Analog voice line intervention status monitoring system and method based on big data

Abstract

The present invention relates to the field of line status monitoring technology, specifically to a system and method for monitoring the intervention status of an analog voice line based on big data, wherein the system includes a voice transmission interference analysis module, wherein the voice transmission interference analysis module extracts display information of a status monitoring display terminal in real time, combines the fluctuation of interactive status information in display information corresponding to different times in historical data, and analyzes the risk relationship of timing communication fluctuations in the line radiation area of ​​the analog voice line caused by the influence of the transmission environment, as well as the risk fluctuation relationship of the use status of each connected device in the analog voice line. The present invention not only realizes real-time feedback on the transmission status monitoring results, but also takes into account that the analog voice transmission route may be affected by environmental interference or different timing changes, realizes dynamic screening of analog voice lines corresponding to different voice transmission times, and assists users in making data transmission decisions for analog voice lines.

Description

Technical Field

[0001] The present invention relates to the technical field of line status monitoring, and in particular to a system and method for monitoring the intervention status of an analog voice line based on big data. Background Art

[0002] As people's demand for communication continues to increase, the demand for status monitoring of analog voice lines is also increasing. Analog voice lines are voice transmission lines used by users of different devices to communicate through voice. Line quality inspection is the quality inspection conducted by analog voice line providers / operators to determine whether the voice traffic running on the lines meets the specifications.

[0003] In the prior art, an analog voice route is often selected first, and then the transmission status of the selected analog voice route is monitored during the voice transmission process. The selection method of the analog voice line in this method is relatively rigid, and does not take into account that the analog voice transmission route may be affected by environmental interference or different time series changes (the transmission status monitoring results corresponding to the same analog voice line at different times may be greatly different). It is not possible to dynamically select the transmission status monitoring of each analog voice line based on historical data. Therefore, the prior art has major defects. Summary of the invention

[0004] The purpose of the present invention is to provide an analog voice line intervention status monitoring system and method based on big data to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solution: a method for monitoring the intervention status of an analog voice line based on big data, the method comprising the following steps:

[0006] S1. Acquire the connection relationship between the interactive ports in each analog voice line during the voice information transmission process, and extract the connection device and line radiation area to which each interactive port on each analog voice line belongs;

[0007] S2. By simulating the location of the connection device to which each interactive port belongs on the voice line and the line radiation area, a digital twin model of the analog voice line is constructed, and the interaction information of each connection device in each analog voice line at different time points is dynamically obtained. The mapping data of the interaction information of the corresponding connection device is bound to the location of the corresponding connection device in the constructed digital twin model of the analog voice line in real time, and the mapping results of the digital twin model of the analog voice line and its binding are fed back to the status monitoring display terminal in real time;

[0008] S3, extracting the display information of the status monitoring display terminal in real time, combining the fluctuation of the interactive status information in the display information corresponding to different times in the historical data, analyzing the risk relationship of the timing communication fluctuation caused by the transmission environment in the line radiation area of ​​the analog voice line, and the use status risk fluctuation relationship of each connected device in the analog voice line, and jumping to S4;

[0009] S4. Combine the fault information corresponding to the analog voice line in the historical data to predict the first fault risk probability corresponding to different times in the obtained time series communication fluctuation risk relationship, and the second fault risk probability corresponding to different times in the use status risk fluctuation relationship of the connected device; generate the fault risk intervention value corresponding to each analog voice line at the current time;

[0010] S5. Sort each analog voice line in ascending order according to the fault risk access value corresponding to the current time, generate a recommended sequence of analog voice lines corresponding to the current time, and assist the user in making data transmission decisions on the analog voice lines.

[0011] Furthermore, the line radiation area includes one or more line radiation sub-areas, and each line radiation sub-area is a line between two adjacent connection devices on the corresponding analog voice line.

[0012] Furthermore, the constructed data twin model of the analog voice line includes the location of the connection device to which each interactive port belongs on the analog voice line and the line radiation area, and is a proportional scaling model of the location of the connection device to which each interactive port belongs on the analog voice line and the location of the line radiation area;

[0013] The interaction information of the connected devices includes the interaction state acquisition time, the data transmission delay corresponding to the corresponding line radiation sub-area, the interaction signal strength value and the transmission data matching degree;

[0014] The data transmission delay corresponding to the corresponding line radiation sub-area indicates the transmission delay between the corresponding connection device and the previous connection device on the analog voice line during data transmission; if there is no previous connection device for the corresponding connection device on the analog voice line, the data transmission delay corresponding to the corresponding line radiation sub-area is 0;

[0015] The transmission data matching degree indicates the ratio of the number of elements in the intersection between the set corresponding to the transmission data content received by the corresponding connection device and the set corresponding to the transmission data content sent by the previous connection device during the data interaction transmission process to the number of elements in the set corresponding to the transmission data content sent by the previous connection device; if the corresponding connection device on the analog voice line does not have a previous connection device, the transmission data matching degree corresponding to the corresponding line radiation sub-area is 1;

[0016] The interaction state collection time corresponding to each interaction state information in the data mapping results bound at the same time of the constructed analog voice line digital twin model is the same.

[0017] In the present invention, the analog voice line is the result of the corresponding connection device and the line radiation sub-area being connected in sequence. The corresponding connection device on the analog voice line does not have a previous connection device, that is, the corresponding connection device is the initiator of the voice communication on the corresponding analog voice line, and thus, by default, there is no data transmission delay (the default data transmission delay is 0), and it is only used as a reference object for subsequent connection devices to judge the data transmission delay; similarly, there is no transmission data matching degree for the corresponding connection device, and the default data transmission matching degree is 1.

[0018] Furthermore, the method for analyzing the risk relationship of timing communication fluctuations caused by the transmission environment in the line radiation area of ​​the simulated voice line includes the following steps:

[0019] S301, recording an array of interaction state information corresponding to the same interaction state collection time of each connected device in the same analog voice line in the historical data as a time sequence communication analysis group corresponding to the corresponding interaction state collection time in the corresponding analog voice line;

[0020] S302, according to the timing communication analysis group corresponding to the corresponding interaction state collection time in the corresponding analog voice line, generate a timing communication analysis data pair corresponding to the corresponding interaction state collection time in the corresponding analog voice line, wherein the first value of the timing communication analysis data pair is the time point of the day to which the corresponding interaction state collection time belongs; the second value is the transmission data interference deviation amount corresponding to the corresponding timing communication analysis group, recorded as IB, ,

[0021] Among them, TD k represents the data transmission delay corresponding to the corresponding line radiation sub-area in the kth element in the timing communication analysis group; L k Indicates the length of the radiation sub-area of ​​the kth element in the corresponding analog voice line, and when k=1, L k =0;DM k represents the transmission data matching degree corresponding to the corresponding line radiation sub-area in the kth element in the timing communication analysis group; KZ represents the total number of elements in the timing communication analysis group; r represents the conversion coefficient preset in the database; CS k It represents the average value of the interactive signal strength values ​​corresponding to the corresponding line radiation sub-areas in each element in the time series communication analysis group; CSZ represents the maximum value of each interactive signal strength value corresponding to the analog voice line belonging to the time series communication analysis group in the historical data;

[0022] S303, constructing a timing communication fluctuation deviation data pair corresponding to a corresponding time point in the corresponding analog voice line according to each timing communication analysis data pair with the same first value in the corresponding analog voice line, wherein the first value in the timing communication fluctuation deviation data pair is equal to the first value in the corresponding timing communication analysis data pair, the second value in the timing communication fluctuation deviation data pair is a timing communication fluctuation deviation value, and the timing communication fluctuation deviation value is equal to the difference between the maximum value and the minimum value in each transmission data interference deviation amount corresponding to the corresponding timing communication analysis data pair;

[0023] S304. In a plane rectangular coordinate system constructed with o as the origin, the time point of the day as the x-axis and the timing communication fluctuation deviation value as the y-axis, the adjacent timing communication fluctuation deviation data pairs corresponding to the corresponding analog voice lines are connected in chronological order, and the function corresponding to the obtained broken line is recorded as FT (x), so as to obtain the timing communication fluctuation risk relationship caused by the transmission environment in the line radiation area of ​​the analog voice line.

[0024] Further, the method for analyzing the risk fluctuation relationship of the use status of each connected device in the analog voice line includes the following steps:

[0025] S311, obtaining a pair of usage status risk data corresponding to different usage durations of each connection device in the analog voice line in the historical data, wherein the second value of the usage status risk data pair is the minimum transmission data interference deviation of the corresponding connection device in a day corresponding to the corresponding date, and the first value of the usage status risk data pair is the usage duration of the corresponding connection device based on the most recent fault maintenance time, and the usage duration is equal to the interval between the corresponding connection device on the corresponding date and the most recent fault maintenance date of the corresponding connection device;

[0026] S312. In a plane rectangular coordinate system constructed with o1 as the origin, the usage time as the x1 axis and the transmission data interference deviation as the y1 axis, the usage status risk data pairs corresponding to the corresponding analog voice lines are connected in order from small to large in terms of usage time, and the function corresponding to the obtained broken line is recorded as US (x1), so as to obtain the usage status risk fluctuation relationship of each connected device in the analog voice line.

[0027] The present invention analyzes the risk relationship of timing communication fluctuation caused by the influence of the transmission environment in the line radiation area of ​​the analog voice line, and the risk fluctuation relationship of the use status of each connection device in the analog voice line, in order to combine the communication failure information in the historical data to respectively realize the prediction of the timing communication fluctuation deviation value and the transmission data interference deviation amount corresponding to different time points, and then predict the probability of communication failure caused by the influence of the transmission environment in the line radiation area of ​​each analog route at different time points, and the probability of communication failure caused by the failure of the connection device of each analog route at different time points; and provide data support for the subsequent generation of the analog voice line recommendation sequence corresponding to the current time.

[0028] Furthermore, when the first fault risk probability corresponding to different times in the predicted timing communication fluctuation risk relationship is obtained, the timing communication fluctuation deviation value corresponding to each communication failure caused by the line radiation area being affected by the transmission environment in the historical data is obtained; according to each timing communication fluctuation deviation value interval preset in the database, the communication failure frequency in each timing communication fluctuation deviation value interval is counted to obtain a line failure frequency statistical data pair corresponding to each timing communication fluctuation deviation value interval, the first value in the line failure frequency statistical data pair is the midpoint of the timing communication fluctuation deviation value interval, and the second value in the line failure frequency statistical data pair is the frequency statistical data corresponding to the corresponding timing communication fluctuation deviation value interval. The result is divided by the quotient of the sum of the frequency statistics corresponding to each preset timing communication fluctuation deviation value interval and the product of the interval length of the corresponding timing communication fluctuation deviation value interval; and the normal distribution function model in matlab is used to fit the statistical data pairs of the frequency of each line fault, and the obtained fitting function is recorded as GL (y); when the function value in GL (y) is the corresponding value of the midpoint of the timing communication fluctuation deviation value interval in the corresponding fitting function, the prediction value corresponding to the frequency statistics result corresponding to the corresponding timing communication fluctuation deviation value interval in the corresponding fitting function is divided by the sum of the frequency statistics results corresponding to each preset timing communication fluctuation deviation value interval and the product of the interval length of the corresponding timing communication fluctuation deviation value interval;

[0029] In the GL(y) of the present invention, y represents the parameter of the timing communication fluctuation deviation value;

[0030] The first failure risk probability corresponding to time xt in the obtained timing communication fluctuation risk relationship is recorded as Pg1, ,

[0031] Among them, FT(xt) represents the function value corresponding to when x is xt in the risk relationship FT(x) of the timing communication fluctuation caused by the transmission environment in the line radiation area of ​​the simulated voice line;

[0032] When predicting the second failure risk probability corresponding to different times in the risk fluctuation relationship of the use status of the connected device, the transmission data interference deviation corresponding to each communication failure caused by the connection device failure in the historical data is obtained; according to each transmission data interference deviation interval preset in the database, the communication failure frequency in each transmission data interference deviation interval is counted to obtain a device failure frequency statistical data pair corresponding to each transmission data interference deviation interval, wherein the first value in the device failure frequency statistical data pair is the midpoint of the transmission data interference deviation interval, and the second value in the device failure frequency statistical data pair is the frequency statistical result corresponding to the corresponding transmission data interference deviation interval divided by the preset transmission data interference deviation interval score. The quotient of the sum of the frequency statistics corresponding to each transmission data interference deviation interval multiplied by the interval length of the corresponding transmission data interference deviation interval; and fitting the statistical data pairs of the frequency of each device failure through the normal distribution function model in matlab, and recording the obtained fitting function as GB (y1); when the function value in GB (y1) is the corresponding value of the midpoint of the transmission data interference deviation interval in the corresponding fitting function, the prediction value corresponding to the quotient of the frequency statistics corresponding to the corresponding transmission data interference deviation interval in the corresponding fitting function divided by the sum of the frequency statistics corresponding to each preset transmission data interference deviation interval and the interval length of the corresponding transmission data interference deviation interval; in GB (y1) of the present invention, y1 represents the parameter of the transmission data interference deviation;

[0033] The obtained usage status risk fluctuation relationship of the connected device is calculated as time x1 T The corresponding first failure risk probability is recorded as Pg2, ,

[0034] Among them, US (x1 T ) represents the risk relationship of timing communication fluctuation US(x1) caused by the transmission environment in the line radiation area of ​​the simulated voice line, where x1 is x1 T The corresponding function value when ;

[0035] The fault risk intervention value corresponding to the i-th analog voice line at the current time is recorded as Ri,

[0036] Ri=Pg1 DQ +β·Pg2 DQ ,

[0037] Among them, Pg1 DQ Pg2 represents the first fault risk probability corresponding to the i-th analog voice line at the current time; DQ represents the second fault risk probability corresponding to the i-th analog voice line at the current time; β represents the risk intervention conversion factor preset in the database.

[0038] The analog voice line intervention status monitoring system based on big data includes the following modules:

[0039] A line radiation information extraction module, which obtains the connection relationship between the interactive ports in each analog voice line during the voice information transmission process, and extracts the connection device and line radiation area to which each interactive port on each analog voice line belongs;

[0040] A model building and information mapping module, which builds a digital twin model of the analog voice line by simulating the position of the connection device to which each interactive port belongs on the voice line and the line radiation area, dynamically obtains the interaction information of each connection device in each analog voice line at different time points, and realizes the real-time data mapping and binding of the interaction information of the corresponding connection device to the corresponding connection device in the constructed digital twin model of the analog voice line, and feeds back the digital twin model of the analog voice line and its bound data mapping results to the status monitoring display terminal in real time;

[0041] A voice transmission interference analysis module, which extracts the display information of the status monitoring display terminal in real time, combines the fluctuation of the interactive status information in the display information corresponding to different times in the historical data, analyzes the risk relationship of the timing communication fluctuation caused by the transmission environment in the line radiation area of ​​the simulated voice line, and the risk fluctuation relationship of the use status of each connected device in the simulated voice line;

[0042] A line intervention risk analysis module, which combines the various fault information corresponding to the simulated voice line in the historical data, predicts the first fault risk probability corresponding to different times in the obtained time sequence communication fluctuation risk relationship, and the second fault risk probability corresponding to different times in the use status risk fluctuation relationship of the connected device; generates a fault risk intervention value corresponding to each simulated voice route at the current time;

[0043] An intervention status decision management module, wherein the intervention status decision management module sorts each analog voice line in ascending order according to the fault risk access value corresponding to the current time, generates a recommended sequence of analog voice lines corresponding to the current time, and assists users in executing data transmission decisions on analog voice lines.

[0044] Furthermore, the line intervention risk analysis module includes a timing communication fluctuation risk probability prediction unit, a usage status risk probability prediction unit and a fault risk intervention analysis unit.

[0045] The time sequence communication fluctuation risk probability prediction unit combines each fault information corresponding to the simulated voice line in the historical data to predict the first fault risk probability corresponding to different times in the obtained time sequence communication fluctuation risk relationship;

[0046] The usage status risk probability prediction unit combines each fault information corresponding to the simulated voice line in the historical data to predict the second fault risk probability corresponding to different times in the usage status risk fluctuation relationship of the connected device;

[0047] The fault risk intervention analysis unit generates a fault risk intervention value corresponding to each simulated voice route at the current time according to the prediction results of the time sequence communication fluctuation risk probability prediction unit and the usage status risk probability prediction unit.

[0048] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: in monitoring the transmission status of the analog voice line, the present invention not only realizes real-time feedback of the transmission status monitoring results, but also takes into account that the analog voice transmission line may be affected by environmental interference or different time sequence changes, and combines historical data with the transmission status monitoring results of the analog voice line to realize dynamic screening of analog voice lines corresponding to different voice transmission times, and assists users in executing data transmission decisions for analog voice lines; it provides a guarantee for reducing the failure rate in the voice communication process and ensuring communication stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0050] Figure 1 It is a structural schematic diagram of the analog voice line intervention status monitoring system based on big data of the present invention;

[0051] Figure 2 It is a flow chart of the method for monitoring the intervention status of an analog voice line based on big data of the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] See also Figure 1 The present invention provides a technical solution: a big data-based analog voice line intervention status monitoring system, the system comprising the following modules:

[0054] A line radiation information extraction module, which obtains the connection relationship between the interactive ports in each analog voice line during the voice information transmission process, and extracts the connection device and line radiation area to which each interactive port on each analog voice line belongs;

[0055] A model building and information mapping module, which builds a digital twin model of the analog voice line by simulating the position of the connection device to which each interactive port belongs on the voice line and the line radiation area, dynamically obtains the interaction information of each connection device in each analog voice line at different time points, and realizes the real-time data mapping and binding of the interaction information of the corresponding connection device to the corresponding connection device in the constructed digital twin model of the analog voice line, and feeds back the digital twin model of the analog voice line and its bound data mapping results to the status monitoring display terminal in real time;

[0056] A voice transmission interference analysis module, which extracts the display information of the status monitoring display terminal in real time, combines the fluctuation of the interactive status information in the display information corresponding to different times in the historical data, analyzes the risk relationship of the timing communication fluctuation caused by the transmission environment in the line radiation area of ​​the simulated voice line, and the risk fluctuation relationship of the use status of each connected device in the simulated voice line;

[0057] A line intervention risk analysis module, the line intervention risk analysis module includes a timing communication fluctuation risk probability prediction unit, a usage status risk probability prediction unit and a fault risk intervention analysis unit,

[0058] The time sequence communication fluctuation risk probability prediction unit combines each fault information corresponding to the simulated voice line in the historical data to predict the first fault risk probability corresponding to different times in the obtained time sequence communication fluctuation risk relationship;

[0059] The usage status risk probability prediction unit combines each fault information corresponding to the simulated voice line in the historical data to predict the second fault risk probability corresponding to different times in the usage status risk fluctuation relationship of the connected device;

[0060] The fault risk intervention analysis unit generates a fault risk intervention value corresponding to each simulated voice route at the current time according to the prediction results of the time sequence communication fluctuation risk probability prediction unit and the usage status risk probability prediction unit.

[0061] An intervention status decision management module, wherein the intervention status decision management module sorts each analog voice line in ascending order according to the fault risk access value corresponding to the current time, generates a recommended sequence of analog voice lines corresponding to the current time, and assists users in executing data transmission decisions on analog voice lines.

[0062] like Figure 2 As shown, a method for monitoring the intervention status of an analog voice line based on big data comprises the following steps:

[0063] S1. Acquire the connection relationship between the interactive ports in each analog voice line during the voice information transmission process, and extract the connection device and line radiation area to which each interactive port on each analog voice line belongs;

[0064] The line radiation area includes one or more line radiation sub-areas, and each line radiation sub-area is a line between two adjacent connection devices on a corresponding analog voice line.

[0065] S2. By simulating the location of the connection device to which each interactive port belongs on the voice line and the line radiation area, a digital twin model of the analog voice line is constructed, and the interaction information of each connection device in each analog voice line at different time points is dynamically obtained. The mapping data of the interaction information of the corresponding connection device is bound to the location of the corresponding connection device in the constructed digital twin model of the analog voice line in real time, and the mapping results of the digital twin model of the analog voice line and its binding are fed back to the status monitoring display terminal in real time;

[0066] In this embodiment, when the analog voice line does not change, the digital twin model of the analog voice line presented by the status monitoring display terminal is fixed, but the mapping data bound in the digital twin model of the analog voice line has different display results at different times, and the interaction status collection time corresponding to each interaction information in the mapping data presented by the status monitoring display terminal at the same time point is the same.

[0067] The constructed data twin model of the analog voice line includes the location of the connection device to which each interactive port belongs on the analog voice line and the line radiation area, and is a proportional scaling model of the location of the connection device to which each interactive port belongs on the analog voice line and the line radiation area;

[0068] The interaction information of the connected devices includes the interaction state acquisition time, the data transmission delay corresponding to the corresponding line radiation sub-area, the interaction signal strength value and the transmission data matching degree;

[0069] The data transmission delay corresponding to the corresponding line radiation sub-area indicates the transmission delay between the corresponding connection device and the previous connection device on the analog voice line during data transmission; if there is no previous connection device for the corresponding connection device on the analog voice line, the data transmission delay corresponding to the corresponding line radiation sub-area is 0;

[0070] The transmission data matching degree indicates the ratio of the number of elements in the intersection between the set corresponding to the transmission data content received by the corresponding connection device and the set corresponding to the transmission data content sent by the previous connection device during the data interaction transmission process to the number of elements in the set corresponding to the transmission data content sent by the previous connection device; if the corresponding connection device on the analog voice line does not have a previous connection device, the transmission data matching degree corresponding to the corresponding line radiation sub-area is 1;

[0071] The interaction state collection time corresponding to each interaction state information in the data mapping results bound at the same time of the constructed analog voice line digital twin model is the same.

[0072] S3, extracting the display information of the status monitoring display terminal in real time, combining the fluctuation of the interactive status information in the display information corresponding to different times in the historical data, analyzing the risk relationship of the timing communication fluctuation caused by the transmission environment in the line radiation area of ​​the analog voice line, and the use status risk fluctuation relationship of each connected device in the analog voice line, and jumping to S4;

[0073] The method for analyzing the risk relationship of timing communication fluctuations caused by the transmission environment in the line radiation area of ​​the simulated voice line comprises the following steps:

[0074] S301, recording an array of interaction state information corresponding to the same interaction state collection time of each connected device in the same analog voice line in the historical data as a time sequence communication analysis group corresponding to the corresponding interaction state collection time in the corresponding analog voice line;

[0075] S302, according to the timing communication analysis group corresponding to the corresponding interaction state collection time in the corresponding analog voice line, generate a timing communication analysis data pair corresponding to the corresponding interaction state collection time in the corresponding analog voice line, wherein the first value of the timing communication analysis data pair is the time point of the day to which the corresponding interaction state collection time belongs; the second value is the transmission data interference deviation amount corresponding to the corresponding timing communication analysis group, recorded as IB, ,

[0076] Among them, TD k represents the data transmission delay corresponding to the corresponding line radiation sub-area in the kth element in the timing communication analysis group; L k Indicates the length of the radiation sub-area of ​​the kth element in the corresponding analog voice line, and when k=1, L k =0;DM k represents the transmission data matching degree corresponding to the corresponding line radiation sub-area in the kth element in the timing communication analysis group; KZ represents the total number of elements in the timing communication analysis group; r represents the conversion coefficient preset in the database; CS kIt represents the average value of the interactive signal strength values ​​corresponding to the corresponding line radiation sub-areas in each element in the time series communication analysis group; CSZ represents the maximum value of each interactive signal strength value corresponding to the analog voice line belonging to the time series communication analysis group in the historical data;

[0077] S303, constructing a timing communication fluctuation deviation data pair corresponding to a corresponding time point in the corresponding analog voice line according to each timing communication analysis data pair with the same first value in the corresponding analog voice line, wherein the first value in the timing communication fluctuation deviation data pair is equal to the first value in the corresponding timing communication analysis data pair, the second value in the timing communication fluctuation deviation data pair is a timing communication fluctuation deviation value, and the timing communication fluctuation deviation value is equal to the difference between the maximum value and the minimum value in each transmission data interference deviation amount corresponding to the corresponding timing communication analysis data pair;

[0078] S304. In a plane rectangular coordinate system constructed with o as the origin, the time point of the day as the x-axis and the timing communication fluctuation deviation value as the y-axis, the adjacent timing communication fluctuation deviation data pairs corresponding to the corresponding analog voice lines are connected in chronological order, and the function corresponding to the obtained broken line is recorded as FT (x), so as to obtain the timing communication fluctuation risk relationship caused by the transmission environment in the line radiation area of ​​the analog voice line.

[0079] The method for analyzing the risk fluctuation relationship of the use status of each connected device in the analog voice line includes the following steps:

[0080] S311, obtaining a pair of usage status risk data corresponding to different usage durations of each connection device in the analog voice line in the historical data, wherein the second value of the usage status risk data pair is the minimum transmission data interference deviation of the corresponding connection device in a day corresponding to the corresponding date, and the first value of the usage status risk data pair is the usage duration of the corresponding connection device based on the most recent fault maintenance time, and the usage duration is equal to the interval between the corresponding connection device on the corresponding date and the most recent fault maintenance date of the corresponding connection device;

[0081] S312. In a plane rectangular coordinate system constructed with o1 as the origin, the usage time as the x1 axis and the transmission data interference deviation as the y1 axis, the usage status risk data pairs corresponding to the corresponding analog voice lines are connected in order from small to large in terms of usage time, and the function corresponding to the obtained broken line is recorded as US (x1), so as to obtain the usage status risk fluctuation relationship of each connected device in the analog voice line.

[0082] S4. Combine the fault information corresponding to the analog voice line in the historical data to predict the first fault risk probability corresponding to different times in the obtained time series communication fluctuation risk relationship, and the second fault risk probability corresponding to different times in the use status risk fluctuation relationship of the connected device; generate the fault risk intervention value corresponding to each analog voice line at the current time;

[0083] When the first fault risk probability corresponding to different times in the predicted sequential communication fluctuation risk relationship is obtained, the sequential communication fluctuation deviation value corresponding to each communication failure caused by the line radiation area being affected by the transmission environment in the historical data is obtained; according to each sequential communication fluctuation deviation value interval preset in the database, the communication failure frequency in each sequential communication fluctuation deviation value interval is counted to obtain a line fault frequency statistical data pair corresponding to each sequential communication fluctuation deviation value interval, wherein the first value in the line fault frequency statistical data pair is the midpoint of the sequential communication fluctuation deviation value interval, and the second value in the line fault frequency statistical data pair is the quotient of the frequency statistical result corresponding to the corresponding sequential communication fluctuation deviation value interval divided by the sum of the frequency statistical results corresponding to each preset sequential communication fluctuation deviation value interval respectively and the product of the interval length of the corresponding sequential communication fluctuation deviation value interval; and the normal distribution function model in matlab is used to fit each line fault frequency statistical data pair, and the obtained fitting function is recorded as GL (y);

[0084] In this embodiment, the normal distribution function model is used in MATLAB software to fit the statistical data pairs of each line fault frequency. The normal distribution function fitting process can also be achieved by selecting fitting tools such as Origin software and CurveFitter software.

[0085] The first failure risk probability corresponding to time xt in the obtained timing communication fluctuation risk relationship is recorded as Pg1, ,

[0086] Among them, FT(xt) represents the function value corresponding to when x is xt in the risk relationship FT(x) of the timing communication fluctuation caused by the transmission environment in the line radiation area of ​​the simulated voice line;

[0087] When predicting the second fault risk probability corresponding to different times in the risk fluctuation relationship of the use status of the connection device, obtain the transmission data interference deviation corresponding to each communication failure caused by the connection device failure in the historical data; according to each transmission data interference deviation interval preset in the database, the communication failure frequency in each transmission data interference deviation interval is counted to obtain a device failure frequency statistical data pair corresponding to each transmission data interference deviation interval, wherein the first value in the device failure frequency statistical data pair is the midpoint of the transmission data interference deviation interval, and the second value in the device failure frequency statistical data pair is the quotient of the frequency statistical result corresponding to the corresponding transmission data interference deviation interval divided by the sum of the frequency statistical results corresponding to each preset transmission data interference deviation interval and the interval length of the corresponding transmission data interference deviation interval; and fit each device failure frequency statistical data pair through the normal distribution function model in matlab, and record the obtained fitting function as GB (y1);

[0088] The obtained usage status risk fluctuation relationship of the connected device is calculated as time x1 T The corresponding first failure risk probability is recorded as Pg2, ,

[0089] Among them, US (x1 T ) represents the risk relationship of timing communication fluctuation US(x1) caused by the transmission environment in the line radiation area of ​​the simulated voice line, where x1 is x1 T The corresponding function value when ;

[0090] The fault risk intervention value corresponding to the i-th analog voice line at the current time is recorded as Ri,

[0091] Ri=Pg1 DQ +β·Pg2 DQ ,

[0092] Among them, Pg1 DQ Pg2 represents the first fault risk probability corresponding to the i-th analog voice line at the current time; DQ represents the second fault risk probability corresponding to the i-th analog voice line at the current time; β represents the risk intervention conversion factor preset in the database.

[0093] S5. Sort each analog voice line in ascending order according to the fault risk access value corresponding to the current time, generate a recommended sequence of analog voice lines corresponding to the current time, and assist the user in making data transmission decisions on the analog voice lines.

[0094] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0095] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for monitoring the intervention status of analog voice lines based on big data, characterized in that: The method comprises the following steps: S1. Acquire the connection relationship between the interactive ports in each analog voice line during the voice information transmission process, and extract the connection device and line radiation area to which each interactive port on each analog voice line belongs; S2. By simulating the location of the connection device to which each interactive port belongs on the voice line and the line radiation area, a digital twin model of the analog voice line is constructed, and the interaction information of each connection device in each analog voice line at different time points is dynamically obtained. The mapping data of the interaction information of the corresponding connection device is bound to the location of the corresponding connection device in the constructed digital twin model of the analog voice line in real time, and the mapping results of the digital twin model of the analog voice line and its binding are fed back to the status monitoring display terminal in real time; S3, extracting the display information of the status monitoring display terminal in real time, combining the fluctuation of the interactive status information in the display information corresponding to different times in the historical data, analyzing the risk relationship of the timing communication fluctuation caused by the transmission environment in the line radiation area of ​​the analog voice line, and the use status risk fluctuation relationship of each connected device in the analog voice line, and jumping to S4; S4. Combine the fault information corresponding to the analog voice line in the historical data to predict the first fault risk probability corresponding to different times in the obtained time series communication fluctuation risk relationship, and the second fault risk probability corresponding to different times in the use status risk fluctuation relationship of the connected device; generate the fault risk intervention value corresponding to each analog voice line at the current time; S5. Sort each analog voice line in ascending order according to the fault risk access value corresponding to the current time, generate a recommended sequence of analog voice lines corresponding to the current time, and assist the user in making data transmission decisions on the analog voice lines.

2. The method for monitoring the analog voice line intervention status based on big data according to claim 1 is characterized in that: The line radiation area includes one or more line radiation sub-areas, and each line radiation sub-area is a line between two adjacent connection devices on a corresponding analog voice line.

3. The method for monitoring the analog voice line intervention status based on big data according to claim 2 is characterized in that: The constructed data twin model of the analog voice line includes the location of the connection device to which each interactive port belongs on the analog voice line and the line radiation area, and is a proportional scaling model of the location of the connection device to which each interactive port belongs on the analog voice line and the line radiation area; The interaction information of the connected devices includes the interaction state acquisition time, the data transmission delay corresponding to the corresponding line radiation sub-area, the interaction signal strength value and the transmission data matching degree; The data transmission delay corresponding to the corresponding line radiation sub-area indicates the transmission delay between the corresponding connection device and the previous connection device on the analog voice line during data transmission; if there is no previous connection device for the corresponding connection device on the analog voice line, the data transmission delay corresponding to the corresponding line radiation sub-area is 0; The transmission data matching degree indicates the ratio of the number of elements in the intersection between the set corresponding to the transmission data content received by the corresponding connection device and the set corresponding to the transmission data content sent by the previous connection device during the data interaction transmission process to the number of elements in the set corresponding to the transmission data content sent by the previous connection device; if the corresponding connection device on the analog voice line does not have a previous connection device, the transmission data matching degree corresponding to the corresponding line radiation sub-area is 1; The interaction state collection time corresponding to each interaction state information in the data mapping results bound at the same time of the constructed analog voice line digital twin model is the same.

4. The method for monitoring the analog voice line intervention status based on big data according to claim 2 is characterized in that: The method for analyzing the risk relationship of timing communication fluctuations caused by the transmission environment in the line radiation area of ​​the simulated voice line comprises the following steps: S301, recording an array of interaction state information corresponding to the same interaction state collection time of each connected device in the same analog voice line in the historical data as a time sequence communication analysis group corresponding to the corresponding interaction state collection time in the corresponding analog voice line; S302, according to the timing communication analysis group corresponding to the corresponding interaction state collection time in the corresponding analog voice line, generate a timing communication analysis data pair corresponding to the corresponding interaction state collection time in the corresponding analog voice line, wherein the first value of the timing communication analysis data pair is the time point of the day to which the corresponding interaction state collection time belongs; the second value is the transmission data interference deviation amount corresponding to the corresponding timing communication analysis group, recorded as IB, , Among them, TD k represents the data transmission delay corresponding to the corresponding line radiation sub-area in the kth element in the timing communication analysis group; L k Indicates the length of the radiation sub-area of ​​the kth element corresponding to the corresponding analog voice line, and when k=1, determine L k =0;DM k represents the transmission data matching degree corresponding to the corresponding line radiation sub-area in the kth element in the timing communication analysis group; KZ represents the total number of elements in the timing communication analysis group; r represents the conversion coefficient preset in the database; CS k It represents the average value of the interactive signal strength values ​​corresponding to the corresponding line radiation sub-areas in each element in the time series communication analysis group; CSZ represents the maximum value of each interactive signal strength value corresponding to the analog voice line belonging to the time series communication analysis group in the historical data; S303, constructing a timing communication fluctuation deviation data pair corresponding to a corresponding time point in the corresponding analog voice line according to each timing communication analysis data pair with the same first value in the corresponding analog voice line, wherein the first value in the timing communication fluctuation deviation data pair is equal to the first value in the corresponding timing communication analysis data pair, the second value in the timing communication fluctuation deviation data pair is a timing communication fluctuation deviation value, and the timing communication fluctuation deviation value is equal to the difference between the maximum value and the minimum value in each transmission data interference deviation amount corresponding to the corresponding timing communication analysis data pair; S304. In a plane rectangular coordinate system constructed with o as the origin, the time point of the day as the x-axis and the timing communication fluctuation deviation value as the y-axis, the adjacent timing communication fluctuation deviation data pairs corresponding to the corresponding analog voice lines are connected in chronological order, and the function corresponding to the obtained broken line is recorded as FT (x), so as to obtain the timing communication fluctuation risk relationship caused by the transmission environment in the line radiation area of ​​the analog voice line.

5. The method for monitoring the analog voice line intervention status based on big data according to claim 4 is characterized in that: The method for analyzing the risk fluctuation relationship of the use status of each connected device in the analog voice line includes the following steps: S311, obtaining a pair of usage status risk data corresponding to different usage durations of each connection device in the analog voice line in the historical data, wherein the second value of the usage status risk data pair is the minimum transmission data interference deviation of the corresponding connection device in a day corresponding to the corresponding date, and the first value of the usage status risk data pair is the usage duration of the corresponding connection device based on the most recent fault maintenance time, and the usage duration is equal to the interval between the corresponding connection device on the corresponding date and the most recent fault maintenance date of the corresponding connection device; S312. In a plane rectangular coordinate system constructed with o1 as the origin, the usage time as the x1 axis and the transmission data interference deviation as the y1 axis, the usage status risk data pairs corresponding to the corresponding analog voice lines are connected in order from small to large in terms of usage time, and the function corresponding to the obtained broken line is recorded as US (x1), so as to obtain the usage status risk fluctuation relationship of each connected device in the analog voice line.

6. The method for monitoring the analog voice line intervention status based on big data according to claim 5 is characterized in that: When the first fault risk probability corresponding to different times in the predicted timing communication fluctuation risk relationship is obtained, the timing communication fluctuation deviation value corresponding to each communication failure caused by the line radiation area being affected by the transmission environment in the historical data is obtained; according to each timing communication fluctuation deviation value interval preset in the database, the communication failure frequency in each timing communication fluctuation deviation value interval is counted to obtain a line failure frequency statistical data pair corresponding to each timing communication fluctuation deviation value interval, wherein the first value in the line failure frequency statistical data pair is the midpoint of the timing communication fluctuation deviation value interval, and the second value in the line failure frequency statistical data pair is the frequency statistical result corresponding to the corresponding timing communication fluctuation deviation value interval. Divide by the quotient of the sum of the frequency statistics corresponding to each preset timing communication fluctuation deviation value interval and the product of the interval length of the corresponding timing communication fluctuation deviation value interval; and fit the statistical data pairs of each line fault frequency through the normal distribution function model in matlab, and record the obtained fitting function as GL (y); when the function value in GL (y) is the corresponding value of the midpoint of the timing communication fluctuation deviation value interval in the corresponding fitting function, the prediction value corresponding to the quotient of the frequency statistics corresponding to the corresponding timing communication fluctuation deviation value interval in the corresponding fitting function divided by the sum of the frequency statistics corresponding to each preset timing communication fluctuation deviation value interval and the interval length of the corresponding timing communication fluctuation deviation value interval; The first failure risk probability corresponding to time xt in the obtained timing communication fluctuation risk relationship is recorded as Pg1, , Among them, FT(xt) represents the function value corresponding to when x is xt in the risk relationship FT(x) of the timing communication fluctuation caused by the transmission environment in the line radiation area of ​​the simulated voice line; When predicting the second failure risk probability corresponding to different times in the risk fluctuation relationship of the use status of the connected device, obtain the transmission data interference deviation corresponding to each communication failure caused by the connection device failure in the historical data; according to each transmission data interference deviation interval preset in the database, the communication failure frequency in each transmission data interference deviation interval is counted to obtain a device failure frequency statistical data pair corresponding to each transmission data interference deviation interval, wherein the first value in the device failure frequency statistical data pair is the midpoint of the transmission data interference deviation interval, and the second value in the device failure frequency statistical data pair is the frequency statistical result corresponding to the corresponding transmission data interference deviation interval divided by the preset The quotient of the sum of the frequency statistics corresponding to each transmission data interference deviation interval and the product of the interval length of the corresponding transmission data interference deviation interval; and fitting the statistical data pairs of the frequency of each device failure through the normal distribution function model in matlab, and recording the obtained fitting function as GB (y1); when the function value in GB (y1) is the corresponding value of the midpoint of the transmission data interference deviation interval in the corresponding fitting function, which is y1, the prediction value corresponding to the quotient of the frequency statistics corresponding to the corresponding transmission data interference deviation interval in the corresponding fitting function divided by the sum of the frequency statistics corresponding to each preset transmission data interference deviation interval and the product of the interval length of the corresponding transmission data interference deviation interval; The obtained usage status risk fluctuation relationship of the connected device is calculated as time x1 T The corresponding first failure risk probability is recorded as Pg2, , Among them, US (x1 T ) represents the risk relationship of timing communication fluctuation US(x1) caused by the transmission environment in the line radiation area of ​​the simulated voice line, where x1 is x1 T The corresponding function value when ; The fault risk intervention value corresponding to the i-th analog voice line at the current time is recorded as Ri, Ri=Pg1 DQ +β·Pg2 DQ , Among them, Pg1 DQ Pg2 represents the first fault risk probability corresponding to the i-th analog voice line at the current time; DQ represents the second fault risk probability corresponding to the i-th analog voice line at the current time; β represents the risk intervention conversion factor preset in the database.

7. The analog voice line intervention status monitoring system based on big data is characterized by: The system includes the following modules: A line radiation information extraction module, which obtains the connection relationship between the interactive ports in each analog voice line during the voice information transmission process, and extracts the connection device and line radiation area to which each interactive port on each analog voice line belongs; A model building and information mapping module, which builds a digital twin model of the analog voice line by simulating the position of the connection device to which each interactive port belongs on the voice line and the line radiation area, dynamically obtains the interaction information of each connection device in each analog voice line at different time points, and realizes the real-time data mapping and binding of the interaction information of the corresponding connection device to the corresponding connection device in the constructed digital twin model of the analog voice line, and feeds back the digital twin model of the analog voice line and its bound data mapping results to the status monitoring display terminal in real time; A voice transmission interference analysis module, which extracts the display information of the status monitoring display terminal in real time, combines the fluctuation of the interactive status information in the display information corresponding to different times in the historical data, analyzes the risk relationship of the timing communication fluctuation caused by the transmission environment in the line radiation area of ​​the simulated voice line, and the risk fluctuation relationship of the use status of each connected device in the simulated voice line; A line intervention risk analysis module, which combines various fault information corresponding to the simulated voice line in the historical data to predict the first fault risk probability corresponding to different times in the obtained time sequence communication fluctuation risk relationship, and the second fault risk probability corresponding to different times in the use status risk fluctuation relationship of the connected device; Generate a fault risk intervention value corresponding to each simulated voice route at the current time; An intervention status decision management module, wherein the intervention status decision management module sorts each analog voice line in ascending order according to the fault risk access value corresponding to the current time, generates a recommended sequence of analog voice lines corresponding to the current time, and assists users in executing data transmission decisions on analog voice lines.

8. The analog voice line intervention status monitoring system based on big data according to claim 7 is characterized by: The line intervention risk analysis module includes a timing communication fluctuation risk probability prediction unit, a usage status risk probability prediction unit and a fault risk intervention analysis unit. The time sequence communication fluctuation risk probability prediction unit combines each fault information corresponding to the simulated voice line in the historical data to predict the first fault risk probability corresponding to different times in the obtained time sequence communication fluctuation risk relationship; The usage status risk probability prediction unit combines each fault information corresponding to the simulated voice line in the historical data to predict the second fault risk probability corresponding to different times in the usage status risk fluctuation relationship of the connected device; The fault risk intervention analysis unit generates a fault risk intervention value corresponding to each simulated voice route at the current time according to the prediction results of the time sequence communication fluctuation risk probability prediction unit and the usage status risk probability prediction unit.

Images