Railway tunnel water level intelligent monitoring and alarming method and platform

Abstract

The invention relates to the technical field of intelligent traffic, in particular to a railway tunnel water level intelligent monitoring and alarming method which comprises the steps that a water level monitoring instruction is responded, monitoring characteristic data collected by a monitoring end are obtained, and the monitoring characteristic data comprise monitoring point position data and video checking data; identifying the monitoring point data, obtaining a fixed position point and water level monitoring data, and calling a safe water level comparison table to obtain a safe water level threshold value corresponding to the fixed position point; generating a water level monitoring curve graph based on the water level monitoring data, intercepting the video check data when the current monitoring water level in the water level monitoring curve graph is higher than a safe water level threshold, and generating a water level alarm interface; and / or, receiving environment associated data, obtaining each estimated time point and a corresponding estimated water level value based on the environment associated data, generating a water level estimation curve graph, and generating a water level alarm interface when the future estimated water level in the water level estimation curve graph is higher than a safe water level threshold value; and sending the water level alarm interface to a management end.

Description

Technical Field

[0001] The present invention relates to the field of intelligent transportation technology, and in particular to a railway tunnel water level intelligent monitoring and alarm method and platform. Background Art

[0002] With the rapid development of railway transportation and the continuous increase in infrastructure construction, the number of railway tunnels has increased year by year. As an important transportation hub, water accumulation in railway tunnels may lead to a series of safety accidents, including corrosion damage to railway facilities, train derailment, line interruption, etc. Therefore, effective monitoring of water levels in railway tunnels is crucial.

[0003] At present, railway tunnel water level monitoring mainly relies on a combination of traditional water level sensors and manual inspections. Manual inspections require a lot of time and manpower, and are difficult to carry out under bad weather conditions, resulting in low inspection efficiency. In addition, most water level sensors have strict requirements on the use environment and can only provide real-time water level data, but cannot predict future water level changes, resulting in the inability to issue warnings and take countermeasures in time when the water level rises. Summary of the invention

[0004] The present invention provides a railway tunnel water level intelligent monitoring and alarm method and platform, which can perform intelligent monitoring and early warning of the railway tunnel water level, thereby improving the water level monitoring efficiency and the ability to predict future water level changes.

[0005] To solve the above technical problems, a technical solution adopted in an embodiment of the present invention is: to provide a railway tunnel water level intelligent monitoring and alarm method, including: responding to a water level monitoring instruction, obtaining monitoring feature data collected by a monitoring terminal, the monitoring feature data including monitoring point data and video verification data, identifying the monitoring point data, obtaining fixed position points and water level monitoring data, calling a safe water level comparison table to obtain a safe water level threshold value corresponding to the fixed position point, generating a water level monitoring curve chart based on the water level monitoring data, when the current monitored water level in the water level monitoring curve chart is higher than the safe water level threshold value, intercepting the video verification data, generating a water level alarm interface, and / or receiving environment-related data, obtaining each estimated time point and the corresponding estimated water level value based on the environment-related data, generating a water level estimation curve chart, when the future estimated water level in the water level estimation curve chart is higher than the safe water level threshold value, generating a water level alarm interface, and sending the water level alarm interface to a management terminal.

[0006] Optionally, a water level monitoring curve graph is generated based on the water level monitoring data, and when the current monitored water level in the water level monitoring curve graph is higher than the safety water level threshold, the video verification data is intercepted to generate a water level alarm interface, including: obtaining a water level monitoring record sequence based on the water level monitoring data, the water level monitoring record sequence including each monitoring time point and the corresponding monitoring water level value, establishing a rectangular coordinate system with the monitoring time as the horizontal axis and the monitoring water level as the vertical axis, drawing water level monitoring points in the rectangular coordinate system according to each monitoring time point and the corresponding monitoring water level value, generating a water level monitoring curve graph based on each water level monitoring point, and when the current monitored water level in the water level monitoring curve graph is higher than the safety water level threshold, generating monitoring water level alarm data and triggering an accident video acquisition request, intercepting the video verification data according to the accident video acquisition request, acquiring accident video data, combining the monitoring water level alarm data and the accident video data to generate a water level alarm interface.

[0007] Optionally, when the current monitored water level in the water level monitoring curve graph is higher than the safety water level threshold, monitoring water level alarm data is generated and an accident video acquisition request is triggered, and the video verification data is intercepted according to the accident video acquisition request to obtain the accident video data, including: determining the vertical coordinate value corresponding to the water level monitoring point most recently drawn in the water level monitoring curve graph as the current monitored water level, comparing the current monitored water level with the safety water level threshold, and when the current monitored water level is higher than the safety water level threshold, generating monitoring water level alarm data and triggering an accident video acquisition request, identifying the accident video acquisition request, obtaining the trigger time point, determining the video boundary time according to the trigger time point and a preset video acquisition rule, the video boundary time including a video start time point and a video end time point, locating the corresponding monitoring video segment in the video verification data according to the video start time point and the video end time point, intercepting the monitoring video segment to obtain the intercepted monitoring video segment, and determining the intercepted monitoring video segment as the accident video data.

[0008] Optionally, receiving environment-related data, obtaining each estimated time point and the corresponding estimated water level value based on the environment-related data, generating a water level estimation curve, and generating a water level alarm interface when the future estimated water level in the water level estimation curve is higher than the safe water level threshold, including: receiving environment-related data, identifying the environment-related data, obtaining environment-related attributes, the environment-related attributes including meteorological-related attributes and behavioral-related attributes, calling a corresponding water level estimation strategy based on the environment-related attributes, and determining each estimated time point according to the water level estimation strategy. A rectangular coordinate system is established with the estimated time as the horizontal axis and the estimated water level as the vertical axis, and water level estimation points are plotted in the rectangular coordinate system according to each estimated time point and the corresponding estimated water level value, and a water level estimation curve is generated based on each water level estimation point, and when the future estimated water level in the water level estimation curve is higher than the safe water level threshold, estimated water level alarm data is generated and an emergency allocation strategy is called, and a scheduling plan is determined according to the emergency allocation strategy, and the estimated water level alarm data and the scheduling plan are combined to generate a water level alarm interface.

[0009] Optionally, the water level prediction strategy includes a rainfall water level prediction strategy, and the corresponding water level prediction strategy is called based on the environment-related attributes, and each estimated time point and the corresponding estimated water level value are determined according to the water level prediction strategy, including: when the environment-related attributes are meteorological-related attributes, the rainfall water level prediction strategy is called based on the meteorological-related attributes, and meteorological-related data is identified based on the rainfall water level prediction strategy to obtain rainfall node data, the rainfall node data includes each rainfall time period and the corresponding rainfall in the period, the fixed position point calls the corresponding historical water level statistical table, the historical water level statistical table includes each rainfall interval and the corresponding historical water level fluctuation value, the rainfall interval to which the rainfall in the period belongs is searched based on the historical water level statistical table, the historical water level fluctuation value corresponding to the rainfall interval is determined as the estimated water level fluctuation value corresponding to the rainfall time period, each rainfall time period is identified, multiple estimated time points are obtained, and the estimated water level value corresponding to each estimated time point is determined respectively according to the current monitored water level and the estimated water level fluctuation value.

[0010] Optionally, each rainfall time period is identified, and multiple estimated time points are obtained. The estimated water level value corresponding to each estimated time point is determined according to the current monitored water level and the estimated water level fluctuation value, including: numbering each rainfall time period in chronological order, obtaining a rainfall sequence number, identifying each rainfall time period according to the rainfall sequence number, respectively obtaining the rainfall start time point and the rainfall end time point of each rainfall time period, and determining the rainfall start time point and the rainfall end time point of each rainfall time period as the estimated time point, wherein the rainfall start time point corresponding to the first rainfall time period in the rainfall sequence number is the first estimated time point, and the rainfall end time point corresponding to the first rainfall time period is the second estimated time point, and the current monitored water level is obtained. The current monitored water level is determined as the initial estimated water level value, the initial estimated water level value is the estimated water level value corresponding to the first estimated time point, the sum of the initial estimated water level value and the estimated water level fluctuation value corresponding to the first rainfall time period is determined as the estimated water level value corresponding to the second estimated time point, the estimated water level value corresponding to the second estimated time point is determined as the estimated water level value corresponding to the rainfall start time of the second rainfall time period, the sum of the estimated water level value corresponding to the rainfall start time of the second rainfall time period and the estimated water level fluctuation value corresponding to the second rainfall time period is determined as the estimated water level value corresponding to the rainfall end time point of the second rainfall time period, and the above steps of obtaining the estimated water level values ​​are repeated until the estimated water level values ​​corresponding to all estimated time points are obtained.

[0011] Optionally, the water level prediction strategy includes a drainage water level prediction strategy, calling the corresponding water level prediction strategy based on the environment-related attributes, and determining each estimated time point and the corresponding estimated water level value according to the water level prediction strategy, including: when the environment-related attributes are behavior-related attributes, calling the drainage water level prediction strategy based on the behavior-related attributes, identifying the behavior-related data based on the drainage water level prediction strategy, and obtaining drainage behavior data, the drainage behavior data including the estimated drainage position and the corresponding estimated drainage time and estimated drainage volume, calling the behavior evaluation table based on the estimated drainage position, and The evaluation table obtains corresponding water level impact data, and the water level impact data includes each drainage grade and the corresponding estimated water level impact value. The drainage grade is determined according to the expected drainage volume, and the corresponding estimated water level impact value is determined based on the drainage grade. The drainage start time point and the drainage end time point of the expected drainage time are determined as the estimated time points, and the current monitored water level is obtained. The current monitored water level is determined as the estimated water level value at the estimated time point corresponding to the drainage start time point, and the sum of the current monitored water level and the estimated water level impact value is determined as the estimated water level value at the estimated time point corresponding to the drainage end time point.

[0012] Optionally, the method also includes: responding to a data upload instruction, receiving real-time collected data sent by the management end, determining the real-time collected data as autonomous update data, identifying the autonomous update data, obtaining autonomous update attributes, the autonomous update attributes including update point data and autonomous update time, locating the corresponding accident video data based on the update point data and autonomous update time, and replacing the accident video data with the autonomous update data.

[0013] Optionally, the method also includes: detecting the monitoring water level value corresponding to the monitoring time point of each monitoring point, marking the monitoring point with an empty monitoring water level value as a supplementary monitoring point; obtaining the distance information between each monitoring point and the supplementary monitoring point, and taking other monitoring points with monitoring water level values ​​within a preset distance as reference monitoring points; processing the distance information of each reference monitoring point according to a distance normalization value to obtain a distance supplementation coefficient; calculating the height difference between each reference monitoring point and the supplementary monitoring point, processing the height difference of each reference monitoring point according to a height normalization value to obtain a height supplementation coefficient; obtaining the first drainage coefficient of each reference monitoring point and the second drainage coefficient of the supplementary monitoring point, processing the difference between each first drainage coefficient and the second drainage coefficient according to a drainage normalization value to obtain a drainage supplementation coefficient; calculating the monitoring water level of the reference monitoring point according to the distance supplementation coefficient, the height supplementation coefficient and the drainage supplementation coefficient to obtain the supplementary water level of the supplementary monitoring point. To solve the above technical problems, another technical solution adopted in the embodiment of the present invention is: to provide a railway tunnel water level intelligent monitoring and alarm platform, comprising: at least one processor, and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the railway tunnel water level intelligent monitoring and alarm method as described in any one of the above items.

[0014] Different from the prior art, the present invention provides an intelligent monitoring and alarm method for water level in a railway tunnel, comprising: responding to a water level monitoring instruction, obtaining monitoring feature data collected by a monitoring terminal, the monitoring feature data including monitoring point data and video verification data; identifying the monitoring point data, obtaining fixed position points and water level monitoring data, calling a safe water level comparison table to obtain a safe water level threshold value corresponding to the fixed position point; generating a water level monitoring curve chart based on the water level monitoring data, and when the current monitored water level in the water level monitoring curve chart is higher than the safe water level threshold value, intercepting the video verification data to generate a water level alarm interface; and / or receiving environment-related data, obtaining each estimated time point and the corresponding estimated water level value based on the environment-related data, generating a water level estimation curve chart, and when the future estimated water level in the water level estimation curve chart is higher than the safe water level threshold value, generating a water level alarm interface; and sending the water level alarm interface to a management terminal. The present invention obtains monitoring feature data collected by the monitoring end, and the monitoring feature data includes monitoring point data and video verification data, so that management personnel can fully understand the actual situation in the tunnel online, reduce dependence on manual inspections, and improve monitoring efficiency; the present invention monitors the water level of the railway tunnel in real time. When the current monitored water level is higher than the safe water level threshold, the video verification data is automatically intercepted to generate a water level alarm interface to realize a real-time alarm function, and the future water level is estimated in advance through environmental correlation data, and potential water level risks are warned to realize the estimated alarm function, thereby improving the safety and emergency response capabilities of railway transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] One or more embodiments are exemplarily described by corresponding drawings, which do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, and the figures in the drawings do not constitute proportional limitations unless otherwise stated.

[0016] Figure 1 It is a flow chart of a railway tunnel water level intelligent monitoring and alarm method provided by an embodiment of the present application; Figure 2 is a schematic diagram of a water level alarm interface provided in an embodiment of the present application; Figure 3 is a schematic diagram of viewing accident video data provided by an embodiment of the present application; Figure 4 It is a structural schematic diagram of a railway tunnel water level intelligent monitoring and alarm platform provided in an embodiment of the present application. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0018] It should be noted that, if there is no conflict, the various features in the embodiments of the present invention can be combined with each other, and all are within the protection scope of the present invention. In addition, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in a different order from the module division in the device schematic diagram or the order in the flow chart.

[0019] The terms "first", "second", "third", "fourth", etc. (if any) in the description and claims of the present invention and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in sequences other than those illustrated or described herein.

[0020] It should be understood that in the present invention, "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products or apparatuses.

[0021] Unless otherwise defined, all technical and scientific terms used in this specification have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0022] See also Figure 1 , Figure 1 : is a flow chart of a railway tunnel water level intelligent monitoring and alarm method provided by an embodiment of the present application, including steps S1 to S5, which are as follows: S1. Respond to the water level monitoring instruction and obtain the monitoring characteristic data collected by the monitoring terminal, wherein the monitoring characteristic data includes monitoring point data and video verification data.

[0023] Among them, the water level monitoring instruction represents the instruction for starting the water level monitoring process; the monitoring end represents the equipment that actually performs the water level monitoring task, which may include an ultrasonic sensor and a high-definition waterproof camera installed in a railway tunnel, and the specific installation location can be set according to actual conditions; the monitoring feature data represents all data collected by the ultrasonic sensor and the high-definition waterproof camera; the monitoring point data represents the specific monitoring location and corresponding water level data collected by the ultrasonic sensor; the video verification data represents real-time video data collected by the high-definition waterproof camera.

[0024] It should be noted that the water level data collected by the ultrasonic sensor can accurately reflect the water level height at the monitoring point, making it easier for the subsequent platform to determine whether the water level height exceeds the safety threshold; the video captured by the high-definition waterproof camera can intuitively assist staff in confirming abnormal water levels, avoid false alarms, and enable staff to take corresponding measures in a timely manner based on the actual water level conditions.

[0025] S2. Identify the monitoring point data, obtain fixed position points and water level monitoring data, and call the safe water level comparison table to obtain the safe water level threshold value corresponding to the fixed position point.

[0026] Among them, the fixed position points represent data that do not change during the monitoring process, including but not limited to the railway tunnel number, tunnel location and monitoring point location; the water level monitoring data represent data that change during the monitoring process, including but not limited to each monitoring time point and the corresponding water level height; the safe water level comparison table represents a table containing water level safety standards for different tunnels and monitoring points, which can be used to determine whether the monitored water level exceeds the safety threshold; the safe water level threshold represents the safe upper limit of the water level at a specific monitoring point under specific conditions. When the monitored water level exceeds this threshold, it indicates that there is a potential safety hazard and an alarm needs to be issued.

[0027] Specifically, the collected monitoring point data are classified according to different data formats, and can be divided into fixed location points and water level monitoring data. According to the fixed location points (such as tunnel number, monitoring point location), the corresponding safe water level threshold is found from the pre-set safe water level comparison table.

[0028] It should be noted that in order to monitor and alarm the water level in railway tunnels, the safety water level standards corresponding to each monitoring point can be pre-set according to different fixed location points and recorded in a safety water level comparison table. The data in the table is usually determined based on historical data, geographical environment, tunnel design specifications and other factors.

[0029] S3. Generate a water level monitoring curve graph based on the water level monitoring data. When the current monitored water level in the water level monitoring curve graph is higher than the safe water level threshold, intercept the video verification data to generate a water level alarm interface.

[0030] Among them, the water level monitoring curve graph represents a graph reflecting the water level changes at the monitoring point over a period of time; the current monitored water level represents the actual water level value of the monitoring point at a specific time point; the water level alarm interface represents an interface containing a water level monitoring curve graph and a video clip corresponding to the abnormal water level (the monitored water level that begins to exceed the safety threshold).

[0031] It should be noted that the water level monitoring curve can intuitively display the trend of water level changes. When the current monitored water level in the water level monitoring curve is higher than the safe water level threshold, the platform can select video clips of a specific time period from the video verification data for further verification and processing by management personnel.

[0032] In some embodiments, step S3 (generating a water level monitoring curve graph based on the water level monitoring data, and when the current monitored water level in the water level monitoring curve graph is higher than the safe water level threshold, intercepting the video verification data to generate a water level alarm interface) specifically includes steps S31-S34: S31. Acquire a water level monitoring record sequence based on the water level monitoring data, wherein the water level monitoring record sequence includes each monitoring time point and a corresponding monitoring water level value.

[0033] Among them, the water level monitoring record sequence records each monitoring time point and the corresponding water level value; the monitoring time point indicates the specific time point for water level measurement, such as 2 pm on July 21, 2024; the monitoring water level value indicates the specific water level height value measured at a certain monitoring time point.

[0034] Example: The sequence of water level monitoring records obtained based on the dynamic point position of monitoring point 1 of tunnel A is as follows: 2024-07-21 08:00: 0.4 m, 2024-07-21 09:00: 0.45 m, 2024-07-21 10:00: 0.6 m.

[0035] S32, establishing a rectangular coordinate system with the monitoring time as the horizontal axis and the monitoring water level as the vertical axis, drawing water level monitoring points in the rectangular coordinate system according to each monitoring time point and the corresponding monitoring water level value, and generating a water level monitoring curve based on each water level monitoring point.

[0036] Among them, the monitoring time represents the time range of the entire monitoring process, such as from 10 am to 8 pm on July 21, 2024; the horizontal axis represents the X-axis in the coordinate system, which is the axis representing time here; the monitored water level represents the water level height; the vertical axis represents the Y-axis in the coordinate system, which is the axis representing the water level height here; the rectangular coordinate system represents a two-dimensional coordinate system used to draw a water level monitoring curve; the water level monitoring point represents the intersection of each monitoring time point and the corresponding monitoring water level value in the rectangular coordinate system.

[0037] Specifically, the intersection of the monitoring time point and the corresponding monitoring water level value is marked in the rectangular coordinate system, the marked point is the water level monitoring point, and the curve formed by connecting all the water level monitoring points is the water level monitoring curve.

[0038] S33. When the current monitored water level in the water level monitoring curve is higher than the safety water level threshold, monitoring water level alarm data is generated and an accident video acquisition request is triggered. The video verification data is intercepted according to the accident video acquisition request to obtain accident video data.

[0039] Among them, the monitored water level alarm data represents the alarm data generated when the current monitored water level is higher than the safe water level threshold, which may specifically include a water level monitoring curve chart and alarm text, etc.; the accident video acquisition request represents a request automatically issued by the platform when a water level alarm is triggered, in order to capture video verification data of the relevant time period; the accident video data represents the captured video clip, which can be used to verify water level abnormalities.

[0040] For example: In the water level monitoring curve corresponding to monitoring point No. 1 of tunnel A, the current monitored water level is 0.6 meters. The current monitored water level of 0.6 meters is compared with the safety water level threshold of 0.5 meters for the monitoring point. The current monitored water level of 0.6 meters is higher than the safety water level threshold of 0.5 meters. Monitoring water level alarm data is generated and an accident video acquisition request is triggered. Based on the accident video acquisition request, relevant video clips when the current monitored water level of 0.6 meters is higher than the safety water level threshold of 0.5 meters are extracted, and a water level alarm interface including a water level monitoring curve, alarm text, relevant video clips, etc. is generated to assist management personnel in checking and determining whether the 0.6-meter water level data obtained by the ultrasonic sensor is abnormal.

[0041] It should be noted that obtaining video verification data can supplement the verification of the accuracy of the water level data obtained by the ultrasonic sensor. When the water level data reading obtained by the ultrasonic sensor exceeds the safe water level threshold, the platform will capture and display the video footage of the corresponding time period to assist management personnel in verifying and determining whether the water level data obtained by the ultrasonic sensor is abnormal.

[0042] In some embodiments, step S33 (when the current monitored water level in the water level monitoring curve is higher than the safety water level threshold, generating monitoring water level alarm data and triggering an accident video acquisition request, intercepting the video verification data according to the accident video acquisition request, and acquiring accident video data) specifically includes steps S331-S335: S331. Determine the ordinate value corresponding to the most recently drawn water level monitoring point in the water level monitoring curve as the current monitored water level.

[0043] The most recently drawn water level monitoring point refers to the most recently drawn water level monitoring point in the water level monitoring curve diagram.

[0044] Example: The sequence of water level monitoring records obtained based on the dynamic point position of monitoring point No. 1 in tunnel A is as follows: 2024-07-21 08:00: 0.4 meters, 2024-07-21 09:00: 0.45 meters, 2024-07-21 10:00: 0.6 meters. The most recently drawn water level monitoring point is the water level monitoring point corresponding to 2024-07-21 10:00: 0.6 meters. The horizontal coordinate value of the water level monitoring point is 2024-07-21 10:00, and the vertical coordinate value is 0.6 meters. Therefore, the current monitored water level is 0.6 meters.

[0045] S332: Compare the current monitored water level with the safety water level threshold, and when the current monitored water level is higher than the safety water level threshold, generate monitoring water level alarm data and trigger an accident video acquisition request.

[0046] S333. Identify the accident video acquisition request, obtain the trigger time point, and determine the video boundary time according to the trigger time point and the preset video acquisition rule. The video boundary time includes the video start time point and the video end time point.

[0047] Among them, the trigger time point represents the time point when the monitored water level exceeds the set safety water level threshold; the preset video acquisition rule represents the pre-set rule for determining the relevant video clips that should be acquired when a water level alarm occurs. The rule may include the conditions, duration, start and end time points, etc. for video acquisition; the video boundary time represents the time point for determining the segmentation of the video clips in the video verification data; the video start time point represents the time when the video clip starts; the video end time point represents the time when the video clip ends.

[0048] It should be noted that obtaining the video boundary time can help the platform to capture relevant video clips more accurately.

[0049] S334: locate the corresponding monitoring video segment in the video verification data according to the video start time point and the video end time point, and intercept the monitoring video segment to obtain the intercepted monitoring video segment.

[0050] Among them, the monitoring video clip represents the relevant video clip corresponding to the monitored water level exceeding the set safety water level threshold; interception represents the process of extracting part of the video data within a specific time range from the entire monitoring video (video verification data), and the extracted video data is the intercepted monitoring video clip, which contains all video content related to the water level within a period of time before the trigger time point.

[0051] For example, if the trigger time is 2:00 p.m. on July 22, 2024, according to the preset video acquisition rules, the video start time is 5 minutes before 2:00 p.m., and the video end time is the trigger time. Through the interception operation, the platform will extract the video clip from 1:55 p.m. to 2:00 p.m. on July 22, 2024 from the monitoring video clip, and this video clip is the intercepted monitoring video clip.

[0052] S335: Determine the intercepted monitoring video segment as accident video data.

[0053] For example, the intercepted monitoring video clip is the video clip from 1:55 pm to 2:00 pm on July 22, 2024, which is the accident video data.

[0054] S34, combining the monitored water level alarm data and the accident video data to generate a water level alarm interface.

[0055] The combination means merging together to form an overall interface, and the overall interface is the water level alarm interface.

[0056] S4, and / or, receiving environment-related data, obtaining each estimated time point and the corresponding estimated water level value based on the environment-related data, generating a water level estimation curve chart, and generating a water level alarm interface when the future estimated water level in the water level estimation curve chart is higher than the safe water level threshold.

[0057] Among them, the environment-related data includes various data related to the monitoring point environment; the estimated time point represents a specific time point in the future; the estimated water level value represents the water level value predicted at the estimated time point; the water level estimation curve represents a chart reflecting the water level change trend within the estimated time; the future estimated water level represents the water level value predicted at a certain time point in the future.

[0058] In some embodiments, step S4 (receiving environment-related data, obtaining each estimated time point and the corresponding estimated water level value based on the environment-related data, generating a water level estimation curve, and generating a water level alarm interface when the future estimated water level in the water level estimation curve is higher than the safe water level threshold) specifically includes steps S41-S45: S41, receiving environment-related data, identifying the environment-related data, and acquiring environment-related attributes, wherein the environment-related attributes include weather-related attributes and behavior-related attributes.

[0059] The meteorological-related attributes represent parameters or data related to weather; and the behavioral-related attributes represent parameters or data related to human activities.

[0060] It should be noted that the receiving environment-related data can provide an estimation basis for the subsequent water level estimation. Rainfall, urban drainage, etc. will have an impact on the height of the water level in the railway tunnel. For example, heavy rainfall may cause the water level in the railway tunnel to rise.

[0061] S42: calling a corresponding water level estimation strategy based on the environment-related attributes, and determining each estimation time point and the corresponding estimated water level value according to the water level estimation strategy.

[0062] The water level prediction strategy refers to a method for predicting future water level changes.

[0063] In some embodiments, the water level prediction strategy includes a rainfall water level prediction strategy, and step S42 (calling the corresponding water level prediction strategy based on the environment-related attributes, and determining each estimated time point and the corresponding estimated water level value according to the water level prediction strategy) specifically includes steps S421-S425: S421: When the environment-related attribute is a meteorological-related attribute, calling a rainfall level prediction strategy based on the meteorological-related attribute.

[0064] The rainfall water level prediction strategy refers to a method for predicting future water levels based on rainfall data.

[0065] S422. Identify meteorological related data based on the rainfall water level prediction strategy to obtain rainfall node data, where the rainfall node data includes each rainfall time period and the corresponding rainfall in the time period.

[0066] Among them, the meteorological related data represents the weather-related data in the environmental related data, which can be obtained through the meteorological station; the rainfall node data represents the detailed information of each rainfall event; the rainfall time period represents the specific time interval corresponding to the rainfall; the rainfall within the segment represents the total amount of rainfall within the specific rainfall time period.

[0067] For example: the total rainfall from 9:00 to 10:00 is 20 mm, and the total rainfall from 11:00 to 12:00 is 30 mm. Then 9:00-10:00 is a rainfall time period, and the corresponding rainfall in this rainfall time period is 20 mm. 11:00-12:00 is a rainfall time period, and the corresponding rainfall in this rainfall time period is 30 mm.

[0068] It should be noted that the rainfall intensity and duration in different time periods can be determined through rainfall node data.

[0069] S423. Call a corresponding historical water level statistics table according to the fixed position point, wherein the historical water level statistics table includes each rainfall interval and the corresponding historical water level fluctuation value.

[0070] Among them, the historical water level statistics table represents a data table that records the water level changes under different rainfall conditions in the past; the rainfall interval represents the classification according to the amount of rainfall; and the historical water level fluctuation value represents the amplitude of water level changes monitored historically under a specific rainfall interval.

[0071] Example: Classification based on the amount of rainfall, such as 0-10 mm, 10-20 mm, 20-30 mm, 30-40 mm, then 0-10 mm, 10-20 mm, 20-30 mm, 30-40 mm are different rainfall intervals, the historical water level fluctuation value corresponding to the rainfall interval 0-10 mm is 0.1 m, the historical water level fluctuation value corresponding to the rainfall interval 10-20 mm is 0.15 m, the historical water level fluctuation value corresponding to 20-30 mm is 0.2 m, and the historical water level fluctuation value corresponding to 30-40 mm is 0.3 m.

[0072] It should be noted that the historical water level fluctuation values ​​can be used to predict the water level changes under similar rainfall conditions.

[0073] S424. Based on the historical water level statistics table, search for the rainfall interval to which the rainfall in the segment belongs, and determine the historical water level fluctuation value corresponding to the rainfall interval as the estimated water level fluctuation value corresponding to the rainfall time period.

[0074] The estimated water level fluctuation value indicates the predicted amplitude of the water level change.

[0075] For example: The rainfall in the rainfall period 10:00-10:11 is 15 mm. In the historical water level statistics table, it is found that 15 mm belongs to the rainfall range 10-20 mm. The historical water level fluctuation value corresponding to the rainfall range 10-20 mm is 0.15 m. Therefore, the estimated water level fluctuation value corresponding to the rainfall period 10:00-10:11 is 0.15 m.

[0076] It should be noted that in order to ensure the accuracy of the estimated water level fluctuation value, it is necessary to ensure that the rainfall time period used for estimation is the same as the time length corresponding to the actual rainfall interval.

[0077] S425, identifying each rainfall time period, obtaining multiple estimated time points, and determining the estimated water level value corresponding to each estimated time point according to the current monitored water level and the estimated water level fluctuation value.

[0078] In some embodiments, step S425 (identifying each rainfall time period, obtaining multiple estimated time points, and determining the estimated water level value corresponding to each estimated time point according to the current monitored water level and the estimated water level fluctuation value) specifically includes steps S4251-S4257: S4251. Number each rainfall time period in chronological order to obtain a rainfall sequence number, identify each rainfall time period according to the rainfall sequence number, and respectively obtain a rainfall start time point and a rainfall end time point of each rainfall time period.

[0079] Among them, the time sequence represents the time sequence of rainfall events, that is, which rainfall time period has rainfall first and which has rainfall later; the numbering can assign a unique identification number to each rainfall time period and arrange them in chronological order; the rainfall sequence number represents a data set generated by numbering the rainfall time periods according to the chronological order of the rainfall time periods, for example, the first rainfall time period is numbered 1, the second rainfall time period is numbered 2, and so on; the rainfall start time point represents the start time of a rainfall time period, that is, the specific time point when rainfall starts within the time period; the rainfall end time point represents the end time of a rainfall time period, that is, the specific time point when rainfall stops within the time period.

[0080] S4252. Determine the rainfall start time point and rainfall end time point of each rainfall time period as estimated time points, wherein the rainfall start time point corresponding to the first rainfall time period in the rainfall sequence number is the first estimated time point, and the rainfall end time point corresponding to the first rainfall time period is the second estimated time point.

[0081] Among them, the first rainfall time period represents the first rainfall time period in chronological order; the first estimated time point represents the first time point for water level estimation in chronological order; the second estimated time point represents the second time point for water level estimation in chronological order.

[0082] S4253. Obtain the current monitored water level, and determine the current monitored water level as an initial estimated water level value, where the initial estimated water level value is the estimated water level value corresponding to the first estimated time point.

[0083] The initial estimated water level value refers to the initial estimated water level value when performing water level estimation.

[0084] S4254. Determine the sum of the initial estimated water level value and the estimated water level fluctuation value corresponding to the first rainfall time period as the estimated water level value corresponding to the second estimated time point.

[0085] S4255. Determine the estimated water level value corresponding to the second estimated time point as the estimated water level value corresponding to the rainfall start time of the second rainfall time period.

[0086] The second rainfall time period refers to the second rainfall time period in chronological order.

[0087] S4256. Determine the sum of the estimated water level value corresponding to the rainfall start time of the second rainfall time period and the estimated water level fluctuation value corresponding to the second rainfall time period as the estimated water level value corresponding to the rainfall end time point of the second rainfall time period.

[0088] S4257. Repeat the above steps of obtaining the estimated water level value until the estimated water level values ​​corresponding to all estimated time points are obtained.

[0089] For example: The rainfall time periods are 2024-07-22 9:00-10:00, 2024-07-21 9:00-10:00, 2024-07-21 11:00-12:00, 2024-07-21 14:00-15:00. The rainfall time periods are arranged in chronological order, and we can get 2024-07-21 9:00-10:00, 2024-07-21 11:00-12:00, 2024-07-21 14:00-15:00, 2024-07-22 9:00-10:00. Then the rainfall time period is 2024-07-21. 9:00-10:00 can be numbered as 1, the rainfall time period 2024-07-21 11:00-12:00 can be numbered as 2, 2024-07-21 14:00-15:00 can be numbered as 3, and 2024-07-22 9:00-10:00 can be numbered as 4. Among them, 2024-07-21 9:00, 2024-07-21 10:00, 2024-07-21 11:00, 2024-07-21 12:00, 2024-07-21 14:00, 2024-07-21 15:00, 2024-07-22 9:00, and 2024-07-22 10:00 are all estimated time points. The first rainfall time period is 2024-07-21 9:00-10:00, the first estimated time point is 2024-07-21 9:00, the second estimated time point is 2024-07-21 10:00, and the second rainfall time period is 2024-07-21 11:00-12:00. The current monitored water level is 0.4 meters, so the estimated water level value corresponding to the first estimated time point 2024-07-21 9:00 is 0.4 meters. If the estimated water level fluctuation value corresponding to the first rainfall period is 0.15 meters, the estimated water level value corresponding to the second estimated time point 2024-07-21 10:00 is the sum of 0.4 meters and 0.15 meters, that is, 0.55 meters. Then 0.55 meters is used as the estimated water level value corresponding to the estimated time point 2024-07-21 11:00. If the estimated water level fluctuation value corresponding to the second rainfall period is 0.1 meters, the estimated water level value corresponding to the estimated time point 2024-07-21 12:00 is the sum of 0.55 meters and 0.1 meters, that is, 0.65 meters. The same idea is used to obtain the estimated water level values ​​corresponding to the remaining estimated time points.

[0090] In some embodiments, the water level prediction strategy includes a rainfall water level prediction strategy, calling the corresponding water level prediction strategy based on the environment-related attributes, and determining each estimated time point and the corresponding estimated water level value according to the water level prediction strategy also includes steps A1-A7: A1. When the environment-related attribute is a behavior-related attribute, a drainage water level prediction strategy is called based on the behavior-related attribute.

[0091] The drainage water level prediction strategy refers to a strategy for predicting the impact of urban drainage behavior on water level.

[0092] A2. Based on the drainage water level prediction strategy, the behavior association data is identified to obtain drainage behavior data, wherein the drainage behavior data includes an estimated drainage position and a corresponding estimated drainage time and an estimated drainage volume.

[0093] Among them, the behavior-related data represents data related to human activities in the environment-related data; the drainage behavior data represents data related to the drainage operation; the expected drainage location represents the specific location where the drainage operation is expected to be performed; the expected drainage time represents the specific time period where the drainage operation is expected to be performed; and the expected drainage volume represents the amount of water expected to be discharged.

[0094] A3. Calling a behavior evaluation table based on the predicted drainage position, and acquiring corresponding water level impact data based on the behavior evaluation table, wherein the water level impact data includes each drainage grade and the corresponding predicted water level impact value.

[0095] Among them, the behavior evaluation table represents a data table used to evaluate the impact of drainage behavior on water level, which contains different drainage behaviors and their corresponding water level impact values, helping the platform to evaluate water level changes; the water level impact data represents data describing the impact of drainage behavior on water level, which can quantify the specific impact of different drainage operations on water level; the drainage grade represents the grade of drainage operation determined according to the expected drainage volume; the estimated water level impact value represents the expected impact value of drainage behavior on water level.

[0096] A4. Determine the drainage grade according to the expected drainage volume, and determine the corresponding estimated water level impact value based on the drainage grade.

[0097] A5. Determine the drainage start time point and the drainage end time point of the expected drainage time as the estimated time points.

[0098] Among them, the drainage start time point indicates the time point when the drainage operation starts. This time point is the starting point of water level estimation, and the water level change needs to be predicted based on this time point; the drainage end time point indicates the time point when the drainage operation ends. This time point indicates the end point of water level estimation, and the platform needs to calculate the final water level change based on this time point.

[0099] A6. Obtain the current monitored water level, and determine the current monitored water level as the estimated water level value at the estimated time point corresponding to the drainage start time point.

[0100] A7. Determine the sum of the current monitored water level and the estimated water level impact value as the estimated water level value at the estimated time point corresponding to the drainage end time point.

[0101] S43, establishing a rectangular coordinate system with the estimated time as the horizontal axis and the estimated water level as the vertical axis, drawing water level estimation points in the rectangular coordinate system according to each estimated time point and the corresponding estimated water level value, and generating a water level estimation curve based on each water level estimation point.

[0102] Among them, the estimated time represents the entire time range for water level prediction, covering all estimated time points; the horizontal axis represents the X-axis in the coordinate system, which is the axis representing time here; the estimated water level represents the estimated water level height; the vertical axis represents the Y-axis in the coordinate system, which is the axis representing the estimated water level height here; the rectangular coordinate system represents a two-dimensional coordinate system used to draw a water level prediction curve; the water level estimation point represents the intersection of each estimated time point and the corresponding estimated water level value in the rectangular coordinate system.

[0103] Specifically, the intersection of the estimated time point and the corresponding estimated water level value is marked in the rectangular coordinate system, and the marked point is the water level estimation point. The curve formed by connecting all the water level estimation points is the water level estimation curve.

[0104] S44. When the future estimated water level in the water level estimation curve is higher than the safety water level threshold, estimated water level alarm data is generated and an emergency allocation strategy is called, and a scheduling schedule is determined according to the emergency allocation strategy.

[0105] Among them, the future estimated water level indicates the predicted water level that may be reached at a certain point in the future; the estimated water level alarm data is a warning message generated when the future estimated water level exceeds the preset safety water level threshold; the emergency deployment strategy indicates the emergency response and resource deployment plan formulated by the platform when the estimated water level may exceed the safety threshold, which may include specific emergency measures, such as personnel mobilization, equipment preparation, traffic control, etc., to ensure that when the water level exceeds the safety threshold, it can respond quickly and reduce potential losses; the scheduling plan table indicates a detailed action plan formulated according to the emergency deployment strategy, including specific scheduling arrangements, time nodes and responsible personnel.

[0106] S45. Combining the estimated water level alarm data and the scheduling plan table to generate a water level alarm interface.

[0107] S5. Send the water level alarm interface to the management terminal.

[0108] The management terminal refers to the terminal device used by the management personnel, which can be a mobile phone, computer, tablet, etc.

[0109] See also Figure 2, Figure 2 It is a schematic diagram of a water level alarm interface provided in an embodiment of the present application, which can be specifically displayed on a web side. The web side platform page window gives a global reminder in the form of a pop-up box, and the alarm details, including the alarm time, specific monitoring point, accident video data, etc., can be viewed through the web side. The bound mobile phone number will receive an alarm reminder SMS. In the SMS reminder, basic information such as the alarm time and specific monitoring point can be prompted. The specific page can be adjusted according to the actual situation, and the present invention does not make specific restrictions on this.

[0110] See also Figure 3 , Figure 3 It is a schematic diagram of viewing accident video data provided by an embodiment of the present application.

[0111] It should be noted that after the staff has checked the accident video data, they can confirm the actual processing situation through this page. Alarm data can be divided into four states: unchecked, checked, false alarm, and completed. Unchecked means that the alarm event has been generated, and the administrator or any user has not checked this information; checked means that after the alarm information is generated, the administrator or any user has checked this message, but no processing has been done; false alarm means that after the alarm information is generated, the staff checked this message and found that this event was a false alarm after checking the accident video data; completed means that after receiving the alarm information, the staff checked it and determined it to be an alarm event, and went to the scene to handle it.

[0112] In some embodiments, the method further specifically comprises steps C1-C3: C1. Respond to the data upload instruction, receive the real-time collected data sent by the management terminal, and determine the real-time collected data as autonomous update data.

[0113] Among them, the data upload instruction refers to the instruction issued by the management end for autonomously uploading data; the real-time collected data refers to data such as pictures or videos of real-time water levels taken by staff; and the autonomous update data refers to the latest captured data used to update existing monitoring data.

[0114] C2. Identify the autonomous update data and obtain autonomous update attributes, where the autonomous update attributes include update point data and autonomous update time.

[0115] Among them, the autonomous update attribute represents the characteristics of the autonomous update data; the update point data represents the data of the monitoring point that needs to be updated; and the autonomous update time represents the specific time point when the staff collects data.

[0116] C3. Based on the update point data and the accident video data corresponding to the autonomous update time positioning, the accident video data is replaced with the autonomous update data.

[0117] Among them, positioning means finding the corresponding accident video data according to the update point data and the autonomous update time; the accident video data means the video data related to a specific monitoring event; replacement means replacing the old accident video data with the new autonomous update data to ensure the data is up-to-date and accurate.

[0118] In the present embodiment, a method for intelligent monitoring and alarming of water level in a railway tunnel is provided, including: responding to a water level monitoring instruction, obtaining monitoring characteristic data collected by a monitoring terminal, the monitoring characteristic data including monitoring point data and video verification data; identifying the monitoring point data, obtaining fixed position points and water level monitoring data, calling a safe water level comparison table to obtain a safe water level threshold value corresponding to the fixed position point; generating a water level monitoring curve graph based on the water level monitoring data, and when the current monitored water level in the water level monitoring curve graph is higher than the safe water level threshold value, intercepting the video verification data to generate a water level alarm interface; and / or receiving environment-related data, obtaining each estimated time point and the corresponding estimated water level value based on the environment-related data, generating a water level estimation curve graph, and when the future estimated water level in the water level estimation curve graph is higher than the safe water level threshold value, generating a water level alarm interface; and sending the water level alarm interface to a management terminal. The present invention obtains monitoring feature data collected by the monitoring end, and the monitoring feature data includes monitoring point data and video verification data, so that management personnel can fully understand the actual situation in the tunnel online, reduce dependence on manual inspections, and improve monitoring efficiency; the present invention monitors the water level of the railway tunnel in real time. When the current monitored water level is higher than the safe water level threshold, the video verification data is automatically intercepted to generate a water level alarm interface to realize a real-time alarm function, and the future water level is estimated in advance through environmental correlation data, and potential water level risks are warned to realize the estimated alarm function, thereby improving the safety and emergency response capabilities of railway transportation.

[0119] This application takes into account that the monitored water level at some monitoring points may be missing, such as when the sensor is damaged, the transmission line is interrupted, etc. In order to solve the above problem, on the basis of the above embodiment, it also includes: The monitoring water level value corresponding to the monitoring time point of each monitoring point is detected, and the monitoring point with an empty monitoring water level value is marked as a supplementary monitoring point. It can be understood that this solution will mark the monitoring points that cannot receive the monitoring water level value, and perform data prediction and supplement on them to fill the missing data.

[0120] The distance information between each monitoring point and the supplementary monitoring point is obtained, and other monitoring points with monitored water level values ​​within the preset distance are used as reference monitoring points. When completing the data, this application takes into account the distance dimension and uses monitoring points within a certain range as reference monitoring points to screen reference data for data prediction.

[0121] The distance information of each reference monitoring point is processed according to the distance normalization value to obtain the distance filling coefficient. The present application takes into account that if the distance between the reference monitoring point and the filling monitoring point is farther, the accuracy of filling with reference to its data will be lower, so the reference degree will be lower. It can be understood that the larger the distance information, the smaller the corresponding distance filling coefficient.

[0122] Calculate the height difference between each reference monitoring point and the padding monitoring point, process the height difference between each reference monitoring point according to the height normalization value, and obtain the height padding coefficient. The present application takes into account that if the height difference between the reference monitoring point and the padding monitoring point is larger, the accuracy of padding with reference to its data will be lower, so the reference degree will also be lower. It is understandable that the larger the height difference, the smaller the corresponding height padding coefficient.

[0123] Obtain the first drainage coefficient of each of the reference monitoring points, and the second drainage coefficient of the complementary monitoring point, process the difference between each of the first drainage coefficient and the second drainage coefficient according to the drainage normalization value, and obtain the drainage complementary coefficient. The present application takes into account that if the difference between the first drainage coefficient and the second drainage coefficient is larger, the accuracy of complementing with reference to their data will be lower, so the reference degree will be lower. It is understandable that the larger the difference, the smaller the corresponding drainage complementary coefficient. Among them, the first drainage coefficient and the second drainage coefficient are pre-set, and the better the drainage performance of the monitoring point, the larger the corresponding drainage coefficient can be.

[0124] The monitored water level value of the reference monitoring point is calculated according to the distance padding coefficient, the height padding coefficient and the drainage padding coefficient to obtain the padding water level of the padding monitoring point. Finally, this scheme calculates a comprehensive padding coefficient by combining the coefficients of the three dimensions of the distance padding coefficient, the height padding coefficient and the drainage padding coefficient, and calculates using the padding coefficient and the monitored water level of the corresponding reference monitoring point to obtain the padding water level of the padding monitoring point.

[0125] In some embodiments, the filling water level of the filling monitoring point is calculated by the following formula: in, For the The filling coefficient corresponding to the reference monitoring point is represents the normalized distance value, Representative The distance information of the reference monitoring points, represents the first fusion weight; Representative The height of the reference monitoring point, Represents the height of the completed monitoring point, represents the normalized value of height, represents the second fusion weight; Representative The first drainage coefficient of the reference monitoring point, Represents the second drainage coefficient to fill in the monitoring point, represents the drainage normalized value, represents the third fusion weight; represents the replenishment water level of the replenishment monitoring point, is the upper limit of the number of reference monitoring points, For the The monitored water level corresponding to the reference monitoring point.

[0126] In the above formula, Represents the distance padding coefficient; Represents the height padding coefficient; Represents the drainage filling coefficient. The first fusion weight, the second fusion weight and the third fusion weight can be preset manually.

[0127] In order to make the future forecast data more accurate, this plan also sets up an adjustment plan, including: In response to the adjustment information of the management end, the adjustment water level actively set by the management end is received. It can be understood that the adjustment water level can be measured on the spot by the management personnel, and the water level is relatively accurate.

[0128] Based on the sum of the first fusion weight, the second fusion weight and the third fusion weight, a comprehensive weight is obtained. In this solution, the sum of the three weights is calculated to obtain a comprehensive weight.

[0129] The first proportion is obtained based on the ratio of the first fusion weight to the comprehensive weight, the second proportion is obtained based on the ratio of the second fusion weight to the comprehensive weight, and the third proportion is obtained based on the ratio of the third fusion weight to the comprehensive weight. It is understandable that this solution will determine the ratio of each fusion weight to the comprehensive weight, and when adjusting the data later, the ratio will be used as a reference for different degrees of adjustment.

[0130] When it is determined that the regulated water level is greater than the replenishing water level, the increased water level difference is obtained according to the difference between the regulated water level and the replenishing water level. It is understandable that if the regulated water level is greater than the replenishing water level, the solution needs to obtain the increased water level difference.

[0131] The first fusion weight is increased and adjusted based on the increased water level difference and the first proportion to obtain the increased and adjusted first fusion weight.

[0132] The second fusion weight is increased and adjusted according to the increased water level difference and the second proportion to obtain the increased and adjusted second fusion weight.

[0133] The third fusion weight is increased and adjusted based on the increased water level difference and the third proportion to obtain the increased and adjusted third fusion weight.

[0134] It is understandable that this solution will adjust the original fusion weight to different degrees according to the first proportion, the second proportion and the third proportion, combined with the amplitude of increasing the water level difference.

[0135] The first fusion weight after increasing and adjusting, the second fusion weight after increasing and adjusting, and the third fusion weight after increasing and adjusting are obtained by the following formula; in, To increase the adjusted first fusion weight, To adjust the water level, is the deviation adjustment value, is the comprehensive weight, To increase the adjusted second fusion weight, To increase the adjusted third fusion weight.

[0136] In the above formula, Represents the first proportion, The larger the difference, the larger the corresponding adjustment. and The adjustment method is similar and will not be described in detail.

[0137] When it is determined that the regulated water level is less than the replenishing water level, a reduced water level difference is obtained according to a difference between the replenishing water level and the regulated water level; Based on the reduced water level difference and the first proportion, the first fusion weight is reduced and adjusted to obtain a reduced and adjusted first fusion weight; According to the reduced water level difference and the second proportion, the second fusion weight is reduced and adjusted to obtain a reduced and adjusted second fusion weight; Based on the reduced water level difference and the third proportion, the third fusion weight is reduced and adjusted to obtain a reduced and adjusted third fusion weight; The reduced adjusted first fusion weight, the reduced adjusted second fusion weight and the reduced adjusted third fusion weight are obtained by the following formula; in, To reduce the adjusted first fusion weight, To adjust the water level, is the deviation adjustment value, is the comprehensive weight, To reduce the adjusted second fusion weight, To reduce the adjusted third fusion weight.

[0138] It is understandable that, unlike the above steps, since this step is to reduce the water level difference, this solution is to reduce the first fusion weight, the second fusion weight and the third fusion weight. Other principles are similar and will not be repeated.

[0139] This application embodiment provides a railway tunnel water level intelligent monitoring and alarm platform, please refer to Figure 4 The railway tunnel water level intelligent monitoring and alarm platform 600 includes: at least one processor 61; a memory 62 communicatively connected to the at least one processor 61; Among them, the memory 62 stores instructions that can be executed by the at least one processor 61, and the instructions are executed by the at least one processor 61 so that the at least one processor 61 can execute the above-mentioned railway tunnel water level intelligent monitoring and alarm method.

[0140] The processor 61 and the memory 62 may be connected via a bus or other means. Figure 4 In the example of bus connection, the memory 62 is a non-volatile computer-readable storage medium that can be used to store non-volatile software programs, non-volatile computer executable programs and modules. The processor 61 executes various functional applications and data processing by running the non-volatile software programs, instructions and modules stored in the memory 62, that is, the intelligent monitoring and alarm method for water level in railway tunnels in the above embodiment is realized.

[0141] The memory 62 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created by the scheduling platform, etc. In addition, the memory 62 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 62 may optionally include a memory 62 remotely arranged relative to the processor 61. These remote memories may be connected to the scheduling platform 600 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0142] The one or more modules are stored in the memory 62, and when executed by the one or more processors 61, the railway tunnel water level intelligent monitoring and alarm method in any of the above embodiments is executed, for example, Figure 1 The method steps in .

[0143] The above-mentioned product can execute the railway tunnel water level intelligent monitoring alarm method provided in the embodiment of the present application, and has the corresponding functional modules and beneficial effects of the execution method. For technical details not fully described in this embodiment, please refer to the railway tunnel water level intelligent monitoring alarm method provided in the embodiment of the present application.

[0144] Through the description of the above embodiments, it can be clearly understood by those skilled in the art that each embodiment can be implemented by means of software plus a general hardware platform, or by hardware. It can be understood by those skilled in the art that all or part of the processes in the above embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above methods. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0145] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them. Under the concept of the present invention, the technical features in the above embodiments or different embodiments may also be combined, the steps may be implemented in any order, and there are many other changes in different aspects of the present invention as described above, which are not provided in detail for the sake of simplicity. Although the present invention has been described in detail with reference to the aforementioned embodiments, a person of ordinary skill 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. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A railway tunnel water level intelligent monitoring and alarm method, characterized in that: include: Responding to the water level monitoring instruction of the monitoring point, obtaining the monitoring characteristic data collected by the monitoring terminal, wherein the monitoring characteristic data includes the monitoring point position data and the video verification data; Identify the monitoring point data, obtain fixed position points and water level monitoring data, and call the safe water level comparison table to obtain the safe water level threshold corresponding to the fixed position points; Generate a water level monitoring curve graph based on the water level monitoring data, and when the current monitored water level in the water level monitoring curve graph is higher than the safe water level threshold, intercept the video verification data to generate a water level alarm interface; And / or, receiving environment-related data, obtaining each estimated time point and the corresponding estimated water level value based on the environment-related data, generating a water level estimation curve graph, and generating a water level alarm interface when the future estimated water level in the water level estimation curve graph is higher than the safe water level threshold; The water level alarm interface is sent to the management terminal.

2. The railway tunnel water level intelligent monitoring and alarm method according to claim 1 is characterized in that: A water level monitoring curve is generated based on the water level monitoring data. When the current monitored water level in the water level monitoring curve is higher than the safe water level threshold, the video verification data is intercepted to generate a water level alarm interface, including: Acquire a water level monitoring record sequence based on the water level monitoring data, wherein the water level monitoring record sequence includes each monitoring time point and the corresponding monitoring water level value; A rectangular coordinate system is established with the monitoring time as the horizontal axis and the monitoring water level as the vertical axis, a water level monitoring point is plotted in the rectangular coordinate system according to each monitoring time point and the corresponding monitoring water level value, and a water level monitoring curve is generated based on each water level monitoring point; When the current monitored water level in the water level monitoring curve is higher than the safety water level threshold, monitoring water level alarm data is generated and an accident video acquisition request is triggered, and the video verification data is intercepted according to the accident video acquisition request to acquire accident video data; The monitored water level alarm data and the accident video data are combined to generate a water level alarm interface.

3. The railway tunnel water level intelligent monitoring and alarm method according to claim 2 is characterized in that: When the current monitored water level in the water level monitoring curve is higher than the safety water level threshold, monitoring water level alarm data is generated and an accident video acquisition request is triggered, and the video verification data is intercepted according to the accident video acquisition request to obtain the accident video data, including: Determine the ordinate value corresponding to the most recently drawn water level monitoring point in the water level monitoring curve as the current monitored water level; Compare the current monitored water level with the safety water level threshold, and when the current monitored water level is higher than the safety water level threshold, generate monitoring water level alarm data and trigger an accident video acquisition request; Identify the accident video acquisition request, obtain the trigger time point, and determine the video boundary time according to the trigger time point and the preset video acquisition rule, where the video boundary time includes the video start time point and the video end time point; Locating a corresponding monitoring video segment in the video verification data according to the video start time point and the video end time point, and intercepting the monitoring video segment to obtain an intercepted monitoring video segment; The intercepted monitoring video segment is determined as accident video data.

4. The railway tunnel water level intelligent monitoring and alarm method according to claim 1 is characterized in that: Receive environment-related data, obtain each estimated time point and the corresponding estimated water level value based on the environment-related data, generate a water level estimation curve graph, and generate a water level alarm interface when the future estimated water level in the water level estimation curve graph is higher than the safe water level threshold, including: receiving environment-related data, identifying the environment-related data, and acquiring environment-related attributes, wherein the environment-related attributes include weather-related attributes and behavior-related attributes; Based on the environment-related attributes, a corresponding water level estimation strategy is called, and each estimation time point and the corresponding estimated water level value are determined according to the water level estimation strategy; A rectangular coordinate system is established with the estimated time as the horizontal axis and the estimated water level as the vertical axis, and a water level estimation point is plotted in the rectangular coordinate system according to each estimated time point and the corresponding estimated water level value, and a water level estimation curve is generated based on each water level estimation point; When the future estimated water level in the water level estimation curve is higher than the safety water level threshold, estimated water level alarm data is generated and an emergency allocation strategy is called, and a scheduling schedule is determined according to the emergency allocation strategy; The estimated water level alarm data and the scheduling plan are combined to generate a water level alarm interface.

5. The railway tunnel water level intelligent monitoring and alarm method according to claim 4 is characterized in that: The water level prediction strategy includes a rainfall water level prediction strategy; Calling a corresponding water level prediction strategy based on the environment-related attributes, and determining each prediction time point and a corresponding predicted water level value according to the water level prediction strategy, including: When the environment-related attribute is a meteorological-related attribute, calling a rainfall level prediction strategy based on the meteorological-related attribute; Based on the rainfall water level prediction strategy, the meteorological related data is identified to obtain rainfall node data, wherein the rainfall node data includes each rainfall time period and the corresponding rainfall amount in the time period; Calling a corresponding historical water level statistics table according to the fixed position point, wherein the historical water level statistics table includes each rainfall interval and the corresponding historical water level fluctuation value; Based on the historical water level statistics table, the rainfall interval to which the rainfall in the segment belongs is searched, and the historical water level fluctuation value corresponding to the rainfall interval is determined as the estimated water level fluctuation value corresponding to the rainfall time period; Each rainfall time period is identified to obtain a plurality of estimated time points, and the estimated water level value corresponding to each estimated time point is determined according to the current monitored water level and the estimated water level fluctuation value.

6. The railway tunnel water level intelligent monitoring and alarm method according to claim 5 is characterized in that: Identify each rainfall time period, obtain multiple estimated time points, and determine the estimated water level value corresponding to each estimated time point according to the current monitored water level and the estimated water level fluctuation value, including: Numbering each rainfall time period in chronological order to obtain a rainfall sequence number, identifying each rainfall time period according to the rainfall sequence number, and obtaining a rainfall start time point and a rainfall end time point of each rainfall time period respectively; Determine the rainfall start time point and rainfall end time point of each rainfall time period as the estimated time point, wherein the rainfall start time point corresponding to the first rainfall time period in the rainfall sequence number is the first estimated time point, and the rainfall end time point corresponding to the first rainfall time period is the second estimated time point; Acquire the current monitored water level, and determine the current monitored water level as an initial estimated water level value, wherein the initial estimated water level value is the estimated water level value corresponding to the first estimated time point; Determine the sum of the initial estimated water level value and the estimated water level fluctuation value corresponding to the first rainfall time period as the estimated water level value corresponding to the second estimated time point; Determine the estimated water level value corresponding to the second estimated time point as the estimated water level value corresponding to the rainfall start time of the second rainfall time period; Determine the sum of the estimated water level value corresponding to the rainfall start time of the second rainfall time period and the estimated water level fluctuation value corresponding to the second rainfall time period as the estimated water level value corresponding to the rainfall end time point of the second rainfall time period; Repeat the above steps of obtaining the estimated water level value until the estimated water level values ​​corresponding to all estimated time points are obtained.

7. The railway tunnel water level intelligent monitoring and alarm method according to claim 6 is characterized in that: The water level prediction strategy includes a drainage water level prediction strategy; Calling a corresponding water level prediction strategy based on the environment-related attributes, and determining each prediction time point and a corresponding predicted water level value according to the water level prediction strategy, including: When the environment-related attribute is a behavior-related attribute, calling a drainage water level prediction strategy based on the behavior-related attribute; Based on the drainage water level prediction strategy, the behavior association data is identified to obtain drainage behavior data, wherein the drainage behavior data includes an estimated drainage position and a corresponding estimated drainage time and an estimated drainage volume; Based on the predicted drainage position, a behavior evaluation table is called, and corresponding water level impact data is obtained based on the behavior evaluation table, wherein the water level impact data includes each drainage level and a corresponding predicted water level impact value; Determine the drainage grade according to the estimated drainage volume, and determine the corresponding estimated water level impact value based on the drainage grade; Determine the drainage start time point and drainage end time point of the expected drainage time as the estimated time points; Obtaining the current monitored water level, and determining the current monitored water level as the estimated water level value at the estimated time point corresponding to the drainage start time point; The sum of the current monitored water level and the estimated water level impact value is determined as the estimated water level value at the estimated time point corresponding to the drainage end time point.

8. The railway tunnel water level intelligent monitoring and alarm method according to claim 1 is characterized in that: The method further comprises: In response to the data upload instruction, receiving the real-time collected data sent by the management end, and determining the real-time collected data as autonomous update data; Identify the autonomous update data and obtain autonomous update attributes, where the autonomous update attributes include update point data and autonomous update time; Based on the update point data and the accident video data corresponding to the autonomous update time positioning, the accident video data is replaced with the autonomous update data.

9. The railway tunnel water level intelligent monitoring and alarm method according to claim 1 is characterized in that: The method further comprises: Detect the monitoring water level value corresponding to the monitoring time point of each monitoring point, and mark the monitoring point whose monitoring water level value is empty as a supplementary monitoring point; Obtaining distance information between each monitoring point and the supplementary monitoring point, and taking other monitoring points with monitored water level values ​​within a preset distance as reference monitoring points; Processing the distance information of each reference monitoring point according to the distance normalization value to obtain a distance filling coefficient; Calculating the height difference between each reference monitoring point and the padding monitoring point, processing the height difference between each reference monitoring point according to the height normalization value, and obtaining a height padding coefficient; Obtaining a first drainage coefficient of each of the reference monitoring points and a second drainage coefficient of the complementary monitoring point, and processing a difference between each of the first drainage coefficient and the second drainage coefficient according to a drainage normalization value to obtain a drainage complementary coefficient; The monitored water level value of the reference monitoring point is calculated according to the distance filling coefficient, the height filling coefficient and the drainage filling coefficient to obtain the filling water level of the filling monitoring point.

10. A railway tunnel water level intelligent monitoring and alarm platform, characterized in that: include: At least one processor, and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the railway tunnel water level intelligent monitoring and alarm method as described in any one of claims 1-9.

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