Method for dynamically dividing rockburst grades of tunnel in construction stage

Abstract

The invention provides a tunnel rockburst grade dynamic division method in a construction stage, and relates to the technical field of tunnel construction.The method comprises the steps that firstly, a rockburst grade dynamic fine division index system is established, different geological units are divided according to the actual site situation, then rockburst events and sample data of all indexes of the rockburst events are collected, and through the data collected by multiple indexes, the rockburst grades are divided into different geological units; compared with a traditional single-index judgment mode, more accurate evaluation can be achieved, and finally, a variable weight function suitable for a rockburst event and an unascertained attribute measurement function of each index of rockburst grade division are put forward; and on the basis of the combined weight of each index of the first rockburst event in the same geological unit, calculating the dynamic weight of each index of other rockburst events in the same geological unit, thereby realizing dynamic evaluation of the rockburst event grade in the same geological unit. The method has the beneficial effect that the rockburst grade of the construction stage can be systematically and comprehensively divided.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel construction, and in particular to a method for dynamically dividing rockburst levels of tunnels during a construction phase. Background Art

[0002] Rockburst refers to the phenomenon of sudden destruction in the open rock mass in deep underground mining or areas with high tectonic stress. This phenomenon is also called rock burst. The cause of the occurrence is that the strain energy accumulated in the open rock mass is suddenly and violently released, causing the rock mass to undergo brittle fracture like an explosion. The impact ground pressure causes a large amount of rock to collapse, and produces a huge sound and air wave impact.

[0003] Rockburst is a common dynamic destruction phenomenon during the construction of deep underground projects. When the high elastic strain energy accumulated in the rock mass is greater than the energy consumed by rock destruction, the balance of the rock structure is destroyed. The excess energy causes the rock to burst, causing rock fragments to peel off and collapse from the rock mass.

[0004] With the advancement of deep underground projects, such as deep buried tunnels, underground plants and mine tunnels, rockburst disasters pose a serious threat to people's lives and property safety. Different levels of rockburst events can occur in different sections of the same tunnel. At present, most of the rockburst grade classification index systems are based on the depth of the blast pit and the rock strength stress ratio, but the dynamic effects of structural surface development and construction are not considered. At the same time, the classification based on the depth of the blast pit and the rock strength stress ratio is too rough, and there is insufficient research on the dynamic and fine classification of rockburst grades by multiple indicators. Therefore, as the project progresses, the rockburst grade classification cannot correctly reflect the actual situation of the rockburst grade, and inaccurate judgments will occur, which cannot provide a reference standard for subsequent construction, seriously threatening the construction and safety of deep buried tunnel projects. Therefore, by considering the emerging multiple indicators and taking different geological units of the same tunnel as the benchmark, the dynamic and fine classification of rockburst grades by multiple indicators can provide valuable rockburst information. Summary of the invention

[0005] A technical problem to be solved by the present disclosure is that the existing classification of rockburst grades according to the depth of the explosion pit and the rock strength stress ratio is too rough, and the research work on the dynamic and fine classification of rockburst grades by multiple indicators is insufficient.

[0006] In order to solve the above technical problems, the present disclosure provides a method for dynamically dividing the rockburst level of a tunnel during the construction phase, which includes:

[0007] S1: Establish a dynamic and fine classification index system for rockburst levels;

[0008] The index system includes: blast pit damage depth, blast pit damage length, blast rock thickness, blast rock shape, blast rock movement characteristics, sound characteristics, rock structure surface integrity, rock rupture duration, support damage degree, structural surface occurrence and free surface characteristics, structural surface group number and spacing, rock strength stress ratio;

[0009] S2: Divide different geological units according to geological forecasts, on-site drilling and excavation conditions, and collect rockburst events;

[0010] S3: Based on the data of each indicator of rock burst events in S2, calculate the objective data weight and subjective experience weight of each indicator.

[0011] Among them, objective data weights can be obtained through CRITIC weights and entropy weights, and subjective experience weights can be obtained through AHP weights and DEMATEL weights;

[0012] S4: Based on the objective data weights and subjective experience weights in S3, the combined weights are calculated using game theory methods;

[0013] S5: The ranking method of approximating ideal solutions is used in combination with the combined weights in S4 to make a relative evaluation of the level of the first rockburst event in the same geological unit;

[0014] S6: Based on the variable weight theory and the unascertained attribute measurement theory, the variable weight function of the rock burst event and the unascertained attribute measurement function of each index in the rock burst event are obtained;

[0015] S7: Based on the combined weights of various indicators of the first rockburst event in the same geological unit, the dynamic weights of various indicators of the remaining rockburst events in the same geological unit are calculated to achieve dynamic evaluation of the rockburst event level in the same geological unit.

[0016] In some embodiments, in the aforementioned method for dynamically dividing rockburst levels of tunnels during construction, the variable weight function and the unascertained attribute measurement function in S6 are specifically:

[0017] S61. Using variable weight theory, establish the state variable weight function S(x) and the index variable weight function W(x)

[0018]

[0019] Among them, x needs to be processed in the indicator direction, positive indicators are processed positively, and negative indicators are processed reversely. 0 For indicators, constant weight; c=0.2,b=0.25,

[0020]

[0021]

[0022] Among them, x 轻 The indicator value representing the upper limit of minor rockburst, x 中 The index value representing the upper limit of moderate rockburst, x 强 The index value representing the upper limit of strong rock burst, x 事件 The index value representing a rockburst event within the same geological unit;

[0023] S62. Using the unascertained attribute measurement theory, establish the unascertained attribute measurement function of each index of rock burst event;

[0024] Among them, the unknown attribute measurement function of the blast pit damage depth is:

[0025]

[0026] The unascertained attribute measurement function of the blast crater damage length is:

[0027]

[0028]

[0029] The unknown attribute measurement function of the thickness of the blasted rock block is:

[0030]

[0031] The unascertained attribute measurement function of the motion characteristics of the blasting rock mass is:

[0032]

[0033] The unascertained attribute measurement function of the support damage degree is:

[0034]

[0035]

[0036] The unascertained attribute measurement function of rock strength stress ratio is:

[0037]

[0038] In some embodiments, in the aforementioned method for dynamically dividing the rockburst level of a tunnel during the construction phase, the qualitative indicators in the indicator system are: the shape of the blasted rock blocks, the sound characteristics, the integrity of the rock structure surface, the duration of rock mass rupture, the occurrence of the structure surface and the characteristics of the free surface; the quantitative indicators are: the depth of the blast pit damage, the length of the blast pit damage, the thickness of the blasted rock blocks, the movement characteristics of the blasted rock blocks, the degree of support damage, the number and spacing of the structure surface groups, and the rock strength stress ratio;

[0039] Among them, quantitative indicators use real data, and except for the number and spacing of structural surface groups, the other indicators need to construct unascertained attribute measurement functions; qualitative indicators are determined by mathematical fuzzy method. At the same time, qualitative indicators and the number and spacing of structural surface groups do not need to construct single indicator unascertained attribute measurement functions. The unascertained attribute measurement is represented by 0 or 1 to calculate the single indicator evaluation matrix.

[0040] In some embodiments, in the aforementioned method for dynamically dividing the rockburst level of a tunnel during the construction phase, the quantitative index takes the upper limit value of different rockburst levels; wherein the rockburst levels include: slight rockburst, moderate rockburst and severe rockburst.

[0041] In some embodiments, in the aforementioned method for dynamically dividing rockburst levels of tunnels during construction, the calculation method of S7 includes:

[0042] S71: Using the game theory algorithm, calculate the combined weights of various indicators for the first rockburst event in the same geological unit;

[0043] S72: Calculate the dynamic weights of the remaining rockburst events in the same geological unit according to the indicator variable weight function W(x);

[0044] S73: According to the established unascertained attribute measurement function of each index of rockburst grade classification, the unascertained attribute measurement of each index of rockburst grade classification is calculated, and the comprehensive attribute measurement μ can be obtained by weighted summation of dynamic weight and unascertained attribute measurement ik , attribute identification is performed according to the confidence criterion to achieve dynamic evaluation of the rockburst event level within the same geological unit.

[0045] In some embodiments, the aforementioned method for dynamically dividing the rockburst level of a tunnel during the construction phase, wherein the entropy method weight and the AHP method weight in S3 are used to reflect the contribution of each indicator in the system, and the CRITIC method weight and the DEMATEL weight are used to reflect the mutual influence between the indicators.

[0046] In some embodiments, in the aforementioned method for dynamically dividing the rockburst level of a tunnel during the construction phase, the subjective experience weight in S3 is obtained by multiplying the weight of the AHP method and the weight of the DEMATEL method to one.

[0047] Through the above technical scheme, the present invention provides a method for dynamically dividing the rockburst level of a tunnel during the construction phase. By establishing a dynamic and fine division index system for rockburst levels and dividing different geological units according to the actual situation on site, rockburst events and sample data of various indicators of rockburst events are collected. The data collected by multiple indicators can be evaluated more accurately than the traditional single indicator judgment method, and the subjective weight and objective weight are calculated based on this, and the combined weight of each indicator is calculated using the game theory method. Finally, the approximate ideal solution sorting method is used to realize the relative evaluation of the first rockburst event level of the same geological unit, and then based on the variable weight theory and the unascertained attribute measurement theory, a variable weight function suitable for rockburst events and an unascertained attribute measurement function for each indicator of rockburst level division are proposed. Based on the combined weights of each indicator of the first rockburst event in the same geological unit, the dynamic weights of each indicator of the remaining rockburst events in the same geological unit are calculated, and the dynamic evaluation of the rockburst event level in the same geological unit is realized, which can systematically and comprehensively divide the rockburst level of the construction phase. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0049] Figure 1 A schematic diagram of a flow chart of a method for dynamically dividing rockburst levels of tunnels during construction provided by an embodiment of the present invention;

[0050] Figure 2 A dynamic classification index system for rockburst levels in tunnels during construction provided by an embodiment of the present invention;

[0051] Figure 3 A TSP division diagram of different geological units provided by an embodiment of the present invention;

[0052] Figure 4 Parameter charts of different geological units provided for embodiments of the present invention;

[0053] Figure 5 A microscopic geological distribution map of a macroscopic geological unit provided in an embodiment of the present invention;

[0054] Figure 6 The state variable weight function S(x) and image provided by the embodiment of the present invention. DETAILED DESCRIPTION

[0055] The following is a further detailed description of the embodiments of the present disclosure in conjunction with the accompanying drawings and examples. The detailed description of the following embodiments and the accompanying drawings are used to exemplarily illustrate the principles of the present disclosure, but cannot be used to limit the scope of the present disclosure. The present disclosure can be implemented in many different forms and is not limited to the specific embodiments disclosed herein, but includes all technical solutions that fall within the scope of the claims.

[0056] The present disclosure provides these embodiments to make the present disclosure thorough and complete, and to fully express the scope of the present disclosure to those skilled in the art. It should be noted that unless otherwise specifically stated, the steps, numerical expressions and numerical values ​​set forth in these embodiments should be interpreted as merely exemplary, and not as limiting.

[0057] All terms used in the present disclosure have the same meanings as understood by one of ordinary skill in the art to which the present disclosure belongs, unless specifically defined otherwise.

[0058] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered part of the specification.

[0059] Embodiment 1

[0060] S1. Through investigation, research and reference, a dynamic and detailed rockburst classification index system is established during the construction phase. Figure 2 The qualitative indicators are: the shape of the blasting rock blocks, the sound characteristics, the integrity of the rock structure surface, the duration of rock mass rupture, the occurrence of the structure surface and the characteristics of the air surface; the quantitative indicators are: the depth of blasting pit damage (m), the length of blasting pit damage (m), the thickness of the blasting rock blocks (cm), the movement characteristics of the blasting rock blocks (m / s), the degree of support damage (T / h), the number and spacing of the structure surface groups, and the rock strength stress ratio; the quantitative indicators use real sample data; the qualitative indicators can be determined by mathematical fuzzy method, and the value 1 represents a slight rock burst, 2 represents a moderate rock burst, 3 represents a strong rock burst, and 4 represents an extremely strong rock burst.

[0061] S2. Use TSP seismic wave exploration to divide geological units. Take the H3DK2+019.8~H3DK1+909.8 rock burst section as an example to divide geological units. Figure 3-Figure 5The tunnel face seen in this forecast shows that the surrounding rock is metamorphic granulite and tonalite, which is weakly weathered, relatively intact and hard. There is no water on the tunnel face, and the tunnel face has good self-stability. The TSP prediction conclusions are divided into 10 geological units, including H3DK2+020~H3DK1+996, H3DK1+996~H3DK1+992, H3DK1+992~H3DK1+985, H3DK1+985~H3DK1+983, H3DK1+983~H3DK1+976, H3DK1+976~H3DK1+968, H3DK1+968~H3DK1+942, H3DK1+942~H3DK1+930, H3DK1+930~H3DK1+917, and H3DK1+917~H3DK1+910.

[0062] S3. First, establish the original database, as shown in Table 1 below, where the number and spacing of structural surface groups and rock strength stress ratio are positive indicators, and the others are negative indicators. The larger the indicator, the higher the rock burst level. The subjective experience weight vector of this index system can be obtained by calculating the AHP weight and DEMATEL weight: W 1 ={0.3323,0.0768,0.0704,0.0199,0.0443,0.0060,0.0363,0.0038,0.2644,0.0272,0.0227,0.0959}; The objective data weight can be obtained by the CRITIC method weight and the entropy method weight. At the same time, referring to the national, industry and enterprise standards, in the classification of rock burst levels, the upper critical value of the rock burst level and the measured data of the rock burst case indicators are regarded as the TOPSIS (top-up ideal solution ranking method) relative evaluation scheme;

[0063] Table 1 Original database of first rockburst indicators in the same geological unit

[0064]

[0065]

[0066] Among them, m is the number of evaluation objects; n is the number of evaluation indicators; x ij It represents the jth index of the i-th evaluation object. At the same time, the number and spacing of structural surface groups and rock strength stress ratio are positive indicators, and the others are negative indicators. The larger the index, the higher the rock burst level. The processing of positive and negative indicators is shown in the following formula:

[0067] Positive indicators are processed positively:

[0068]

[0069] Negative indicator reversal processing:

[0070]

[0071] Normalize the original rockburst evaluation matrix X to obtain X * ij

[0072]

[0073] Calculate the objective data weight vector W of the indicator according to the entropy method 2 ={0.0673,0.0662,0.0970,0.0847,0.1571,0.0749,0.0749,0.0749,0.0670,0.0749,0.0749,0.0864} and the objective data weight vector W of the CRITIC method 3 ={0.0500,0.0514,0.1513,0.1674,0.1217,0.0641,0.0641,0.0641,0.0594,0.0641,0.0641,0.0786}, and game theory is used to calculate the combined weight w* of subjective and objective weights.

[0074]

[0075] Solve (α 1 ,α 2 ,…,α L ), and normalized

[0076]

[0077] Finally, the combined weight w* is obtained:

[0078]

[0079] From this we can get

[0080]

[0081] The solution of the linear equation system is obtained: α 1 =0.9792,α 2 =-1.2572,α 3 =1.4416 After normalization, we can get:

[0082]

[0083] Finally, the combined weight vector w*={0.27, 0.06, 0.14, 0.13, 0.02, 0.00, 0.03, 0.00, 0.22, 0.02, 0.02, 0.08} is obtained.

[0084] S4. Combine the combined weights of each evaluation index with the TOPSIS method to establish a combined weighted TOPSIS evaluation system. * ij Multiply it with the combination weight to get the weighted normalized matrix V.

[0085]

[0086] Select the maximum value of each evaluation index to form the "positive ideal solution v + ={0.27,0.06,0.14,0.13,0.02,0,0.03,0,0.22,0.02,0.02,0.08}”, the minimum value constitutes the “negative ideal solution v － ={0,……,0}".

[0087] Calculate the distance between the evaluation object and the positive and negative ideal solutions, that is, the Euclidean distance, as shown in the following formula:

[0088]

[0089] The Euclidean distance between the evaluation object and the positive and negative ideal solutions is calculated by the formula, D + 轻微岩爆临界 =0, D + 中等岩爆临界 =0.12, D + 强烈岩爆临界 =0.39, D + 首次岩爆 =0.21; D - 轻微岩爆临界 =0.42, D - 中等岩爆临界 =0.31, D - 强烈岩爆临界 =0.05, D - 首次岩爆 =0.31.

[0090] And calculate the closeness C i , as shown below,

[0091]

[0092] So, C i ∈(0,1),C 轻微岩爆临界 =1.0000,C 中等岩爆临界 =0.7222,C 强烈岩爆临界=0.1216. The larger the relative closeness C value, the closer the evaluation case is to the positive ideal solution, and the smaller the rockburst level of this event; the smaller the C value, the closer the evaluation case is to the negative ideal solution, and the larger the rockburst level. According to the critical values ​​of different rockburst levels C, the rockburst level of a rockburst event is systematically evaluated by interpolation method, and it is re-ranked to obtain the relative evaluation of the first rockburst level of the same geological unit, as shown in Table 2 below.

[0093] Table 2 Closeness C of the first rockburst case in the same geological unit

[0094] Case C Value Rockburst grade ranking Rockburst level First rock burst 0.5989 1 Strong rock burst

[0095] When dynamically evaluating the rockburst level of the same geological unit, the original database of the second rockburst of the same geological unit is established in combination with the calculation of the first rockburst event, such as Figure 1 and as shown in Table 3 below.

[0096] Table 3 The original database of the second rockburst index of the same geological unit

[0097]

[0098]

[0099]

[0100] In the formula, m is the number of evaluation objects; n is the number of evaluation indicators; x ij Represents the jth indicator of the i-th evaluation object.

[0101] The original evaluation matrix X of the second rockburst is normalized, the positive index is positively processed, and the negative index is reversed. Refer to formula (31) (32), where the number and spacing of structural surface groups and rock strength stress ratio are positive indicators, and the others are negative indicators. That is, the larger the index, the higher the rockburst grade. X is obtained. * ij

[0102]

[0103] Finally, from formula (3-5), we can get

[0104] μ={1,...,1}; λ={0.80,0.81,0.57,0.50,0.56,0.50,0.50,0.50,0.75,0.50,0.50,0.33};

[0105] α={0,……,0}; let c={0.2,……,0.2}; b={0.25,……,0.25}, then a={0.65,0.68,0.38,0.35,0.38,0.35,0.35,0.35,0.35,0.55,0.35,0.35,0.3}, all satisfy

[0106] The combined weights of the first rockburst event indicators of the same geological unit are known, w* = {0.27, 0.06, 0.14, 0.13, 0.02, 0.00, 0.03, 0.00, 0.22, 0.02, 0.02, 0.08}, and the formula (1) and the attached Figure 6 The state variable weight function value of each index of the second rockburst can be obtained as S(xsecond rockburst)={0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.25, 0.2, 0.2, 0.25, 0.2}; The dynamic weight of each index of the second rockburst can be obtained as W(xsecond rockburst)={0.27, 0.06, 0.14, 0.13, 0.02, 0, 0.03, 0, 0.22, 0.02, 0.02, 0.08} by formula (2);

[0107] According to the rockburst index unascertained attribute measurement function (Equations 6 to 29), the unascertained attribute measurement value μ of each index is calculated respectively. ijk and comprehensive attribute measure μ ik (Formula 39) and fill in the following Table 4,

[0108]

[0109] Where: w j is the dynamic weight of each index of the second rockburst.

[0110] Attribute recognition is performed according to the confidence criterion. The confidence λ is generally taken as 0.6 to 0.7. The confidence λ is taken as 0.65 in this paper based on the relevant literature. 1 ,D 2 ,…,D 4} are ordered, and D 1 >D 2 >…>D 4 , then D 1 It is a minor rock burst, D 2 For medium rock burst, D 3 For strong rock burst, D 4 It is an extremely strong rock burst;

[0111] Where k is an integer, then the rockburst event is considered to belong to the kth evaluation category D k .

[0112] Table 4 Second rockburst index attribute measurement table

[0113]

[0114]

[0115] The attribute identification result is determined by the above formula (40), 0.71>0.65, so the comprehensive attribute measurement of the rock burst event is D 1 Level, that is, slight rock burst; if the comprehensive attribute measure μ ik Zhong Ruoμ i1 If it is greater than 0.65, it is D 1 Level; if μ i1 is less than 0.65, while μ i1 and μ i2 If the sum is greater than 0.65, then it is D 2 That is, medium rock burst; if μ i1 and μ i2 The sum is less than 0.65, and μ i1 , μ i2 and μ i3 If the sum is greater than 0.65, then it is D 3 It is a strong rock burst; if μ i1 , μ i2 and μ i3 The sum is less than 0.65, and μ i1 , μ i2 , μ i3 and μ i4 If the sum is greater than 0.65, then it is D 4 That is an extremely strong rock burst.

[0116] So far, various embodiments of the present disclosure have been described in detail. In order to avoid obscuring the concept of the present disclosure, some details known in the art are not described. Based on the above description, those skilled in the art can fully understand how to implement the technical solution disclosed here.

[0117] Although some specific embodiments of the present disclosure have been described in detail by way of examples, it should be understood by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the present disclosure. It should be understood by those skilled in the art that the above embodiments may be modified or some technical features may be replaced by equivalents without departing from the scope and spirit of the present disclosure. In particular, the various technical features mentioned in the various embodiments may be combined in any manner as long as there is no structural conflict.

Claims

1. A method for dynamically classifying rockburst levels in tunnels during construction, characterized in that: include: S1: Establish a dynamic and fine classification index system for rockburst levels; The index system includes: blast pit damage depth, blast pit damage length, blast rock thickness, blast rock shape, blast rock movement characteristics, sound characteristics, rock structure surface integrity, rock rupture duration, support damage degree, structural surface occurrence and free surface characteristics, structural surface group number and spacing, rock strength stress ratio; S2: Divide different geological units according to geological forecasts, on-site drilling and excavation conditions, and collect rockburst events; S3: Based on the data of each indicator of rock burst events in S2, calculate the objective data weight and subjective experience weight of each indicator. Among them, objective data weights can be obtained through CRITIC weights and entropy weights, and subjective experience weights can be obtained through AHP weights and DEMATEL weights; S4: Based on the objective data weights and subjective experience weights in S3, the combined weights are calculated using game theory methods; S5: The ranking method of approximating ideal solutions is used in combination with the combined weights in S4 to make a relative evaluation of the level of the first rockburst event in the same geological unit; S6: Based on the variable weight theory and the unascertained attribute measurement theory, the variable weight function of the rock burst event and the unascertained attribute measurement function of each index in the rock burst event are obtained; S7: Based on the combined weights of various indicators of the first rockburst event in the same geological unit, the dynamic weights of various indicators of the remaining rockburst events in the same geological unit are calculated to achieve dynamic evaluation of the rockburst event level in the same geological unit.

2. A method for dynamically dividing rockburst levels of tunnels during construction according to claim 1, characterized in that: The variable weight function and unascertained attribute measurement function in S6 are specifically: S61. Using variable weight theory, establish the state variable weight function S(x) and the index variable weight function W(x) Among them, x needs to be processed in the indicator direction, positive indicators are processed positively, and negative indicators are processed reversely. 0 For indicators, constant weight; c=0.2,b=0.25, Among them, x 轻 The indicator value representing the upper limit of minor rockburst, x 中 The index value representing the upper limit of moderate rockburst, x 强 The index value representing the upper limit of strong rock burst, x 事件 The index value representing a rockburst event within the same geological unit; S62. Using the unascertained attribute measurement theory, establish the unascertained attribute measurement function of each index of rock burst event; Among them, the unknown attribute measurement function of the blast pit damage depth is: The unascertained attribute measurement function of the blast crater damage length is: The unknown attribute measurement function of the thickness of the blasted rock block is: The unascertained attribute measurement function of the motion characteristics of the blasting rock mass is: The unascertained attribute measurement function of the support damage degree is: The unascertained attribute measurement function of rock strength stress ratio is:

3. A method for dynamically dividing rockburst levels of tunnels during construction according to claim 1, characterized in that: The qualitative indicators in the index system are: the shape of the blasting rock blocks, the sound characteristics, the integrity of the rock mass structural surface, the duration of rock mass rupture, the occurrence of the structural surface and the characteristics of the free surface; the quantitative indicators are: the depth of the blasting pit, the length of the blasting pit, the thickness of the blasting rock blocks, the movement characteristics of the blasting rock blocks, the degree of support damage, the number and spacing of the structural surface groups, and the rock strength stress ratio; Among them, quantitative indicators use real data, and except for the number and spacing of structural surface groups, the other indicators need to construct unascertained attribute measurement functions; qualitative indicators are determined by mathematical fuzzy method. At the same time, qualitative indicators and the number and spacing of structural surface groups do not need to construct single indicator unascertained attribute measurement functions. The unascertained attribute measurement is represented by 0 or 1 to calculate the single indicator evaluation matrix.

4. A method for dynamically dividing rockburst levels of tunnels during construction according to claim 3, characterized in that: The quantitative index takes the upper limit value of different rock burst levels; Among them, rock burst levels include: minor rock burst, moderate rock burst and severe rock burst.

5. A method for dynamically dividing rockburst levels of tunnels during construction according to claim 2, characterized in that: The calculation method of S7 includes: S71: Using the game theory algorithm, calculate the combined weights of various indicators for the first rockburst event in the same geological unit; S72: Calculate the dynamic weights of the remaining rockburst events in the same geological unit according to the indicator variable weight function W(x); S73: According to the established unascertained attribute measurement function of each index of rockburst grade classification, the unascertained attribute measurement of each index of rockburst grade classification is calculated, and the comprehensive attribute measurement μ can be obtained by weighted summation of dynamic weight and unascertained attribute measurement ik , attribute identification is performed according to the confidence criterion to achieve dynamic evaluation of the rockburst event level within the same geological unit.

6. A method for dynamically dividing rockburst levels of tunnels during construction according to claim 1, characterized in that: The entropy weight and AHP weight in S3 are used to reflect the contribution of each indicator in the system, and the CRITIC weight and DEMATEL weight are used to reflect the mutual influence between the indicators.

7. A method for dynamically dividing rockburst levels of tunnels during construction according to claim 1, characterized in that: The subjective experience weight in S3 is obtained by multiplying the AHP weight and the DEMATEL weight.

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