Roadway impact risk evaluation method, device and equipment

Abstract

The invention relates to a roadway impact risk evaluation method, device and equipment. The method comprises the following steps: obtaining an evaluation value of each primary critical index of a roadway to be evaluated; the primary critical index is used for representing the surrounding rock mechanical property, the roadway support condition and the roadway size of the roadway to be evaluated; determining a weight matrix based on an AHP-entropy weight method and the evaluation value; inputting the evaluation value and the weight matrix into an evaluation model constructed based on an approximate ideal solution sorting method for calculation, and determining a first approximate matrix; performing product operation on the weight matrix and the first close matrix to obtain an evaluation matrix; and evaluating the danger level of the to-be-evaluated roadway by using the evaluation matrix. By adopting the method, the surrounding rock mechanical property of the to-be-evaluated roadway, the roadway support condition and the roadway size are considered, the AHP and entropy weight method combined weighting is combined, the comprehensive evaluation model is established by depending on the approximate ideal solution sorting method, and finally the evaluation matrix which can be directly used for evaluating the roadway impact risk level is given.

Description

Technical Field

[0001] The present application relates to the field of coal mine safety technology, and in particular to a tunnel impact hazard assessment method, a tunnel impact hazard assessment device and a computer device. Background Art

[0002] According to the mineral resource report, coal resources buried at a depth of more than 1,000 meters account for more than 50%. With the continuous increase in coal mining intensity and mining depth, ground stress increases nonlinearly, and deep coal and rock are more likely to induce rock burst disasters. According to statistics, more than 90% of rock bursts occur in tunnels. Severe impact dynamic loads often cause the failure of tunnel support equipment, resulting in instability and damage to the tunnel. Therefore, tunnel impact hazard assessment has become an important part of safe coal mining.

[0003] In recent years, the research on rock burst factors has focused on critical stress. However, whether rock burst occurs or not, only considering and comparing critical stress cannot guarantee the accuracy of the evaluation results of tunnel rock burst hazard. In order to make the evaluation results closer to the actual dangerous situation, it is urgent to provide a new method for evaluating the danger of tunnel rock burst, so as to provide a theoretical basis for taking corresponding protective measures and support design in tunnels to reduce the danger of rock burst. Summary of the invention

[0004] Based on this, it is necessary to provide a tunnel impact hazard assessment method, a tunnel impact hazard assessment device and a computer device to address the above technical problems.

[0005] In the first aspect, the present application provides a method for evaluating the impact hazard of a tunnel, the method comprising: respectively obtaining evaluation values ​​of each first-level critical indicator of the tunnel to be evaluated; the each first-level critical indicator is used to characterize the surrounding rock mechanical properties, tunnel support conditions and tunnel dimensions of the tunnel to be evaluated; based on the AHP-entropy weight method and the evaluation values, determining the combined weights of each first-level critical indicator to obtain a weight matrix; inputting the evaluation values ​​and the weight matrix into an evaluation model constructed based on the approximate ideal solution sorting method for calculation, determining the degree of proximity of each first-level critical indicator to the positive ideal solution, and forming a first proximity matrix; performing a product operation on the weight matrix and the first proximity matrix to obtain an evaluation matrix; and using the evaluation matrix to judge the hazard level of the tunnel to be evaluated.

[0006] In one embodiment, the first-level critical indicators include critical softening radius, critical convergence displacement, critical load, critical energy and critical mining depth.

[0007] In one embodiment, the step of respectively obtaining the evaluation values ​​of each first-level critical indicator of the lane to be evaluated includes: respectively obtaining the values ​​of the second-level critical indicators corresponding to each first-level critical indicator of the lane to be evaluated; and calculating the evaluation value of each first-level critical indicator according to the values ​​of the second-level critical indicators.

[0008] In one embodiment, the secondary critical indicators corresponding to the critical softening radius are uniaxial compressive strength, deformation modulus index, elastic modulus, damage internal friction angle, softening modulus, residual modulus, residual strength coefficient, support stress and tunnel radius; the secondary critical indicators corresponding to the critical convergence displacement are uniaxial compressive strength, deformation modulus index, elastic modulus, damage internal friction angle, softening modulus, residual modulus, residual strength coefficient, support stress and tunnel radius; the secondary critical indicators corresponding to the critical load are uniaxial compressive strength, deformation modulus index, damage internal friction angle, residual strength coefficient and support stress; the secondary critical indicators corresponding to the critical energy are uniaxial compressive strength, deformation modulus index, elastic modulus, damage internal friction angle, softening modulus, residual modulus, residual strength coefficient, Poisson's ratio, support stress and tunnel radius; the secondary critical indicators corresponding to the critical mining depth are uniaxial compressive strength, deformation modulus index, damage internal friction angle, residual strength coefficient, rock bulk density and support stress.

[0009] In one embodiment, the hazard levels are divided into no impact hazard, weak impact hazard, medium impact hazard and strong impact hazard; the evaluation value of the critical softening radius under no impact hazard is not greater than 4m, the evaluation value of the critical convergence displacement is not greater than 20mm, the evaluation value of the critical load is not greater than 10Pa, and the evaluation value of the critical energy is not greater than 10 4 J, the evaluation value of the critical mining depth is not greater than 400m; the evaluation value of the critical softening radius of the weak impact hazard is greater than 4m and not greater than 5m, the evaluation value of the critical convergence displacement is greater than 20mm and not greater than 30mm, the evaluation value of the critical load is greater than 10Pa and not greater than 14Pa, and the evaluation value of the critical energy is greater than 10 4 J and not more than 10 5 J, the evaluation value of the critical mining depth is greater than 400m and not greater than 600m; the evaluation value of the critical softening radius of the medium impact risk is greater than 5m and not greater than 6m, the evaluation value of the critical convergence displacement is greater than 30mm and not greater than 40mm, the evaluation value of the critical load is greater than 14Pa and not greater than 18Pa, and the evaluation value of the critical energy is greater than 10 5 J and not more than 10 6J, the evaluation value of the critical mining depth is greater than 600m and not greater than 800m; the evaluation value of the critical softening radius of the strong impact hazard is greater than 6m, the evaluation value of the critical convergence displacement is greater than 40mm, the evaluation value of the critical load is greater than 18Pa, and the evaluation value of the critical energy is greater than 10 6 J, the evaluation value of the critical mining depth is greater than 800m.

[0010] In one embodiment, the step of using the evaluation matrix to judge the danger level of the lane to be evaluated includes: using the first four elements in the evaluation matrix as critical reference values ​​of no impact danger, weak impact danger, medium impact danger and strong impact danger respectively, and using the fifth element in the evaluation matrix as the comparison value of the lane to be evaluated; comparing the comparison value with the critical reference value; if the comparison value is less than the critical reference value of no impact danger, then the danger level of the lane to be evaluated is determined to be no impact danger; if the comparison value is between the critical reference values ​​of no impact danger and weak impact danger, then the danger level of the lane to be evaluated is determined to be weak impact danger; if the comparison value is between the critical reference values ​​of weak impact danger and strong impact danger, then the danger level of the lane to be evaluated is determined to be medium impact danger; if the comparison value is greater than the critical reference value of strong impact danger, then the danger level of the lane to be evaluated is determined to be strong impact danger.

[0011] In one embodiment, the step of determining the combined weight of each first-level critical indicator based on the AHP-entropy weight method and the evaluation value includes: determining the subjective weight of each first-level critical indicator based on the hierarchical analysis method; determining the objective weight of each first-level critical indicator based on the entropy weight method and the evaluation value; and combining the subjective weight and the objective weight using the Euclidean distance function to obtain the combined weight of each first-level critical indicator.

[0012] In one embodiment, the evaluation value and the weight matrix are input into the evaluation model for calculation to determine the closeness of each first-level critical indicator to the positive ideal solution, including: generating a weighted decision matrix according to the evaluation value and the weight matrix; determining the positive and negative ideal solutions of each first-level critical indicator based on the weighted decision matrix; respectively calculating the distance from each first-level critical indicator to the positive and negative ideal solutions, and calculating the closeness of each first-level critical indicator to the positive ideal solution based on the distance.

[0013] In the second aspect, the present application also provides a tunnel impact hazard assessment device, which includes: an acquisition module, used to respectively obtain the evaluation values ​​of each first-level critical indicator of the tunnel to be evaluated; a weight module, used to determine the combined weights of each first-level critical indicator based on the AHP-entropy weight method and the evaluation values, and obtain a weight matrix; a calculation module, used to input the evaluation values ​​and the weight matrix into an evaluation model constructed based on the approximate ideal solution sorting method for calculation, determine the degree of proximity of each first-level critical indicator to the positive ideal solution, and form a first proximity matrix; perform a product operation on the weight matrix and the first proximity matrix to obtain an evaluation matrix; an evaluation module, used to use the evaluation matrix to judge the hazard level of the tunnel to be evaluated.

[0014] In a third aspect, an embodiment of the present application provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of a method for evaluating the hazard of tunnel impact when executing the computer program.

[0015] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of a method for evaluating the hazard of tunnel impact are implemented.

[0016] One of the above technical solutions has the following advantages or beneficial effects: The present application proposes a method for evaluating the impact hazard of a tunnel based on critical indicators. The first-level critical indicators in the critical indicators can be used to characterize the mechanical properties of the surrounding rock, the tunnel support conditions and the tunnel dimensions of the tunnel to be evaluated, and can then be used as an important indicator and criterion for the occurrence of rock burst when the tunnel to be evaluated is disturbed in a specific ground stress environment. At the same time, the AHP (hierarchy analysis method) and the entropy weight method are combined for weighting, and a comprehensive evaluation model is established by relying on the approximate ideal solution sorting method. Finally, an evaluation matrix that can be directly used to evaluate the tunnel impact hazard level is given, which provides a theoretical basis for taking corresponding protective measures and support design to reduce the risk of rock burst. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A schematic diagram of a process flow of a tunnel impact hazard assessment method in one embodiment of the present application;

[0018] Figure 2 A schematic diagram of a flow chart of a tunnel impact hazard assessment method in another embodiment of the present application;

[0019] Figure 3 A schematic diagram of a process for verifying a tunnel impact hazard assessment method in an embodiment of the present application using a comprehensive index method;

[0020] Figure 4 This is a structural block diagram of a tunnel impact hazard assessment device in one embodiment of the present application;

[0021] Figure 5 This is a diagram of the internal structure of a computer device in one embodiment of the present application. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0023] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0024] Tunnels are various passages drilled between the surface and the ore body, mainly used for ore transportation, ventilation, drainage, pedestrians and various necessary preparatory projects for metallurgical equipment to mine ore.

[0025] Hazard assessment refers to the process of evaluating the degree of damage to a system, equipment or structure when subjected to external disturbances. The degree of danger of rock burst in coal rock mass is defined as rock burst hazard, which depends on multiple factors, including geological conditions, working face parameters, support measures, etc.

[0026] The tunnel impact hazard assessment method provided in this application is as follows: Figure 1 As shown, in one embodiment, the following steps may be included:

[0027] S110, respectively obtaining evaluation values ​​of each first-level critical index of the roadway to be evaluated; each first-level critical index is used to characterize the surrounding rock mechanical properties, roadway support conditions and roadway dimensions of the roadway to be evaluated.

[0028] Among them, the mechanical properties of surrounding rock mainly include hardness, firmness, stability, agglomeration, oxidizability and spontaneous combustion, water content, crushing and swelling, natural angle of repose, etc. These properties jointly determine the application and stability of surrounding rock in engineering.

[0029] The purpose of tunnel support is to maintain the stability of the tunnel surrounding rock, prevent deformation and damage of the surrounding rock, and ensure that the tunnel maintains the necessary space during use; it can further ease and reduce the movement of the surrounding rock, prevent excessive reduction of the tunnel cross-section, and avoid the fall of scattered and damaged surrounding rock.

[0030] The tunnel dimensions mainly include net width, net height and cross-sectional dimensions. The net width of the tunnel refers to the horizontal distance between the inner walls on both sides of the tunnel or the exposed length ends of the anchors. The net height refers to the height from the ballast surface or floor to the top beam or top shotcrete surface, the exposed length ends of the anchors. The cross-sectional dimensions are the lengths of the tunnel in the horizontal and vertical directions, including the wall height and arch height.

[0031] Specifically, the evaluation values ​​of each first-level critical index of the roadway to be evaluated can be obtained in a variety of ways, for example, by searching for measured data and related information on the working face, or by theoretical calculation and data analysis.

[0032] S120, based on the AHP-entropy weight method and the evaluation value, determine the combined weights of the first-level critical indicators to obtain a weight matrix.

[0033] AHP, the full name of which is Analytic Hierarchy Process, means analytic hierarchy process. The analytic hierarchy process (AHP) is one of the subjective weighting methods. It is applicable to system problems with complex hierarchical structures and multiple indicators, so as to determine the subjective weights of indicators at all levels. The analytic hierarchy process combines qualitative analysis and quantitative calculation. By combining quantifiable standards with difficult-to-quantify standards, it provides a corresponding evaluation system for multi-criteria decision-making. The analytic hierarchy process is widely used in many fields. According to the core objectives of the evaluation, users organize multi-indicator factors from the bottom element layer to the top target layer in an orderly manner to construct a hierarchical structural model. The judgment matrix is ​​established by pairwise comparison (generally, the maximum and minimum values ​​are removed, and then the average value is calculated to obtain the final judgment matrix). The relative size information of the numbers is used to calculate the weights to obtain the scores of the importance of each indicator. The higher the score, the greater the indicator weight. Finally, the importance of each factor is calculated.

[0034] The Entropy Weight Method (EWM) is an objective weighting method used for comprehensive evaluation of multiple indicators. The weights of indicators are determined by calculating information entropy, which is not affected by subjective factors. The Entropy Weight Method is an objective method to determine weights based on the basic principles of information theory. Information is regarded as an indicator of the orderliness of the system, while entropy represents a measure of the disorder of the system. When the information entropy of an indicator is low, it means that the indicator provides more information, so it plays a more important role in the comprehensive evaluation and has a greater corresponding weight.

[0035] By combining the analytic hierarchy process (AHP) and the entropy weight method, a calculation method of combined weight (CW for short) is proposed to better integrate subjective and objective issues and avoid the bias caused by a single weighting method.

[0036] S130, input the evaluation value and the weight matrix into the evaluation model constructed based on the approximate ideal solution sorting method for calculation, determine the proximity of each first-level critical indicator to the positive ideal solution, and form a first approximation matrix.

[0037] The TOPSIS method is a multi-attribute decision analysis method that ranks multiple solutions by detecting the evaluation object and the optimal solution. The basic idea of ​​the TOPSIS method is to define the positive ideal solution and negative ideal solution of the decision problem, and then rank the evaluation object according to the degree of proximity to the positive ideal solution to find the optimal solution. Generally, the specific steps of the TOPSIS method are as follows: dimensionless evaluation matrix: dimensionless processing of the original data matrix to eliminate the influence of different dimensions. Determine the positive and negative ideal solutions: determine the positive ideal solution (the best value of each attribute) and the negative ideal solution (the worst value of each attribute) based on the dimensionless data. Calculate the distance from each evaluation object to the positive and negative ideal solutions: use the Euclidean distance formula to calculate the distance from each evaluation object to the positive and negative ideal solutions. Calculate the relative proximity or relative closeness value (i.e. the degree of proximity mentioned above) of each evaluation object: calculate the relative proximity of each evaluation object to the positive ideal solution based on the distance. Sorting: sort the evaluation objects according to the relative proximity, and the solution with high proximity is the best.

[0038] S140, performing a product operation on the weight matrix and the first approximation matrix to obtain an evaluation matrix.

[0039] S150, using the evaluation matrix to judge the danger level of the lane to be evaluated.

[0040] It should be noted that the execution subject of the steps in the above embodiments can be a computer device. In the tunnel impact hazard evaluation method of the above embodiment, the first-level critical index in the critical index can be used to characterize the surrounding rock mechanical properties, tunnel support conditions and tunnel dimensions of the tunnel to be evaluated, and then can be used as an important indicator and criterion for the occurrence of rock burst in the tunnel to be evaluated under a specific ground stress environment. At the same time, combined with AHP (hierarchy analysis method) and entropy weight method, a comprehensive evaluation model is established by relying on the approximate ideal solution sorting method, and finally an evaluation matrix that can be directly used to evaluate the tunnel impact hazard level is given, which provides a theoretical basis for taking corresponding protective measures and support design to reduce the risk of rock burst.

[0041] In one embodiment, each primary critical indicator includes a critical softening radius, a critical convergence displacement, a critical load, a critical energy and a critical mining depth.

[0042] Regarding the critical softening radius: the occurrence of rock burst is the result of the instability of the coal-rock deformation system, and the damage caused by rock burst is the result of the elastic zone in the coal-rock deformation system releasing its stored elastic energy after the instability. According to the rock burst disturbance response instability theory, the coal-rock deformation system after instability can be divided into two regions. The first region is the elastic zone in the coal-rock deformation system. The elastic zone releases its stored elastic energy, which leads to the destruction of rock burst. Therefore, the elastic zone of the coal-rock deformation system can be called the power zone; the second region is the plastic softening zone in the coal-rock deformation system, also known as the resistance zone. The energy released by the elastic zone is consumed in the softening zone of the coal-rock deformation system, which plays a role in preventing deeper damage. The size of the softening zone can be obtained by the drill cuttings method, and the peak position of the drill cuttings is the radius of the softening zone. The softening zone of the coal-rock deformation system when rock burst occurs is called the critical softening zone. The radius of the critical softening zone indirectly reflects the peak position of the support pressure and the size of the critical softening zone. The farther the peak position of the support pressure is from the free surface, the larger the critical softening zone is and the smaller the risk of rock burst is. The risk of rock burst can be judged or predicted based on the radius of the softening zone.

[0043] Regarding the critical convergence displacement: before the tunnel is excavated, the rock mass is in and maintains a state of stress equilibrium; as the excavation proceeds, the surrounding rock adjacent to the tunnel will experience two stages: unloading rebound and stress redistribution, and the stress state of the surrounding rock will also change from three-dimensional to two-dimensional. In this process, the rock mass on the free surface will deform, slip, fracture, or even fall off. By monitoring the convergence of the tunnel, the characteristics of the surrounding rock deformation are mastered, and then its collapse mode is studied, which provides a theoretical basis for tunnel design and support parameters, thereby improving the quality of tunnel support, reducing the tunnel disrepair rate, and ensuring safe production during the entire mining process. The critical convergence displacement is the amount of deformation of each point around the tunnel surrounding rock tending to the center. It is an important parameter indicator for judging the dynamic changes of surrounding rock deformation, and thus judging the stability of the surrounding rock. According to the tunnel convergence monitoring data, the actual convergence displacement is obtained. If the actual convergence displacement is close to the critical convergence displacement, it means that the system is in danger of rock burst. At this time, if there is a disturbance, the actual convergence displacement may reach the critical convergence displacement and rock burst may occur. The larger the critical convergence displacement, the smaller the risk of rock burst. The risk of rock burst can be judged or predicted based on the critical convergence displacement.

[0044] Regarding the critical load: the load corresponding to the unstable equilibrium point of the tunnel system is called the critical load. The critical load is an important indicator to characterize the rock burst caused by the disturbance of the tunnel in a specific geostress environment, and it is also the theoretical basis of stress control theory in the rock burst prevention and control theory. The critical load reflects the comprehensive intrinsic properties of the surrounding rock structure that cause rock burst. The closer the rock stress is to this critical value, the greater the risk of rock burst. Exploring the influencing factors of rock burst in the tunnel is a key issue in rock burst prevention and control. Based on the mechanical and geometric properties of the coal rock structure, the theoretical solution of the critical load is calculated. When the external load reaches the critical load, rock burst will occur in the tunnel. The larger the critical load, the smaller the risk of rock burst. According to the critical load, the risk of rock burst can be judged or predicted.

[0045] Regarding critical energy: obvious energy dissipation characteristics will appear in the process of rock burst formation. From a macroscopic perspective, the system composed of coal and surrounding rock is in an open state. Under the influence of tunnel excavation or coal seam mining, the energy in the "coal surrounding rock" system is gradually released or suddenly released. The former shows rheological phenomena, and the latter shows rock burst. In addition, multiple energy dissipation processes are carried out simultaneously inside the system, which in turn drives the entire system to develop into a non-equilibrium nonlinear region. From a microscopic perspective, under the influence of external disturbance stress fields, the microscopic defects inside coal and rock materials will gradually evolve from a disordered state to an ordered state, and eventually form macroscopic cracks extending in a specific direction. The expansion of these cracks eventually leads to the instability and destruction of coal and rock materials, and the microscopic elements of coal and rock also show the characteristics of a dissipative structure. Therefore, under the influence of external mining disturbances, the concentration of stress or strain energy leads to an increase in the structural free energy of the system, so that the system reaches a critical stable state. At the macro level, it manifests as the spalling of the coal wall, the stick-slip movement between the coal seam and the roof or floor, etc.; at the micro level, this state is manifested as the convergence, nucleation and stable expansion of cracks inside the coal rock. The excavation of the tunnel drives the overall energy of some areas of the coal-rock system to increase, accompanied by the increase in the amplitude of energy change. When the energy change amplitude of these areas is greater than the threshold of the system's dynamic instability, it will lead to the occurrence of impact instability, and finally the system will jump to another new stable and orderly state. Affected by the far-field stress, the area near the tunnel surface will experience stress concentration. When the concentrated stress value exceeds the peak strength of the coal body, the coal body will be destroyed to form a softening zone, and the surrounding rock around the softening zone is still in the elastic zone and has not yet been destroyed. As the far-field stress increases, the tunnel surrounding rock system is in a critical stable equilibrium state. At this time, if there is a disturbance, the tunnel surrounding rock deformation system will become unstable. When rock burst occurs, the energy stored in the elastic zone will be released rapidly: part of the energy is used to destroy the coal body in the softening zone, and the remaining energy is released in the form of rock burst, which manifests as a dynamic phenomenon. According to the mechanical and geometric properties of coal rock mass structure, the theoretical solution of critical energy is calculated. When the energy stored in the elastic zone reaches the critical energy, rock burst will occur in the tunnel. The greater the critical energy, the smaller the risk of rock burst. The energy stored in the elastic zone under the critical state is calculated to judge or predict the risk of rock burst, and the magnitude of rock burst is estimated.

[0046] Regarding the critical mining depth: there is a critical mining depth for rock burst mines. When the mining depth is less than this, rock burst does not occur or occurs less frequently; when the mining depth is greater than this, rock burst will occur frequently. Therefore, the critical mining depth is used as a critical indicator of the rock burst area. According to the mechanical and geometric properties of the coal rock structure, the theoretical solution of the critical mining depth is calculated. The greater the critical mining depth, the smaller the risk of rock burst. According to the critical mining depth, the risk of rock burst is judged or predicted.

[0047] In one embodiment, S110 specifically includes: respectively obtaining the value of the second-level critical indicator corresponding to each first-level critical indicator of the lane to be evaluated; and calculating the evaluation value of each first-level critical indicator according to the value of the second-level critical indicator.

[0048] In one embodiment, the secondary critical indicators corresponding to the critical softening radius are uniaxial compressive strength, deformation modulus index, elastic modulus, damage internal friction angle, softening modulus, residual modulus, residual strength coefficient, support stress and tunnel radius; the secondary critical indicators corresponding to the critical convergence displacement are uniaxial compressive strength, deformation modulus index, elastic modulus, damage internal friction angle, softening modulus, residual modulus, residual strength coefficient, support stress and tunnel radius; the secondary critical indicators corresponding to the critical load are uniaxial compressive strength, deformation modulus index, damage internal friction angle, residual strength coefficient and support stress; the secondary critical indicators corresponding to the critical energy are uniaxial compressive strength, deformation modulus index, elastic modulus, damage internal friction angle, softening modulus, residual modulus, residual strength coefficient, Poisson's ratio, support stress and tunnel radius; the secondary critical indicators corresponding to the critical mining depth are uniaxial compressive strength, deformation modulus index, damage internal friction angle, residual strength coefficient, rock bulk density and support stress.

[0049] In this embodiment, through theoretical derivation and analysis, the critical softening radius can be obtained by the following formula:

[0050]

[0051] At this time, the critical softening radius ρ cr and the tunnel radius a, uniaxial compressive strength σ c , softening modulus λ s , residual modulus λ f , elastic modulus E, internal friction angle of damaged coal rock Coal rock residual strength coefficient ξ, deformation modulus index K and support stress P s When the geometric dimensions of the tunnel, the support stress and the mechanical properties of the surrounding rock are given, the critical softening radius ρ can be calculated by formula (100): cr , determine the plastic softening range of the tunnel.

[0052] At the same time, the critical convergence displacement can be obtained by the following formula:

[0053]

[0054] in,

[0055] It can be seen that the critical convergence displacement u cr and the tunnel radius a, uniaxial compressive strength σ c , softening modulus λs , residual modulus λ f , elastic modulus E, internal friction angle of damaged coal rock Coal rock residual strength coefficient ξ, deformation modulus index K and support stress P s When the geometric dimensions of the tunnel, the support stress and the mechanical properties of the surrounding rock are given, the critical convergence displacement u can be calculated by equations (200) and (300): cr .

[0056] At the same time, the critical load can be obtained by the following formula:

[0057]

[0058] At this time, the critical load P cr and uniaxial compressive strength σ c , internal friction angle of damaged coal rock Coal rock residual strength coefficient ξ, deformation modulus index K and support stress P s When the support stress and the mechanical properties of the surrounding rock are given, the critical load P can be calculated by formula (400): cr , determine the critical value of tunnel instability.

[0059] At the same time, the critical energy can be obtained by the following formula:

[0060]

[0061] At this time, the critical energy Π cr and the tunnel radius a, uniaxial compressive strength σ c , softening modulus λ s , residual modulus λ f , Poisson's ratio v, elastic modulus E, internal friction angle of damaged coal rock Coal rock residual strength coefficient ξ, deformation modulus index K, support stress P s and the critical load P cr When the geometric dimensions of the tunnel, the support stress and the mechanical properties of the surrounding rock are given, the theoretical solution of the critical energy can be calculated by equation (500): cr , determine the critical value of tunnel instability.

[0062] At the same time, the critical mining depth can be obtained by the following formula:

[0063]

[0064] At this time, the critical mining depth H cr The rock bulk density γ and uniaxial compressive strength σ c , internal friction angle of damaged coal rock Coal rock residual strength coefficient ξ, deformation modulus index K and support stress P sWhen the support stress and the mechanical properties of the surrounding rock are given, the critical mining depth H can be calculated by formula (600): cr , determine the critical value of mining depth.

[0065] In one embodiment, the hazard levels are divided into no impact hazard, weak impact hazard, medium impact hazard and strong impact hazard; the evaluation value of the critical softening radius under no impact hazard is not greater than 4m, the evaluation value of the critical convergence displacement is not greater than 20mm, the evaluation value of the critical load is not greater than 10Pa, and the evaluation value of the critical energy is not greater than 10 4 The evaluation value of critical mining depth is not more than 400m; the evaluation value of critical softening radius of weak impact hazard is greater than 4m and less than 5m, the evaluation value of critical convergence displacement is greater than 20mm and less than 30mm, the evaluation value of critical load is greater than 10Pa and less than 14Pa, and the evaluation value of critical energy is greater than 10 4 J and not more than 10 5 J, the evaluation value of the critical mining depth is greater than 400m and less than 600m; the evaluation value of the critical softening radius of medium impact risk is greater than 5m and less than 6m, the evaluation value of the critical convergence displacement is greater than 30mm and less than 40mm, the evaluation value of the critical load is greater than 14Pa and less than 18Pa, and the evaluation value of the critical energy is greater than 10 5 J and not more than 10 6 J, the evaluation value of the critical mining depth is greater than 600m and not greater than 800m; the evaluation value of the critical softening radius of strong impact danger is greater than 6m, the evaluation value of the critical convergence displacement is greater than 40mm, the evaluation value of the critical load is greater than 18Pa, and the evaluation value of the critical energy is greater than 10 6 J, the evaluation value of critical mining depth is greater than 800m.

[0066] In this embodiment, the rock burst level evaluation criteria system established can be specifically referred to in the following table (for example, 4 to 5 in the table can be understood as greater than 4 and not greater than 5, and the same is true for other ranges, which will not be repeated here):

[0067]

[0068] Among them, B1, B2, B3, B4, and B5 represent the critical softening radius, critical load, critical convergence displacement, critical energy, and critical mining depth, respectively, and Q0, Q1, Q2, and Q3 correspond to the reference values ​​of no impact hazard, weak impact hazard, medium impact hazard, and strong impact hazard, respectively.

[0069] In one embodiment, S150 specifically includes: using the first four elements in the evaluation matrix as critical reference values ​​of no impact hazard, weak impact hazard, medium impact hazard and strong impact hazard respectively, and using the fifth element in the evaluation matrix as the comparison value of the lane to be evaluated; comparing the comparison value with the critical reference value; if the comparison value is less than the critical reference value of no impact hazard, then the hazard level of the lane to be evaluated is determined to be no impact hazard; if the comparison value is between the critical reference values ​​of no impact hazard and weak impact hazard, then the hazard level of the lane to be evaluated is determined to be weak impact hazard; if the comparison value is between the critical reference values ​​of weak impact hazard and strong impact hazard, then the hazard level of the lane to be evaluated is determined to be medium impact hazard; if the comparison value is greater than the critical reference value of strong impact hazard, then the hazard level of the lane to be evaluated is determined to be strong impact hazard.

[0070] In this embodiment, the evaluation matrix can be in the form of: Q = {Q0, Q1, Q2, Q3, Q}, the rock burst evaluation data Q to be measured is input into the rock burst grade evaluation index system, if the obtained Q < Q0, it is determined that there is no rock burst; if Q∈(Q0, Q1), it is determined that there is weak rock burst; if Q∈(Q1, Q3), it is determined that there is moderate rock burst; if Q>Q3, it is determined that there is strong rock burst.

[0071] In one embodiment, S120 specifically includes: determining the subjective weight of each first-level critical indicator based on the hierarchical analysis method; determining the objective weight of each first-level critical indicator based on the entropy weight method and the evaluation value; and combining the subjective weight and the objective weight using the Euclidean distance function to obtain the combined weight of each first-level critical indicator.

[0072] In one embodiment, S130 specifically includes: generating a weighted decision matrix according to the evaluation value and the weight matrix; determining the positive and negative ideal solutions of each first-level critical indicator based on the weighted decision matrix; respectively calculating the distance from each first-level critical indicator to the positive and negative ideal solutions, and calculating the degree of closeness of each first-level critical indicator to the positive ideal solution according to the distance.

[0073] This application proposes a tunnel impact hazard evaluation method based on critical indicators, and proposes critical indicators of rock burst pressure, including critical softening radius, critical convergence displacement, critical load, critical energy and critical mining depth, as important indicators and criteria for characterizing the occurrence of rock burst pressure when a tunnel is disturbed in a specific geostress environment. A combined weight (CW-TOPSIS) comprehensive evaluation model is established by combining the analytic hierarchy process (AHP) and the entropy weight method, and finally an evaluation criterion system that can be directly used to evaluate the tunnel impact hazard level is given, which provides a theoretical basis for taking corresponding protective measures and support design to reduce the risk of rock burst pressure.

[0074] like Figure 2As shown, a specific implementation of the present application is that the steps of the tunnel impact hazard assessment method based on critical indicators are:

[0075] Firstly, the critical index of rock burst in tunnel is selected, and the subjective weight and objective weight of the index are calculated respectively to obtain the combined weight. Secondly, the rock burst grade evaluation criterion system is established according to different critical values. The weighted decision matrix Z and the relative close value matrix F are calculated in turn by using the comprehensive evaluation model of rock burst hazard, and the comprehensive evaluation model formula Q = W × F is calculated.

[0076] Finally, a comprehensive evaluation space Q for rock burst hazard is constructed, and rock burst hazard is divided into four evaluation levels. The hazard levels are ranked based on the evaluation criteria system to obtain the rock burst hazard level of the tunnel to be evaluated.

[0077] The specific steps include:

[0078] Step 1: Determine the critical index of tunnel impact hazard

[0079] The various principles of the comprehensive evaluation model of rock burst hazard in tunnels are established, and the three-layer structure of the comprehensive evaluation model is determined. Among them, the comprehensive evaluation of rock burst hazard is the target layer, and the critical indicators are used to determine the rock burst hazard of tunnels. The first-level evaluation indicators are determined as follows: critical softening radius, critical load, critical convergence displacement, critical energy and critical mining depth. Each first-level indicator is further divided into second-level indicators, and the second-level indicators involve a total of 11 parameters, including 9 surrounding rock properties (uniaxial compressive strength, deformation modulus index, elastic modulus, damage internal friction angle, softening modulus, residual modulus, residual strength coefficient, Poisson's ratio, rock bulk density), support stress and tunnel radius.

[0080] Step 2: Calculate subjective weights using AHP

[0081] Organize the multi-index factors from the bottom element layer to the top target layer in an orderly manner to build a hierarchical structural model. Use the pairwise comparison method to establish a judgment matrix (generally remove the maximum and minimum values, and then calculate the average value to get the final judgment matrix), use the relative size information of the numbers to calculate the weight, and get the score of the importance of each indicator. The higher the score, the greater the indicator weight, and finally calculate the importance of each factor.

[0082] Each data A in the judgment matrix represents the importance of i compared with index j. The element a in the judgment matrix A ij It is composed of the results of comparing two indicators, each element is greater than zero, and a ij *a ji=1, when i=j, the two indicators are the same, so they are equally important and are recorded as 1, so the diagonal elements of the judgment matrix are 1. That is, the importance of the indicator is determined by comparing the factor layer indicators with the higher-level indicator belonging ranges one by one:

[0083]

[0084] Find the maximum eigenvalue λ of the judgment matrix A max And its corresponding eigenvector; then normalize the obtained eigenvector to get the required weight.

[0085] The calculation results are checked for consistency to ensure that the weights obtained are reasonable and reliable. Step 1: Calculate the consistency index Step 2: Find the corresponding average random consistency index; Step 3: Calculate the consistency ratio If CR < 0.1, the consistency of the judgment matrix can be considered acceptable, otherwise the judgment matrix needs to be modified.

[0086] The relative importance of each indicator in the comprehensive evaluation model of rock burst hazard is compared pairwise, and the indicator weights are processed and classified to construct the corresponding judgment matrix.

[0087] Step 3: Calculate objective weights using entropy weight method

[0088] Construct the initial rock burst evaluation matrix Y = (y ij ) m×n In the comprehensive evaluation model, the larger the data of some indicators, the better (benefit-oriented indicators), while the smaller the data of some indicators, the better (cost-oriented indicators). In order to eliminate the influence of different indicator dimensions, the values ​​of each indicator are mapped to the interval of [0, 1], and then the decision evaluation is standardized to obtain R = (r ij ) m×n , commonly used methods include max-min standardization and Z-score standardization. Calculate the proportion P of the i-th sample under a certain indicator and the indicator information entropy value e j , and finally calculate the weight of each indicator. The specific steps are as follows:

[0089] Construct the initial rock burst evaluation matrix Y = (y ij ) m×n :

[0090]

[0091] Among them, m is the number of objects of comprehensive evaluation, and n is the number of indicators of comprehensive evaluation.

[0092] Map the values ​​of each indicator to the interval [0, 1], and then standardize the decision evaluation to obtain R = (rij ) m×n :

[0093]

[0094] Calculate the proportion P of the i-th sample under a certain indicator and the indicator information entropy value e j :

[0095]

[0096] Calculate the objective weight of comprehensive evaluation index of impact hazard:

[0097]

[0098] Among them, w Bj ∈[0,1], and

[0099] Step 4: Calculate the combination weights using the analytic hierarchy process (AHP) and entropy weight method

[0100] Establish a decision optimization model:

[0101]

[0102] In the formula, w j is the combined weight of AHP and entropy weight method, and B are the subjective preference coefficient and the objective preference coefficient respectively.

[0103] Introducing the Euclidean distance function D(w Aj ,w Bj ), establish the consistency equation of the difference between subjective and objective weights and corresponding preference coefficients:

[0104]

[0105] Step 5: Establish CW-TOPSIS comprehensive evaluation model

[0106] The evaluation objects are sorted according to their closeness to the idealized goal to determine the order of merit of the evaluation objects.

[0107] Construct the weighted decision matrix after combining the weights of AHP-entropy weight method:

[0108]

[0109] In the formula, w j is the combined weight of each indicator, w j ∈[0,1], and

[0110] According to the properties of the evaluation indicators, the positive ideal solution and the negative ideal solution are determined: the positive ideal solution is the evaluation object that takes the maximum value on each indicator, and the negative ideal solution is the evaluation object that takes the minimum value on each indicator;

[0111]

[0112] Calculate the distance from each evaluation object to the positive ideal solution:

[0113]

[0114] Calculate the distance from each evaluation object to the negative ideal solution:

[0115]

[0116] Calculate the relative closeness of each evaluation object to the positive ideal solution based on the distance:

[0117]

[0118] The higher the relative closeness value, the closer the evaluation object is to the positive ideal solution, and the comprehensive evaluation result of each evaluation object is determined. Finally, the calculation results of the comprehensive evaluation model are as follows:

[0119] Q=W×F

[0120] Among them, W is the comprehensive weight matrix; F is the matrix composed of the relative closeness values ​​of each evaluation object.

[0121] The following takes the first comprehensive mining area of ​​Junde Coal Mine as an example to describe the specific implementation method of this application in more detail.

[0122] like Figure 2 As shown, this embodiment provides a tunnel impact hazard assessment method based on a critical index, and the tunnel impact hazard assessment method based on a critical index includes the following steps:

[0123] First, the mining area index profile is input, which are critical softening radius, critical load, critical convergence displacement, critical energy and critical mining depth.

[0124]

[0125]

[0126] According to the established comprehensive evaluation model for rock burst hazard, the measured data and relevant information of the working face are found, and the evaluation index value of the first comprehensive mining area and the combined weight of the AHP-entropy weight method are obtained, as shown in the following table:

[0127]

[0128] According to the combined weighting principle of the AHP-entropy weight method, the comprehensive weight matrix W of the first-level evaluation indicators is determined as follows:

[0129] W = (w ij ) 1×5 = [0.1233 0.3294 0.1358 0.2040 0.2076]

[0130] The matrix F composed of the relative closeness values of the first-level evaluation indicators is determined as follows:

[0131]

[0132] The calculation results of the comprehensive evaluation model are as follows:

[0133] Q = W × F = [0.4536 0.4822 0.5155 0.5387 0.4735]

[0134] The comprehensive evaluation space Q of the rock burst hazard is Q = {Q0, Q1, Q2, Q3, Q} = {0.4536, 0.4822, 0.5155, 0.5387, 0.4735}. Therefore, the evaluation results of the rock burst hazard levels are: Q0 = 0.4536, Q1 = 0.4822, Q2 = 0.5155, Q3 = 0.5387, Q = 0.4735. Among them, the relative closeness value is Q = 0.4735 ∈ (Q0, Q1) = (0.4536, 0.4822). Therefore, the predicted evaluation result of the rock burst level in the first fully-mechanized mining district by using the CW-TOPSIS rock burst hazard comprehensive evaluation model is weak rock burst hazard.

[0135] As Figure 3 shown, the results of the CW-TOPSIS rock burst comprehensive evaluation method are verified by using the comprehensive index method of coal seam impact hazard. This method comprehensively analyzes the key geological factors and mining technical factors affecting the occurrence of rock bursts, evaluates the influence degree of these factors on rock bursts, and calculates the impact hazard index to overall evaluate the rock burst hazard status in a specific area. The comprehensive index method of coal seam impact hazard is used for the evaluation of coal seam impact hazard, and the comprehensive index is represented by W t .

[0136] According to the geological factors and mining technical factors of the working face in the first fully-mechanized mining district, the impact hazard indexes of each influencing factor are determined.

[0137] According to the comprehensive index method, it is calculated that W t = 0.38, indicating that the working face belongs to the weak-medium impact hazard level (0.25 < Wt ≤ 0.5). The results of the comprehensive index method are consistent with those of the comprehensive evaluation method. The working face in the first fully-mechanized mining district has the conditions for the occurrence of rock bursts and the potential risk of rock burst occurrence.

[0138] In summary, this application adopts the method of theoretical analysis, based on the perspective of tunnel surrounding rock-support system, to construct critical indicators of rock burst (critical softening radius, critical load, critical convergence displacement, critical energy, critical mining depth), and adopts the linear stress-strain constitutive relationship considering the residual strength of coal and rock materials to establish a three-linear circular tunnel surrounding rock-support system mechanical model; theoretically analyze the influence of surrounding rock mechanical properties, support stress and tunnel radius on the critical indicators of rock burst in circular tunnel surrounding rock-support system, and determine the main controlling factors of critical indicators; based on the critical indicators of rock burst, establish a comprehensive evaluation model of rock burst hazard, and propose a CW-TOPSIS comprehensive evaluation method of rock burst hazard. The research results aim to improve the rock burst theory of "tunnel surrounding rock-support" system and improve the existing comprehensive evaluation method of rock burst hazard, which has a certain guiding role in the prevention and evaluation of rock burst in tunnels.

[0139] It should be understood that, for the aforementioned various method embodiments, although the various steps in the flow chart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flow chart of the method embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0140] Based on the same inventive concept, the embodiment of the present application also provides a tunnel impact hazard assessment device for implementing the tunnel impact hazard assessment method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more tunnel impact hazard assessment device embodiments provided below can refer to the limitations of the tunnel impact hazard assessment method above, and will not be repeated here.

[0141] In one embodiment, Figure 4 As shown, a tunnel impact hazard assessment device 400 is provided, comprising: an acquisition module 401, a weight module 402, a calculation module 403 and an assessment module 404, wherein:

[0142] An acquisition module 401 is used to respectively acquire evaluation values ​​of each first-level critical index of the lane to be evaluated;

[0143] A weight module 402 is used to determine the combined weights of each primary critical index based on the AHP-entropy weight method and the evaluation value to obtain a weight matrix;

[0144] The calculation module 403 is used to input the evaluation value and the weight matrix into the evaluation model constructed based on the approximate ideal solution sorting method to perform calculations, determine the degree of proximity between each primary critical index and the positive ideal solution, and form a first proximity matrix; perform a product operation on the weight matrix and the first proximity matrix to obtain an evaluation matrix;

[0145] The evaluation module 404 is used to judge the danger level of the lane to be evaluated by using the evaluation matrix.

[0146] In one embodiment, each primary critical indicator includes a critical softening radius, a critical convergence displacement, a critical load, a critical energy and a critical mining depth.

[0147] In one embodiment, the acquisition module 401 is specifically used to respectively acquire the value of the second-level critical indicator corresponding to each first-level critical indicator of the lane to be evaluated; and calculate the evaluation value of each first-level critical indicator according to the value of the second-level critical indicator.

[0148] In one embodiment, the secondary critical indicators corresponding to the critical softening radius are uniaxial compressive strength, deformation modulus index, elastic modulus, damage internal friction angle, softening modulus, residual modulus, residual strength coefficient, support stress and tunnel radius; the secondary critical indicators corresponding to the critical convergence displacement are uniaxial compressive strength, deformation modulus index, elastic modulus, damage internal friction angle, softening modulus, residual modulus, residual strength coefficient, support stress and tunnel radius; the secondary critical indicators corresponding to the critical load are uniaxial compressive strength, deformation modulus index, damage internal friction angle, residual strength coefficient and support stress; the secondary critical indicators corresponding to the critical energy are uniaxial compressive strength, deformation modulus index, elastic modulus, damage internal friction angle, softening modulus, residual modulus, residual strength coefficient, Poisson's ratio, support stress and tunnel radius; the secondary critical indicators corresponding to the critical mining depth are uniaxial compressive strength, deformation modulus index, damage internal friction angle, residual strength coefficient, rock bulk density and support stress.

[0149] In one embodiment, the hazard levels are divided into no impact hazard, weak impact hazard, medium impact hazard and strong impact hazard; the evaluation value of the critical softening radius under no impact hazard is not greater than 4m, the evaluation value of the critical convergence displacement is not greater than 20mm, the evaluation value of the critical load is not greater than 10Pa, and the evaluation value of the critical energy is not greater than 10 4 The evaluation value of critical mining depth is not more than 400m; the evaluation value of critical softening radius of weak impact hazard is greater than 4m and less than 5m, the evaluation value of critical convergence displacement is greater than 20mm and less than 30mm, the evaluation value of critical load is greater than 10Pa and less than 14Pa, and the evaluation value of critical energy is greater than 10 4 J and not more than 10 5J, the evaluation value of the critical mining depth is greater than 400m and less than 600m; the evaluation value of the critical softening radius of medium impact risk is greater than 5m and less than 6m, the evaluation value of the critical convergence displacement is greater than 30mm and less than 40mm, the evaluation value of the critical load is greater than 14Pa and less than 18Pa, and the evaluation value of the critical energy is greater than 10 5 J and not more than 10 6 J, the evaluation value of the critical mining depth is greater than 600m and not greater than 800m; the evaluation value of the critical softening radius of strong impact danger is greater than 6m, the evaluation value of the critical convergence displacement is greater than 40mm, the evaluation value of the critical load is greater than 18Pa, and the evaluation value of the critical energy is greater than 10 6 J, the evaluation value of critical mining depth is greater than 800m.

[0150] In one embodiment, the evaluation module 404 is specifically used to use the first four elements in the evaluation matrix as critical reference values ​​of no impact hazard, weak impact hazard, medium impact hazard and strong impact hazard respectively, and use the fifth element in the evaluation matrix as the comparison value of the lane to be evaluated; compare the comparison value with the critical reference value; if the comparison value is less than the critical reference value of no impact hazard, then the hazard level of the lane to be evaluated is determined to be no impact hazard; if the comparison value is between the critical reference values ​​of no impact hazard and weak impact hazard, then the hazard level of the lane to be evaluated is determined to be weak impact hazard; if the comparison value is between the critical reference values ​​of weak impact hazard and strong impact hazard, then the hazard level of the lane to be evaluated is determined to be medium impact hazard; if the comparison value is greater than the critical reference value of strong impact hazard, then the hazard level of the lane to be evaluated is determined to be strong impact hazard.

[0151] In one embodiment, the weight module 402 is specifically used to determine the subjective weight of each first-level critical indicator based on the hierarchical analysis method; determine the objective weight of each first-level critical indicator based on the entropy weight method and the evaluation value; and combine the subjective weight and the objective weight using the Euclidean distance function to obtain the combined weight of each first-level critical indicator.

[0152] In one embodiment, the calculation module 403 is specifically used to generate a weighted decision matrix based on the evaluation value and the weight matrix; based on the weighted decision matrix, determine the positive and negative ideal solutions of each first-level critical indicator; calculate the distance from each first-level critical indicator to the positive and negative ideal solutions respectively, and calculate the degree of proximity of each first-level critical indicator to the positive ideal solution based on the distance.

[0153] For the specific definition of the tunnel impact hazard assessment device, please refer to the definition of the tunnel impact hazard assessment method above, which will not be repeated here. Each module in the above-mentioned tunnel impact hazard assessment device can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0154] In addition, in the implementation of the tunnel impact hazard assessment device in the above-mentioned example, the logical division of each program module is only an example. In actual application, the above-mentioned functions can be assigned to different program modules as needed, for example, for the configuration requirements of the corresponding hardware or the convenience of software implementation. That is, the internal structure of the tunnel impact hazard assessment device is divided into different program modules to complete all or part of the functions described above.

[0155] In one embodiment, Figure 5 As shown, a computer device is also provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0156] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0157] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0158] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0159] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0160] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification. In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0161] The terms "including" and "having" and any variations thereof in the embodiments herein are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or (module) units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products or devices.

[0162] The "first\second" mentioned in this article is only to distinguish similar objects, and does not represent a specific order for the objects. It is understandable that the "first\second" can be interchanged with the specific order or sequence where permitted. It should be understood that the objects distinguished by "first\second" can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than those illustrated or described herein.

[0163] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for evaluating the risk of tunnel impact, characterized in that: The method comprises: Obtaining evaluation values ​​of each first-level critical index of the roadway to be evaluated respectively; each first-level critical index is used to characterize the surrounding rock mechanical properties, roadway support conditions and roadway dimensions of the roadway to be evaluated; Based on the AHP-entropy weight method and the evaluation value, the combined weights of the first-level critical indicators are determined to obtain a weight matrix; Input the evaluation value and the weight matrix into the evaluation model constructed based on the approximate ideal solution sorting method for calculation, determine the closeness of each primary critical index to the positive ideal solution, and form a first closeness matrix; Performing a product operation on the weight matrix and the first proximity matrix to obtain an evaluation matrix; The evaluation matrix is ​​used to judge the danger level of the lane to be evaluated.

2. The method according to claim 1, characterized in that: The first-level critical indicators include critical softening radius, critical convergence displacement, critical load, critical energy and critical mining depth.

3. The method according to claim 2, characterized in that The step of respectively obtaining the evaluation values ​​of each primary critical index of the lane to be evaluated comprises: Respectively obtain the value of the second-level critical index corresponding to each first-level critical index of the lane to be evaluated; According to the value of the second-level critical indicator, the evaluation value of each first-level critical indicator is calculated accordingly.

4. The method according to claim 3, characterized in that The secondary critical indicators corresponding to the critical softening radius are uniaxial compressive strength, deformation modulus index, elastic modulus, damage internal friction angle, softening modulus, residual modulus, residual strength coefficient, support stress and tunnel radius; The secondary critical indicators corresponding to the critical convergence displacement are uniaxial compressive strength, deformation modulus index, elastic modulus, damage internal friction angle, softening modulus, residual modulus, residual strength coefficient, support stress and tunnel radius; The secondary critical indicators corresponding to the critical load are uniaxial compressive strength, deformation modulus index, damage internal friction angle, residual strength coefficient and support stress; The secondary critical indicators corresponding to the critical energy are uniaxial compressive strength, deformation modulus index, elastic modulus, damage internal friction angle, softening modulus, residual modulus, residual strength coefficient, Poisson's ratio, support stress and tunnel radius; The secondary critical indicators corresponding to the critical mining depth are uniaxial compressive strength, deformation modulus index, damage internal friction angle, residual strength coefficient, rock bulk density and support stress.

5. The method according to any one of claims 2 to 4, characterized in that The hazard levels are divided into no impact hazard, weak impact hazard, medium impact hazard and strong impact hazard; The evaluation value of the critical softening radius without impact risk is not greater than 4m, the evaluation value of the critical convergence displacement is not greater than 20mm, the evaluation value of the critical load is not greater than 10Pa, and the evaluation value of the critical energy is not greater than 10 4 J, the evaluation value of the critical mining depth is not greater than 400m; The evaluation value of the critical softening radius of the weak impact risk is greater than 4m and not greater than 5m, the evaluation value of the critical convergence displacement is greater than 20mm and not greater than 30mm, the evaluation value of the critical load is greater than 10Pa and not greater than 14Pa, and the evaluation value of the critical energy is greater than 10 4 J and not more than 10 5 J, the evaluation value of the critical mining depth is greater than 400m and not greater than 600m; The evaluation value of the critical softening radius of the medium impact risk is greater than 5m and not greater than 6m, the evaluation value of the critical convergence displacement is greater than 30mm and not greater than 40mm, the evaluation value of the critical load is greater than 14Pa and not greater than 18Pa, and the evaluation value of the critical energy is greater than 10 5 J and not more than 10 6 J, the evaluation value of the critical mining depth is greater than 600m and not greater than 800m; The evaluation value of the critical softening radius of the strong impact hazard is greater than 6m, the evaluation value of the critical convergence displacement is greater than 40mm, the evaluation value of the critical load is greater than 18Pa, and the evaluation value of the critical energy is greater than 10 6 J, the evaluation value of the critical mining depth is greater than 800m.

6. The method according to claim 5, characterized in that The step of using the evaluation matrix to judge the danger level of the lane to be evaluated includes: The first four elements in the evaluation matrix are used as critical reference values ​​of no impact hazard, weak impact hazard, medium impact hazard and strong impact hazard, respectively, and the fifth element in the evaluation matrix is ​​used as the comparison value of the roadway to be evaluated; Comparing the comparison value with the critical reference value; If the comparison value is less than the critical reference value of no impact danger, the danger level of the roadway to be evaluated is determined to be no impact danger; If the comparison value is between the critical reference values ​​of no impact danger and weak impact danger, the danger level of the roadway to be evaluated is determined to be weak impact danger; If the comparison value is between the critical reference values ​​of weak impact hazard and strong impact hazard, the hazard level of the roadway to be evaluated is determined to be medium impact hazard; If the comparison value is greater than the critical reference value of the strong impact hazard, the hazard level of the to-be-evaluated lane is determined to be a strong impact hazard.

7. The method according to any one of claims 1 to 4, characterized in that The step of determining the combined weights of the first-level critical indicators based on the AHP-entropy weight method and the evaluation value includes: Based on the analytic hierarchy process, the subjective weight of each first-level critical indicator is determined; Based on the entropy weight method and the evaluation value, determining the objective weight of each primary critical indicator; The subjective weight and the objective weight are combined using the Euclidean distance function to obtain the combined weight of each primary critical indicator.

8. The method according to any one of claims 1 to 4, characterized in that The step of inputting the evaluation value and the weight matrix into the evaluation model for calculation to determine the degree of proximity between each primary critical index and the positive ideal solution comprises: Generate a weighted decision matrix according to the evaluation value and the weight matrix; Based on the weighted decision matrix, determining positive and negative ideal solutions for each primary critical indicator; The distances from each first-level critical indicator to the positive and negative ideal solutions are calculated respectively, and the degree of proximity of each first-level critical indicator to the positive ideal solution is calculated based on the distances.

9. A tunnel impact hazard assessment device, characterized in that: The device comprises: An acquisition module, used to respectively acquire the evaluation values ​​of each first-level critical index of the lane to be evaluated; A weight module is used to determine the combined weights of each primary critical index based on the AHP-entropy weight method and the evaluation value to obtain a weight matrix; A calculation module, used for inputting the evaluation value and the weight matrix into the evaluation model constructed based on the approximate ideal solution sorting method to perform calculation, determine the closeness of each primary critical index to the positive ideal solution, and form a first close matrix; perform a product operation on the weight matrix and the first close matrix to obtain an evaluation matrix; An evaluation module is used to use the evaluation matrix to judge the danger level of the lane to be evaluated.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

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