Decision-making method and system for deep roadway surrounding rock grading and anchor rod supporting

Abstract

The invention relates to the technical field of roadway supporting, in particular to a deep roadway surrounding rock grading and anchor rod supporting decision-making method and system, and the method comprises the steps: obtaining roadway data information; based on the crustal stress parameter, the rock stratum strength parameter, the underground water influence and the mining influence, the roadway surrounding rock stability level is obtained; and based on the roadway data information and roadway mine pressure appearance judgment, obtaining roadway basic support information according to the roadway surrounding rock stability level. According to the method, the roadway surrounding rock stability level is obtained, corresponding supporting forms and parameters are given according to supporting experience qualitative rating, deep roadway supporting quantitative division and qualitative rating are combined, and the graded supporting technology is more scientific. The problem that the deep roadway support parameter design is mainly based on engineering experience, and support parameters designed by engineering technicians with different experiences under the same engineering geological condition possibly have large differences is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel support, and in particular to a decision-making method and system for surrounding rock classification and anchor support of deep tunnels. Background Art

[0002] At present, as the mining depth in the central and eastern mining areas of my country (including Huainan, Huaibei, Shandong, Henan, etc.) has reached 800~1000m, mining areas such as Shanxi and Shaanxi have gradually entered the deep mining area. The complex and abnormal mechanical environment under deep conditions seriously restricts the safe and efficient mining of coal. The restrictive effect of deep coal roadway support technology on production safety is becoming increasingly prominent. In the process of deep roadway support design, the evaluation of roadway surrounding rock stability is still mainly qualitative, and the selection of support parameters mainly depends on the on-site experience and engineering analogy of engineering and technical personnel. With the significant increase in the intensity and depth of coal mining, the geological conditions are becoming more and more complex, which puts forward higher requirements for the quantification, standardization and intelligence of roadway support technology. Summary of the invention

[0003] The present invention provides a decision-making method and system for surrounding rock classification and anchor support of deep tunnels, which is used to solve one of the defects in the prior art, realize the combination of quantitative classification and qualitative rating of deep tunnel support, and make the graded support technology more scientific. It solves the problem that the design of deep tunnel support parameters is mainly based on engineering experience, and the support parameters designed by engineering technicians with different experiences may be quite different under the same engineering geological conditions.

[0004] The present invention provides a decision-making method for surrounding rock classification and anchor support of deep tunnels, comprising: Obtaining lane data information; Based on ground stress parameters, rock formation strength parameters, groundwater influence and mining influence, the stability level of tunnel surrounding rock is obtained; Based on the tunnel data information and the evaluation of the tunnel mining pressure, the basic tunnel support information is obtained according to the stability level of the tunnel surrounding rock.

[0005] According to a deep tunnel surrounding rock classification and anchor support decision-making method provided by the present invention, the tunnel surrounding rock stability level is obtained based on ground stress parameters, rock formation strength parameters, groundwater influence and mining influence, including: Based on the ground stress parameters and rock formation strength parameters, the initial surrounding rock strength coefficient is obtained; Based on at least one of the influence of groundwater and the influence of mining, the initial surrounding rock strength coefficient is corrected to obtain the actual surrounding rock strength coefficient; Based on the actual surrounding rock strength coefficient, the tunnel surrounding rock stability level is obtained.

[0006] According to a decision method for surrounding rock classification and anchor support of a deep tunnel provided by the present invention, the initial surrounding rock strength coefficient is obtained based on the ground stress parameter and the rock formation strength parameter, which includes: Based on the maximum horizontal principal stress σ H and the average strength of the top plate σ 顶 , obtain the top plate stress intensity coefficient A; Based on the vertical principal stress σ v Average strength of coal body in the tunnel σ 帮 , obtain the stress intensity coefficient B of the laneway side; The roof hazard coefficient C is obtained based on the thickness h of the weak interlayer within 10m of the roof.

[0007] According to a decision method for surrounding rock classification and bolt support of deep tunnels provided by the present invention, the initial surrounding rock strength coefficient is corrected based on at least one of the influence of groundwater and the influence of mining to obtain the actual surrounding rock strength coefficient, which includes: Obtain the basic top pressure equivalent as the mining impact index of the working face; Based on the mining impact index of the working face, the first correction coefficient is obtained; Based on the first correction coefficient, the initial surrounding rock strength coefficient is corrected to obtain the actual surrounding rock strength coefficient.

[0008] According to a decision method for surrounding rock classification and bolt support of deep tunnels provided by the present invention, the initial surrounding rock strength coefficient is corrected based on at least one of the influence of groundwater and the influence of mining to obtain the actual surrounding rock strength coefficient, which includes: Obtain the water seepage volume of 10m tunnel as the groundwater impact indicator of the working face; Based on the groundwater impact index of the working face, the second modified positive coefficient is obtained; Based on the second correction coefficient, the initial surrounding rock strength coefficient is corrected to obtain the actual surrounding rock strength coefficient.

[0009] According to a deep tunnel surrounding rock classification and anchor support decision-making method provided by the present invention, the tunnel surrounding rock stability level is obtained based on the actual surrounding rock strength coefficient, which includes: Based on the actual surrounding rock strength coefficient, the stability classification set of the tunnel surrounding rock is obtained; Based on the roadway surrounding rock stability classification set, the roadway surrounding rock stability level is obtained.

[0010] According to a decision method for surrounding rock classification and bolt support of deep tunnels provided by the present invention, after obtaining basic tunnel support information based on tunnel data information and tunnel mine pressure manifestation evaluation according to the tunnel surrounding rock stability level, the method further includes: Based on the basic support information of the tunnel, the tunnel support plan and tunnel support cross-section diagram are generated.

[0011] The present invention also provides a decision-making system for surrounding rock classification and anchor support in deep tunnels, comprising: Acquisition module, obtains lane data information; The first processing module obtains the stability level of the tunnel surrounding rock based on the ground stress parameters, rock formation strength parameters, groundwater influence and mining influence; The second processing module obtains the basic support information of the tunnel based on the tunnel data information and the evaluation of the tunnel mining pressure and the stability level of the tunnel surrounding rock.

[0012] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the decision-making method for deep tunnel surrounding rock classification and anchor support is implemented as described above.

[0013] The present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements the decision-making method for deep tunnel surrounding rock classification and anchor support as described above.

[0014] The method for decision-making on classification of surrounding rock and anchor support of deep tunnels provided by the present invention obtains tunnel data information, collects and analyzes on-site mine pressure data, including anchor cable stress, tunnel surface displacement, roof separation and other mine pressure data, obtains mine pressure manifestation evaluation of tunnels, and then establishes a tunnel sample database. Based on the tunnel sample database, quantitative classification indicators and methods for surrounding rock of deep tunnels are established, and the stability level of surrounding rock of tunnels is obtained based on ground stress parameters, rock formation strength parameters, groundwater influence and mining influence. Combined with support experience, qualitative rating is used to give corresponding support forms and parameters, so as to realize the combination of quantitative classification and qualitative rating of deep tunnel support, and the graded support technology is more scientific. It solves the problem that the design of support parameters of deep tunnels is mainly based on engineering experience, and the support parameters designed by engineering and technical personnel with different experience may be quite different under the same engineering geological conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 It is a tunnel support design reference result diagram output by the decision system for deep tunnel surrounding rock classification and bolt support provided by an embodiment of the present invention; Figure 2 This is an operation interface diagram of a decision-making system for surrounding rock classification and bolt support of deep tunnels provided by an embodiment of the present invention; Figure 3 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] The embodiment of the present invention provides a decision-making system for surrounding rock classification and bolt support of deep tunnels, including: Acquisition module, obtains lane data information; The first processing module obtains the stability level of the tunnel surrounding rock based on the ground stress parameters, rock formation strength parameters, groundwater influence and mining influence; The second processing module obtains the basic support information of the tunnel based on the tunnel data information and the evaluation of the tunnel mining pressure and the stability level of the tunnel surrounding rock.

[0019] The embodiment of the present invention provides a decision-making system for deep tunnel surrounding rock classification and anchor support, which avoids the problem that there are many methods for calculating anchor support parameters, the calculation process is relatively complicated, and a large amount of theoretical calculation and repeated verification process are required, which is difficult for engineering designers to master and apply. It solves the problem that the existing design system is developed based on mathematical expressions extracted from engineering experience, has a limited scope of application, and cannot meet the requirements of quantification, standardization and intelligence of deep tunnel support. Language programming is used to establish a tunnel surrounding rock stability evaluation and support design decision-making system, which organically combines the quantitative evaluation of tunnel surrounding rock stability with experts to achieve the standardization, standardization and intelligence of deep tunnel anchor support design.

[0020] Based on the decision-making system for surrounding rock classification and anchor support of deep tunnels provided by the embodiment of the present invention, a decision-making method for surrounding rock classification and anchor support of deep tunnels can be performed, including: Obtaining lane data information; Based on ground stress parameters, rock formation strength parameters, groundwater influence and mining influence, the stability level of tunnel surrounding rock is obtained; Based on the tunnel data information and the evaluation of the tunnel mining pressure, the basic tunnel support information is obtained according to the stability level of the tunnel surrounding rock.

[0021] The deep tunnel surrounding rock classification and anchor support decision-making method of the embodiment of the present invention obtains tunnel data information, and obtains tunnel mine pressure manifestation evaluation based on on-site mine pressure data collection and analysis, including anchor cable stress, tunnel surface displacement, roof delamination and other mine pressure data, and then establishes a tunnel sample database. Based on the tunnel sample database, a quantitative classification index and method for deep tunnel surrounding rock is established, and the tunnel surrounding rock stability level is obtained based on ground stress parameters, rock formation strength parameters, groundwater influence and mining influence. Combined with the support experience, qualitative rating is used to give the corresponding support form and parameters, so as to realize the combination of quantitative classification and qualitative rating of deep tunnel support, and the graded support technology is more scientific. It solves the problem that the design of deep tunnel support parameters is mainly based on engineering experience, and the support parameters designed by engineering and technical personnel with different experience under the same engineering geological conditions may vary greatly.

[0022] The acquisition module obtains tunnel data information, that is, by inputting basic tunnel information, ground stress parameters, and rock formation parameters, a tunnel sample database is established.

[0023] The basic information of the tunnel includes tunnel name, tunnel width, tunnel centerline height, roof inclination, tunnel type, 10m tunnel water inflow, first pressure step, mining height, direct top filling coefficient and other information, and the cross-sectional shape of the tunnel is given in a graphical way.

[0024] The ground stress parameters include five parameters: tunnel burial depth, vertical principal stress, minimum horizontal principal stress, maximum horizontal principal stress, and direction of maximum horizontal principal stress.

[0025] The rock layer parameters manage the lithology, thickness, weak layer thickness and other information of the roof / bottom plate in a table format.

[0026] The first processing module can automatically calculate the stability level of the tunnel surrounding rock based on ground stress parameters, rock strength parameters, groundwater influence and mining influence.

[0027] The third processing module automatically determines the basic support information of the tunnel based on the large amount of sample tunnel data information and tunnel mine pressure manifestation evaluation obtained by the acquisition module and the tunnel surrounding rock stability level obtained by the second processing module.

[0028] The basic support information of the tunnel is the basic support form and specific parameters of the tunnel, including the row and spacing of anchor rods, anchor rod model, tray model, steel belt model, drilling depth, drilling diameter, pre-tightening torque, design anchoring force, specifications and quantity of anchoring agents; the row and spacing of anchor cables, anchor cable model, tray model, steel beam model, drilling depth, drilling diameter, pre-tightening force, specifications and quantity of anchoring agents, mesh and other basic and specific parameters.

[0029] Based on the prestressed anchor support technology and combined with the stability level of the tunnel surrounding rock, the tunnel classification support forms and specific parameters are proposed as shown in Table 1.

[0030] Table 1

[0031] According to an embodiment provided by the present invention, obtaining the stability level of the surrounding rock of the tunnel based on the ground stress parameters, the rock formation strength parameters, the groundwater influence and the mining influence includes: Based on the ground stress parameters and rock formation strength parameters, the initial surrounding rock strength coefficient is obtained; Based on at least one of the groundwater influence and the mining influence, the initial surrounding rock strength coefficient is corrected to obtain the actual surrounding rock strength coefficient; Based on the actual surrounding rock strength coefficient, the tunnel surrounding rock stability level is obtained.

[0032] In this embodiment, the surrounding rock of the tunnel is quantitatively classified for the first time, and the initial support form and support parameters are given. Then, the classification index is corrected in combination with the influence of groundwater and mining.

[0033] After the basic indicators are determined, the categories of basic indicators can be used as the preliminary classification of coal roadway surrounding rocks. Preliminary classification is generally adopted in the early stage of roadway support design. At this stage, the survey data is incomplete, the work is not in-depth enough, and various correction factors are difficult to determine. As a preliminary classification, the level of basic indicators can be used as the basic category of roadway surrounding rocks.

[0034] Among the factors that affect the stability of surrounding rock, ground stress, surrounding rock strength and rock mass integrity are the basic properties of surrounding rock, which are the common characteristics of surrounding rock of various types of coal roadways and reflect the basic characteristics of roadways, but they are not all the important factors affecting roadway stability. Groundwater status and mining dynamic pressure are also important factors affecting rock mass quality and stability.

[0035] The surrounding rock strength coefficient includes the roof stress intensity coefficient A, the roadway wall stress intensity coefficient B and the roof hazard coefficient C. The surrounding rock strength coefficient is used as a grading index. The three coefficients are comprehensive factors, which respectively reflect the relative relationship between the two indicators and the basic properties and characteristics of the roadway surrounding rock conditions, which is convenient for the mining area to grasp and classify the correspondingly in the on-site operation. The three factors are cross-combined to divide the roadway surrounding rock stability into the four levels shown in Table 2.

[0036] Table 2

[0037] According to an embodiment provided by the present invention, obtaining the initial surrounding rock strength coefficient based on the ground stress parameter and the rock formation strength parameter includes: Based on the maximum horizontal principal stress σH and the average strength of the top plate σ 顶 , obtain the top plate stress intensity coefficient A; Based on the vertical principal stress σ v Average strength of coal body in the tunnel σ 帮 , obtain the stress intensity coefficient B of the laneway side; The roof hazard coefficient C is obtained based on the thickness h of the weak interlayer within 10m of the roof.

[0038] In this embodiment, the maximum horizontal principal stress σ is selected from the ground stress parameters and the rock formation strength parameters. H , vertical principal stress σ v , average strength of roof σ 顶 , average strength of coal body in roadway σ 帮 and the thickness of the weak interlayer h within 10m of the roof. The weak interlayer within 10m of the roof is a rock layer with a strength less than 25MPa or a layer joint spacing and layer thickness less than 1m. Three basic quantitative indicators for the classification of tunnel surrounding rocks are obtained: The top plate stress intensity coefficient A is the maximum horizontal stress σ H The average strength of the surrounding rock of the roof within 10m is 顶 The ratio of , which comprehensively reflects the mechanical properties of the roof rock strata.

[0039] The stress intensity coefficient B of the road side is the vertical stress σ v and the average strength of the coal body in the roadway σ 帮 Ratio, that is , comprehensively reflecting the mechanical properties of the surrounding rock of the tunnel side.

[0040] The roof hazard coefficient C refers to the ratio of the sum of the thickness of the rock layers with a strength of less than 25 MPa or a layer joint spacing and layer thickness of less than 1 m within 10 m of the roof to the total thickness, that is, .

[0041] According to an embodiment provided by the present invention, the initial surrounding rock strength coefficient is corrected based on at least one of the groundwater influence and the mining influence to obtain the actual surrounding rock strength coefficient, including: Obtain the basic top pressure equivalent as the mining impact index of the working face; Based on the mining impact index of the working face, the first correction coefficient is obtained; Based on the first correction coefficient, the initial surrounding rock strength coefficient is corrected to obtain the actual surrounding rock strength coefficient.

[0042] In this embodiment, the larger the basic top pressure step and mining height, the greater the impact of mining on this working face. After the direct top collapse, the higher the filling degree of the goaf, the smaller the impact. The basic top pressure equivalent is used as the mining impact index of this working face: p e =241.3ln l b +52.6 h m -15.5 N

[0043] in, p e is the basic top pressure equivalent, kPa; l b is the initial pressing step length, m; h m is the mining height, m; N It is the filling factor of the direct top, which is the ratio of the direct top to the mining height.

[0044] The impact of mining is an important basis for determining the parameters of advanced strengthening support for the working face. It has little influence on the selection of basic support forms for the tunnel. Therefore, it is not used as an overall classification indicator for the tunnel, but as a reference for strengthening support. Considering the practicality and accessibility of indicator selection, the impact of mining on this working face is divided into four levels, namely, not obvious, obvious, strong, and very strong, and the roof strength coefficient, roadway stress intensity coefficient, and roof hazard coefficient are corrected, as shown in Table 3.

[0045] Table 3

[0046] According to an embodiment provided by the present invention, the initial surrounding rock strength coefficient is corrected based on at least one of the groundwater influence and the mining influence to obtain the actual surrounding rock strength coefficient, including: Obtain the water seepage volume of 10m tunnel as the groundwater impact indicator of the working face; Based on the groundwater impact index of the working face, the second modified positive coefficient is obtained; Based on the second correction coefficient, the initial surrounding rock strength coefficient is corrected to obtain the actual surrounding rock strength coefficient.

[0047] In this embodiment, groundwater is an important factor affecting the stability of tunnel surrounding rock. The main effects of groundwater are dissolving soluble cements in rocks and structural surfaces, corroding fine particles in fillings, softening and loosening rocks, mudding fillings, reducing strength, and increasing dynamic and static water pressures. The impact of these effects on rock mass quality is not reflected in the basic index classification, and correction measures are required to reflect their impact on surrounding rock. In this embodiment, when considering the impact of water in the classification of surrounding rock of underground engineering, the correction method is adopted, and a quantitative correction coefficient is given.

[0048] In order to facilitate on-site measurement, the average strength of the roof and the average strength of the coal body on the side of the roadway are corrected according to the 10m tunnel seepage volume (L / min) in the Engineering Rock Mass Classification Standard (GB / T 50218-2014), as shown in Table 4.

[0049] Table 4

[0050] According to an embodiment provided by the present invention, obtaining the stability level of the tunnel surrounding rock based on the actual surrounding rock strength coefficient includes: Based on the actual surrounding rock strength coefficient, the stability classification set of the tunnel surrounding rock is obtained; Based on the roadway surrounding rock stability classification set, the roadway surrounding rock stability level is obtained.

[0051] (1) Classification of roof stress intensity coefficient

[0052] The K-means clustering algorithm is used to input the number of clusters 3 and the data of the stress intensity coefficient of the roadway roof, and finally outputs three clusters that meet the minimum variance standard. Considering that the division of the stress intensity coefficient of the roadway roof is widely used and the classification is simple and intuitive, the intervals corresponding to the above three cluster centers are rounded and divided, and combined with the degree of mine pressure manifestation of the roadway roof under different roadway roof stress intensity coefficient conditions, the roadway roof stress intensity coefficient is divided into three categories. The specific classification parameters are shown in Table 5.

[0053] Table 5

[0054] (2) Classification of road side stress intensity coefficient

[0055] The K-means clustering algorithm is used to input the number of clusters 3 and the data of the roadway wall stress intensity coefficient, and finally outputs 3 clusters that meet the minimum variance standard. Considering that the roadway wall stress intensity coefficient division is widely used and ensures that the classification is simple and intuitive, the roadway wall stress intensity coefficient is divided into 3 categories according to the intervals corresponding to the above 3 cluster centers, and combined with the degree of mine pressure manifestation of the roadway wall under different roadway wall stress intensity coefficient conditions, the roadway wall stress intensity coefficient is divided into 3 categories. The specific classification parameters are shown in Table 6.

[0056] Table 6

[0057] (3) Classification of roof hazard factors

[0058] The K-means clustering algorithm is used to input the number of clusters 3 and the roof hazard coefficient data, and finally outputs 3 clusters that meet the minimum variance standard. Considering that the roof hazard coefficient division is widely used and the classification is simple and intuitive, the intervals corresponding to the above three cluster centers are rounded and divided, and combined with the degree of mine pressure manifestation in the on-site tunnel under different roof hazard coefficient conditions, the roof is divided into 3 categories according to the roof hazard coefficient. The specific classification parameters are shown in Table 7.

[0059] Table 7

[0060] According to an embodiment provided by the present invention, after obtaining basic tunnel support information based on tunnel data information and tunnel mine pressure manifestation evaluation according to the tunnel surrounding rock stability level, the method further includes: Based on the basic support information of the tunnel, the tunnel support plan and tunnel support cross-section diagram are generated.

[0061] In this embodiment, the overall support plan of each tunnel is automatically generated based on the basic information and support design information of each tunnel. The overall support plan consists of five parts: tunnel section size, roof support details, two side support details, support material list, and support plan schematic diagram. It has the functions of automatically drawing support design section diagrams, automatically calculating the number of support materials, and exporting support plans with one click.

[0062] Support design reference table 1 initial support form and parameters, Figure 1 The specific support method of typical tunnels of the same category is automatically given to provide the support parameters of the tunnel.

[0063] The support design of each tunnel includes two parts: the support design of the roof and the support design of the two sides.

[0064] The support design of the roof determines the row spacing and spacing of anchor rods, anchor rod model, tray model, steel belt model, drilling depth, drilling diameter, pre-tightening torque, design anchoring force, and the specifications and quantity of anchoring agents; the row spacing and spacing of anchor cables, anchor cable model, tray model, steel beam model, drilling depth, drilling diameter, pre-tightening force, and the specifications and quantity of anchoring agents; and basic information such as the roof mesh.

[0065] The support design of the two gangs determines the row spacing and spacing of anchor rods, anchor rod model, tray model, steel belt model, drilling depth, drilling diameter, pre-tightening torque, design anchoring force, and the specifications and quantity of anchoring agents; the row spacing and spacing of anchor cables, anchor cable model, tray model, steel beam model, drilling depth, drilling diameter, pre-tightening force, and the specifications and quantity of anchoring agents; and basic information such as the top plate mesh.

[0066] Click the Export button to export the entire design into a Word document. Figure 2 shown.

[0067] Figure 3 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 3 As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830 and a communication bus 840, wherein the processor 810, the communication interface 820 and the memory 830 communicate with each other through the communication bus 840. The processor 810 may call the logic instructions in the memory 830 to execute the decision method for deep tunnel surrounding rock classification and bolt support of the above embodiment.

[0068] In addition, the logic instructions in the above-mentioned memory 830 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0069] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the decision-making method for deep tunnel surrounding rock classification and anchor support of the above-mentioned embodiment.

[0070] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the decision-making method for deep tunnel surrounding rock classification and anchor support of the above-mentioned embodiment.

[0071] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0072] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0073] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A decision-making method for surrounding rock classification and bolt support in deep tunnels, characterized in that: include: Obtaining lane data information; Based on ground stress parameters, rock formation strength parameters, groundwater influence and mining influence, the stability level of tunnel surrounding rock is obtained; Based on the tunnel data information and the evaluation of the tunnel mining pressure, the basic tunnel support information is obtained according to the stability level of the tunnel surrounding rock.

2. The decision-making method for surrounding rock classification and bolt support of deep tunnels according to claim 1 is characterized in that: The tunnel surrounding rock stability level obtained based on ground stress parameters, rock formation strength parameters, groundwater influence and mining influence includes: Based on the ground stress parameters and rock formation strength parameters, the initial surrounding rock strength coefficient is obtained; Based on at least one of the groundwater influence and the mining influence, the initial surrounding rock strength coefficient is corrected to obtain the actual surrounding rock strength coefficient; Based on the actual surrounding rock strength coefficient, the tunnel surrounding rock stability level is obtained.

3. The decision-making method for surrounding rock classification and bolt support of deep tunnels according to claim 2 is characterized in that: The method of obtaining the initial surrounding rock strength coefficient based on the ground stress parameter and the rock formation strength parameter includes: Based on the maximum horizontal principal stress σ H and the average strength of the top plate σ 顶 , obtain the top plate stress intensity coefficient A; Based on the vertical principal stress σ v Average strength of coal body in the tunnel σ 帮 , obtain the stress intensity coefficient B of the laneway side; The roof hazard coefficient C is obtained based on the thickness h of the weak interlayer within 10m of the roof.

4. The decision-making method for surrounding rock classification and bolt support of deep tunnels according to claim 2 is characterized in that: The correcting the initial surrounding rock strength coefficient based on at least one of the groundwater influence and the mining influence to obtain the actual surrounding rock strength coefficient comprises: Obtain the basic top pressure equivalent as the mining impact index of the working face; Based on the mining impact index of the working face, the first correction coefficient is obtained; Based on the first correction coefficient, the initial surrounding rock strength coefficient is corrected to obtain the actual surrounding rock strength coefficient.

5. The decision-making method for surrounding rock classification and bolt support of deep tunnels according to claim 2 is characterized in that: The correcting the initial surrounding rock strength coefficient based on at least one of the groundwater influence and the mining influence to obtain the actual surrounding rock strength coefficient comprises: Obtain the water seepage volume of 10m tunnel as the groundwater impact indicator of the working face; Based on the groundwater impact index of the working face, the second modified positive coefficient is obtained; Based on the second correction coefficient, the initial surrounding rock strength coefficient is corrected to obtain the actual surrounding rock strength coefficient.

6. The decision-making method for surrounding rock classification and bolt support of deep tunnels according to claim 2 is characterized in that: The tunnel surrounding rock stability level obtained based on the actual surrounding rock strength coefficient includes: Based on the actual surrounding rock strength coefficient, the stability classification set of the tunnel surrounding rock is obtained; Based on the roadway surrounding rock stability classification set, the roadway surrounding rock stability level is obtained.

7. The method for decision-making on surrounding rock classification and bolt support of deep tunnels according to any one of claims 1 to 6, characterized in that: After obtaining basic tunnel support information based on tunnel data information and tunnel mine pressure manifestation evaluation according to tunnel surrounding rock stability level, the method further includes: Based on the basic support information of the tunnel, the tunnel support plan and tunnel support cross-section diagram are generated.

8. A decision-making system for surrounding rock classification and bolt support in deep tunnels, characterized in that: include: Acquisition module, obtains lane data information; The first processing module obtains the stability level of the tunnel surrounding rock based on the ground stress parameters, rock formation strength parameters, groundwater influence and mining influence; The second processing module obtains the basic support information of the tunnel based on the tunnel data information and the evaluation of the tunnel mining pressure and the stability level of the tunnel surrounding rock.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the decision-making method for deep tunnel surrounding rock classification and anchor support is implemented as described in any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the decision-making method for deep tunnel surrounding rock classification and anchor support is implemented as described in any one of claims 1 to 7.

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