change value, and adjusts the transmission line according to the degree of influence.

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

[0012] Divide the line operation time period into several time sub-units, obtain the line operation data field of each sub-unit, query the number of null values ​​in the data field of each sub-unit through SQL, and compare the number of null values ​​in the data field of each sub-unit with the sub-unit null value number threshold:

[0013] If the number of null values ​​in the data field of a subunit is greater than the subunit null value number threshold, it indicates that the number of null values ​​in the data field of the subunit exceeds the limit, a data null value number abnormality signal is generated, and the subunit is marked as a data abnormality subunit;

[0014] On the contrary, if the number of null values ​​in the data field of the subunit is less than or equal to the subunit null value number threshold, it indicates that the number of null values ​​in 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, the ratio of the number of null values ​​in the data abnormal subunit to the total number of characters in the corresponding subunit is obtained, which is recorded as the abnormal null value ratio; the abnormal null value ratio of each subunit is calculated for variance to obtain the abnormal ratio fluctuation value;

[0016] Obtain the maximum and minimum null value numbers in all subunits, calculate the difference between the maximum null value number and the minimum control number, and obtain the null value deviation value;

[0017] Multiply the variance value of the number of null values ​​of the line by the null value deviation value to obtain the data missing coefficient value.

[0018] Preferably, the data status signal is obtained according to the data missing coefficient value, specifically:

[0019] comparing the missing data coefficient value with the missing data coefficient threshold;

[0020] If the data missing coefficient value is greater than or equal to the data missing coefficient threshold, it indicates that the number of null values ​​of the data anomaly subunit changes significantly during the line operation period, and complete information data transmission cannot be performed during the line operation period, generating a data missing signal;

[0021] If the data missing coefficient value is less than the data missing coefficient threshold, it indicates that the number of null values ​​of the data anomaly sub-unit changes little during the line operation time period, and complete information data can be transmitted during the line operation time period to generate a data complete signal.

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

[0023] Obtain the number of null values ​​in the field of the line operation data of the current period, and substitute the number of null values ​​in the field into the number of null values ​​in the line operation data field and the time coordinate system;

[0024] If the number of null values ​​in the field 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 number of null values ​​in the field of the line operation data of the current period is in the adjustment zone, a control analysis signal is generated;

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

[0027] Preferably, the number of null values ​​in the field of the line operation data of all the collection periods in 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, which are input as coordinate points into the line operation data field null value number and time coordinate system to obtain the line operation data curve;

[0028] 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 in the start period of the analysis period is calculated, and the obtained difference is calculated by the ratio of the time interval between the current period and the start period of the analysis period to obtain the slope difference XLC;

[0029] Obtain the difference between the number of null values ​​in all collection periods within the analysis period and the threshold value of the number of null values ​​in the collection period, calculate all the differences through the variance formula, and 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 value change value BHZ, wherein 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.

[0031] Preferably, the influence degree on the line output transmission is determined according to the field null value change value pair, specifically:

[0032] Calculate the difference between the field null value change value BHZ and the field null value change value threshold to obtain the null value difference KBC, and compare the null value difference KBC with the preset null value difference YKC:

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

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

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

[0036] After receiving a signal indicating a high degree of impact, the control alarm will sound an alarm, indicating that the line transmission effect during the analysis period affects actual use and needs to be stopped for maintenance immediately;

[0037] After receiving a small signal indicating the degree of impact, a prediction is made on the line to determine how long the line can continue to be used.

[0038] Preferably, the duration for which the line can continue to be used is determined as follows:

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

[0040] Get the total time of the analysis cycle as ST, using the formula Get the growth rate value ZV;

[0041] Get the number of field null values ​​KS and the second data field null value threshold DEY in the current period of the line, and use the formula Get the line's continued usability time CXT.

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

[0043] 1. The present invention discloses a remote monitoring and management platform based on a 2M line. In a specific embodiment, an analysis period is set to divide the analysis period into a number of collection periods, the slope difference and floating value within the analysis period are obtained, and the field null value change value is calculated by the slope difference and floating value; the field null value change value can reflect the degree of influence on the line output transmission, judge the degree of influence of the line data transmission on the actual use process, and make corresponding processing measures according to the degree of influence.

[0044] 2. The 2M line remote monitoring and management platform described in the present invention, when the adjustment prediction module receives a large impact signal or a data missing signal, it indicates that the line transmission data cannot be used normally and needs to be stopped for maintenance immediately; after receiving a small impact signal, it indicates that the line can continue to be used, but it is necessary to predict the sustainable use time of the line to determine whether the remaining transmission work can be completed. If the transmission work can be completed within the sustainable use time of the line, there is no need to stop the line for maintenance immediately, and maintenance can be carried out after the work is completed, thereby ensuring work efficiency without affecting actual use. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The present invention will be further described below in conjunction with the accompanying drawings.

[0046] Figure 1 is a system flow chart of Embodiment 1 of the present invention;

[0047] Figure 2 This is a flow chart for obtaining the change value of the field null value in the second embodiment of the present invention. DETAILED DESCRIPTION

[0048] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0049] Embodiment 1

[0050] like Figure 1 As shown, a 2M line-based remote monitoring and management platform according to an embodiment of the present invention includes a front-end acquisition device, a data analysis module, a judgment module, and an adjustment prediction module;

[0051] A front-end acquisition device, the front-end acquisition device is used to collect line operation data, obtain a data missing coefficient value by analyzing the line operation data, and obtain a data status signal according to the data missing coefficient value; wherein the data status signal includes a data complete signal and a data missing signal;

[0052] 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 line operation data field null value quantity as the Y axis and the time as the X axis, sets a first data field null value quantity threshold and a second data field null value quantity threshold, and the first data field null value quantity threshold is less than the second data field null value quantity threshold, and marks the first data field null value quantity threshold and the second data field null value quantity threshold in the line operation data field null value quantity and time coordinate system to obtain two straight lines parallel to the X axis; marks the area below the first data field null value quantity threshold straight line as a high-quality area, marks the area between the first data field null value quantity threshold straight line and the second data field null value quantity threshold straight line as an adjustment area, and marks the area above the second data field null value quantity threshold straight line as a danger zone;

[0053] A judgment module, which obtains the line operation data of the current period, makes a judgment, and generates a control signal; the control signal includes a line sustainable operation signal and a control analysis signal;

[0054] The adjustment prediction module sets the analysis period after obtaining the regulation analysis signal, divides the analysis period into several collection periods, and obtains the change value of the field null value; judges the degree of influence on the line output transmission according to the change value, and adjusts the transmission line according to the degree of influence.

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

[0056] Divide the line operation time period into several time sub-units, obtain the line operation data field of each sub-unit, query the number of null values ​​in the data field of each sub-unit through SQL, and compare the number of null values ​​in the data field of each sub-unit with the sub-unit null value number threshold:

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

[0058] On the contrary, if the number of null values ​​in the data field of the subunit is less than or equal to the subunit null value number threshold, it indicates that the number of null values ​​in 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 value number abnormal signal, the ratio of the number of null values ​​in the data abnormal sub-unit to the total number of characters in the corresponding sub-unit is obtained, which is 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 ratio fluctuation value;

[0060] Obtain the maximum and minimum null value numbers in all subunits, calculate the difference between the maximum null value number and the minimum control number, and obtain the null value deviation value;

[0061] Multiply the variance value of the number of null values ​​of the line by the null value deviation value to obtain the data missing coefficient value.

[0062] In a specific embodiment, SQL is a standard programming language for managing and operating relational database systems; SQL can be used to perform various operations on the database, such as query, update, delete and insert. The number of null values ​​in the data field of each sub-unit can be queried through SQL. The sub-unit null value number threshold is set according to actual experience. The sub-unit null value number threshold can be set manually. The actual number of null values ​​queried is compared with the sub-unit null value number threshold. When the actual query value is greater than the sub-unit null value number threshold, a data null value number abnormal signal is generated, and the sub-unit is marked as a data null value abnormal signal. An abnormal sub-unit generates a data null value number normal signal when the number of null values ​​in the data field of the sub-unit is less than or equal to the sub-unit null value number threshold, and marks the sub-unit as a data normal sub-unit; an abnormal ratio fluctuation value is obtained by obtaining the variance value of the abnormal null value ratio of all data abnormal sub-units, and the abnormal null value ratio is the ratio of the number of null values ​​of the data abnormal sub-unit to the total number of characters of the corresponding sub-unit. 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 fluctuation in the number of null values ​​of the data abnormal sub-unit during the line operation period, and the more unstable the signal transmission.

[0063] The data status signal is obtained according to the data missing coefficient value, specifically:

[0064] comparing the missing data coefficient value with the missing data coefficient threshold;

[0065] If the data missing coefficient value is greater than or equal to the data missing coefficient threshold, it indicates that the number of null values ​​of the data anomaly subunit changes significantly during the line operation period, and complete information data transmission cannot be performed during the line operation period, generating a data missing signal;

[0066] If the data missing coefficient value is less than the data missing coefficient threshold, it indicates that the number of null values ​​of the data anomaly sub-unit changes little during the line operation time period, and complete information data can be transmitted during the line operation time period to generate a data complete signal.

[0067] It should be noted that the data missing coefficient threshold indicates the maximum value of data missing that the line can withstand to achieve normal data transmission, and can be set according to historical experience; the data missing signal indicates that the data missing coefficient value is greater than or equal to the data missing coefficient threshold, indicating that the number of null values ​​of the data abnormality sub-unit changes significantly during the line operation time period, and complete information data cannot be transmitted during the line operation time period; and the data complete signal indicates that although there is data missing when the line is transmitting signals, the basic framework content can still be transmitted, such as audio data transmission. The data complete signal indicates that a small amount of data is missing, but only part of the voice is missing when the segment is played, which can affect the listener's information reception level, but the audio can still be played normally, and the data missing signal in this embodiment indicates that the audio cannot be played normally and the listener cannot receive the audio information at all.

[0068] Embodiment 2

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

[0070] Obtain the number of null values ​​in the field of the line operation data of the current period, and substitute the number of null values ​​in the field into the number of null values ​​in the line operation data field and the time coordinate system;

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

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

[0073] If the number of empty values ​​in the field of the line operation data of the current period is in the danger zone, a fault signal is generated.

[0074] It should be noted that the quality zone indicates that there are fewer null values ​​in the field in the current period, which will not affect the line transmission effect, and the data transmission quality is good; the adjustment zone is between the first data field null value number threshold line and the second data field null value number threshold line, indicating that the number of null values ​​in the field 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 working or stop maintenance, and regulation and analysis signals are required; the danger zone indicates that there are more null values ​​in the field in the current period, which affects normal use, and the actual use effect is poor, and the line needs to be stopped immediately for maintenance.

[0075] The number of null values ​​in the line operation data field of all the collection periods in 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 are used as coordinate points and input into the line operation data field null value number and time coordinate system to obtain the line operation data curve;

[0076] 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 in the start period of the analysis period is calculated, and the obtained difference is calculated by the ratio of the time interval between the current period and the start period of the analysis period to obtain the slope difference XLC;

[0077] Obtain the difference between the number of null values ​​in all collection periods within the analysis period and the threshold value of the number of null values ​​in the collection period, calculate all the differences through the variance formula, and obtain the floating value FDZ.

[0078] Substitute the slope difference XLC and the floating value FDZ into the formula BHZ=XLC×a1+FDZ×a2 to obtain the field null value change value BHZ, where a1 and a2 are 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.

[0079] In a specific embodiment, the slope difference XLC is the difference between the number of field null values ​​of the line operation data in the current period and the number of field null values ​​of the line operation data in the period starting with the analysis period, and then 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 start time to the current time, and can reflect the degree of change of the number of field null values ​​of the line operation data in the current period and the number of field null values ​​of the line operation data in the period starting with the analysis period. The floating value FDZ is the difference between the number of null values ​​in all collection periods in the analysis period and the threshold value of the number of null values ​​in the collection period, and all the differences are obtained by variance calculation. The field null value change value BHZ is calculated according to the influence degree coefficient of the slope difference XLC and the floating value FDZ. The larger the field null value change value BHZ is, the greater the degree of change of the line operation data curve in the analysis period is, and the greater the degree of influence on the line output transmission is.

[0080] The threshold value of the number of null values ​​in the collection period is set according to historical experience.

[0081] It should be noted that by setting the analysis period, the analysis period is divided into several collection periods, the slope difference XLC and the floating value FDZ within 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 impact on the line output transmission.

[0082] The influence on the line output transmission is determined based on the change in the null value of the field:

[0083] Calculate the difference between the field null value change value BHZ and the field null value change value threshold to obtain the null value difference KBC, and compare the null value difference KBC with the preset null value difference YKC:

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

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

[0086] It should be noted that the signal with a large impact degree is obtained when the empty-variant difference value KBC is greater than or equal to the preset empty-variant difference value YKC. The signal with a large impact degree means that although the line can transmit data and the transmitted data can also be analyzed to obtain a complete data signal, the actual use of the data is greatly affected. For example, the voice quality may be poor, and the video may be stuck or distorted, which affects the actual use. The signal with a small impact degree is obtained when the empty-variant difference value KBC is less than the preset empty-variant difference value YKC. In actual use, the data can continue to work normally. The field empty value change value can be used to intelligently judge the impact of the actual use of the line transmission, improve the user experience, and ensure the quality of data transmission.

[0087] The field null value change value threshold and the preset null value difference value YKC are preset values, which are manually set based on historical experience.

[0088] Embodiment 3

[0089] Adjust the lines according to the degree of impact, specifically:

[0090] After receiving a signal indicating a high degree of impact, the control alarm will sound an alarm, indicating that the line transmission effect during the analysis period affects actual use and needs to be stopped for maintenance immediately;

[0091] After receiving a small signal indicating the degree of impact, a prediction is made on the line to determine how long the line can continue to be used.

[0092] It should be noted that when the adjustment prediction module receives a large impact signal or a data missing signal, it means that the line transmission data cannot be used normally and needs to be stopped immediately for maintenance; when a small impact signal is received, it means that the line can still 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 transmission work can be completed within the sustainable use time of the line, there is no need to stop the line for maintenance immediately, and maintenance can be carried out after the work is completed to ensure work efficiency.

[0093] Determine how long the line can continue to be used, specifically:

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

[0095] Get the total time of the analysis cycle as ST, using the formula Get the growth rate value ZV;

[0096] Get the number of field null values ​​KS and the second data field null value threshold DEY in the current period of the line, and use the formula Get the line's continued usable time CXT.

[0097] It should be noted that the growth value ZZ is the total rising value obtained by summing the Y-axis coordinate data of all coordinate points in each rising trend curve segment, and the total falling value is obtained by summing the Y-axis coordinate data of all coordinate points in each falling trend curve segment. The difference between the total rising value and the total falling value is obtained, which represents the overall growth value of the field null value data in the analysis period. The growth value is divided by the total time of the analysis period ST to obtain the growth rate value ZV. The difference between the number of field null values ​​KS in the current period of the line and the second data field null value number threshold DEY can be obtained, and then divided by the growth rate value ZV to obtain the time when the number of character null values ​​increases to the second data field null value number threshold. Combined with the remaining working time of the line, it can be analyzed whether the line needs to stop working immediately for maintenance to ensure work efficiency without affecting actual use.

[0098] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A remote monitoring and management platform based on 2M lines, characterized by: include A front-end acquisition device, the front-end acquisition device is used to collect line operation data, obtain a data missing coefficient value by analyzing the line operation data, and obtain a data status signal according to the data missing coefficient value; wherein the data status signal includes a data complete signal and a data missing signal; 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 line operation data field null value quantity as the Y axis and the time as the X axis, sets a first data field null value quantity threshold and a second data field null value quantity threshold, and the first data field null value quantity threshold is less than the second data field null value quantity threshold, and marks the first data field null value quantity threshold and the second data field null value quantity threshold in the line operation data field null value quantity and time coordinate system to obtain two straight lines parallel to the X axis; marks the area below the first data field null value quantity threshold straight line as a high-quality area, marks the area between the first data field null value quantity threshold straight line and the second data field null value quantity threshold straight line as an adjustment area, and marks the area above the second data field null value quantity threshold straight line as a danger zone; A judgment module, which obtains the line operation data of the current period, makes a judgment, and generates a control signal; the control signal includes a line sustainable operation signal and a control analysis signal; The adjustment prediction module sets the analysis period after obtaining the regulation and analysis signal, divides the analysis period into several collection periods, and obtains the change value of the field null value; judges the degree of influence on the line output transmission according to the change value, and adjusts the transmission line according to the degree of influence.

2. According to claim 1, a 2M line-based remote monitoring and management platform is characterized in that: The data missing coefficient value is obtained by analyzing the line operation data, which is: Divide the line operation time period into several time sub-units, obtain the line operation data field of each sub-unit, query the number of null values ​​in the data field of each sub-unit through SQL, and compare the number of null values ​​in the data field of each sub-unit with the sub-unit null value number threshold: If the number of null values ​​in the data field of a subunit is greater than the subunit null value number threshold, it indicates that the number of null values ​​in the data field of the subunit exceeds the limit, a data null value number abnormality signal is generated, and the subunit is marked as a data abnormality subunit; On the contrary, if the number of null values ​​in the data field of the subunit is less than or equal to the subunit null value number threshold, it indicates that the number of null values ​​in the data field of the subunit meets the standard, a normal data null value number signal is generated, and the subunit is marked as a normal data subunit.

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

4. According to claim 3, a 2M line-based remote monitoring and management platform is characterized in that: The data status signal is obtained according to the data missing coefficient value, specifically: comparing 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 null values ​​of the data anomaly subunit changes significantly during the line operation period, and complete information data transmission cannot be performed during the line operation period, 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 null values ​​of the data anomaly sub-unit changes little during the line operation time period, and complete information data can be transmitted during the line operation time period to generate a data complete signal.

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

6. According to claim 1, a 2M line-based remote monitoring and management platform is characterized in that: The number of null values ​​in the line operation data field of all the collection periods in 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 are used as coordinate points and input into the line operation data field null value number and time coordinate system to obtain the line operation data curve; 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 in the start period of the analysis period is calculated, and the obtained difference is calculated by the ratio of the time interval between the current period and the start period of the analysis period to obtain the slope difference XLC; Obtain the difference between the number of null values ​​in all collection periods within the analysis period and the threshold value of the number of null values ​​in the collection period, calculate all the differences through the variance formula, and obtain the floating value FDZ.

7. A 2M line-based remote monitoring and management platform according to claim 6, characterized in that: Substitute the slope difference XLC and the floating value FDZ into the formula BHZ=XLC×a1+FDZ×a2 to obtain the field null value change value BHZ, where a1 and a2 are 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. The 2M line-based remote monitoring and management platform according to claim 7 is characterized in that: According to the BHZ value of the field null value change, the impact on the line output transmission is judged, specifically: Calculate the difference between the field null value change value BHZ and the field null value change value threshold to obtain the null value difference KBC, and compare the null value difference KBC with the preset null value difference YKC: If the empty variation difference value KBC is greater than or equal to the preset empty variation difference value YKC, it indicates that the field empty value change value exceeds the standard, and a signal with a large impact degree is generated; If the empty variation difference value KBC is less than the preset empty variation difference value YKC, it indicates that the field empty value change value does not exceed the standard, indicating that the impact degree is a small signal.

9. A 2M line-based remote monitoring and management platform according to claim 8, characterized in that: Adjust the lines according to the degree of impact, specifically: After receiving a signal indicating a high degree of impact, the control alarm will sound an alarm, indicating that the line transmission effect during the analysis period affects actual use and needs to be stopped for maintenance immediately; After receiving a small signal indicating the degree of impact, a prediction is made on the line to determine how long the line can continue to be used.

10. A 2M line-based remote monitoring and management platform according to claim 9, characterized in that: Determine how long the line can continue to be used, specifically: Obtain all the rising trend curve segments and the falling trend curve segments in the line operation data curve, sum the Y-axis coordinate data of all coordinate points in each rising trend curve segment to obtain the rising total value, sum the Y-axis coordinate data of all coordinate points in each falling trend curve segment to obtain the falling total value, and obtain the difference between the rising total value and the falling total value as the growth value ZZ; Get the total time of the analysis cycle as ST, using the formula Get the growth rate value ZV; Get the number of field null values ​​KS and the second data field null value threshold DEY in the current period of the line, and use the formula Get the line's continued usable time CXT.

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