Roadway deformation influence factor analysis method and system based on data monitoring

Abstract

The invention discloses a roadway deformation influence factor analysis method and system based on data monitoring, relates to the technical field of data processing, and carries out roadway surrounding rock stability evaluation based on mining equipment operation data and supporting structure state data. Performing adjacent roadway influence evaluation based on the mining roadway state data; performing roadway deformation risk assessment based on the roadway surrounding rock stability assessment result and the adjacent roadway influence assessment result, and performing roadway deformation risk early warning according to the roadway deformation risk assessment result; potential safety hazards can be found in time, accidents such as collapse, equipment failure or support failure can be avoided, areas with unstable factors can be accurately judged by monitoring mining equipment and roadway states in real time, so that mining plans are reasonably adjusted, resource waste is avoided, and the mining efficiency is improved by evaluating the influence of adjacent roadways. The influence of excessive mining on the surrounding environment can be avoided, surrounding land and water sources are protected, and sustainable and safe mining of a mine is achieved.

Description

Technical Field

[0001] The present application relates to the field of data processing, and more specifically to a method and system for analyzing factors affecting tunnel deformation based on data monitoring. Background Art

[0002] In the process of modernization, infrastructure construction is crucial to the economies of all countries. Mineral resources are important raw materials for the construction of large-scale infrastructure such as roads, bridges, and railways. The existence of mining provides the necessary resource support for these construction projects. As mining activities continue to deepen, the stability of the roadway is crucial to the safe production during the mining process. In the safe production process of mining, roadway stability monitoring is the core link to prevent roof accidents and ensure mining safety. The existing technology has the following main shortcomings: First, the data collection dimension is single, and most systems only focus on the independent monitoring of support structure stress or tunnel displacement, and lack the coordinated analysis of equipment operating conditions and surrounding rock deformation; second, the evaluation model is static, and the dynamic control method is not used to establish a real-time parameter response mechanism; it is impossible to establish a full-domain perception system covering equipment, environment, and structure, which makes it difficult to meet the needs of modern mines for real-time risk warnings, increasing safety risks in the mining process.

[0003] In order to solve the problems raised in this background technology, the present application designs a method and system for analyzing factors affecting tunnel deformation based on data monitoring. Summary of the Invention

[0004] In response to the above-mentioned technical deficiencies, this application proposes a method and system for analyzing factors affecting tunnel deformation based on data monitoring.

[0005] To solve the above technical problems, the present invention adopts the following technical solution: This application provides a method for analyzing factors affecting roadway deformation based on data monitoring, which includes the following specific steps: S1. Acquire mining equipment operation data, support structure status data, and mining tunnel status data; S2. Evaluate the stability of the surrounding rock of the roadway based on the operating data of the mining equipment and the status data of the support structure; S3. Conduct impact assessment on adjacent tunnels based on mining tunnel status data; S4. Conduct a roadway deformation risk assessment based on the roadway surrounding rock stability assessment results and the adjacent roadway impact assessment results, and issue a roadway deformation risk warning based on the roadway deformation risk assessment results.

[0006] It should be noted that, as a preferred technical solution for the method for analyzing factors affecting roadway deformation based on data monitoring, the specific steps of S1 are: S11. Acquire mining equipment operation data through a pressure sensor and an acceleration sensor, wherein the mining equipment operation data includes load data applied by the mining equipment to each collection point on the surrounding rock of the roadway and vibration angular frequency data of the mining equipment; S12. Acquire support structure status data through pressure sensors and a database, wherein the support structure status data includes external force data acting on the support structure at each acquisition point of the tunnel surrounding rock, support structure length data, and cross-sectional area data; S13. Acquire mining tunnel status data from a database, wherein the mining tunnel status data includes average bulk density data of the tunnel surrounding rock, mining depth data, and goaf width data; S14. Storing the collected data in a storage component for use in the analysis process.

[0007] It should be noted that, as a preferred technical solution for the method for analyzing factors affecting roadway deformation based on data monitoring, S2 includes the following specific steps: S21, obtaining a dynamic load impact assessment value corresponding to each sampling point in the tunnel surrounding rock based on the load data applied by the mining equipment to each sampling point on the tunnel surrounding rock and the vibration angular frequency data of the mining equipment; S22, obtaining a support structure deformation assessment value corresponding to each sampling point in the tunnel surrounding rock based on the external force data acting on the support structure, the support structure length data, and the cross-sectional area data; S23. Obtain the dynamic load influence assessment value and support structure deformation assessment value results corresponding to each sampling point of the tunnel surrounding rock, and obtain the stability assessment value corresponding to each sampling point of the tunnel surrounding rock by weighted addition of the dynamic load influence assessment value and support structure deformation assessment value corresponding to each sampling point of the tunnel surrounding rock. It should be noted that the dynamic load influence assessment value is a characterization of the equivalent dynamic load strength caused by the mining equipment on the tunnel during mining, and the support structure deformation assessment value is a factor for analyzing whether the support structure will cause excessive deformation and affect the safety of the tunnel. Therefore, by comprehensively considering the equivalent dynamic load strength caused by the mining equipment on the tunnel during mining and whether the support structure will cause excessive deformation, the stability corresponding to each sampling point of the tunnel surrounding rock is assessed, thereby improving the accuracy of the stability assessment value. S24. The stability assessment value of the tunnel surrounding rock is obtained by summing up the stability assessment values corresponding to each sampling point and then averaging them. It should be noted that by summing up the stability assessment values corresponding to each sampling point of the tunnel surrounding rock and then averaging them, the stability assessment values corresponding to different sampling points can be comprehensively evaluated, and the stability assessment values corresponding to each sampling point can be fully considered, avoiding focusing on the stability assessment value corresponding to a single sampling point and ignoring the stability assessment values corresponding to other sampling points, thereby improving the accuracy of the stability assessment value of the tunnel surrounding rock.

[0008] It should be noted that, as a preferred technical solution for the method for analyzing factors affecting roadway deformation based on data monitoring, the specific step of S21 is: performing a dynamic load influence assessment based on the load data of each sampling point applied by the mining equipment on the roadway surrounding rock and the vibration angular frequency data of the mining equipment, wherein the dynamic load influence assessment calculation formula of each sampling point on the roadway surrounding rock is: , where i is the number corresponding to each sampling point on the surrounding rock of the roadway, i is any item from 1 to N, T is the operation cycle of the mining equipment, is the dynamic load data at time t corresponding to the i-th collection point on the surrounding rock of the roadway, is the reference load data corresponding to the i-th collection point on the surrounding rock of the roadway, is the attenuation coefficient of the roadway rock mass, is the vibration angular frequency of the mining equipment during operation, is the critical frequency of the roadway rock mass. It should be noted that in this formula The function of is to express the dynamic force exerted by the mining equipment on each sampling point on the surrounding rock of the roadway during normal operation, which is the basis for calculating the dynamic load impact assessment value; It is the load safety reference value, used to quantify the degree of deviation from the actual load; is the attenuation coefficient of the roadway rock mass, obtained from the core vibration test, which represents the ability of the roadway rock mass to absorb vibration energy. The softer the rock layer, the larger the value. It is the vibration angular frequency of the mining equipment during operation, reflecting the vibration characteristics of the mining equipment during operation. The higher the frequency, the stronger the disturbance to the roadway rock mass. The design significance is to monitor whether the tunnel rock mass and the mining equipment will resonate during operation, which requires key monitoring. The acquisition method is to obtain the rock mass stiffness through acoustic wave detection. In this formula, The part reflects the average load state of the mining equipment during the operation cycle, and eliminates the interference of instantaneous overload or underload through time integration; in this formula Part of it is used to quantify the energy consumption effect of mining equipment vibration on the tunnel rock mass.

[0009] It should be noted that, as a preferred technical solution for the method for analyzing factors affecting roadway deformation based on data monitoring, the specific steps of S22 are: based on the external force data, support structure length data, and cross-sectional area data acting on the support structure at each sampling point of the roadway surrounding rock, the deformation evaluation value of the support structure at each sampling point of the roadway surrounding rock is calculated as follows: , where T is the operating cycle of mining equipment, is the external force acting on the support structure at the i-th collection point at time t during the operation cycle of the mining equipment, is the length of the support structure corresponding to the i-th collection point, is the cross-sectional area of the support structure corresponding to the i-th collection point, is the elastic modulus of the supporting structure, is the reference average deformation corresponding to the i-th collection point. It should be noted that in this formula The setting is because the deformation of the supporting structure is an external force, and the magnitude of the external force will be different at different time points; The setting is because the length of the support structure is proportional to the deformation it bears, and a long support structure is more susceptible to external forces than a short support structure; The reason for setting is that the cross-sectional area of the support structure determines its ability to resist external forces. The larger the area, the greater the pressure it can withstand. It is an important parameter to measure the stiffness of the support structure material. Materials with high elastic modulus deform less when subjected to external forces, while materials with low elastic modulus deform more when subjected to external forces. It is an important parameter for quantifying the degree of deviation of the support structure deformation; T reflects the cumulative effect of the support structure deformation under load. Considering the time effect can more accurately describe the state of the support structure during the operation cycle of the mining equipment. In this formula, The cumulative deformation of the support structure during the entire mining equipment operation cycle is analyzed in part by integrating the changes in the external forces acting on the support structure at each sampling point during the mining equipment operation cycle.

[0010] It should be noted that, as a preferred technical solution for the method for analyzing factors affecting roadway deformation based on data monitoring, the specific step of S3 is: based on the average bulk density data of the roadway surrounding rock, the mining depth data, and the goaf width data, the adjacent roadway impact assessment is performed. The calculation formula for the adjacent roadway impact assessment is: ,in is the average bulk density data of the surrounding rock of the roadway, H is the mining depth data, D is the span data of the goaf, k is the stress attenuation index, is the reference lateral transfer stress increment. It should be noted that in this formula represents the original ground stress, The method of obtaining is to obtain from the geological report, which is the basis for determining the original ground stress. H is obtained from the difference between the surface elevation and the roadway elevation. The larger H is, the higher the original ground stress is. D is obtained from the width of the goaf in the mining technical drawings. The wider the goaf is, the larger the stress transfer range is. k is obtained through rock strength testing. The harder the rock layer, the smaller k is. Characterizes the coupling effect of the span and depth of the goaf. When D is much smaller than H, it means that the goaf is narrow and the stress increase is weak. When D is much larger than H, it means large-scale mining and the stress increase is significant. The result of this formula is to analyze the stress increment of the overburden load of the tunnel transferred to the side of the tunnel after the formation of the goaf, and evaluate the impact of additional loads on adjacent tunnels when mining equipment is mining.

[0011] It should be noted that, as the preferred technical solution for the analysis method of factors affecting tunnel deformation based on data monitoring, the specific steps of S4 are: obtaining the tunnel surrounding rock stability assessment results and the adjacent tunnel influence assessment results, weighting the tunnel surrounding rock stability assessment value and the adjacent tunnel influence assessment value and adding them together to obtain the tunnel hazard assessment value; comparing the tunnel hazard assessment value with the set tunnel hazard assessment value threshold; if the tunnel hazard assessment value is greater than or equal to the set tunnel hazard assessment value threshold, the tunnel state is judged to be unqualified and an early warning is issued; if the tunnel hazard assessment value is less than the set tunnel hazard assessment value threshold, the tunnel state is judged to be qualified. It should be noted that there may be mutual correlation and influence between various risk factors during tunnel deformation. Weighted summation can comprehensively evaluate different risk factors, comprehensively consider various risks of tunnel deformation, and avoid focusing on a single factor while ignoring other important risk sources that cause tunnel deformation.

[0012] A roadway deformation influencing factor analysis system based on data monitoring is implemented based on the above-mentioned roadway deformation influencing factor analysis method based on data monitoring, and specifically includes a roadway data acquisition module, a roadway stability assessment module, a roadway impact assessment module, and a deformation analysis and early warning module, wherein the roadway data acquisition module is used to obtain mining equipment operation data, support structure status data, and mining roadway status data; The tunnel stability assessment module is used to assess the tunnel surrounding rock stability based on mining equipment operation data and support structure status data; The tunnel impact assessment module is used to assess the impact of adjacent tunnels based on mining tunnel status data; The deformation analysis and early warning module is used to perform a roadway deformation risk assessment based on the roadway surrounding rock stability assessment results and the adjacent roadway impact assessment results, and to provide a roadway deformation risk early warning based on the roadway deformation risk assessment results.

[0013] An electronic device comprises: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the above-mentioned method for analyzing factors affecting tunnel deformation based on data monitoring by calling the computer program stored in the memory.

[0014] A computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the above-mentioned method for analyzing factors affecting tunnel deformation based on data monitoring.

[0015] Compared with the prior art, the beneficial effects of the present invention are: the present invention obtains mining equipment operation data, support structure status data and mining tunnel status data; performs tunnel surrounding rock stability assessment based on mining equipment operation data and support structure status data; performs adjacent tunnel impact assessment based on mining tunnel status data; performs tunnel deformation risk assessment based on tunnel surrounding rock stability assessment results and adjacent tunnel impact assessment results, and performs tunnel deformation risk warning based on tunnel deformation risk assessment results; through tunnel deformation risk warning, potential safety hazards can be discovered in time to avoid accidents such as landslides, equipment failures or support failures; through real-time monitoring of mining equipment and tunnel status, it can accurately determine which areas have unstable factors, thereby reasonably adjusting the mining plan and avoiding waste of resources; through impact assessment of adjacent tunnels, the impact of excessive mining on the surrounding environment can be avoided, thereby reducing damage to the mine ecology, protecting surrounding land and water sources, and achieving sustainable and safe mining of mines. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a schematic diagram of the overall process of the tunnel deformation influencing factors analysis method based on data monitoring in this application.

[0017] Figure 2 This is a schematic flow chart of step S2 of the method for analyzing factors affecting tunnel deformation based on data monitoring in this application.

[0018] Figure 3 This is a schematic diagram of the overall framework of the tunnel deformation influencing factors analysis system based on data monitoring in this application.

[0019] Figure 4 This is a schematic diagram of the process for obtaining the tunnel deformation hazard assessment value based on the tunnel deformation influencing factor analysis method of this application based on data monitoring. DETAILED DESCRIPTION

[0020] In order to better understand the present application, various aspects of the present application will be described in more detail with reference to the accompanying drawings.

[0021] In order to solve the technical problems raised in the background technology, this application provides a preferred embodiment: The specific contents of this embodiment are: like Figure 1 As shown in FIG, the method for analyzing factors affecting roadway deformation based on data monitoring includes the following specific steps: S1. Acquire mining equipment operation data, support structure status data, and mining tunnel status data; In this embodiment, the specific steps of S1 are: S11. Acquire mining equipment operation data through a pressure sensor and an acceleration sensor, wherein the mining equipment operation data includes load data applied by the mining equipment to each collection point on the surrounding rock of the roadway and vibration angular frequency data of the mining equipment; S12. Acquire support structure status data through pressure sensors and a database, wherein the support structure status data includes external force data acting on the support structure at each acquisition point of the tunnel surrounding rock, support structure length data, and cross-sectional area data; S13. Acquire mining tunnel status data from a database, wherein the mining tunnel status data includes average bulk density data of the tunnel surrounding rock, mining depth data, and goaf width data; S14. Storing the collected data in a storage component for use in the analysis process.

[0022] In one implementation of the present invention, the mining equipment operation data is obtained through pressure sensors and acceleration sensors, which are used to analyze the average load status of the mining equipment during the operation cycle and quantify the energy consumption effect of the mining equipment vibration on the tunnel rock mass. The support structure status data is obtained through pressure sensors and a database, which is used to analyze the cumulative deformation of the support structure during the entire mining equipment operation cycle. The mining tunnel status data is obtained through a database, which is used to analyze the stress increment of the tunnel's overburden load transferred to the side of the tunnel after the goaf is formed.

[0023] S2, such as Figure 2 As shown, the tunnel surrounding rock stability assessment is performed based on the mining equipment operation data and support structure status data; In this embodiment, S2 includes the following specific steps: S21, obtaining a dynamic load impact assessment value corresponding to each sampling point in the tunnel surrounding rock based on the load data applied by the mining equipment to each sampling point on the tunnel surrounding rock and the vibration angular frequency data of the mining equipment; In this embodiment, the specific step of S21 is: performing a dynamic load impact assessment based on the load data of each sampling point applied by the mining equipment on the surrounding rock of the roadway and the vibration angular frequency data of the mining equipment, wherein the dynamic load impact assessment calculation formula of each sampling point on the surrounding rock of the roadway is: , where i is the number corresponding to each sampling point on the surrounding rock of the roadway, i is any item from 1 to N, T is the operation cycle of the mining equipment, is the dynamic load data at time t corresponding to the i-th collection point on the surrounding rock of the roadway, is the reference load data corresponding to the i-th collection point on the surrounding rock of the roadway, is the attenuation coefficient of the roadway rock mass, is the vibration angular frequency of the mining equipment during operation, is the critical frequency of the roadway rock mass. It should be noted that in this formula The function of is to express the dynamic force exerted by the mining equipment on each sampling point on the surrounding rock of the roadway during normal operation, which is the basis for calculating the dynamic load impact assessment value; It is the load safety reference value, used to quantify the degree of deviation from the actual load; is the attenuation coefficient of the roadway rock mass, obtained from the core vibration test, which represents the ability of the roadway rock mass to absorb vibration energy. The softer the rock layer, the larger the value. It is the vibration angular frequency of the mining equipment during operation, reflecting the vibration characteristics of the mining equipment during operation. The higher the frequency, the stronger the disturbance to the roadway rock mass. The design significance is to monitor whether the tunnel rock mass and the mining equipment will resonate during operation, which requires key monitoring. The acquisition method is to obtain the rock mass stiffness through acoustic wave detection. In this formula, The part reflects the average load state of the mining equipment during the operation cycle, and eliminates the interference of instantaneous overload or underload through time integration; in this formula Part of it is used to quantify the energy consumption effect of mining equipment vibration on the roadway rock mass; for example, The basis and benefits of this formula are: Changes over time are the basis for calculating the dynamic load impact assessment value. Used to quantify the degree of deviation from the actual load, It is the ability of the tunnel rock mass to absorb vibration energy. Reflects the vibration characteristics of mining equipment during operation, Monitor whether resonance occurs between the tunnel rock mass and the mining equipment during operation. The exponential function is used to describe the attenuation effect of the rock mass on high-frequency vibration. This is in line with physical principles. Reference load data is used as a benchmark to ensure the objectivity and comparability of the evaluation results, providing an accurate basis for subsequent decision-making. This formula can specifically quantify the impact of dynamic loads at different collection points, facilitate the identification of potential danger areas, and consider dynamic load data in the time dimension to make the evaluation results closer to the actual situation and improve the accuracy of the evaluation. By introducing the attenuation coefficient and critical frequency, the attenuation effect of the rock mass on high-frequency vibration is scientifically simulated to avoid the evaluation results deviating from reality.

[0024] S22, obtaining a support structure deformation assessment value corresponding to each sampling point in the tunnel surrounding rock based on the external force data acting on the support structure, the support structure length data, and the cross-sectional area data; In this embodiment, the specific step of S22 is: based on the external force data acting on the support structure at each sampling point of the tunnel surrounding rock, the support structure length data and the cross-sectional area data, the deformation evaluation value of the support structure at each sampling point of the tunnel surrounding rock is calculated as follows: , where T is the operating cycle of mining equipment, is the external force acting on the support structure at the i-th collection point at time t during the operation cycle of the mining equipment, is the length of the support structure corresponding to the i-th collection point, is the cross-sectional area of the support structure corresponding to the i-th collection point, is the elastic modulus of the supporting structure, is the reference average deformation corresponding to the i-th collection point. It should be noted that in this formula The setting is because the deformation of the support structure is caused by external forces, and the magnitude of the external forces will vary at different points in time; The setting is because the length of the support structure is proportional to the deformation it bears, and a long support structure is more susceptible to external forces than a short support structure; The reason for setting is that the cross-sectional area of the support structure determines its ability to resist external forces. The larger the area, the greater the pressure it can withstand. It is an important parameter to measure the stiffness of the support structure material. Materials with high elastic modulus deform less when subjected to external forces, while materials with low elastic modulus deform more when subjected to external forces. It is an important parameter for quantifying the degree of deviation of the support structure deformation; T reflects the cumulative effect of the support structure deformation under load. Considering the time effect can more accurately describe the state of the support structure during the operation cycle of the mining equipment. In this formula, The cumulative deformation of the support structure during the entire mining equipment operation cycle is analyzed by integrating the changes in the external forces acting on the support structure at each sampling point during the mining equipment operation cycle. The basis and benefits of It is the force acting on the support structure, which changes with time and is the basis for evaluating the deformation of the support structure. The cross-sectional area directly affects the rigidity and deformation capacity of the support structure. The elastic modulus of the support structure Describes the stiffness of the material and is an important parameter for evaluating deformation. Used for standardized deformation assessment, it facilitates comparison of deformation at different collection points. This formula comprehensively considers external forces, support structure dimensions, and material properties, enabling comprehensive assessment of support structure deformation. By introducing a reference average deformation, standardized comparisons of deformation at different collection points can be performed, facilitating analysis and decision-making. External force data changes over time, and the formula can reflect the dynamic deformation of the support structure. S23. Obtain the dynamic load influence assessment value and support structure deformation assessment value results corresponding to each sampling point of the tunnel surrounding rock, and obtain the stability assessment value corresponding to each sampling point of the tunnel surrounding rock by weighted addition of the dynamic load influence assessment value and support structure deformation assessment value corresponding to each sampling point of the tunnel surrounding rock. It should be noted that the dynamic load influence assessment value is a characterization of the equivalent dynamic load strength caused by the mining equipment on the tunnel during mining, and the support structure deformation assessment value is a factor for analyzing whether the support structure will cause excessive deformation and affect the safety of the tunnel. Therefore, by comprehensively considering the equivalent dynamic load strength caused by the mining equipment on the tunnel during mining and whether the support structure will cause excessive deformation, the stability corresponding to each sampling point of the tunnel surrounding rock is assessed, thereby improving the accuracy of the stability assessment value. S24. The stability assessment value of the tunnel surrounding rock is obtained by summing up the stability assessment values corresponding to each sampling point and then averaging them. It should be noted that by summing up the stability assessment values corresponding to each sampling point of the tunnel surrounding rock and then averaging them, the stability assessment values corresponding to different sampling points can be comprehensively evaluated, and the stability assessment values corresponding to each sampling point can be fully considered, avoiding focusing on the stability assessment value corresponding to a single sampling point and ignoring the stability assessment values corresponding to other sampling points, thereby improving the accuracy of the stability assessment value of the tunnel surrounding rock.

[0025] S3. Evaluate the impact of adjacent tunnels based on the mining tunnel status; In this embodiment, the specific step of S3 is: based on the average bulk density data of the roadway surrounding rock, the mining depth data, and the goaf width data, the adjacent roadway impact assessment is performed. The calculation formula for the adjacent roadway impact assessment is: ,in is the average bulk density data of the surrounding rock of the roadway, H is the mining depth data, D is the span data of the goaf, k is the stress attenuation index, is the reference lateral transfer stress increment. It should be noted that in this formula represents the original ground stress, The method of obtaining is to obtain from the geological report, which is the basis for determining the original ground stress. H is obtained from the difference between the surface elevation and the roadway elevation. The larger H is, the higher the original ground stress is. D is obtained from the width of the goaf in the mining technical drawings. The wider the goaf is, the larger the stress transfer range is. k is obtained through rock strength testing. The harder the rock layer, the smaller k is. Characterizes the coupling effect between the span and depth of the goaf. When D is much smaller than H, it means the goaf is narrow and the stress increase is weak. When D is much larger than H, it means large-scale mining and the stress increase is significant. The result of this formula is to analyze the stress increment of the overburden load of the roadway after the formation of the goaf and to evaluate the impact of the additional load on the adjacent roadway when the mining equipment is mining. For example, The basis and benefits of the formula Indicates the original ground stress, which is the stress state naturally existing in the stratum and is the basis for evaluation. is the average bulk density of the rock formation surrounding the roadway, reflecting the weight of the rock formation per unit volume, which is crucial for calculating the distribution of ground stress. H represents the depth of mining activities, which directly affects the distribution of ground stress. D represents the span of the goaf, but for the sake of consistency, it can be understood as the key width parameter in the evaluation. The larger it is, the greater the impact on the adjacent roadways may be. k represents the rate at which ground stress decays with distance, reflecting the change law of ground stress at different distances. It represents the increase in lateral stress under specific conditions and is used to correct the assessment results. The formula comprehensively considers multiple geological and engineering parameters, and can more accurately assess the impact of the goaf on adjacent tunnels, ensure the reliability of the assessment results, and reduce adverse effects on surrounding tunnels.

[0026] As attached Figure 4 As shown, S4, based on the tunnel surrounding rock stability assessment results and the adjacent tunnel impact assessment results, the tunnel deformation hazard assessment is performed, and the tunnel deformation hazard warning is issued according to the tunnel deformation hazard assessment results.

[0027] In this embodiment, the specific steps of S4 are: obtaining the tunnel surrounding rock stability assessment results and the adjacent tunnel influence assessment results, weighting the tunnel surrounding rock stability assessment value and the adjacent tunnel influence assessment value and adding them together to obtain the tunnel hazard assessment value; comparing the tunnel hazard assessment value with the set tunnel hazard assessment value threshold. If the tunnel hazard assessment value is greater than or equal to the set tunnel hazard assessment value threshold, the tunnel state is determined to be unqualified and an early warning prompt is issued; if the tunnel hazard assessment value is less than the set tunnel hazard assessment value threshold, the tunnel state is determined to be qualified. It should be noted that there may be mutual correlation and influence between the various risk factors during tunnel deformation. The weighted summation can comprehensively evaluate different risk factors and comprehensively consider the various risks of tunnel deformation, avoiding focusing on a single factor and ignoring other important risk sources that cause tunnel deformation.

[0028] It should be noted here that the setting parameters (such as weights and thresholds, etc.) in this embodiment need to be set by technical personnel in this field based on relevant experiments. The specific experimental method is: obtain mining equipment operation data, support structure status data and mining tunnel status data and substitute them into each step in this embodiment to calculate the tunnel deformation hazard assessment value, obtain the tunnel deformation hazard assessment value, import the tunnel deformation hazard assessment value and the actual tunnel deformation hazard result into the fitting software for continuous fitting, and output the tunnel deformation hazard assessment value that conforms to the set parameters (such as weights and thresholds, etc.) of the actual tunnel deformation hazard result.

[0029] According to the above implementation content, this embodiment has the following advantages over the existing technology: this embodiment obtains mining equipment operation data, support structure status data and mining tunnel status data; performs tunnel surrounding rock stability assessment based on mining equipment operation data and support structure status data; performs adjacent tunnel impact assessment based on mining tunnel status; performs tunnel deformation risk assessment based on tunnel surrounding rock stability assessment results and adjacent tunnel impact assessment results, and performs tunnel deformation risk warning based on tunnel deformation risk assessment results; through tunnel deformation risk warning, potential safety hazards can be discovered in time to avoid accidents such as landslides, equipment failures or support failures. Through real-time monitoring of mining equipment and tunnel status, it is possible to accurately determine which areas have unstable factors, thereby reasonably adjusting the mining plan and avoiding waste of resources. Through impact assessment of adjacent tunnels, the impact of excessive mining on the surrounding environment can be avoided, thereby reducing damage to the mine ecology, protecting surrounding land and water sources, and achieving sustainable and safe mining of mines.

[0030] like Figure 3 As shown, this embodiment also provides a tunnel deformation influencing factor analysis system based on data monitoring, which is implemented based on the above-mentioned tunnel deformation influencing factor analysis method based on data monitoring, and specifically includes a tunnel data acquisition module, a tunnel stability assessment module, a tunnel impact assessment module and a deformation analysis and early warning module, wherein the tunnel data acquisition module is used to obtain mining equipment operation data, support structure status data and mining tunnel status data; The tunnel stability assessment module is used to assess tunnel surrounding rock stability based on mining equipment operation data and support structure status data; The roadway impact assessment module is used to assess the impact of adjacent roadways based on mining roadway status data; The deformation analysis and early warning module is used to evaluate the deformation risk of the roadway based on the stability assessment results of the roadway surrounding rock and the impact assessment results of adjacent roadways, and to provide early warning of the roadway deformation risk based on the roadway deformation risk assessment results.

[0031] The specific steps for each unit module in the data monitoring-based tunnel deformation influencing factor analysis system of the present application to realize the corresponding functions can be referred to the steps in the embodiment of the data monitoring-based tunnel deformation influencing factor analysis method above, and will not be repeated here.

[0032] This embodiment further provides an electronic device, comprising: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the above-mentioned method for analyzing factors affecting tunnel deformation based on data monitoring by calling the computer program stored in the memory.

[0033] The memory can be used to store instructions, programs, codes, code sets, or instruction sets. The memory can include a program storage area and a data storage area. The program storage area can store instructions for implementing an operating system, instructions for at least one function, and instructions for implementing the method for analyzing factors affecting roadway deformation based on data monitoring provided in the above-mentioned embodiment. The data storage area can store data involved in the method for analyzing factors affecting roadway deformation based on data monitoring provided in the above-mentioned embodiment.

[0034] The processor may include one or more processing cores. The processor executes instructions, programs, code sets, or instruction sets stored in memory, accesses data stored in memory, and performs the various functions and processes data of the present application. The processor may be at least one of an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field-programmable gate array (FPGA), a central processing unit (CPU), a controller, a microcontroller, and a microprocessor. It is understood that for different devices, the electronic components used to implement the above-mentioned processor functions may also be other, and the embodiments of the present application are not specifically limited thereto.

[0035] A communication bus may also be included. This communication bus may include a path for transmitting information between the aforementioned components. Examples of communication buses include the PCI (Peripheral Component Interconnect) bus and the EISA (Extended Industry Standard Architecture) bus. Communication buses can be categorized as address buses, data buses, and control buses.

[0036] This embodiment further proposes a computer-readable storage medium storing instructions. When the instructions are executed on a computer, the computer executes the above-mentioned method for analyzing factors affecting tunnel deformation based on data monitoring.

[0037] For example, the computer readable storage medium can be a read-only memory, a random access memory, a read-only CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0038] The above embodiments can be implemented in whole or in part via software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. A computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions according to the embodiments of the present application are fully or partially generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another. For example, computer instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center via a wired network or / and a wireless network. A computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server or data center that contains a collection of one or more available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives.

[0039] The terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0040] The above description is merely a preferred embodiment of the present application and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of application of this application is not limited to technical solutions formed by a specific combination of the aforementioned technical features. It also encompasses other technical solutions formed by any combination of the aforementioned technical features or their equivalents, without departing from the aforementioned application concept. For example, a technical solution formed by replacing the aforementioned features with (but not limited to) technical features with similar functions claimed in this application.

Claims

1. The method for analyzing factors affecting tunnel deformation based on data monitoring is characterized by: include: S1. Acquire mining equipment operation data, support structure status data, and mining tunnel status data; S2. Evaluate the stability of the surrounding rock of the roadway based on the operating data of the mining equipment and the status data of the support structure; S3. Conduct impact assessment on adjacent tunnels based on mining tunnel status data; S4. Conduct a roadway deformation risk assessment based on the roadway surrounding rock stability assessment results and the adjacent roadway impact assessment results, and issue a roadway deformation risk warning based on the roadway deformation risk assessment results.

2. The method for analyzing factors affecting tunnel deformation based on data monitoring according to claim 1, characterized in that: The S2 includes the following specific steps: S21, obtaining a dynamic load impact assessment value corresponding to each sampling point in the tunnel surrounding rock based on the load data applied by the mining equipment to each sampling point on the tunnel surrounding rock and the vibration angular frequency data of the mining equipment; S22, obtaining a support structure deformation assessment value corresponding to each sampling point in the tunnel surrounding rock based on the external force data acting on the support structure, the support structure length data, and the cross-sectional area data at each sampling point in the tunnel surrounding rock; S23, obtaining dynamic load influence assessment values and support structure deformation assessment values corresponding to each sampling point of the tunnel surrounding rock, and obtaining stability assessment values corresponding to each sampling point of the tunnel surrounding rock by weighted addition of the dynamic load influence assessment values and support structure deformation assessment values corresponding to each sampling point; S24. The stability assessment value of the tunnel surrounding rock is obtained by summing and averaging the stability assessment values corresponding to the sampling points of the tunnel surrounding rock.

3. The method for analyzing factors affecting roadway deformation based on data monitoring according to claim 2, characterized in that: The specific step of S21 is: based on the load data of each sampling point applied by the mining equipment on the surrounding rock of the roadway and the vibration angular frequency data of the mining equipment, the dynamic load impact evaluation calculation formula of each sampling point on the surrounding rock of the roadway is: , where i is the number corresponding to each sampling point on the surrounding rock of the roadway, i is any item from 1 to N, T is the operation cycle of the mining equipment, is the dynamic load data at time t corresponding to the i-th collection point on the surrounding rock of the roadway, is the reference load data corresponding to the i-th collection point on the surrounding rock of the roadway, is the attenuation coefficient of the roadway rock mass, is the vibration angular frequency of the mining equipment during operation, is the critical frequency of the roadway rock mass.

4. The method for analyzing factors affecting tunnel deformation based on data monitoring according to claim 3, characterized in that: The specific steps of S22 are: based on the external force data, support structure length data and cross-sectional area data acting on the support structure at each sampling point of the tunnel surrounding rock, the deformation evaluation value of the support structure at each sampling point of the tunnel surrounding rock is calculated as follows: , where T is the operation cycle of mining equipment, is the external force acting on the support structure at the i-th collection point at time t during the operation cycle of the mining equipment, is the length of the support structure corresponding to the i-th collection point, is the cross-sectional area of the support structure corresponding to the i-th collection point, is the elastic modulus of the supporting structure, is the reference average deformation corresponding to the i-th collection point.

5. The method for analyzing factors affecting tunnel deformation based on data monitoring according to claim 4, characterized in that: The specific steps of S3 are: obtaining the impact assessment of adjacent roadways based on the average bulk density data of the roadway surrounding rock, the mining depth data and the goaf width data.

6. The method for analyzing factors affecting tunnel deformation based on data monitoring according to claim 5, characterized in that: The specific steps of S4 are: obtaining the results of the roadway surrounding rock stability assessment and the adjacent roadway influence assessment, weighting the roadway surrounding rock stability assessment value and the adjacent roadway influence assessment value and adding them together to obtain a roadway hazard assessment value; comparing the roadway hazard assessment value with a set roadway hazard assessment value threshold; if the roadway hazard assessment value is greater than or equal to the set roadway hazard assessment value threshold, determining that the roadway state is unqualified and issuing an early warning prompt; If the tunnel hazard assessment value is less than the set tunnel hazard assessment value threshold, the tunnel status is determined to be a qualified status.

7. A system for analyzing factors affecting roadway deformation based on data monitoring, which is implemented based on the method for analyzing factors affecting roadway deformation based on data monitoring according to any one of claims 1 to 6, and is characterized in that: It specifically includes a tunnel data acquisition module, a tunnel stability assessment module, a tunnel impact assessment module and a deformation analysis and early warning module, wherein the tunnel data acquisition module is used to obtain mining equipment operation data, support structure status data and mining tunnel status data; The tunnel stability assessment module is used to assess the tunnel surrounding rock stability based on mining equipment operation data and support structure status data; The tunnel impact assessment module is used to assess the impact of adjacent tunnels based on mining tunnel status data; The deformation analysis and early warning module is used to perform a roadway deformation risk assessment based on the roadway surrounding rock stability assessment results and the adjacent roadway impact assessment results, and to provide a roadway deformation risk early warning based on the roadway deformation risk assessment results.

8. An electronic device comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; It is characterized in that the processor executes the method for analyzing factors affecting tunnel deformation based on data monitoring as described in any one of claims 1 to 6 by calling the computer program stored in the memory.

9. A computer-readable storage medium, characterized in that Instructions are stored, and when the instructions are run on a computer, the computer is caused to execute the method for analyzing factors affecting tunnel deformation based on data monitoring as described in any one of claims 1 to 6.

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