CN112837182A

CN112837182A - Method for evaluating safety and stability of shield tunneling

Info

Publication number: CN112837182A
Application number: CN202011587527.0A
Authority: CN
Inventors: 王伟; 高成梁; 刘华南; 徐亮; 郎秋玲; 郭玉峰; 郭航; 王兴; 马鹏达
Original assignee: Changchun Institute of Applied Chemistry of CAS
Current assignee: Changchun Institute of Applied Chemistry of CAS; Changchun Institute Technology
Priority date: 2020-12-29
Filing date: 2020-12-29
Publication date: 2021-05-25

Abstract

The invention provides a method for evaluating safety and stability of shield tunneling, which comprises the following steps: the method comprises the following steps: selecting evaluation indexes of straight line segments of the shield interval, and acquiring comprehensive weight vectors W of the evaluation indexes based on comprehensive weight calculation of a game theory; step two: constructing an extension cloud matrix according to the evaluation index; step three: and judging the shield tunneling safety level of each monitoring point according to the comprehensive weight vector W of the evaluation index and the scalable cloud matrix. The method provided by the invention comprehensively weights the subjective weight and the objective weight of the evaluation index calculated by the analytic hierarchy process and the entropy method by using the decision model constructed by the game theory, so that the evaluation result considers the subjective factor and accords with the objective rule, and the extension cloud model for evaluating the shield tunneling stability is constructed based on the matter element theory, and can fully reflect the uncertainty relation among the shield construction safety influence factors and improve the accuracy of the evaluation result.

Description

Method for evaluating safety and stability of shield tunneling

Technical Field

The invention relates to the technical field of civil engineering, in particular to a method for evaluating safety and stability of shield tunneling.

Background

When the subway interval construction is carried out on a sandy gravel stratum, the stratum is lost due to the change of the stratum stress state caused by shield tunneling, so that the soil stability of the tunnel face is influenced, the ground surface can be sunk in a large area in serious conditions, and the surrounding environment is greatly influenced. Therefore, the accurate evaluation of the shield tunneling safety and stability is the key for reducing the risk of safety accidents and ensuring the smooth construction. Scholars at home and abroad carry out a great deal of research on the analysis and evaluation of the shield construction risk of the subway tunnel. Isaksson^[1]A tunnel construction risk analysis method based on a reliability theory is provided; eskesen^[2]A whole set of reference standards and risk assessment technology in the whole life cycle of the tunnel and the underground engineering are provided; lihui et al^[3]Combining a layer analysis method and a fuzzy comprehensive evaluation method, and providing a construction stage risk evaluation method for a subway tunnel adjacent to an existing building; wu Shen et al^[4]The safety risk evaluation is carried out on the buildings around the shield tunnel construction by adopting the material element theory and the evidence theory; ren Qiang (strengthening of the kidney)^[5]Evaluating the safety risk of the shield construction of the four-line of the Beijing subway by using an R ═ P multiplied by C grading method; ren Jian xi, etc^[6]A shield construction analysis and evaluation system under the condition of adjacent buildings is established by adopting a fuzzy comprehensive evaluation method, and shield tunneling is carried out on a certain section of the third line of the Xian subwayEvaluating the risk level; huchangming et al^[7]Establishing a risk extension evaluation model for the subway shield construction of the soft soil stratum by applying an extension theory; cluster crystal^[8]Weighting the safety evaluation indexes of the subway shield construction by using a structure entropy weight method, and constructing a subway shield construction safety evaluation model based on a gray comprehensive evaluation method; liu dun weng and so on^[9]Providing a shield tunnel safety evaluation method based on a cloud model theory; yang equal^[10]The safety of shield construction in the peat soil is evaluated by utilizing a cloud model and an improved entropy weight method. Although the research has a certain effect in the evaluation of the subway shield construction risk and the safety, the used evaluation method has obvious defects in the aspect of analyzing uncertainty problems, the empowerment subjectivity of some methods is larger, the calculation precision of some methods is not high due to limited samples, and the calculation process of some methods is complex and is not beneficial to the grasping of construction technicians.

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WU Xian-guo,FENG Zong-bao,QIN Wen-wei,et al.Risk assessment of adjacent buildings induced by shield tunneling construction based on matter-element theory and extension theory[J].Railway Standard Design, 2020,64(04):104-110.

[5] Beijing subway shield construction risk evaluation and control technology research [ D ]. China geological university, 2010.

REN Qiang.Study on risk evaluation and control technology of shielding construction of Beijing underground[D],China University of Geosciences,2010

[6] Nippon construction, Yangfeng, Zhuyuan Wei, Xian subway shield construction risk assessment under the condition of adjacent buildings [ J ] railway engineering report, 2016,33(07):88-93.

REN Jian-xi,YANG Feng,ZHU Yuan-wei.The risk assessment of shield construction under the condition of adjacent buildings in Xi’an metro[J].Journal of Railway Engineering Society,2016,33(07):88-93.

[7] Researches on extension evaluation methods of shield construction risks of soft soil layer subway in Huchangming, Congestion, Meiyuan, and the like [ J ] safety and environmental science report, 2017,17(01):21-26.

On the risk evaluation of the metro shield construction in the soft soil condition background with the extension method[J].Journal of Safety and Environment,2017,17(01):21-26.

[8] Cluster crystal, subway shield construction safety evaluation research based on structure entropy weight method [ D ]. university of northeast finance, 2016.

CONG Jing.A study of metro shield construction safety evaluation based on structure entropy weight method[D]. Dongbei University of Finance and Economics,2016.

[9] Liu Tun, Jia Hao fire, Zhou sing Xiao, etc. Shield tunnel excavation face stability evaluation based on cloud model [ J ]. Beijing university of transportation report, 2019,43(03):43-49.

LIU Dun-wen,JIA Hao-ran,ZHOU Chang-xiao,et al.Stability evaluation of excavation face of shield tunnel based on cloud model[J].Journal of Beijing Jiaotong University,2019,43(03):43-49.

[10] Yang Zhong, Ruanyun fen, Chen Zhao Hui, etc. based on the cloud model, the shield construction safety level [ J ] is evaluated, and the report on the water conservancy and building engineering, 2019,17(03): 150-.

YANG Yun,RUAN Yong-fen,CHEN Zhao-hui,et al.Evaluation of shield construction safety classes based on cloud model[J].Journal of Water Resources and Architectural Engineering,2019,17(03):150-154.

[11] Boy beauty, game theory and its application [ M ]. shanghai, university of finance and publishing, 2015.

[12] Comprehensive evaluation technology of leaf-meaning, Kolihua, Huangde Yu, System and its application [ M ]. Beijing, Metallurgical Press, 2006.

[13] Yangchun, Chuiwen, science [ M ]. Beijing, scientific Press, 2014.

[14] Litdereli, du\40546. uncertain artificial intelligence [ M ]. beijing, national defense industrial press, 2005.

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[16] Shenshiwei, Saujunchen, Dajun, etc. the entropy value empowerment method-based jointed rock mass tunnel blasting quality extension evaluation [ J ] civil engineering report, 2013, 46(12):118-126.

SHEN Shi-wei,XU Jun-chen,DAI Shu-lin,et al.Extenics evaluation of joint rock tunnel blasting quality based on entropy weighting method[J].China Civil Engineering Journal,2013,46(12):118-126.

[17] For example, Han Minchun, Game theory [ M ]. Wuhan, Wuhan university Press, 2006.

[18] China department of housing and urban and rural construction, urban rail transit engineering monitoring technical Specification GB50911-2013[ S ]. Beijing, China building industry Press, 2013.

[19] China department of housing and urban and rural construction, urban rail transit engineering measurement Specification GB/T50308-.

[20] The shield tunnel construction and acceptance standard of housing of the people' S republic of China and Ministry of urban and rural construction is GB50446-2017[ S ]. Beijing, China society for the development of building industry, 2017.

Disclosure of Invention

The invention aims to overcome the defects in the prior art and provides a comprehensive evaluation method based on the combination of a game theory and an extensible cloud model.

A shield tunneling safety and stability evaluation method comprises the following steps:

the method comprises the following steps: selecting evaluation indexes of straight line segments of the shield interval, and calculating a combined weight based on a game theory to obtain a comprehensive weight vector W of the evaluation indexes;

step two: constructing an extension cloud matrix according to the evaluation index;

step three: and judging the shield tunneling safety level of each monitoring point according to the comprehensive weight vector W of the evaluation index and the scalable cloud matrix.

Further, according to the method for evaluating the safety and stability of shield tunneling, the evaluation indexes include: and 5 evaluation indexes of surface settlement, building settlement, river bank settlement, pipeline settlement and segment deformation are provided.

Further, according to the method for evaluating the safety and stability of shield tunneling, the first step includes the following steps:

step 11: supposing that the object to be evaluated has n evaluation indexes, determining the weight of each index by adopting m weighting methods to obtain a weight vector W_k；

W_k＝(W_k1,W_k2,L,W_kn),k＝(1,2,L,m)

Step 12: according to the weight vector W_kDetermining a weight set W of the index to be evaluated;

in the formula: w_kA set of basis weight vectors; alpha is alpha_kIs a linear combination weight coefficient;

step 13: in the above formula, alpha_kAnd performing optimization solution to minimize the deviation between the weight set and each weight vector, and constructing a countermeasure model as follows:

step 14: optimizing a linear equation set of a first derivative condition of the strategy model according to the strategy model to obtain a linear combination weight coefficient vector alpha_kI.e., (α)₁，α₂，…，α_m)

Step 15: for the linear combination weight coefficient vector alpha_kCarrying out normalization processing to obtain a comprehensive weight vector W;

further, according to the method for evaluating the safety and stability of shield tunneling, the second step includes the following steps:

step 21: according to the calculation method of objective weight, determining the entropy e of each evaluation index_jCoefficient of difference g_jAnd entropy weight w_j；

Step 22: according to a subjective weight calculation method, a judgment matrix of evaluation indexes is constructed, the subjective weight of each evaluation index is calculated, and the calculation result is subjected to normalization test;

step 23: according to the safety and stability judgment standard of each evaluation index and the entropy value e_jCoefficient of difference g_jAnd entropy weight w_jDetermining expected Ex, entropy En and super-entropy He;

step 24: constructing an extension cloud model R according to the expected Ex, the entropy En and the super entropy He and the matter element theory₀；

Step 25: root of herbaceous plantAccording to the extension cloud model R₀Constructing an extensible cloud matrix;

calculating the relevance between the sample to be evaluated and each index of the safety level based on a composite cloud model, namely, generating a normal random number En' calculated by taking En as a mean value and He as a standard deviation by using Matlab, and making a deterministic value in the sample to be evaluated be x_iCloud entropy of (x)_i，μ_i). The correlation is calculated as follows:

constructing a cloud matrix Q according to the relevance, as shown in the following formula:

further, according to the method for evaluating the safety and stability of shield tunneling, the third step includes the following steps:

step 31: calculating a comprehensive extension cloud evaluation matrix of the extension cloud matrix according to the following formula based on a comprehensive weight vector W determined by a game theory method;

wherein, b_ijEvaluating the component of the matrix B for comprehensive extension cloud, namely representing the comprehensive certainty degree of a certain sample corresponding to a certain index;

step 32: accumulating the certainty degrees of the same grade according to the comprehensive extension cloud evaluation matrix to obtain the certainty degrees of each monitoring point under each grade;

step 33: and judging the shield tunneling safety level of each monitoring point according to the maximum certainty principle.

Further, in the method for evaluating the safety and stability of shield tunneling, the step 21 includes:

supposing m waits by using entropy methodTest sample composition evaluation object set { A }_iN index data form an index set { X ═ 1, 2, …, m_jJ ═ 1, 2, …, n), where x_ijRepresenting the original value of the jth index of the ith sample to be tested;

the proportion y occupied by different quantities in different indexes is obtained after standardization treatment_ijThe formed standard matrix Y is shown as a formula (1); proportion y of quantity j in index i_ijIs calculated as shown in equation (2), the entropy e of any index is calculated as shown in equation (3):

Y＝(y_ij)_m×n,(i＝1,2,L,m；j＝1,2,L,n) (1)

k in the formula (3) is related to the number m of samples of the system and is constant; when the degree of order is 0, the entropy value is maximum, namely e is 1; when m samples are in a completely disordered distribution, y_ijAt 1/m, the entropy value at this time is zero for the utility value of the overall evaluation, and therefore, the difference coefficient g of the j-th index_jThe difference between the entropy value of the index and 1 is determined, as shown in formula (4):

g_j＝1-e_j (j＝1,2,L,n) (4)

the essence of estimating the index weight by the entropy method is to calculate by using a value coefficient of the index information, wherein the higher the value coefficient is, the greater the importance of the value coefficient is; weight w of j-th index_jAs shown in formula (5):

further, in the method for evaluating the safety and stability of shield tunneling as described above, the step 22 includes:

firstly, determining a shield tunneling safety and stability evaluation standard;

secondly, calculating the expected Ex, the entropy En and the super-entropy He of the evaluation index according to the shield tunneling safety and stability evaluation standard;

Ex＝(C_max+C_min)/2

En＝(C_max-C_min)/6

He＝s

in the formula: c_max、C_minS is a constant, which is the maximum and minimum boundary values of a certain grade of a certain evaluation index in the evaluation criterion.

Has the advantages that:

the method provided by the invention comprehensively weights the evaluation indexes by using the game theory, the analytic hierarchy process and the entropy method, so that the evaluation result not only considers subjective factors but also accords with objective rules, and an extendable cloud model for evaluating shield tunneling stability is constructed based on the matter element theory, and the model can fully reflect the uncertain relation among shield construction safety influence factors and improve the accuracy of the evaluation result.

Drawings

FIG. 1 is a schematic diagram of the position and direction of a shield zone;

FIG. 2 shows pebbles in a shield zone;

FIG. 3(a) is a cloud drop map of surface subsidence;

FIG. 3(b) is a cloud drop diagram of building settlement;

FIG. 3(c) is a river levee settlement cloud drop diagram;

FIG. 3(d) is a cloud drop diagram of pipeline settlement;

fig. 3(e) is a segment deformation cloud drop diagram.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention are described clearly and completely below, and it is obvious that the described embodiments are some, not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The invention provides a method for evaluating safety and stability of shield tunneling, which comprises the following steps:

the method comprises the following steps: selecting evaluation indexes of straight line segments of the shield interval, and calculating comprehensive weight based on game theory to obtain comprehensive weight vectors W of the evaluation indexes;

Specifically, firstly, based on the combined weight calculation of the game theory, subjective weighting adopted singly can cause the evaluation result to deviate from the reality due to the influence of subjective factors, and objective weighting adopted singly cannot reflect the comprehensiveness of the evaluation result. The comprehensive weighting based on the game theory can exactly solve the weighting problem objectively, reasonably and scientifically.

And secondly, establishing an extensible cloud model, wherein the extensible cloud theory can couple the object element model with the cloud model, and the cloud model is analyzed by using the object element theory. The uncertainty mathematical model for researching the object elements and the transformation thereof on the basis of the object element theory and the extension set in the extensibility and qualitatively and quantitatively converting the objective objects in the cloud model is comprehensively used to more accurately evaluate the advantages and disadvantages and the feasibility of the research objects.

And finally, calculating the certainty of the evaluation index based on the comprehensive evaluation matrix of the extension cloud to obtain a result, calculating the comprehensive evaluation matrix of the extension cloud, accumulating the certainty of the same grade to obtain the certainty of each monitoring point under each grade, and judging the shield tunneling safety grade of each monitoring point according to the maximum certainty principle.

The invention deals with the game theory^[11]Entropy method^[12]Evaluation of extension^[13]And cloud model^[14]The method is combined to construct a comprehensive evaluation model.

1 cloud extension principle

1.1 cloud model

The cloud model is made by the Ledeyi instituteThe uncertainty mathematical model for qualitative and quantitative conversion of objective things is usually made up of expectation Ex, entropy En and super-entropy He^[15]And (4) equal cloud numerical feature value representation. Where Ex is expected to be the most representative point in the domain space, i.e., the best sample. The entropy En is used for measuring the uncertainty degree of the qualitative concept, is determined by the ambiguity and the randomness of the qualitative concept, and reflects the discreteness of cloud droplets and the value interval of the cloud droplets approved by the qualitative concept. The super-entropy He is the uncertainty of the entropy measure, reflecting the thickness of the cloud droplets. It is desirable that Ex and entropy En are calculated as shown in formulas 1 to 2.

Ex＝(C_max+C_min)/2 (1)

En＝(C_max-C_min)/6 (2)

He＝s (3)

In the formula: c_max、C_minS is a constant, and is the maximum and minimum boundary values of a certain class of criteria.

1.2 the extension theory and extension set is used for evaluating the advantages and disadvantages and feasibility of the research object by researching the object and its transformation theory based on the object theory and extension set, and qualitatively and quantitatively analyzing the object by introducing the object R. The extension evaluation method is one of the main applications of the extension theory, and the theoretical framework of the method is constructed by the matter element theory and the extension mathematics, wherein the matter element is the logical cell and the basic unit of the extension theory^[16]Expressed in the form of an ordered triplet of R ═ { N, c, x }. Wherein N is an evaluation object, c is an index of the evaluation object, and x is a characteristic value of c. The expression of the basic element is shown in formula 4.

1.3 Tuopy cloud model

The extended cloud theory is a method for coupling an object model and a cloud model and analyzing the cloud model by using the object model theory.

An expression of an extensible cloud model constructed based on an extensible cloud theory is shown as a formula 5.

In the formula: r_jIs a unit element, N_jIs the jth evaluation category, c_jIs the jth feature index, x_j＝(Ex_j， En_j，He_j) Is N_jAbout feature c_jA specified magnitude interval.

Assuming that the evaluation category is T, obtaining an n-dimensional composite cloud model R with m evaluation categories in a form of matter elements through actually measured data, wherein the n-dimensional composite cloud model R is shown as a formula 6.

In the formula: t is_j(j ═ 1, 2, …, m) for the j-th assessment category; mu.s_ij(x_ij) Is a corresponding magnitude x_ij(i ═ 1, 2, …, n ═ 1, 2, …, m) degrees of membership; j and i are respectively the serial number and the physical dimension of the evaluation index and the corresponding characteristic value.

Calculating the degree of association between the sample to be evaluated and each index of the safety level based on a composite cloud model, namely, generating a normal random number En' by using Matlab to calculate by taking En as a mean value and He as a standard deviation and making a definite numerical value in the sample to be evaluated be x_iCloud entropy of (x)_i，μ_i). The correlation calculation is shown in equation 7.

And constructing a scalable cloud matrix Q according to the relevance, as shown in a formula 8.

1.4 Risk level determination

When the risk level is determined, the comprehensive certainty matrix B is calculated by multiplying the index weight vector W and the extension cloud matrix Q. And each sample has corresponding certainty factor for each grade, the certainty factors of the same grade are accumulated, and the evaluation grade of the sample is determined according to the maximum certainty factor. The comprehensive certainty matrix is shown in equation 9.

In the formula, b_ijThe component of the integrated certainty matrix B is the integrated certainty that a sample corresponds to an index.

2 game theory empowerment method

2.1 theory of game theory

The game theory is a mathematical method for researching how to select the most reasonable strategy of an individual under the influence of multifactorial conditions, and is also called game theory "^[17]The essence of the method is a mathematical model which adopts mathematical language to express the dependency relationship between the characteristics and the quantity of the object to be evaluated. When an object to be evaluated is influenced by various factors and the influence degrees of the factors are different, the weight values of the evaluation indexes determined by the influence factors are different, and the evaluation result is greatly influenced by the weight of the evaluation index. The evaluation result deviates from reality due to the influence of subjective factors by singly adopting subjective weighting, and the comprehensiveness of the evaluation result cannot be reflected by singly adopting objective weighting. The combined weighting based on the game theory can exactly solve the weighting problem objectively, reasonably and scientifically.

Assuming that the object to be evaluated has n evaluation indexes, the weights of the indexes can be determined by m weighting methods, and the obtained weight vector W_kAs shown in equation 10.

W_k＝(W_k1,W_k2,L,W_kn),k＝(1,2,L,m) (10)

According to the weight vector W_kThe weight set W of the index to be evaluated can be determined, as shown in equation 11.

In the formula: w_kA set of basis weight vectors; alpha is alpha_kThe weight coefficients are linearly combined.

For alpha in formula 11_kAnd (4) carrying out optimization solution to minimize the deviation between the weight set and each weight vector, and constructing a countermeasure model according to the deviation, wherein the equation is shown as a formula 12.

The linear equation set of the first derivative condition optimized for the countermeasure model, as shown in equation 13, is obtained from which the linear combination weight coefficient vector α is obtained_kI.e., (α)₁，α₂，…，α_m)

The weight coefficient α is linearly combined as shown in equation 14_kNormalization processing is performed and the integrated weight vector W is determined according to equation 15^*。

2.2 Objective empowerment

The entropy method is an objective weighting method capable of reflecting index variation degree, and the influence of subjective factors on the evaluation result is avoided to a certain extent by judging the utility value of the index by utilizing the inherent information of the evaluation index. Suppose that there are m samples to be measured to form an evaluation object set { A_iN index data form an index set { X ═ 1, 2, …, m_jJ ═ 1, 2, …, n), where x_ijIndicates the ith to be measuredThe original value of the j-th index of the sample. The proportion y occupied by different quantities in different indexes is obtained after standardization treatment_ijThe formed standard matrix Y is shown as formula 16, and the proportion Y of the quantity value j in the index i_ijIs calculated as shown in equation 17, and the entropy value e of any index is calculated as shown in equation 18.

Y＝(y_ij)_m×n,(i＝1,2,L,m；j＝1,2,L,n) (16)

K in equation 16 is a constant number related to the number of samples m of the system. When the degree of order is 0, its entropy value is maximum, i.e., e ═ 1. When m samples are in a completely disordered distribution, y_ijAt 1/m, the entropy value at this time is zero for the utility value of the overall evaluation, and therefore, the difference coefficient g of the j-th index_jDetermined by the difference between the entropy of the indicator and 1, as shown in equation 19.

g_j＝1-e_j(j＝1,2,L,n) (19)

The essence of estimating the index weight by the entropy method is to calculate by using a value coefficient of the index information, and the higher the value coefficient is, the greater the importance is. Weight w of j-th index_jAs shown in equation 20.

2.3 subjective empowerment

The subjective weight mainly adopts an analytic hierarchy process to evaluate index factors { U }₁，U₂，…，U_mFactors u in_ijAnd (3) carrying out importance analysis, wherein the value can be determined according to a 1-9 level scaling method, and establishing a judgment matrix as shown in table 1. Solving the judgment matrix to obtain the matrix maximumLarge eigenvalue lambda_maxAnd the corresponding characteristic vector A ═ a₁， a₂，…，a_m]The weights of the indices are determined by normalization. The calculation of the maximum eigenvalue is shown in equation 21.

TABLE 1 evaluation index factor judgment matrix

The consistency of the judgment matrix directly reflects the objective order of the evaluation objects and can be calculated by equation 22. Where CR is the consistency ratio of the decision matrix and CI is the consistency index, which can be calculated from equation 23. RI is a random consistency index, and its value can be determined by table 2.

As can be seen from the consistency test, when the CI is larger, the judgment matrix is indicated to be worse in consistency. When CI is 0, judging that the matrix has complete consistency; when CR is less than 0.1, judging that the matrix has relatively satisfactory consistency; otherwise, the determination matrix needs to be adjusted.

TABLE 2 judge matrix consistency index

3 case analysis

3.1 general overview of the engineering

The tunnel shield is arranged between a Chengdu subway No. 17 line and a Fengxi river station and five city hospital stations, the length of the tunnel on the left line is 1610.186m, the length of the tunnel on the right line is 1611.485m, and one shield machine is respectively used on the left line and the right line. The shield sections are arranged in the south-north direction along the Fengxi large road, the traffic flow along the line is large, buildings (structures) on two sides are numerous, and the Fengxi river is arranged on the west side of the line. The longitudinal slope gradient of the interval tunnel is 10.063 per mill, and the radius of the curve of the minimum plane is 450 m. The minimum buried depth of the top of the tunnel in the region is about 9.5m, the maximum buried depth is about 20m, the tunnel in the region mainly penetrates through a compact pebble soil layer, the construction of the shield region can bring serious influence to the surrounding environment, and the safety and stability of shield tunneling need to be evaluated. The engineering position and the line trend are shown in figure 1, the soil layer parameters are shown in table 3, and the pebbles in the shield zone are shown in figure 2.

TABLE 3 Main parameters of each soil layer in shield tunnel section

3.2 Game theory-based combinatorial weight computation

3.2.1 selection of evaluation index

In order to accurately evaluate the safety and stability of shield tunneling, 5 evaluation indexes of surface subsidence, building subsidence, river bank subsidence, pipeline subsidence and segment deformation are selected according to the general engineering and shield construction experience of the Chengdu area, and the monitoring data of the straight line segment of the shield interval are evaluated. The monitoring data are shown in table 4.

TABLE 4 Shield Tunnel Interval straight-line segment monitoring data

3.2.2 calculation of evaluation index weight

According to regional engineering experience and relevant expert suggestions, the selected evaluation indexes are subjected to subjective weight calculation by adopting an analytic hierarchy process, the influence degree of the evaluation indexes on the shield tunneling safety and stability is determined, and a judgment matrix is constructed, as shown in table 5. And the subjective weight calculation results were subjected to a consistency check as shown in table 6. Therefore, the requirement of consistency check is met.

TABLE 5 evaluation index judgment matrix for shield driving stability

TABLE 6 subjective weight consistency test results of evaluation indexes

Entropy value weighting is performed on the evaluation index data in table 4 by expressions (16) to (20), and the combined weight of each evaluation index is calculated by expression (15), and the calculation results are shown in table 7.

TABLE 7 evaluation index entropy value empowerment calculation results

And (4) constructing an alignment model according to the subjective weight vector and the objective weight vector obtained by calculation and the formulas (10) to (15), and calculating a comprehensive weight vector. The linear combination coefficient α 1 of the subjective weight vector is 0.6508, and the linear combination coefficient α 2 of the objective weight vector is 0.4715. After normalization, α 1 was 0.5799 and α 2 was 0.4201. The results of the integrated weight calculation are shown in table 8.

TABLE 8 evaluation index weight calculation results

3.3 construction of the scalable cloud model

3.3.1 shield tunneling safety and stability discrimination Standard

According to the 'Chengdu track traffic construction engineering monitoring and measuring management method' and the relevant standards^[19～21]The shield tunneling safety and stability is required to be classified into a dangerous level (level I), an early warning level (level II) and a safe level (level III), and a shield tunneling safety and stability judgment standard is constructed as shown in a table 9.

TABLE 9 shield tunneling safety and stability discrimination Standard

3.3.2 comprehensive evaluation model of scalable cloud

The monitoring data of each section is calculated by the formulas (16) to (20), and the entropy value e of each evaluation index is determined_jCoefficient of difference g_jAnd entropy weight w_jThe calculation results are shown in table 9. And (4) calculating expected Ex, entropy En and super-entropy He of the shield tunneling evaluation index according to the shield tunneling safety and stability judgment standard and the formulas (1) to (3). According to the characteristics of the evaluation index parameters of the embodiment, the super entropy He is 0.01, and an extension cloud model R is constructed according to the matter element theory₀As shown in equation 21. The cloud drop maps of the evaluation indexes are calculated by using Matlab, as shown in fig. 3(a) -3 (e), and the constructed extension cloud matrices are shown in table 10.

Table 10 evaluation index extension cloud matrix

3.4 analysis of evaluation results

And (3) calculating a comprehensive extension cloud evaluation matrix according to the combination weight determined by the game theory method and the formula (9), accumulating the degrees of certainty of the same grade as shown in a table 11 to obtain the degrees of certainty of each monitoring point under each grade, judging the shield tunneling safety grade of each monitoring point according to the maximum degree of certainty principle, and obtaining an evaluation result as shown in a table 12.

TABLE 11 comprehensive extension cloud evaluation matrix

Table 12 comprehensive cloud extension evaluation results

According to the comprehensive extension cloud evaluation result, the safety levels of the monitoring points 1-6, 8 and 9 are level III, the construction is in a safety level state, and the safety level state is basically consistent with the result reflected by the field monitoring data. The safety levels of the monitoring points 7, 10, 11 and 17 are II levels, the construction is in an early warning state, the deformation of the segment is within the range of an early warning value and is close to a control value through field monitoring data, the safety state of the whole construction needs to be closely monitored due to the increase of the deformation of the segment, and corresponding technical measures are taken to reduce the safety risk brought by shield excavation prevention. The safety levels of the monitoring points 12-16, 18 and 19 are I levels, the monitoring points belong to a dangerous state, the monitoring data show that the surface subsidence, the pipeline subsidence and the segment deformation are close to control values, the shield construction condition is severe, the shield tunneling state, the tunneling parameters and various monitoring data need to be closely concerned, the safety risk is reduced by adjusting the shield construction parameters, and the construction safety problem caused by shield tunneling is avoided. And comparing the comprehensive cloud extension evaluation result with an evaluation result obtained according to the field monitoring data, wherein the comprehensive cloud extension evaluation results of the monitoring points 1-6, 8, 9 and 17 are consistent with the field evaluation result, and the comprehensive cloud extension evaluation results of other monitoring points are higher than the field evaluation result by one grade. Because the internal relevance among all monitoring projects is reflected by the extension cloud model, the evaluation result is a comprehensive reflection of all monitoring data, and the evaluation on the safety and stability of shield tunneling construction is more consistent with the actual situation. Therefore, the comprehensive evaluation model for shield tunneling safety and stability based on the game theory and the scalable cloud has application value in practical engineering, and the evaluation result is more favorable for controlling the safety and stability of shield construction. The model is established on the basis of geological conditions of water-rich large-particle-size high boulder content in a Wenjiang area of a metropolis, so that the comprehensive extension cloud evaluation model can provide theoretical basis and data reference for carrying out corresponding comprehensive evaluation on shield tunneling safety and stability of a sandy gravel stratum in the metropolis.

4 conclusion

(1) Aiming at the problems that the evaluation reference index of the shield tunneling safety stability is single, the evaluation result is one-sidedly, the uncertainty relation among all indexes cannot be reflected and the like at present, the game theory and the extensible cloud model are combined, and the comprehensive extensible cloud evaluation model suitable for the water-rich sandy gravel stratum in the Chengdu area is provided, wherein the evaluation indexes are weighted by adopting the combined weight combining the hierarchical analysis and the entropy value theory, the subjective sidedness existing in single weighting is avoided, and the calculation result accords with the objective reality.

(2) Taking construction of a Chengdu subway shield interval as an example, based on 5 evaluation indexes such as ground settlement, building settlement, river bank settlement, pipeline settlement and segment deformation, a comprehensive extension cloud model is adopted to evaluate the safety and stability of 19 monitoring points, and the evaluation results are compared with on-site monitoring evaluation results, wherein the evaluation results of all the monitoring points in a III-level state are basically consistent. For the monitoring points in the early warning state, the evaluation result of the comprehensive cloud model is a comprehensive evaluation of the safety state reflected by each evaluation index, so that the evaluation result is one grade higher than the field monitoring evaluation result. The extension cloud model has greater superiority in evaluating the uncertain relation among the indexes, so that the comprehensive extension cloud evaluation result is more in line with the actual situation.

(3) The comprehensive evaluation model based on the game theory and the scalable cloud considers the fuzziness, the randomness and the actual distribution rule in the shield tunneling safety stability evaluation index information, avoids information loss caused by data normalization, and meanwhile, combines and weights the original data by using a method of combining an analytic hierarchy process and an entropy theory to enable the weights of all indexes to be more scientific and reasonable, and can provide scientific reference for shield tunneling safety stability evaluation under the condition of water-rich sandy gravel stratum in a region of success.

Finally, it should be noted that: the above examples are only used to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims

1. A shield tunneling safety and stability evaluation method is characterized by comprising the following steps:

the method comprises the following steps: selecting evaluation indexes of straight line segments of the shield interval, and acquiring a comprehensive weight vector W of the evaluation indexes based on combined weight calculation of a game theory;

2. The shield tunneling safety and stability evaluation method according to claim 1, wherein the evaluation index includes: and 5 evaluation indexes of surface settlement, building settlement, river bank settlement, pipeline settlement and segment deformation are provided.

3. The shield tunneling safety and stability evaluation method according to claim 1, wherein the first step comprises the following steps:

W_k＝(W_k1,W_k2,…,W_kn),k＝(1,2,…,m)

step 14: optimizing a linear equation system of a first derivative condition according to the strategy model to obtain a linear combination weight coefficient vector alpha_kI.e., (α)₁，α₂，…，α_m)

4. the shield tunneling safety and stability evaluation method according to claim 1, wherein the second step includes the steps of:

Step 22: according to the calculation method of the subjective weight, a judgment matrix of the evaluation indexes is constructed, the subjective weight of each evaluation index is calculated, and the calculation result is subjected to normalization test;

Step 25: according to the extension cloud model R₀Constructing an extensible cloud matrix;

5. the shield tunneling safety and stability evaluation method according to claim 1, wherein the third step includes the steps of:

wherein, b_ijThe component of the comprehensive extension cloud evaluation matrix B is expressed, namely the comprehensive certainty degree of a certain sample corresponding to a certain index is expressed;

6. The shield tunneling safety and stability evaluation method according to claim 3, wherein the step 21 includes:

an entropy method is utilized to assume that m samples to be measured form an evaluation object set { A }_iN index data form an index set { X ═ 1, 2, …, m_jJ ═ 1, 2, …, n), where x_ijRepresenting the original value of the jth index of the ith sample to be tested;

Y＝(y_ij)_m×n,(i＝1,2,…,m；j＝1,2,…,n) (1)

g_j＝1-e_j(j＝1,2,…,n) (4)

7. the shield tunneling safety and stability evaluation method according to claim 3, wherein the step 22 includes:

Ex＝(C_max+C_min)/2

En＝(C_max-C_min)/6

He＝s