Data processing system and method based on situation processing

Abstract

The invention discloses a data processing system and method based on situation processing, and belongs to the technical field of data processing systems. Comprising an optical path configuration unit, a monitoring optical fiber, a voiceprint library, a factor assembling module, a factor configuration unit, a primary preprocessing unit, a cycle setting unit, a secondary preprocessing unit, a data merging processing unit, a situation processing unit and a display unit. Through the mode, mass data can be analyzed and processed in real time, so that quick response to constantly changing conditions and environments is realized; according to the invention, situation early warning and visual display can be carried out for the construction type, the specific position, the construction time and the like on the to-be-detected line in the construction process.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing systems, and in particular to a data processing system and method based on situation processing. Background Art

[0002] The urban lifeline safe operation monitoring system is a safety guarantee for timely perception, early prediction and warning, and efficient disposal and response of urban lifeline risks.

[0003] Although there are some systems that can monitor project construction, such as CN112150623A, which calculates the safety distance between the construction project and the city lifeline through a risk assessment module, if the safety distance is less than the set value, it is determined that the construction project has safety hazards.

[0004] However, it mainly conducts risk assessment before project construction. It is impossible to provide situation warning and intuitive display of the construction type, specific location, construction time, etc. on the line to be tested during the project construction process; at the same time, how to analyze and process massive data in real time to achieve rapid response to changing situations and environments is also a technical problem that the present invention needs to solve.

[0005] Based on this, the present invention designs a data processing system and method based on situation processing to solve the above problems. Summary of the invention

[0006] In view of the above-mentioned shortcomings of the prior art, the present invention provides a data processing system and method based on situation processing.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0008] A data processing system based on situation processing, comprising:

[0009] An optical path configuration unit, used to configure n optical fiber lines according to the path direction of the road to be tested in the city, and map the positions of the n optical fiber lines;

[0010] Monitoring optical fiber is used to detect sound waves in each channel. When the sound waves exceed the threshold range, it is considered that an event has occurred, and the abnormal sound waves are intercepted and sent to the voiceprint library;

[0011] Voiceprint library: The voiceprint library identifies the construction type corresponding to the abnormal sound wave through the voiceprint detection model, and outputs the voiceprint matching similarity; the construction type includes equipment and action; the location of the abnormal channel, the time of abnormal occurrence and the voiceprint library recognition result are transmitted to the factor assembly module;

[0012] The factor assembly module is used to assemble the location of the abnormal channel, the time of abnormal occurrence, the voiceprint library recognition results and factors to form real-time event data;

[0013] A factor configuration unit is used to configure the effective monitoring range of the factor;

[0014] A primary preprocessing unit compares the assembled real-time event data with the factor configuration unit, performs data filtering, retains the initial screening real-time event data, and discards invalid real-time event data;

[0015] A cycle setting unit is used to set the total time Q seconds for a cycle detection of n optical fiber lines, and the detection time of each optical fiber line is Q / n seconds;

[0016] The secondary preprocessing unit determines whether the amount of data detected in Q / n seconds by the channel where the initial screening real-time event data is located is ≥70%×Q / n. If so, the initial screening real-time event data of the channel detected this time is retained as valid real-time event data; if not, the initial screening real-time event data of the channel detected this time is discarded;

[0017] The data merging processing unit is used to merge the valid real-time event data within the span of a channels within b min on the same optical fiber line and the same construction type to obtain a real-time event data set; merge the channel and time to form a channel interval and a time interval, and take the average value of the hit rate;

[0018] A situation processing unit, used to divide the merged real-time event data set into n batches, perform situation calculations on each batch, and output a situation data set;

[0019] The display unit is used to display the configured n optical fiber lines through a map plate; and to display the situation data sets one by one and to display event alarms.

[0020] Furthermore, the n optical fiber lines are numbered 1 to n; the length of each optical fiber line is L 1～n , assuming that the length of each channel is s meters, then each optical fiber line has m 1～n Channels, m 1～n =L 1～n / s; the starting channels of the n optical fiber lines are the same.

[0021] Furthermore, the locations of the n optical fiber lines are mapped, and the steps are as follows:

[0022] (1) Set the GPS data of the starting channel;

[0023] (2) According to the path direction of the urban road to be tested, the turning point of the optical fiber line is marked on the map;

[0024] (3) Based on the length of the optical fiber line, draw on the map each optical fiber line starting from the starting channel and passing through the calibrated turning point;

[0025] (4) Pair each channel with GPS data.

[0026] Furthermore, the factors include optical fiber line, starting channel, ending channel, starting time, ending time, construction type, hit rate, weather, channel range affected by the event, and time range affected by the event.

[0027] Furthermore, the effective monitoring range of the configuration factor specifically includes:

[0028] Configure fiber lines: select one or more of the n fiber lines as the fiber lines to be monitored. The unselected fiber lines are in sleep mode and are not monitored.

[0029] Configure the start channel: Set the start channel of n optical fiber lines to the same one;

[0030] Configure the end channel: configure the end channel according to the number of channels of each optical fiber line;

[0031] Configure start time: Set the start time according to the time when monitoring needs to be started;

[0032] Configure end time: Set the end time according to the time when monitoring needs to end;

[0033] Configure construction type: Enter the construction type that needs to be monitored;

[0034] Configuration hit rate > 90%;

[0035] Configure weather: Enter the weather type that meets the monitoring conditions;

[0036] Configure the range of channels affected by the event to be a;

[0037] The time range of the configuration event impact is b min.

[0038] Furthermore, a=8~10; b=3~6.

[0039] Furthermore, the specific steps of a pre-processing unit are:

[0040] (1) Determine whether the optical fiber line of the real-time event data is a configured optical fiber line. If so, it is an optical fiber line with monitoring turned on, and the data is retained; if not, it is an optical fiber line in a dormant state, monitoring is not turned on, and the data is discarded;

[0041] (2) determining whether the position of the abnormal channel of the real-time event data is within the interval between the configured start channel and the end channel; if so, retaining the data; if not, discarding the data;

[0042] (3) Determine whether the abnormal occurrence time of the real-time event data is within the time range from the configured start time to the end time. If so, retain the data; if not, discard the data;

[0043] (4) determining whether the construction type of the voiceprint library recognition result in the real-time event data is one of the configuration construction types, if so, retaining the data; if not, discarding the data;

[0044] (5) Determine whether the hit rate of the voiceprint library recognition result in the real-time event data is greater than 90%. If so, retain the data; if not, discard the data;

[0045] (6) Determine whether the weather of the real-time event data meets the monitoring conditions. If yes, keep the data; if no, discard the data;

[0046] (7) The retained data is transmitted to the secondary data processing unit as the primary screening real-time event data; the primary screening real-time event data is simplified to: location-time-construction type-hit rate.

[0047] Furthermore, the specific steps of the situation processing unit are:

[0048] (1) Input the real-time event data set A1; assign a batch number according to the fiber line number;

[0049] (2) Obtain the real-time event data set B with the same batch number and the same construction type within the previous b min k ; k represents the number of real-time event data sets obtained;

[0050] (3) If k = 0, it means that there is no real-time event data set of the same optical fiber line and the same construction type within b min, and this real-time event data set is considered as new event data;

[0051] (4) If k≠0, obtain the real-time event data set B of the same optical fiber line and the same construction type within b min k ;

[0052] (5) Calculate real-time event dataset A1 and real-time event dataset B k the middle channel;

[0053] (6) Calculate the intermediate channel of the real-time event dataset A1 and the real-time event dataset B k The difference between the middle channels |e k ∣;

[0054] (7) Determine whether |e exists k ∣≤a;

[0055] If it does not exist, then all ∣e k ∣>a, it means that the event is too far away from the acquired event channel, and this real-time event data set is considered to be new event data;

[0056] If it exists, the real-time event dataset A1 is combined with |e k The real-time event data set B with |≤a is merged, and the channel and time are merged to form the channel interval and time interval. The hit rate is averaged to form the event update data;

[0057] (8) Calculate the intermediate channel T of the channel interval of new event data and event update data, merge the new event data and event update data of the same optical fiber line, the same intermediate channel T, and the same construction type, and count the total number of new event data and event update data merged on the day as the data volume, forming h situation data sets {location construction type data volume}.

[0058] A data processing method based on situation processing, using the data processing system based on situation processing, comprises the following steps:

[0059] 1. Light path configuration, cycle setting and factor configuration;

[0060] The optical path configuration unit configures n optical fiber lines according to the path direction of the urban road to be tested. The n optical fiber lines are numbered 1 to n. The length of each optical fiber line is L. 1～n , assuming that the length of each channel is s meters, then each optical fiber line has m 1～n Channels, m 1～n =L 1～n / s; the starting channels of the n optical fiber lines are the same; and the positions of the n optical fiber lines are mapped at the same time;

[0061] The cycle setting unit sets the total time Q seconds for a cycle detection of n optical fiber lines, and the detection time of each optical fiber line is Q / n seconds; the optical fiber line, the start channel, the end channel, the start time, the end time, the construction type, the hit rate, the weather, the channel range affected by the event, and the time range affected by the event are configured through the factor configuration unit;

[0062] 2. Monitoring and identification, data assembly to form real-time event data;

[0063] The monitoring optical fiber detects the sound waves of each channel. When the sound waves exceed the threshold range, it is considered that an event has occurred. The abnormal sound waves are intercepted and sent to the voiceprint library. The construction type corresponding to the abnormal sound waves and the output hit rate are identified through the voiceprint detection model; the construction type includes equipment and action; the location of the abnormal channel, the time of abnormal occurrence and the recognition result of the voiceprint library are transmitted to the factor assembly module; the factor assembly module assembles the location of the abnormal channel, the time of abnormal occurrence, the recognition result of the voiceprint library and the factors to form real-time event data;

[0064] 3. The primary preprocessing unit compares the assembled real-time event data with the factor configuration unit, performs data filtering, retains the initial screening real-time event data, and discards invalid real-time event data; the specific steps are:

[0065] (1) Determine whether the optical fiber line of the real-time event data is a configured optical fiber line. If so, it is an optical fiber line with monitoring turned on, and the data is retained; if not, it is an optical fiber line in a dormant state, monitoring is not turned on, and the data is discarded;

[0066] (2) determining whether the position of the abnormal channel of the real-time event data is within the interval between the configured start channel and the end channel; if so, retaining the data; if not, discarding the data;

[0067] (3) Determine whether the abnormal occurrence time of the real-time event data is within the time range from the configured start time to the end time. If so, retain the data; if not, discard the data;

[0068] (4) determining whether the construction type of the voiceprint library recognition result in the real-time event data is one of the configuration construction types, if so, retaining the data; if not, discarding the data;

[0069] (5) Determine whether the hit rate of the voiceprint library recognition result in the real-time event data is greater than 90%. If so, retain the data; if not, discard the data;

[0070] (6) Determine whether the weather of the real-time event data meets the monitoring conditions. If yes, keep the data; if no, discard the data;

[0071] (7) The retained data is transmitted to the secondary data processing unit as the primary screening real-time event data; the primary screening real-time event data is simplified to: location-time-construction type-hit rate;

[0072] Fourth, the secondary preprocessing unit determines whether the amount of data detected in Q / n seconds of the channel where the initial screening real-time event data is located is ≥70%×Q / n. If so, the initial screening real-time event data of the channel detected this time is retained as valid real-time event data; if not, the initial screening real-time event data of the channel detected this time is discarded;

[0073] 5. The data merging processing unit merges the valid real-time event data within the span of a channels within b min on the same optical fiber line and the same construction type to obtain a real-time event data set; merges the channel and time to form a channel interval and a time interval, and takes the average hit rate;

[0074] 6. The situation processing unit divides the merged real-time event data set into n batches for situation calculation and outputs the situation data set; the specific steps are:

[0075] (1) Input the real-time event data set A1; assign a batch number according to the fiber line number;

[0076] (2) Obtain the real-time event data set B with the same batch number and the same construction type within the previous b min k ; k represents the number of real-time event data sets obtained;

[0077] (3) If k = 0, it means that there is no real-time event data set of the same optical fiber line and the same construction type within b min, and this real-time event data set is considered as new event data;

[0078] (4) If k≠0, obtain the real-time event data set B of the same optical fiber line and the same construction type within b min k ;

[0079] (5) Calculate real-time event dataset A1 and real-time event dataset B k the middle channel;

[0080] (6) Calculate the intermediate channel of the real-time event dataset A1 and the real-time event dataset B k The difference between the middle channels |e k ∣;

[0081] (7) Determine whether |e exists k ∣≤a;

[0082] If it does not exist, then all ∣e k ∣>a, it means that the event is too far away from the acquired event channel, and this real-time event data set is considered to be new event data;

[0083] If it exists, the real-time event dataset A1 is combined with |e k The real-time event data set B with |≤a is merged, and the channel and time are merged to form the channel interval and time interval. The hit rate is averaged to form the event update data;

[0084] (8) Calculate the intermediate channel T of the channel interval of new event data and event update data, merge the new event data and event update data of the same optical fiber line, the same intermediate channel T, and the same construction type, and count the total number of new event data and event update data merged on the day as the data volume, forming h situation data sets {location construction type data volume}, and display the event alarm information through the display unit.

[0085] Furthermore, by clicking on the data volume, a data expansion instruction is triggered to display new event data and event update data under the situation data set one by one.

[0086] Compared with the prior art, the present invention has the following beneficial effects:

[0087] After the abnormal sound waves occur at the channel on each line, the present invention is identified by the voiceprint library and assembled by the factor assembly module to form a real-time event data; when an abnormal sound wave exists in a channel, the nearby channels may also be monitored, and there are many types of abnormal sound waves, and there are also some abnormal sound waves that do not need to be detected. Therefore, the data volume of real-time event data is relatively large, and factor configuration is required; the factor configuration unit can realize effective and reasonable adjustment of the monitoring range, which is conducive to the subsequent filtering of other events and improving monitoring efficiency;

[0088] The present invention can filter out a large amount of invalid data after being processed by a pre-processing unit. In actual use, it can even collect 100 pieces of data, and only about 30 pieces of valid data are left, which is conducive to greatly reducing the subsequent data processing pressure;

[0089] After being processed by the secondary preprocessing unit, the present invention can further filter out a large amount of invalid data. In actual use, it can even collect 100 pieces of data, and only about 10 valid data are left, which is conducive to further significantly reducing the subsequent data processing pressure;

[0090] Since abnormal sound waves may also be detected in the surrounding channels (about 8 spans) of the channel when a continuous event occurs, each event may have multiple valid real-time event data. Therefore, the present invention regards the valid real-time event data within a channel span within b min of the same optical fiber line and the same construction type as the data of the same event, and can further merge the data to reduce the amount of data for subsequent processing and form a real-time event data set;

[0091] The present invention divides the merged real-time event data set into n batches through a situation processing unit to perform situation calculations respectively, that is, the real-time event data set of each optical fiber line is respectively subjected to a situation calculation, and the situation data set is output; the situation processing result can be displayed intuitively, and an alarm can be issued through a display unit;

[0092] In summary, the present invention can perform real-time analysis and processing of massive amounts of data to achieve rapid response to changing situations and environments; during the construction process, the present invention can provide situation warnings and intuitive displays of the type of construction, specific location, construction time, etc. occurring on the line to be tested. BRIEF DESCRIPTION OF THE DRAWINGS

[0093] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0094] Figure 1 A schematic diagram of the optical path configuration of the present invention;

[0095] Figure 2 This is a schematic diagram of an event alarm display of the present invention;

[0096] Figure 3 It is a schematic diagram of triggering a data expansion instruction according to the present invention. DETAILED DESCRIPTION

[0097] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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.

[0098] Embodiment 1

[0099] In some embodiments, please refer to the attached instructions. Figure 1-3 , a data processing system based on situation processing, comprising:

[0100] The optical path configuration unit is used to configure n optical fiber lines according to the path direction of the urban road to be tested. The n optical fiber lines are numbered 1 to n. The length of each optical fiber line is L. 1～n , assuming that the length of each channel is s meters, then each optical fiber line has m 1～n Channels, m 1～n =L 1～n / s; the starting channels of the n optical fiber lines are the same, and the ending channels can be the same or different; and the positions of the n optical fiber lines are mapped at the same time;

[0101] Among them, m 1 Indicates the number of channels of optical fiber line 1, mn Indicates the number of channels of fiber line n;

[0102] For example Figure 1 As shown, 9 optical fiber lines are configured in Nanjing, among which the length of optical fiber line No. 1 is 1 km, and the length of each channel is set to 1 meter, so the number of channels is 1000;

[0103] The steps of mapping the locations of n optical fiber lines are as follows:

[0104] (1) Set the GPS data of the starting channel;

[0105] (2) According to the path direction of the urban road to be tested, the turning point of the optical fiber line is marked on the map;

[0106] (3) Based on the length of the optical fiber line, draw on the map each optical fiber line starting from the starting channel and passing through the calibrated turning point;

[0107] (4) Pair each channel with GPS data;

[0108] Monitoring optical fiber is used to detect sound waves in each channel. When the sound wave (frequency or amplitude) exceeds the threshold range, it is considered that an event has occurred, and the abnormal sound wave is intercepted and sent to the voiceprint library;

[0109] Voiceprint library, which uses voiceprint detection model (such as DFCNN voiceprint detection model) to identify the construction type corresponding to the abnormal sound wave and output the voiceprint matching similarity (hit rate); construction type includes equipment and action; the location of the abnormal channel (channel 142 of optical fiber line 1), the time of abnormal occurrence and the voiceprint library recognition result (construction type and hit rate) are transmitted to the factor assembly module;

[0110] For example, when an excavator performs digging, the hit rate is 100%; when a cutting machine performs cutting, the hit rate is 100%;

[0111] The factor assembly module is used to assemble the location of the abnormal channel, the time of abnormal occurrence, the voiceprint library recognition results and factors to form real-time event data;

[0112] The factors include optical fiber line, starting channel, ending channel, starting time, ending time, construction type, hit rate, weather, channel range affected by the event, and time range affected by the event;

[0113] For example, the real-time event data formed after assembling factors: Fiber optic line 1 (channel 1-channel 1000, 8:00-22:00), fiber optic line 1 channel 142-2024.5.6 15:25:31-excavator digging-hit rate 100%, sunny day, the channel range affected by the event is 8, and the time range affected by the event is 5 minutes;

[0114] After the abnormal sound waves occur in the channel on each line, they are all identified by the voiceprint library and assembled by the factor assembly module to form a real-time event data. When an abnormal sound wave exists in a channel, the nearby channels may also be monitored. At the same time, there are many types of abnormal sound waves, and there are also some abnormal sound waves that do not need to be detected. Therefore, the data volume of real-time event data is relatively large, and factor configuration is required.

[0115] A factor configuration unit is used to configure the effective monitoring range of the factor;

[0116] The steps of configuring the optical fiber line are as follows: selecting one or more of the n optical fiber lines as the optical fiber lines to be monitored, and the unselected optical fiber lines are in a dormant state and are not monitored; the optical fiber lines can be selected as needed to start monitoring;

[0117] The steps of configuring the starting channel are: setting the starting channels of n optical fiber lines to the same one, for example, channel 1;

[0118] The steps of configuring the end channel are as follows: according to the number of channels of each optical fiber line, respectively configure the end channel, for example, optical fiber line No. 1 has 1000 channels, the starting channel is channel 1, and the end channel is set to channel 1000; optical fiber line No. 2 has 2000 channels, the starting channel is channel 1, and the end channel is set to channel 2000;

[0119] The steps to configure the start time are as follows: Set the start time according to the time you need to start monitoring. For example, if you need to start monitoring at 8 am, set the start time to 8:00;

[0120] The steps to configure the end time are as follows: Set the end time according to the time when monitoring needs to end. For example, if monitoring needs to end at 10 pm, the end time is set to 22:00;

[0121] The steps for configuring the construction type are: input the construction type to be monitored; for example, excavator digging, cutter cutting, tamping machine tamping, etc.;

[0122] Configuration hit rate > 90%;

[0123] The steps to configure the weather are: enter the weather type that meets the monitoring conditions (sunny, cloudy, overcast, etc.); since optical fiber is sensitive and severe weather such as heavy rain has a greater impact on optical fiber, it leads to more false alarms;

[0124] Configure the range of channels affected by the event to be a, where a = 8 to 10;

[0125] Configure the time range of event impact to be b min, where b = 3 to 6;

[0126] The factor configuration unit can effectively and reasonably adjust the monitoring range, which is conducive to filtering out other events and improving monitoring efficiency;

[0127] A primary preprocessing unit compares the assembled real-time event data with the factor configuration unit, performs data filtering, retains the initial screening real-time event data, and discards invalid real-time event data;

[0128] The specific steps are:

[0129] (1) Determine whether the optical fiber line of the real-time event data is a configured optical fiber line. If so, it is an optical fiber line with monitoring turned on, and the data is retained; if not, it is an optical fiber line in a dormant state, monitoring is not turned on, and the data is discarded;

[0130] (2) determining whether the position of the abnormal channel of the real-time event data is within the interval between the configured start channel and the end channel; if so, retaining the data; if not, discarding the data;

[0131] (3) Determine whether the abnormal occurrence time of the real-time event data is within the time range from the configured start time to the end time. If so, retain the data; if not, discard the data;

[0132] (4) determining whether the construction type of the voiceprint library recognition result in the real-time event data is one of the configuration construction types, if so, retaining the data; if not, discarding the data;

[0133] (5) Determine whether the hit rate of the voiceprint library recognition result in the real-time event data is greater than 90%. If so, retain the data; if not, discard the data;

[0134] (6) Determine whether the weather of the real-time event data meets the monitoring conditions. If yes, keep the data; if no, discard the data;

[0135] (7) The retained data is transmitted to the secondary data processing unit as primary screening real-time event data;

[0136] The initial screening of real-time event data can be simplified as: Fiber optic line 1 channel 142-2024.5.6 15:25:31-excavator digging soil-hit rate 100%.

[0137] After being processed by a pre-processing unit, a large amount of invalid data can be filtered out. In actual use, it is even possible to collect 100 pieces of data, and only about 30 valid data are left in the end, which is conducive to greatly reducing the subsequent data processing pressure;

[0138] A cycle setting unit is used to set the total time Q seconds for a cycle detection of n optical fiber lines, and the detection time of each optical fiber line is Q / n seconds;

[0139] Normally, one piece of data can be detected per second, and the channel under construction can normally detect Q / n pieces of data; but considering packet loss and other situations, it is set that the channel under construction can normally detect 70% × Q / n pieces of data;

[0140] If 70%×Q / n pieces of data are not detected, and only 60%×Q / n pieces of data are detected, it means that the construction event is a discontinuous event and is considered to be an unexpected interference event, and the 60%×Q / n pieces of data need to be discarded;

[0141] For example, if there are 9 optical fiber lines, and a detection cycle is set to 90 seconds, and each optical fiber line is detected for 10 seconds, for a continuous construction event, the channel where the construction occurs can detect 7 or more real-time event data; if only 6 data are detected, it means that the construction event is a discontinuous event and is considered to be an interference accident, and these 6 data are discarded;

[0142] The secondary preprocessing unit determines whether the amount of data detected in Q / n seconds by the channel where the initial screening real-time event data is located is ≥70%×Q / n. If so, the initial screening real-time event data of the channel detected this time is retained as valid real-time event data; if not, the initial screening real-time event data of the channel detected this time is discarded;

[0143] For example, within 90 seconds, if 8 data are detected on channel 4 of line 1, the event near channel 4 is considered to be a continuous construction event, otherwise it is a discontinuous construction event, and these 8 data are retained; if 3 data are detected on channel 245 of line 2, the event near channel 245 is considered to be an interference event, and these 3 data are deleted;

[0144] After being processed by the secondary pre-processing unit, a large amount of invalid data can be further filtered out. In actual use, it can even collect 100 pieces of data, and only about 10 valid data are left in the end, which is conducive to further significantly reducing the subsequent data processing pressure;

[0145] The data merging processing unit is used to merge the valid real-time event data within the span of a channels within b min on the same optical fiber line and the same construction type to obtain a real-time event data set; merge the channels and time to form a channel interval (the channel endpoints take the minimum channel and the maximum channel) and a time interval (the time endpoints take the minimum time point and the maximum time point), and take the average value of the hit rate;

[0146] Since abnormal sound waves may also be detected in the surrounding channels (about 8 spans) of the channel when a continuous event occurs, each event may have multiple valid real-time event data. Therefore, the valid real-time event data within a channel span within b min on the same optical fiber line and the same construction type are considered to be the data of the same event.

[0147] For example, the following are two valid real-time event data:

[0148] Fiber optic line No. 1, channel 146 - 2024.5.6 15:28:01 - Excavator digging - hit rate 100%.

[0149] Fiber optic line No. 1, channel 142 - 2024.5.6 15:25:31 - Excavator digging - hit rate 100%;

[0150] The merged real-time event dataset is:

[0151] Optical fiber line 1, channels 142 to 146 - 2024.5.6 15:25:31 to 2024.5.6 15:28:01 - excavator digging - hit rate 100%;

[0152] Preferably, a is 8 and b is 5 minutes, because optical fiber is sensitive, and when construction occurs, abnormal sound waves can be detected in multiple channels near one channel. Under the premise of the same optical fiber line, the same construction type, and occurring within 5 minutes, the effective real-time event data within the span of 8 channels can be considered as the data of the same event. Therefore, the data input to the situation processing unit after the event occurs is the real-time event data set after the merger;

[0153] At the same time, when merging, if the minimum channel = the maximum channel, only the time is merged. For example, near channel 356 of optical fiber line 1, only channel 356 detected excavator digging events at multiple times such as 15:30:00, 15:30:10...15:31:50 on May 6, 2024, and the hit rate was 100%. Then the real-time event data set after merging is: channel 356 of optical fiber line 1-2024.5.6 15:30:00~2024.5.6 15:31:50-excavator digging-hit rate 100%;

[0154] A situation processing unit is used to divide the merged real-time event data set into n batches and perform situation calculations on each batch, that is, perform a situation calculation on the real-time event data set of each optical fiber line and output the situation data set;

[0155] The specific steps are:

[0156] (1) Input the real-time event data set A1; assign a batch number according to the fiber line number;

[0157] For example, a new real-time event data set A1 is received: Channels 145 to 148 of Optical Fiber Line 1 - 2024.5.6 15:29:50 to 2024.5.6 15:30:00 - Excavator digging - Hit rate 100%. The batch number 1 is assigned.

[0158] (2) Obtain the real-time event data set B with the same batch number (i.e., the same optical fiber line) and the same construction type within the previous b min. k ; k represents the number of real-time event data sets obtained;

[0159] (3) If k = 0, it means that there is no real-time event data set of the same optical fiber line and the same construction type within b min, and this real-time event data set is considered as new event data;

[0160] (4) If k≠0, obtain the real-time event data set B of the same optical fiber line and the same construction type within b min k ;

[0161] For example, there are two real-time event data sets of optical fiber line No. 1 and excavator digging within 5 minutes:

[0162] Optical fiber line 1, channels 142 to 146 - 2024.5.6 15:25:31 to 2024.5.6 15:28:01 - excavator digging - hit rate 100%;

[0163] Optical fiber line No. 1, channels 158 to 160 - 2024.5.6 15:27:22 to 2024.5.6 15:28:20 - excavator digging - hit rate 100%;

[0164] (5) Calculate real-time event dataset A1 and real-time event dataset B k the middle channel;

[0165] The middle channel 146 or channel 147 of channels 145 to 148 of optical fiber line No. 1 (select any one, for example, select channel 146);

[0166] Channel 144, the middle channel of channels 142 to 146 of optical fiber line No. 1;

[0167] Channel 159, the middle channel of channels 158 to 160 on optical fiber line 1;

[0168] (6) Calculate the intermediate channel of the real-time event dataset A1 and the real-time event dataset B k The difference between the middle channels |e k ∣;

[0169] For example: |146-144|=2; |146-159|=13;

[0170] (7) Determine whether |e exists k ∣≤a;

[0171] If it does not exist, then all ∣e k ∣>a, it means that the event is too far away from the acquired event channel, and this real-time event data set can be considered as new event data;

[0172] If it exists, the real-time event dataset A1 is combined with |e k The real-time event data set B with |≤a is merged, and the channel and time are merged to form a channel interval (the channel endpoints take the minimum channel and the maximum channel) and a time interval (the time endpoints take the minimum time point and the maximum time point), and the hit rate is averaged to form event update data;

[0173] For example: |148-144|=4<8;

[0174] The event update data is: Optical fiber line No. 1 channel 142 to 148 - 2024.5.6 15:25:31 to 2024.5.615:30:00 - excavator digging - hit rate 100%;

[0175] (8) Calculate the intermediate channel T of the channel interval of new event data and event update data, merge the new event data and event update data of the same optical fiber line, the same intermediate channel T, and the same construction type, and count the total number of new event data and event update data merged on the day as the data volume, forming h situation data sets {location construction type data volume};

[0176] The display unit is used to display the configured n optical fiber lines through the map plate; and to display the situation data sets one by one to achieve the purpose of alarm;

[0177] Example of situation data set display:

[0178] Location construction type data volume

[0179] Two excavators dug soil near Channel 145 of Optical Fiber Line 1

[0180] 15 lines were cut by the cutting machine near channel 25 of No. 2 optical fiber line

[0181] Today, there are 2 alarm data under the first situation data set. By clicking the data volume to trigger the data expansion command, the 2 data under the situation data set (new event data and event update data of the excavator digging type with the middle channel of the No. 1 optical fiber line being channel 145) are expanded and displayed one by one. The following is an example:

[0182] Optical fiber line No. 1, channel 145 - 2024.5.6 8:00:01 ~ 2024.5.6 8:02:01 - excavator digging - hit rate 100%;

[0183] Optical fiber line No. 1, channels 144 to 146 - 2024.5.6 10:00:00 to 2024.5.6 10:02:30 - excavator digging - hit rate 100%;

[0184] Optical fiber line No. 1, channels 144 to 146 - 2024.5.6 20:00:00 to 2024.5.6 20:02:20 - excavator digging - hit rate 100%.

[0185] Embodiment 2

[0186] In some embodiments, Figure 1-3 As shown, a data processing method based on situation processing is implemented using the data processing system based on situation processing, comprising the following steps:

[0187] 1. Light path configuration, cycle setting and factor configuration;

[0188] The optical path configuration unit configures n optical fiber lines according to the path direction of the urban road to be tested. The n optical fiber lines are numbered 1 to n. The length of each optical fiber line is L. 1～n , assuming that the length of each channel is s meters, then each optical fiber line has m 1～n Channels, m 1～n =L 1～n / s; the starting channels of the n optical fiber lines are the same; and the positions of the n optical fiber lines are mapped at the same time;

[0189] The cycle setting unit sets the total time Q seconds for a cycle detection of n optical fiber lines, and the detection time of each optical fiber line is Q / n seconds; the optical fiber line, the start channel, the end channel, the start time, the end time, the construction type, the hit rate, the weather, the channel range affected by the event, and the time range affected by the event are configured through the factor configuration unit;

[0190] 2. Monitoring and identification, data assembly to form real-time event data;

[0191] The monitoring optical fiber detects the sound waves of each channel. When the sound waves exceed the threshold range, it is considered that an event has occurred. The abnormal sound waves are intercepted and sent to the voiceprint library. The construction type corresponding to the abnormal sound waves and the output hit rate are identified through the voiceprint detection model; the construction type includes equipment and action; the location of the abnormal channel, the time of abnormal occurrence and the recognition result of the voiceprint library are transmitted to the factor assembly module; the factor assembly module assembles the location of the abnormal channel, the time of abnormal occurrence, the recognition result of the voiceprint library and the factors to form real-time event data;

[0192] 3. The primary preprocessing unit compares the assembled real-time event data with the factor configuration unit, performs data filtering, retains the initial screening real-time event data, and discards invalid real-time event data; the specific steps are:

[0193] (1) Determine whether the optical fiber line of the real-time event data is a configured optical fiber line. If so, it is an optical fiber line with monitoring turned on, and the data is retained; if not, it is an optical fiber line in a dormant state, monitoring is not turned on, and the data is discarded;

[0194] (2) determining whether the position of the abnormal channel of the real-time event data is within the interval between the configured start channel and the end channel; if so, retaining the data; if not, discarding the data;

[0195] (3) Determine whether the abnormal occurrence time of the real-time event data is within the time range from the configured start time to the end time. If so, retain the data; if not, discard the data;

[0196] (4) determining whether the construction type of the voiceprint library recognition result in the real-time event data is one of the configuration construction types, if so, retaining the data; if not, discarding the data;

[0197] (5) Determine whether the hit rate of the voiceprint library recognition result in the real-time event data is greater than 90%. If so, retain the data; if not, discard the data;

[0198] (6) Determine whether the weather of the real-time event data meets the monitoring conditions. If yes, keep the data; if no, discard the data;

[0199] (7) The retained data is transmitted to the secondary data processing unit as the primary screening real-time event data; the primary screening real-time event data can be simplified as: location-time-construction type-hit rate;

[0200] Fourth, the secondary preprocessing unit determines whether the amount of data detected in Q / n seconds of the channel where the initial screening real-time event data is located is ≥70%×Q / n. If so, the initial screening real-time event data of the channel detected this time is retained as valid real-time event data; if not, the initial screening real-time event data of the channel detected this time is discarded;

[0201] 5. The data merging processing unit merges the valid real-time event data of the same optical fiber line, the same construction type, and within the span range of a channels within b min to obtain a real-time event data set;

[0202] Event merging includes channel merging, time merging, and hit rate merging. When merging channels, the channel endpoints take the minimum channel and the maximum channel to form the merged channel interval. When merging time, the time endpoints take the minimum time point and the maximum time point to form the merged time interval. The hit rate takes the average value.

[0203] For example, the following are two valid real-time event data:

[0204] Fiber optic line No. 1, channel 146 - 2024.5.6 15:28:01 - Excavator digging - hit rate 100%.

[0205] Fiber optic line No. 1, channel 142 - 2024.5.6 15:25:31 - Excavator digging - hit rate 100%;

[0206] The merged real-time event dataset is:

[0207] Optical fiber line 1, channels 142 to 146 - 2024.5.6 15:25:31 to 2024.5.6 15:28:01 - excavator digging - hit rate 100%;

[0208] 6. The situation processing unit divides the merged real-time event data set into n batches for situation calculation and outputs the situation data set; the specific steps are:

[0209] (1) Input a new real-time event data set A1; assign a batch number according to the fiber line number;

[0210] For example, a new real-time event data set A1 is received: Channels 145 to 148 of Optical Fiber Line 1 - 2024.5.6 15:29:50 to 2024.5.6 15:30:00 - Excavator digging - Hit rate 100%. The batch number 1 is assigned.

[0211] (2) Obtain the real-time event data set B with the same batch number and the same construction type within the previous b min k ; k represents the number of real-time event data sets obtained;

[0212] (3) If k = 0, it means that there is no real-time event data set of the same optical fiber line and the same construction type within b min, and this real-time event data set is considered as new event data;

[0213] (4) If k≠0, obtain the real-time event data set B of the same optical fiber line and the same construction type within b min k ;

[0214] For example, there are two real-time event data sets of optical fiber line No. 1 and excavator digging within 5 minutes:

[0215] Optical fiber line 1, channels 142 to 146 - 2024.5.6 15:25:31 to 2024.5.6 15:28:01 - excavator digging - hit rate 100%;

[0216] Optical fiber line No. 1, channels 158 to 160 - 2024.5.6 15:27:22 to 2024.5.6 15:28:20 - excavator digging - hit rate 100%;

[0217] (5) Calculate real-time event dataset A1 and real-time event dataset B k the middle channel;

[0218] The middle channel 146 or channel 147 of channels 145 to 148 of optical fiber line No. 1 (select any one, for example, select channel 146);

[0219] Channel 144, the middle channel of channels 142 to 146 of optical fiber line No. 1;

[0220] Channel 159, the middle channel of channels 158 to 160 on optical fiber line 1;

[0221] (6) Calculate the intermediate channel of the real-time event dataset A1 and the real-time event dataset B k The difference between the middle channels |e k ∣;

[0222] For example: |146-144|=2; |146-159|=13;

[0223] (7) Determine whether |e exists k ∣≤a;

[0224] If it does not exist, then all ∣e k ∣>a, it means that the event is too far away from the acquired event channel, and this real-time event data set can be considered as new event data;

[0225] If it exists, the real-time event dataset A1 is combined with |e k The real-time event data set B with |≤a is merged, and the channel and time are merged to form the channel interval and time interval. The hit rate is averaged to form the event update data;

[0226] For example: |148-144|=4<8;

[0227] The event update data is: Optical fiber line No. 1 channel 142 to 148 - 2024.5.6 15:25:31 to 2024.5.615:30:00 - excavator digging - hit rate 100%;

[0228] (8) Calculate the intermediate channel T of the channel interval of new event data and event update data, merge the new event data and event update data of the same optical fiber line, the same intermediate channel T, and the same construction type, and count the total number of new event data and event update data merged on the day as the data volume, forming h situation data sets {location construction type data volume}, and display the event alarm information through the display unit.

[0229] Example of situation data set display:

[0230] Location construction type data volume

[0231] Two excavators dug soil near Channel 145 of Optical Fiber Line 1

[0232] 15 lines were cut by the cutting machine near channel 25 of No. 2 optical fiber line

[0233] Today, there are 2 alarm data under the first situation data set. By clicking the data volume to trigger the data expansion command, the 2 data under the situation data set (new event data and event update data of the excavator digging type with the middle channel of the No. 1 optical fiber line being channel 145) are expanded and displayed one by one. The following is an example:

[0234] Optical fiber line No. 1, channel 145 - 2024.5.6 8:00:01 ~ 2024.5.6 8:02:01 - excavator digging - hit rate 100%;

[0235] Optical fiber line No. 1, channels 144 to 146 - 2024.5.6 10:00:00 to 2024.5.6 10:02:30 - excavator digging - hit rate 100%;

[0236] Optical fiber line No. 1, channels 144 to 146 - 2024.5.6 20:00:00 to 2024.5.6 20:02:20 - excavator digging - hit rate 100%.

[0237] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A data processing system based on situation processing, characterized in that: include: An optical path configuration unit, used to configure n optical fiber lines according to the path direction of the road to be tested in the city, and map the positions of the n optical fiber lines; Monitoring optical fiber is used to detect sound waves in each channel. When the sound waves exceed the threshold range, it is considered that an event has occurred, and the abnormal sound waves are intercepted and sent to the voiceprint library; Voiceprint library: The voiceprint library identifies the construction type corresponding to the abnormal sound wave through the voiceprint detection model, and outputs the voiceprint matching similarity; the construction type includes equipment and action; the location of the abnormal channel, the time of abnormal occurrence and the voiceprint library recognition result are transmitted to the factor assembly module; The factor assembly module is used to assemble the location of the abnormal channel, the time of abnormal occurrence, the voiceprint library recognition results and factors to form real-time event data; A factor configuration unit is used to configure the effective monitoring range of the factor; A primary preprocessing unit compares the assembled real-time event data with the factor configuration unit, performs data filtering, retains the initial screening real-time event data, and discards invalid real-time event data; A cycle setting unit is used to set the total time Q seconds for a cycle detection of n optical fiber lines, and the detection time of each optical fiber line is Q / n seconds; The secondary preprocessing unit determines whether the amount of data detected in Q / n seconds by the channel where the initial screening real-time event data is located is ≥70%×Q / n. If so, the initial screening real-time event data of the channel detected this time is retained as valid real-time event data; if not, the initial screening real-time event data of the channel detected this time is discarded; The data merging processing unit is used to merge the valid real-time event data within the span of a channels within b min on the same optical fiber line and the same construction type to obtain a real-time event data set; merge the channel and time to form a channel interval and a time interval, and take the average value of the hit rate; A situation processing unit, used to divide the merged real-time event data set into n batches, perform situation calculations on each batch, and output a situation data set; A display unit, used for displaying the configured n optical fiber lines through a map plate; And display the situation data set one by one, and display the event alarm.

2. The data processing system based on situation processing according to claim 1, characterized in that: n optical fiber lines are numbered 1 to n; the length of each optical fiber line is L 1～n , assuming that the length of each channel is s meters, then each optical fiber line has m 1～n Channels, m 1～n =L 1～n / s; the starting channels of the n optical fiber lines are the same.

3. The data processing system based on situation processing according to claim 2, characterized in that: Map the locations of n optical fiber lines. The steps are: (1) Set the GPS data of the starting channel; (2) According to the path direction of the urban road to be tested, the turning point of the optical fiber line is marked on the map; (3) Based on the length of the optical fiber line, draw on the map each optical fiber line starting from the starting channel and passing through the calibrated turning point; (4) Pair each channel with GPS data.

4. The data processing system based on situation processing according to claim 3 is characterized in that: The factors include optical fiber line, starting channel, ending channel, starting time, ending time, construction type, hit rate, weather, channel range affected by the event, and time range affected by the event.

5. The data processing system based on situation processing according to claim 4 is characterized in that: The effective monitoring range of configuration factors specifically includes: Configure fiber lines: select one or more of the n fiber lines as the fiber lines to be monitored. The unselected fiber lines are in sleep mode and are not monitored. Configure the start channel: Set the start channel of n optical fiber lines to the same one; Configure the end channel: configure the end channel according to the number of channels of each optical fiber line; Configure start time: Set the start time according to the time when monitoring needs to be started; Configure end time: Set the end time according to the time when monitoring needs to end; Configure construction type: Enter the construction type that needs to be monitored; Configuration hit rate > 90%; Configure weather: Enter the weather type that meets the monitoring conditions; Configure the range of channels affected by the event to be a; The time range of the configuration event impact is b min.

6. The data processing system based on situation processing according to claim 5, characterized in that: a=8~10;b=3~6.

7. The data processing system based on situation processing according to claim 6, characterized in that: The specific steps of a pre-processing unit are: (1) determining whether the optical fiber line of the real-time event data is a configured optical fiber line, and if so, whether it is an optical fiber line for which monitoring is enabled, and retaining the data; If not, it is a fiber line in sleep mode, monitoring is not enabled, and data is discarded; (2) determining whether the position of the abnormal channel of the real-time event data is within the interval between the configured start channel and the end channel; if so, retaining the data; if not, discarding the data; (3) Determine whether the abnormal occurrence time of the real-time event data is within the time range from the configured start time to the end time. If so, retain the data; if not, discard the data; (4) determining whether the construction type of the voiceprint library recognition result in the real-time event data is one of the configuration construction types, if so, retaining the data; if not, discarding the data; (5) Determine whether the hit rate of the voiceprint library recognition result in the real-time event data is greater than 90%. If so, retain the data; if not, discard the data; (6) Determine whether the weather of the real-time event data meets the monitoring conditions. If yes, keep the data; if no, discard the data; (7) The retained data is transmitted to the secondary data processing unit as the primary screening real-time event data; the primary screening real-time event data is simplified to: location-time-construction type-hit rate.

8. The data processing system based on situation processing according to claim 7, characterized in that: The specific steps of the situation processing unit are: (1) Input the real-time event data set A1; assign a batch number according to the fiber line number; (2) Obtain the real-time event data set B with the same batch number and the same construction type within the previous b min k ; k represents the number of real-time event data sets obtained; (3) If k = 0, it means that there is no real-time event data set of the same optical fiber line and the same construction type within b min, and this real-time event data set is considered as new event data; (4) If k≠0, obtain the real-time event data set B of the same optical fiber line and the same construction type within b min k ; (5) Calculate real-time event dataset A1 and real-time event dataset B k The middle channel; (6) Calculate the intermediate channel of the real-time event dataset A1 and the real-time event dataset B k The difference between the middle channels |e k ∣; (7) Determine whether |e exists k ∣≤a; If it does not exist, then all ∣e k ∣>a, it means that the event is too far away from the acquired event channel, and this real-time event data set is considered to be new event data; If it exists, the real-time event dataset A1 is combined with |e k The real-time event data set B with |≤a is merged, and the channel and time are merged to form the channel interval and time interval. The hit rate is averaged to form the event update data; (8) Calculate the intermediate channel T of the channel interval of new event data and event update data, merge the new event data and event update data of the same optical fiber line, the same intermediate channel T, and the same construction type, and count the total number of new event data and event update data merged on the day as the data volume, forming h situation data sets {location construction type data volume}.

9. A data processing method based on situation processing, using the data processing system based on situation processing according to claim 8, characterized in that: The following steps are involved:

1. Light path configuration, cycle setting and factor configuration; The optical path configuration unit configures n optical fiber lines according to the path direction of the urban road to be tested. The n optical fiber lines are numbered 1 to n. The length of each optical fiber line is L. 1～n , assuming that the length of each channel is s meters, then each optical fiber line has m 1～n Channels, m 1～n =L 1～n / s; the starting channels of the n optical fiber lines are the same; and the positions of the n optical fiber lines are mapped at the same time; The cycle setting unit sets the total time of a cycle detection of n optical fiber lines to Q seconds, and the detection time of each optical fiber line is Q / n seconds; Configure the optical fiber line, starting channel, ending channel, starting time, ending time, construction type, hit rate, weather, channel range affected by the event, and time range affected by the event through the factor configuration unit; 2. Monitoring and identification, data assembly to form real-time event data; The monitoring optical fiber detects the sound waves of each channel. When the sound waves exceed the threshold range, it is considered that an event has occurred. The abnormal sound waves are intercepted and sent to the voiceprint library. The construction type corresponding to the abnormal sound waves and the output hit rate are identified through the voiceprint detection model; the construction type includes equipment and action; the location of the abnormal channel, the time of abnormal occurrence and the recognition result of the voiceprint library are transmitted to the factor assembly module; the factor assembly module assembles the location of the abnormal channel, the time of abnormal occurrence, the recognition result of the voiceprint library and the factors to form real-time event data; 3. The primary preprocessing unit compares the real-time event data obtained after assembly with the factor configuration unit, performs data filtering, retains the preliminary screening real-time event data, and discards invalid real-time event data; The specific steps are: (1) determining whether the optical fiber line of the real-time event data is a configured optical fiber line, and if so, whether it is an optical fiber line for which monitoring is enabled, and retaining the data; If not, it is a fiber line in sleep mode, monitoring is not enabled, and data is discarded; (2) determining whether the position of the abnormal channel of the real-time event data is within the interval between the configured start channel and the end channel; if so, retaining the data; if not, discarding the data; (3) Determine whether the abnormal occurrence time of the real-time event data is within the time range from the configured start time to the end time. If so, retain the data; if not, discard the data; (4) determining whether the construction type of the voiceprint library recognition result in the real-time event data is one of the configuration construction types, if so, retaining the data; if not, discarding the data; (5) Determine whether the hit rate of the voiceprint library recognition result in the real-time event data is greater than 90%. If so, retain the data; if not, discard the data; (6) Determine whether the weather of the real-time event data meets the monitoring conditions. If yes, keep the data; if no, discard the data; (7) The retained data is transmitted to the secondary data processing unit as the primary screening real-time event data; the primary screening real-time event data is simplified to: location-time-construction type-hit rate; Fourth, the secondary preprocessing unit determines whether the amount of data detected in Q / n seconds of the channel where the initial screening real-time event data is located is ≥70%×Q / n. If so, the initial screening real-time event data of the channel detected this time is retained as valid real-time event data; if not, the initial screening real-time event data of the channel detected this time is discarded; 5. The data merging processing unit merges the valid real-time event data within the span of a channels within b min on the same optical fiber line and the same construction type to obtain a real-time event data set; merges the channel and time to form a channel interval and a time interval, and takes the average hit rate; 6. The situation processing unit divides the merged real-time event data set into n batches to perform situation calculations respectively and output the situation data set; The specific steps are: (1) Input the real-time event data set A1; assign a batch number according to the fiber line number; (2) Obtain the real-time event data set B with the same batch number and the same construction type within the previous b min k ; k represents the number of real-time event data sets obtained; (3) If k = 0, it means that there is no real-time event data set of the same optical fiber line and the same construction type within b min, and this real-time event data set is considered as new event data; (4) If k≠0, obtain the real-time event data set B of the same optical fiber line and the same construction type within b min k ; (5) Calculate real-time event dataset A1 and real-time event dataset B k the middle channel; (6) Calculate the intermediate channel of the real-time event dataset A1 and the real-time event dataset B k The difference between the middle channels |e k ∣; (7) Determine whether |e exists k ∣≤a; If it does not exist, then all ∣e k ∣>a, it means that the event is too far away from the acquired event channel, and this real-time event data set is considered to be new event data; If it exists, the real-time event dataset A1 is combined with |e k The real-time event data set B with |≤a is merged, and the channel and time are merged to form the channel interval and time interval. The hit rate is averaged to form the event update data; (8) Calculate the intermediate channel T of the channel interval of new event data and event update data, merge the new event data and event update data of the same optical fiber line, the same intermediate channel T, and the same construction type, and count the total number of new event data and event update data merged on the day as the data volume, forming h situation data sets {location construction type data volume}, and display the event alarm information through the display unit.

10. The data processing method based on situation processing according to claim 9, characterized in that: Clicking on the data volume triggers the data expansion command to display the new event data and event update data under the situation data set one by one.

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