Method and system for tunnel stratum monitoring and early warning based on cosmic ray muons

Abstract

The invention discloses a method and system for tunnel stratum monitoring and early warning based on cosmic ray muons, and the method comprises the steps: firstly obtaining an average value and a standard deviation of ground surface cosmic ray muon flux, and then collecting the tunnel cosmic ray muon flux of a to-be-monitored point in each preset time period in real time; based on the average value of the earth surface cosmic ray muon flux and the tunnel cosmic ray muon flux, a muon flux attenuation value in each preset time period is calculated, if the muon flux attenuation value in a certain preset time period exceeds a preset threshold range, it is judged that the stratum is suspected to change, an over-limit alarm is triggered, and the condition that the stratum is suspected to change is judged. The cosmic ray muon flux attenuation value is used as a monitoring index, the change of the cosmic ray muon flux attenuation value directly reflects the change of a stratum structure, complex geological investigation is not needed, and the muon detector is high in stability, long in service life and very suitable for tunnel stratum safety monitoring projects needing continuous and stable monitoring. And the accuracy and the reliability of a tunnel stratum monitoring result are obviously improved.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel stratum monitoring and early warning, and in particular to a method and system, electronic equipment, and computer-readable storage medium for tunnel stratum monitoring and early warning based on cosmic ray muons. Background Art

[0002] With the acceleration of urbanization, tunnels, as important hubs of urban transportation, are directly related to the normal operation of urban life and public safety. During the operation of tunnels, the ground conditions may change due to factors such as earthquake activity, nearby construction disturbances, and material aging, which in turn affects the stability of the tunnel structure and may even cause tunnel collapse in severe cases. Therefore, it is particularly important to strengthen the monitoring and early warning of ground changes during tunnel operation. The traditional monitoring and early warning method for tunnel operation mainly adopts a combination of manual inspection and regular measurement. Professionals regularly enter the tunnel to visually check the integrity of the tunnel lining, water seepage, and signs of ground subsidence. At the same time, measurement equipment such as levels and total stations are used to monitor the displacement of key points in the tunnel to obtain quantitative data on the deformation of the tunnel structure. However, the state change of the tunnel lining is often a reflection of the accumulation of ground changes to a certain extent. It is impossible to capture the initial signs of ground changes in time, thus missing the best opportunity for prevention and intervention. In addition, although the regular measurement data is accurate, the time interval between the data is too long, and it is impossible to warn of sudden ground changes in time.

[0003] At present, sensors are buried in tunnel segments or in soil to achieve real-time remote monitoring of the state of the strata; or holes are drilled at monitoring points and sensors are placed in the holes to monitor changes in the strata. For example, patent CN108825304A discloses a shield tunnel stratum stability and tunnel structure long-term health monitoring system, which monitors the state of the segments by placing earth pressure gauges, osmometers, stress gauges, strain gauges, crack gauges and other sensors inside and on the outer surface of the segments, thereby judging the stability of the strata; patent CN117870608A discloses a stratum deformation early warning method and early warning system, which measures the change in stratum migration parameters by placing buried wireless sensing devices at multiple monitoring points, selects a monitoring point to calculate the theoretical change value, and compares the measured data of other points with the theoretical value, thereby providing a stratum deformation early warning. However, the existing method of monitoring formation changes through sensors is difficult to repair or replace in time once the sensor fails or is damaged, which will lead to the loss or interruption of monitoring data. Moreover, as time goes by, the measurement accuracy of the sensor will decrease, affecting the reliability of the monitoring results. In addition, the accuracy of the monitoring results depends on the accuracy of the geological parameters. It is difficult to obtain accurate geological parameters in practical applications, resulting in poor accuracy of the monitoring results. Summary of the invention

[0004] The present invention provides a method and system for tunnel stratum monitoring and early warning based on cosmic ray muons, an electronic device, and a computer-readable storage medium, which can significantly improve the accuracy and reliability of tunnel stratum monitoring results.

[0005] According to one aspect of the present invention, a method for tunnel stratum monitoring and early warning based on cosmic ray muons is provided, which is characterized by comprising the following contents:

[0006] Collect the cosmic ray muon flux above the surface of the monitoring point over a period of time, and calculate the average value and standard deviation of the surface cosmic ray muon flux;

[0007] Collect the tunnel cosmic ray muon flux of the monitoring point in each preset time period;

[0008] The muon flux attenuation value in each preset time period is calculated based on the average value of the surface cosmic ray muon flux and the tunnel cosmic ray muon flux. If the muon flux attenuation value in a preset time period exceeds the preset threshold range, an over-limit alarm is triggered.

[0009] Furthermore, the following contents are also included:

[0010] After the over-limit alarm is triggered, the cosmic ray muon flux above the surface of the monitored point for a period of time is collected again, and the new values ​​of the average value and standard deviation of the surface cosmic ray muon flux are calculated. The new average value is compared with the old average value. If the difference between the two is less than three times the old standard deviation, the formation change alarm is triggered. If the difference between the two is greater than three times the old standard deviation, the new average value and standard deviation replace the old average value and standard deviation for analysis and calculation.

[0011] Furthermore, the following contents are also included:

[0012] A series of muon flux attenuation values ​​of the monitoring point are obtained, and the prediction model is used to predict the muon flux attenuation value of the next time period based on the series of muon flux attenuation values. If the predicted muon flux attenuation value of the next time period exceeds the preset threshold range, an over-limit warning is triggered.

[0013] Furthermore, the expression of the prediction model is:

[0014] Y t =φ1Y t-1 +φ2Y t-2 +…+φ p Y t-p +ε t -θ1ε t-1 -…-θ q ε t-q

[0015] Among them, Y trepresents the muon flux attenuation value in the tth time period, ε t represents the error in the tth time period, p and q represent the order of autoregression and moving average, respectively, which are determined by the autocorrelation coefficient and partial autocorrelation coefficient, φ i and θ i represents the autoregressive coefficient and the moving average coefficient, which are solved using the least squares estimation method.

[0016] Furthermore, the preset threshold range of the muon flux attenuation value is: Among them, h a Indicates the preset threshold range, and σ a They respectively represent the mean value and standard deviation of the muon flux attenuation value of the monitored point in the initial monitoring stage.

[0017] Furthermore, the process of collecting the cosmic ray muon flux above the surface of the monitoring point over a period of time includes the following:

[0018] Select a flat and unobstructed area above the surface of the monitoring point to deploy the muon detector, start the muon detector for continuous measurement, record the flux value of cosmic ray muons once an hour, and calculate the cosmic ray muon flux based on the following formula: Among them, I represents the cosmic ray muon flux, N represents the number of muons measured within one hour, S represents the effective detection area of ​​the muon detector, and Δt represents the measurement time.

[0019] In addition, the present invention also provides a system for tunnel stratum monitoring and early warning based on cosmic ray muons, comprising:

[0020] The surface muon data acquisition module is used to collect the cosmic ray muon flux above the surface of the monitoring point within a period of time, and calculate the average value and standard deviation of the surface cosmic ray muon flux;

[0021] The tunnel muon data acquisition module is used to collect the tunnel cosmic ray muon flux of the monitoring point in each preset time period;

[0022] The muon data calculation and over-limit alarm module is used to calculate the muon flux attenuation value in each preset time period based on the average value of the surface cosmic ray muon flux and the tunnel cosmic ray muon flux. If the muon flux attenuation value in a preset time period exceeds the preset threshold range, an over-limit alarm is triggered.

[0023] Furthermore, it also includes:

[0024] The formation change alarm module is used to collect the cosmic ray muon flux above the surface of the monitored point for a period of time again after the over-limit alarm is triggered, and calculate the new value of the average value and standard deviation of the surface cosmic ray muon flux, and compare the new average value with the old average value. If the difference between the two is less than three times the old standard deviation, the formation change alarm is triggered. If the difference between the two is greater than three times the old standard deviation, the new average value and standard deviation will replace the old average value and standard deviation for analysis and calculation.

[0025] In addition, the present invention also provides an electronic device, including a processor and a memory, wherein the memory stores a computer program, and the processor executes the steps of the above method by calling the computer program stored in the memory.

[0026] In addition, the present invention also provides a computer-readable storage medium for storing a computer program for tunnel stratum monitoring and early warning based on cosmic ray muons, and the computer program executes the steps of the method described above when running on a computer.

[0027] The present invention has the following beneficial effects:

[0028] The method for tunnel stratum monitoring and early warning based on cosmic ray muons of the present invention utilizes the cosmic ray muon flux attenuation value as a monitoring indicator, and its change directly reflects the change of the stratum structure without relying on complex geological surveys. In addition, the muon detector has strong stability and long service life, and is very suitable for tunnel stratum safety monitoring projects that require continuous and stable monitoring, which significantly improves the accuracy and reliability of tunnel stratum monitoring results.

[0029] In addition, the system for tunnel stratum monitoring and early warning based on cosmic ray muons of the present invention also has the above advantages.

[0030] In addition to the above-described purposes, features and advantages, the present invention has other purposes, features and advantages. The present invention will be further described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The drawings constituting a part of this application are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0032] Figure 1 It is a flow chart of a method for tunnel stratum monitoring and early warning based on cosmic ray muons according to a preferred embodiment of the present application.

[0033] Figure 2 It is a schematic diagram of deploying muon detectors in a tunnel in a preferred embodiment of the present application.

[0034] Figure 3 It is another flow chart of the method for tunnel stratum monitoring and early warning based on cosmic ray muons according to the preferred embodiment of the present application.

[0035] Figure 4 It is another flow chart of the method for tunnel stratum monitoring and early warning based on cosmic ray muons according to the preferred embodiment of the present application.

[0036] Figure 5 It is a schematic diagram of the module structure of a system for tunnel stratum monitoring and early warning based on cosmic ray muons according to another embodiment of the present application.

[0037] Description of Reference Numerals

[0038] 1. Tunnel; 2. Segment; 3. Muon detector; 4. Network cable; 5. Switch; 6. PC terminal of monitoring center. DETAILED DESCRIPTION

[0039] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0040] Reference Figure 1 The preferred embodiment of the present application provides a method for tunnel stratum monitoring and early warning based on cosmic ray muons, comprising the following contents:

[0041] Step S1: collecting the cosmic ray muon flux above the surface of the monitoring point within a period of time, and calculating the average value and standard deviation of the surface cosmic ray muon flux;

[0042] Step S2: collecting the tunnel cosmic ray muon flux of the monitoring point in each preset time period;

[0043] Step S3: The muon flux attenuation value in each preset time period is calculated based on the average value of the surface cosmic ray muon flux and the tunnel cosmic ray muon flux. If the muon flux attenuation value in a preset time period exceeds a preset threshold range, an over-limit alarm is triggered.

[0044] It can be understood that the method for monitoring and early warning of tunnel formations based on cosmic ray muons in this embodiment first collects the cosmic ray muon flux above the surface of the monitored point within a period of time, and calculates the average value and standard deviation of the surface cosmic ray muon flux, which is used as the reference data for the subsequent muon flux attenuation calculation. Then, the tunnel cosmic ray muon flux of the monitored point in each preset time period is collected in real time, and then the muon flux attenuation value in each preset time period is calculated based on the average value of the surface cosmic ray muon flux and the tunnel cosmic ray muon flux. Since energy loss occurs when muons pass through the formation, the greater the material density, the greater the energy lost by muons passing through the unit length in the material, and the higher the muon flux attenuation, it can be judged whether the formation has changed according to the degree of muon flux attenuation. If the muon flux attenuation value in a preset time period exceeds the preset threshold range, it is judged that the formation is suspected to have changed, and an over-limit alarm is triggered, so that real-time monitoring and early warning of formation structure changes can be achieved, which provides a solid technical guarantee for quickly identifying and effectively responding to potential formation safety hazards. Therefore, the method for tunnel stratum monitoring and early warning based on cosmic ray muons of the present invention utilizes the cosmic ray muon flux attenuation value as a monitoring indicator, and its change directly reflects the change in the stratum structure without relying on complex geological surveys. In addition, the muon detector has strong stability and long service life, and is very suitable for tunnel stratum safety monitoring projects that require continuous and stable monitoring, which significantly improves the accuracy and reliability of tunnel stratum monitoring results.

[0045] It can be understood that in step S1, a flat and unobstructed area is selected above the surface of each monitoring point to deploy a muon detector, and the muon detector is started to perform continuous measurement, for example, for 24 hours, and the flux value of cosmic ray muons is recorded once every hour, and the cosmic ray muon flux is calculated based on the following formula: Among them, I represents the cosmic ray muon flux, N represents the number of muons measured in one hour, S represents the effective detection area of ​​the muon detector, and Δt represents the measurement time. Then, the average value I and standard deviation σ of the surface cosmic ray muon flux of each monitoring point are calculated. I , and use it as the benchmark data for subsequent muon flux decay calculations.

[0046] It can be understood that in step S2, a muon detector is installed just above the tunnel segment at each monitoring point, ensuring that the detection surface is horizontal and facing upward, and real-time measurement of muon information passing through the overlying strata, and automatically calculating the cosmic ray muon flux data in the tunnel once every predetermined time period (for example, every hour), and transmitting the muon flux data to the PC of the monitoring center. The schematic diagram of the deployment of the muon detector in the tunnel is shown in FIG. Figure 2As shown, multiple muon detectors 3 are deployed on the segments 2 in the tunnel 1. Multiple muon detectors 3 are connected to the switch 5 through the network cable 4. The switch 5 serves as a communication hub and transmits the muon information collected by each detector to the monitoring center PC 6 through the network port communication method. The remote client can browse the network and view the monitoring data in real time through the Internet. Among them, the muon detector 3 includes a dark box, a data acquisition and processing module, and a muon detection module. The muon detection module is composed of a plastic scintillator. When the cosmic ray muon enters the dark box and passes through the detection module, the plastic scintillator is stimulated to generate photons. The data acquisition and processing module collects the photon signal and performs amplification, filtering, and flux calculation processing, thereby collecting muon information. It can be understood that by directly installing the muon detector on the tunnel segment, the subsequent maintenance and replacement work is greatly facilitated, and the operation and maintenance cost is reduced. In addition, the plastic scintillator muon detector has strong stability and long service life, which is very suitable for tunnel and formation safety monitoring projects that require continuous and stable monitoring.

[0047] It can be understood that in step S3, when muons pass through a substance, energy loss will occur. The greater the density of the substance, the greater the energy lost per unit length of the muon passing through the substance, and the higher the flux attenuation. Therefore, the formation change can be judged according to the flux attenuation. Specifically, the muon flux attenuation value of each preset time period is calculated based on the following formula: ΔI = II t , where ΔI represents the muon flux attenuation value, I t is the muon flux value in the t-th time period measured in step S2. Then, the muon flux attenuation value in each time period is compared with the preset threshold range. If the muon flux attenuation value in a preset time period exceeds the preset threshold range, it can be preliminarily judged that the formation is suspected to have changed, and an over-limit alarm is triggered. If the muon flux attenuation value in a preset time period is within the preset threshold range, it is judged that the formation has not changed, and no alarm is triggered.

[0048] Optionally, for each point to be monitored, the muon flux attenuation data of the initial monitoring stage is counted, and the initial monitoring stage represents the stage when the formation has not yet changed. Then, the average value I of the muon flux attenuation data of the initial monitoring stage is calculated. a and standard deviation σ a , so that the preset threshold range of the muon flux attenuation value of the monitoring point can be determined as: h a =I a ±3σ a , when the muon flux attenuation value of the monitored point in a certain period of time exceeds h a , an over-limit warning is triggered.

[0049] Alternatively, if Figure 3As shown, the method for tunnel formation monitoring and early warning based on cosmic ray muons also includes the following contents:

[0050] Step S4: After the over-limit alarm is triggered, the cosmic ray muon flux above the surface of the monitored point within a period of time is collected again, and the new value of the average value and standard deviation of the surface cosmic ray muon flux is calculated, and the new average value is compared with the old average value. If the difference between the two is less than three times the old standard deviation, the formation change alarm is triggered. If the difference between the two is greater than three times the old standard deviation, the new average value and standard deviation replace the old average value and standard deviation for analysis and calculation.

[0051] It can be understood that the comparison between the muon flux attenuation value obtained based on real-time measurement and the preset threshold range in the above step S3 can only accurately determine the abnormality of the muon flux attenuation value, and the abnormality of the muon flux attenuation value may be caused by changes in the stratum structure or changes in the number of cosmic ray muons reaching the area. Therefore, after the over-limit alarm is triggered, the muon detector is used again above the surface of the alarm monitoring point to continuously measure for a period of time, and the mean and standard deviation of the surface cosmic ray muon flux during this period are calculated, and the new mean is compared with the old mean. If the difference between the two is less than 3σ I , it is determined that the muon flux attenuation value exceeds the limit due to formation changes, and the formation change alarm is activated; if the difference between the two exceeds 3σ I , it is determined that the excess of the muon flux attenuation value is caused by the change in the number of cosmic ray muons arriving in this area. At this time, the benchmark data needs to be updated, that is, the new values ​​of the flux mean and standard deviation replace the old values, and the new flux mean and standard deviation are used for subsequent analysis and calculation.

[0052] It can be understood that after the over-limit alarm is triggered, the present invention collects new values ​​of the average value and standard deviation of the surface cosmic ray muon flux at the alarm point again, and compares and analyzes the new average value with the old average value, so as to accurately determine whether the over-limit of the muon flux attenuation value is caused by changes in the stratum structure or by changes in the number of cosmic ray muons reaching the area, thereby improving the accuracy of tunnel stratum monitoring and early warning.

[0053] Alternatively, if Figure 4 As shown, the method for tunnel formation monitoring and early warning based on cosmic ray muons also includes the following contents:

[0054] Step S5: For each point to be monitored, a series of muon flux attenuation values ​​of the point to be monitored is obtained, and a prediction model is used to predict the muon flux attenuation value of the next time period based on the series of muon flux attenuation values. If the predicted muon flux attenuation value of the next time period exceeds the preset threshold range, an over-limit warning is triggered.

[0055] Specifically, for each monitoring point, a series of historical muon flux attenuation values ​​of the monitoring point are collected, and the ARMA prediction model is constructed as follows:

[0056] Y t =φ1Y t-1 +φ2Y t-2 +…+φ p Y t-p +ε t -θ1ε t-1 -…-θ q ε t-q

[0057] Among them, Y t represents the muon flux attenuation value in the tth time period, ε t represents the error in the tth time period, p and q represent the order of autoregression and moving average, respectively, which are determined by the autocorrelation coefficient and partial autocorrelation coefficient, φ i and θ i Represents the autoregressive coefficient and the moving average coefficient, which are solved by the least squares estimation method. Based on the historical muon flux attenuation value and the ARMA prediction model, the muon flux attenuation value of the next time period can be accurately predicted, and then the predicted muon flux attenuation value is compared with the preset threshold range, so that the formation change warning can be carried out in advance.

[0058] It can be understood that for each monitoring point, the present invention also collects a series of historical muon flux attenuation values ​​of the monitoring point, and constructs a prediction model, and uses the historical attenuation data and the prediction model to predict the attenuation data of the next time, so that early warning of stratum changes can be achieved, further improving the reliability of tunnel stratum monitoring. In addition, all over-limit alarms, stratum change alarms and early warning information are transmitted to the client in real time through the network, so that users can quickly understand and respond to alarm and warning information.

[0059] In addition, if Figure 5 As shown, another embodiment of the present invention further provides a system for monitoring and early warning of tunnel strata based on cosmic ray muons, preferably using the method for monitoring and early warning of tunnel strata based on cosmic ray muons as described above, the system comprising:

[0060] The surface muon data acquisition module is used to collect the cosmic ray muon flux above the surface of the monitoring point within a period of time, and calculate the average value and standard deviation of the surface cosmic ray muon flux;

[0061] The tunnel muon data acquisition module is used to collect the tunnel cosmic ray muon flux of the monitoring point in each preset time period;

[0062] The muon data calculation and over-limit alarm module is used to calculate the muon flux attenuation value in each preset time period based on the average value of the surface cosmic ray muon flux and the tunnel cosmic ray muon flux. If the muon flux attenuation value in a preset time period exceeds the preset threshold range, an over-limit alarm is triggered.

[0063] It can be understood that the method for monitoring and early warning of tunnel formations based on cosmic ray muons in this embodiment first collects the cosmic ray muon flux above the surface of the monitored point within a period of time, and calculates the average value and standard deviation of the surface cosmic ray muon flux, which is used as the reference data for the subsequent muon flux attenuation calculation. Then, the tunnel cosmic ray muon flux of the monitored point in each preset time period is collected in real time, and then the muon flux attenuation value in each preset time period is calculated based on the average value of the surface cosmic ray muon flux and the tunnel cosmic ray muon flux. Since energy loss occurs when muons pass through the formation, the greater the material density, the greater the energy lost by muons passing through the unit length in the material, and the higher the muon flux attenuation, it can be judged whether the formation has changed according to the degree of muon flux attenuation. If the muon flux attenuation value in a preset time period exceeds the preset threshold range, it is judged that the formation is suspected to have changed, and an over-limit alarm is triggered, so that real-time monitoring and early warning of formation structure changes can be achieved, which provides a solid technical guarantee for quickly identifying and effectively responding to potential formation safety hazards. Therefore, the system for tunnel stratum monitoring and early warning based on cosmic ray muons of the present invention uses the cosmic ray muon flux attenuation value as a monitoring indicator, and its change directly reflects the change of the stratum structure without relying on complex geological surveys. In addition, the muon detector has strong stability and long service life, which is very suitable for tunnel stratum safety monitoring projects that require continuous and stable monitoring, and significantly improves the accuracy and reliability of tunnel stratum monitoring results.

[0064] Optionally, the system for tunnel stratum monitoring and early warning based on cosmic ray muons further includes:

[0065] The formation change alarm module is used to collect the cosmic ray muon flux above the surface of the monitored point for a period of time again after the over-limit alarm is triggered, and calculate the new value of the average value and standard deviation of the surface cosmic ray muon flux, and compare the new average value with the old average value. If the difference between the two is less than three times the old standard deviation, the formation change alarm is triggered. If the difference between the two is greater than three times the old standard deviation, the new average value and standard deviation will replace the old average value and standard deviation for analysis and calculation.

[0066] In addition, the system for tunnel stratum monitoring and early warning based on cosmic ray muons also includes:

[0067] The muon flux attenuation prediction module is used to obtain a series of muon flux attenuation values ​​of the monitoring point, and use the prediction model to predict the muon flux attenuation value of the next time period based on a series of muon flux attenuation values. If the predicted muon flux attenuation value of the next time period exceeds the preset threshold range, an over-limit alarm is triggered.

[0068] It can be understood that the various modules of the system embodiment correspond to the various steps of the above method embodiment, so the specific working principles of each module are not repeated here, and the corresponding references can be made to the various steps of the above method embodiment.

[0069] In addition, another embodiment of the present invention further provides an electronic device, including a processor and a memory, wherein the memory stores a computer program, and the processor executes the steps of the above method by calling the computer program stored in the memory.

[0070] In addition, another embodiment of the present invention further provides a computer-readable storage medium for storing a computer program for tunnel formation monitoring and early warning based on cosmic ray muons, wherein the computer program executes the steps of the method described above when running on a computer.

[0071] The general form of computer readable storage media includes: floppy disk, flexible disk, hard disk, magnetic tape, any other magnetic medium, CD-ROM, any other optical medium, punch cards, paper tape, any other physical medium with a pattern of holes, random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), flash erasable programmable read-only memory (FLASH-EPROM), any other memory chip or cartridge, or any other medium that can be read by a computer. The instructions can further be transmitted or received by a transmission medium. The term transmission medium can include any tangible or intangible medium that can be used to store, encode or carry instructions for execution by a machine, and includes digital or analog communication signals or other intangible media that facilitate the communication of the above instructions. Transmission media include coaxial cables, copper wires and optical fibers, which include the wires of a bus used to transmit a computer data signal.

[0072] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0073] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0074] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0075] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0076] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0077] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

[0078] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for tunnel stratum monitoring and early warning based on cosmic ray muons, characterized in that: Includes the following: Collect the cosmic ray muon flux above the surface of the monitoring point over a period of time, and calculate the average value and standard deviation of the surface cosmic ray muon flux; Collect the tunnel cosmic ray muon flux of the monitoring point in each preset time period; The muon flux attenuation value in each preset time period is calculated based on the average value of the surface cosmic ray muon flux and the tunnel cosmic ray muon flux. If the muon flux attenuation value in a preset time period exceeds the preset threshold range, an over-limit alarm is triggered.

2. The method for tunnel stratum monitoring and early warning based on cosmic ray muons according to claim 1, characterized in that: Also included are the following: After the over-limit alarm is triggered, the cosmic ray muon flux above the surface of the monitored point for a period of time is collected again, and the new values ​​of the average value and standard deviation of the surface cosmic ray muon flux are calculated. The new average value is compared with the old average value. If the difference between the two is less than three times the old standard deviation, the formation change alarm is triggered. If the difference between the two is greater than three times the old standard deviation, the new average value and standard deviation replace the old average value and standard deviation for analysis and calculation.

3. The method for tunnel stratum monitoring and early warning based on cosmic ray muons according to claim 1, characterized in that: Also included are the following: A series of muon flux attenuation values ​​of the monitoring point are obtained, and the prediction model is used to predict the muon flux attenuation value of the next time period based on the series of muon flux attenuation values. If the predicted muon flux attenuation value of the next time period exceeds the preset threshold range, an over-limit warning is triggered.

4. The method for tunnel stratum monitoring and early warning based on cosmic ray muons as claimed in claim 3, characterized in that: The expression of the prediction model is: Y t =φ1Y t-1 +φ2Y t-2 +…+φ p Y t-p +e t -θ1ε t-1 -…-θ q e t-q Among them, Y t represents the muon flux attenuation value in the tth time period, ε t represents the error in the tth time period, p and q represent the order of autoregression and moving average, respectively, which are determined by the autocorrelation coefficient and partial autocorrelation coefficient, φ i and θ i represents the autoregressive coefficient and the moving average coefficient, which are solved using the least squares estimation method.

5. The method for tunnel stratum monitoring and early warning based on cosmic ray muons according to claim 1, characterized in that: The preset threshold range for the muon flux decay value is: Among them, h a Indicates the preset threshold range, and σ a They respectively represent the mean value and standard deviation of the muon flux attenuation value of the monitored point in the initial monitoring stage.

6. The method for tunnel stratum monitoring and early warning based on cosmic ray muons according to claim 1, characterized in that: The process of collecting the cosmic ray muon flux above the surface of the monitoring point over a period of time includes the following: Select a flat and unobstructed area above the surface of the monitoring point to deploy the muon detector, start the muon detector for continuous measurement, record the flux value of cosmic ray muons once an hour, and calculate the cosmic ray muon flux based on the following formula: Among them, I represents the cosmic ray muon flux, N represents the number of muons measured within one hour, S represents the effective detection area of ​​the muon detector, and Δt represents the measurement time.

7. A system for tunnel stratum monitoring and early warning based on cosmic ray muons, characterized in that: include: The surface muon data acquisition module is used to collect the cosmic ray muon flux above the surface of the monitoring point within a period of time, and calculate the average value and standard deviation of the surface cosmic ray muon flux; The tunnel muon data acquisition module is used to collect the tunnel cosmic ray muon flux of the monitoring point in each preset time period; The muon data calculation and over-limit alarm module is used to calculate the muon flux attenuation value in each preset time period based on the average value of the surface cosmic ray muon flux and the tunnel cosmic ray muon flux. If the muon flux attenuation value in a preset time period exceeds the preset threshold range, an over-limit alarm is triggered.

8. The system for tunnel stratum monitoring and early warning based on cosmic ray muons as claimed in claim 7, characterized in that: Also includes: The formation change alarm module is used to collect the cosmic ray muon flux above the surface of the monitored point for a period of time again after the over-limit alarm is triggered, and calculate the new value of the average value and standard deviation of the surface cosmic ray muon flux, and compare the new average value with the old average value. If the difference between the two is less than three times the old standard deviation, the formation change alarm is triggered. If the difference between the two is greater than three times the old standard deviation, the new average value and standard deviation will replace the old average value and standard deviation for analysis and calculation.

9. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores a computer program, and the processor executes the steps of the method according to any one of claims 1 to 6 by calling the computer program stored in the memory.

10. A computer-readable storage medium for storing a computer program for tunnel stratum monitoring and early warning based on cosmic ray muons, characterized in that: When the computer program is run on a computer, the steps of the method according to any one of claims 1 to 6 are executed.

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