CN114548725A - Deep foundation pit stability evaluation method based on entropy weight-level analysis fuzzy comprehensive evaluation method - Google Patents

Abstract

A method for evaluating the stability of deep foundation pits based on entropy weight-analytic hierarchy process fuzzy comprehensive evaluation method belongs to the field of geotechnical mechanics and engineering. The present invention not only considers the objectivity of the index weight assignment, but also considers the risk occurrence probability and the accident damage loss degree. The main steps include: constructing an evaluation index system; determining the evaluation index weight based on the analytic hierarchy process; The weight of the evaluation index is revised; the comprehensive weight of the index is determined; the safety level is divided; the safety level is determined; the fuzzy comprehensive evaluation is performed to obtain the evaluation score. The present invention proposes a difference coefficient, and based on the coefficient, performs a linear weighted combination of the weights of the indicators calculated by the AHP and the entropy weight method, and combines the refined deep foundation pit construction safety status rating table to comprehensively and quantitatively evaluate. Steady state of deep foundation pits. The invention solves the problem that the judgment matrix A is affected by the experience level of experts in the existing analysis method, can objectively and accurately weight the evaluation index, and improves the credibility of the weight calculation.

Description

A Stability Evaluation Method of Deep Foundation Pit Based on Entropy Weight-Analytic Hierarchy Process Fuzzy Comprehensive Evaluation Method

technical field

The invention belongs to the technical field of construction engineering, and relates to a deep foundation pit stability evaluation method based on an entropy weight-analytic hierarchy process fuzzy comprehensive evaluation method.

Background technique

The stability of deep foundation pit is affected by many factors such as stratum conditions, groundwater distribution and surrounding building environment. There is often a certain deviation between the design of the supporting structure and the actual engineering needs. The monitoring data can reflect the force and deformation of the corresponding parts of the rock and soil in real time, which has an important guiding role in the design and adjustment of the foundation pit supporting structure. Therefore, it is of great engineering value and scientific significance to carry out research on monitoring data analysis methods for the stability assessment of deep foundation pits.

At present, the commonly used deep foundation pit stability assessment methods mainly include: fault tree method, WBS method, analytic hierarchy process, fuzzy comprehensive evaluation method, and entropy weight method. Among them, the fault tree method and the WBS method can make a concise and vivid description of the factors and logical relationships that affect the stability of deep foundation pits through qualitative analysis. However, their analysis process is complicated, and they lack systematic quantitative consideration for the stability of deep foundation pits. Although the analytic hierarchy process-fuzzy comprehensive evaluation method systematically considers the factors affecting the stability of deep foundation pits, and decomposes them comprehensively, the structure is clear, which makes up for the deficiencies of the above two methods. However, AHP overemphasizes the role of the experience level of decision makers, which makes the determination of the evaluation index weights contain certain subjective factors. The entropy weight method can objectively consider the effect of a single influencing factor, but because a set of recognized standard evaluation index models has not yet been formed in the current research field of deep foundation pit construction, it is easy to deviate from the actual situation by simply using the entropy weight method for index weight analysis. result. In addition, in the previous classification of the safety status of deep foundation pit construction, the safety level is often divided into 3-4 levels, with low precision. The selection and determination of warning values need to be set by expert experience, ignoring risk occurrence and damage loss, etc. The influence of factors on the stability assessment of deep foundation pits.

SUMMARY OF THE INVENTION

According to the above-mentioned technical problem, the present invention provides a deep foundation pit stability evaluation method based on the entropy weight-analytic hierarchy process fuzzy comprehensive evaluation method. The present invention proposes a difference coefficient, and based on the coefficient, performs a linear weighted combination of the weights of the indicators calculated by the AHP and the entropy weight method, combined with the refined deep foundation pit construction safety status rating table, comprehensively and quantitatively considered Steady state of deep foundation pits.

In order to achieve the above object, the technical means adopted in the present invention are as follows:

A method for evaluating the stability of deep foundation pits based on entropy weight-analytic hierarchy process fuzzy comprehensive evaluation method, comprising the following steps:

S1. Build an evaluation index system;

S2. Determine the weight of the evaluation index based on the analytic hierarchy process;

S3. Based on the entropy weight method, the weight of the evaluation index is revised;

S4. Determine the comprehensive weight of the indicators;

S5, the division of security levels;

S6. Determine the security level;

S7. Fuzzy comprehensive evaluation to obtain evaluation scores.

Further, the specific implementation process of the step S1 is as follows:

S11. According to the main deformation of the foundation pit in the construction process, for example: deformation of the supporting structure, deformation of the surrounding environment and monitoring of the environment in the pit, etc., determine the index factors affecting the stability of the deep foundation pit, and build a hierarchical evaluation index system;

S12. Set the index probability level, and build a multi-level index evaluation model that affects the safety and stability of the deep foundation pit. Example: The first-level indicators include the deep foundation pit supporting structure, the surrounding environment and the environment inside the pit, etc. Each first-level indicator is determined by several second-level indicators. The content of the second-level indicators can be divided into horizontal displacement of structural piles, vertical displacement of structural piles, settlement of surrounding buildings, inclination of surrounding buildings, changes in groundwater levels inside and outside the foundation pit, etc. .

Further, the implementation process of the step S2 is as follows:

S21. Use the analytic hierarchy process to compare each index factor in the same level with respect to the upper level, give a certain judgment on the relative importance of each index factor in each level, and combine the 1-9 scaling method to The importance is scored, and the judgment matrix A of each level is constructed;

S22, make assumptions on the judgment matrix A, the assumptions are as follows:

Among them, a _ij is the relative importance ratio of index i and index j;

S23. Multiply each row of the judgment matrix A to obtain a new vector

S24, take each component of _w to the nth power, and normalize it, and finally obtain the weight vector Wi:

其中(i＝1，2，…，n)

where (i=1,2,...,n)

S25. Introduce consistency indicators, as follows:

Among them, λ _max represents the largest characteristic root of the judgment matrix, and the larger the CI value, the worse the consistency of the judgment matrix.

S26. Use the consistency index and the random consistency index RI to perform consistency check:

则表示通过检验，认为层次分析的排序结果满足一致性，特征向量即为权向量；若不通过，则重新构造判断矩阵或对矩阵中的元素进行调整，直到满足一致性检验。When the consistency ratio

If it passes the test, it is considered that the ranking result of AHP satisfies the consistency, and the eigenvector is the weight vector; if it fails, the judgment matrix is reconstructed or the elements in the matrix are adjusted until the consistency test is satisfied.

Further, the implementation process of the step S3 is as follows:

S31. After passing the consistency check, standardize the judgment matrix A, and denote it as R:

其中

in

S32, after standardizing the judgment matrix A, calculate the entropy E _j of each evaluation index:

In the evaluation process, if the entropy value is larger, the reliability of the evaluation result is lower; on the contrary, the smaller the entropy value is, the reliability of the evaluation result is higher;

S33. Using the deviation d _j of each index, calculate the correction coefficient μ _j of each index:

其中d_j＝1-E_j

where d _j =1-E _j

S34. Use the correction coefficient μ _j to correct the initial weight W _j calculated by the analytic hierarchy process, and obtain the weight coefficient θ _j corrected by the entropy weight method:

Further, the implementation process of the step S4 is as follows:

The weight index difference coefficient ρ is proposed, and the weight W _j and the weight correction coefficient θ _j are combined and calculated by linear weighting to determine the comprehensive index weight w _j :

w _j =ρW _j +(1-ρ)θ _j

Among them, ρ represents the proportion of the weight determined by the AHP to the combined weight; 1-ρ represents the proportion of the weight calculated by the entropy weight method to the combined weight.

The ratio of the weight determined by the AHP to the combined weight, that is, the difference coefficient ρ of the weight index is determined according to the specific situation required, and the calculation of the difference coefficient ρ is as follows:

Among them, P _i (i=1, 2, 3, ... n) is the vector of the AHP weight values arranged in ascending order, and n is the number of evaluation indicators.

Further, in the step S5: the safety level is divided according to the probability of risk occurrence and the degree of loss caused by accident damage.

Further, the implementation process of the step S6 is as follows:

S61. Substitute the measured data of the evaluation index into the standard interval of the reference index for the evaluation of the safety state level of deep foundation pit construction, and determine the degree of membership of a single index with respect to each state level, denoted as r _ij ;

S62, forming a judgment set of any single index on all state levels, and determining the safe and stable state level of the evaluation index according to the principle of maximum membership, and the judgment set is as follows:

r _i ={r _i1 , r _i2 , r _i3 ,...r _im }

S63, the fuzzy comprehensive evaluation of the bottom layer is integrated to the upper layer in turn to obtain the total evaluation matrix R′:

Further, the implementation process of the step S7 is as follows:

S71, according to the comprehensive index weight w _j determined in step S4 and the total evaluation matrix R' obtained in step S63, obtain the fuzzy evaluation result, as follows:

B=W×R′=(b ₁ , b ₂ , . . . , b _m )

Among them, B is the fuzzy evaluation result, W is the revised weight matrix, and R' is the membership matrix. According to the maximum membership principle max{b _j }(j=1,2,3,...m), the deep foundation pit is determined. Comprehensive security and stability level;

S72. Select the weight components for each level to perform a weighted average on them to obtain an evaluation score. The formula for the weighted average is as follows:

Among them, b _j represents the level value corresponding to the j-th state level in the evaluation vector B, v _j represents the score of the j-level environmental quality, m is the selected positive real number, and F is the final score value.

Compared with the prior art, the beneficial effects of the present invention are:

(1) The deep foundation pit stability assessment method based on the entropy weight-analytic hierarchy process fuzzy comprehensive evaluation method provided by the present invention proposes a coefficient of difference ρ, and based on this coefficient, the indexes calculated by the analytic hierarchy process and the entropy weight method are calculated The weights are linearly weighted to enhance the objectivity of the determination of the indicator weights. The invention solves the problem that the judgment matrix A is affected by the experience level of experts in the existing analysis method, can objectively and accurately weight the evaluation index, and improves the credibility of the weight calculation.

(2) The deep foundation pit stability evaluation method based on the entropy weight-analytic hierarchy process fuzzy comprehensive evaluation method provided by the present invention, on the basis of "Construction Foundation Pit Engineering Monitoring Technical Standard", through statistical analysis of the actual measurement of deep foundation pit engineering in various regions of my country Time data series, with 95% guaranteed rate of monitoring data feature points as monitoring and control indicators, combined with the probability of risk occurrence and the degree of accident damage, the previous classification standards for the safety level of 4-level foundation pits have been improved, and the construction of deep foundation pits has been formulated. The reference index table for the 5-level assessment of safety status makes the classification of the safety level of the foundation pit more detailed, and the determination of the stability level of the deep foundation pit is more convincing. Good implementation of early warning classification.

Based on the above reasons, the present invention can be widely promoted in the fields of building engineering construction and the like.

Description of drawings

Fig. 1 is the flow chart of the method of the present invention.

FIG. 2 is a structural diagram of a multi-level evaluation index provided by the present invention.

FIG. 3 is a safety state evaluation index system of a deep foundation pit project provided by an embodiment of the present invention.

Detailed ways

In order for those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only Embodiments are part of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

It should be noted that the terms "first" and "second" in the description and claims of the present invention and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used may be interchanged under appropriate circumstances such that the embodiments of the invention described herein can be practiced in sequences other than those illustrated or described herein. Furthermore, the terms "comprising" and "having", and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those expressly listed Rather, those steps or units may include other steps or units not expressly listed or inherent to these processes, methods, products or devices.

The present invention proposes a weight index difference coefficient, improves the entropy weight-analytic hierarchy process fuzzy comprehensive evaluation model, and refines the construction safety state level of the deep foundation pit. On this basis, a new method for deep foundation pit stability analysis is proposed. The solution is:

(1) The difference coefficient ρ is proposed, and based on this coefficient, the weights of the indicators calculated by the AHP and the entropy weight method are linearly weighted and combined, which enhances the objectivity of the determination of the indicator weights and solves the problem of judgment in the existing analysis methods. The problem that matrix A is affected by the experience level of experts can objectively and accurately weight the evaluation indicators, which improves the credibility of the weight calculation.

(2) The deep foundation pit stability evaluation method based on the entropy weight-analytic hierarchy process fuzzy comprehensive evaluation method provided by the present invention, on the basis of "Construction Foundation Pit Engineering Monitoring Technical Standard", through statistical analysis of the actual measurement of deep foundation pit engineering in various regions of my country Time data series, with 95% guaranteed rate of monitoring data feature points as monitoring and control indicators, combined with the probability of risk occurrence and the degree of accident damage, the previous classification standards for the safety level of 4-level foundation pits have been improved, and the construction of deep foundation pits has been formulated. The reference index table for the 5-level assessment of safety status makes the classification of the safety level of the foundation pit more detailed, and the determination of the stability level of the deep foundation pit is more convincing. Good implementation of early warning classification.

As shown in Figure 1, the present invention provides a kind of deep foundation pit stability evaluation method based on entropy weight-analytic hierarchy process fuzzy comprehensive evaluation method, comprising the following steps:

S1. Build an evaluation index system;

S2. Determine the weight of the evaluation index based on the analytic hierarchy process;

S3. Based on the entropy weight method, the weight of the evaluation index is revised;

S4. Determine the comprehensive weight of the indicators;

S5, the division of security levels;

S6. Determine the security level;

S7. Fuzzy comprehensive evaluation to obtain evaluation scores.

During specific implementation, as a preferred embodiment of the present invention, the specific implementation process of step S1 is as follows:

S11. Determine the index factors affecting the stability of the deep foundation pit, and construct a hierarchical evaluation index system, as shown in Figure 2;

At present, the commonly used methods for determining the stability evaluation index of deep foundation pits are: (1) work breakdown structure method (WBS), (2) risk breakdown structure method (RBS), (3) WBS-RBS method, (4) Expert investigation method, (5) checklist method, (6) diagram method, (7) brainstorming method, etc. Due to the different scope of application of each analysis method, there are also certain differences among the index factors. In the previous research results, the deformation that can be detected in the construction process of the foundation pit can be roughly divided into: foundation pit supporting structure (horizontal displacement of structural piles, vertical displacement of structural piles, lateral displacement of maintenance walls, etc.) Surrounding environment (subsidence of surrounding buildings, inclination of surrounding buildings, width of cracks in surrounding buildings, etc.) environment inside the foundation pit (uplift of the bottom of the foundation pit, groundwater levels inside and outside the foundation pit, etc.).

S12. Set the index probability level, and build a multi-level index evaluation model that affects the safety and stability of the deep foundation pit.

During specific implementation, as a preferred embodiment of the present invention, the implementation process of step S2 is as follows:

S21. Use the analytic hierarchy process to compare each index factor in the same level with respect to the upper level, and give a certain judgment on the relative importance of each index factor in each level (the evaluation process of the analytic hierarchy process mainly depends on Expert experience level, combined with the 1-9 scale method to give the evaluation results, so the results obtained contain a certain subjective color, which is the disadvantage of the AHP, and it is also the patent that uses the entropy weight method to The improvement of the AHP. Among them, the entropy weight method is one of the objective weighting methods. The weighting process mainly considers the characteristics of the data itself and is not affected by human subjective factors), combined with the 1-9 scaling method to its importance Score (see Table 1) to construct a judgment matrix A for each level.

Table 1 1-9 Scaling method

S22, make assumptions on the judgment matrix A, the assumptions are as follows:

Among them, a _ij is the relative importance ratio of index i and index j;

S23. Multiply each row of the judgment matrix A to obtain a new vector

每个分量开n次方，并对其进行归一化处理，最终得到权重向量W_i：S24, will

Take each component to the nth power and normalize it, and finally get the weight vector W _i :

其中(i＝1，2，…，n)

where (i=1,2,...,n)

S25. Introduce consistency indicators, as follows:

Among them, λ _max represents the largest characteristic root of the judgment matrix, and the larger the CI value, the worse the consistency of the judgment matrix.

S26. Use the consistency index and the random consistency index RI (see Table 2) to perform consistency check:

则表示通过检验，认为层次分析的排序结果满足一致性，特征向量即为权向量；When the consistency ratio

It means that it passes the test and considers that the ranking results of AHP satisfy the consistency, and the feature vector is the weight vector;

If it fails, reconstruct the judgment matrix or adjust the elements in the matrix until the consistency check is satisfied.

Table 2 Stochastic consistency index RI value

During specific implementation, as a preferred embodiment of the present invention, the implementation process of step S3 is as follows:

S31. After passing the consistency check, standardize the judgment matrix A, and denote it as R:

其中

in

S32, after standardizing the judgment matrix A, calculate the entropy E _j of each evaluation index:

In the evaluation process, if the entropy value is larger, the reliability of the evaluation result is lower; on the contrary, the smaller the entropy value is, the reliability of the evaluation result is higher;

S33. Using the deviation d _j of each index, calculate the correction coefficient μ _j of each index:

其中d_j＝1-E_j

where d _j =1-E _j

S34. Use the correction coefficient μ _j to correct the initial weight W _j calculated by the analytic hierarchy process, and obtain the weight coefficient θ _j corrected by the entropy weight method:

During specific implementation, as a preferred embodiment of the present invention, the implementation process of step S4 is as follows:

In order to make the weight assignment not only have the advantages of the decision maker's experience, but also try to avoid the random subjectivity of the weighting, the weight index difference coefficient ρ is proposed, and the weight W _j and the weight correction coefficient θ _j are combined and calculated by linear weighting to determine the index. Comprehensive weight w _j :

w _j =ρW _j +(1-ρ)θ _j

Among them, ρ represents the proportion of the weight determined by the AHP to the combined weight; 1-ρ represents the proportion of the weight calculated by the entropy weight method to the combined weight.

The ratio ρ of the weights determined by the AHP to the combined weights is determined according to the specific conditions required, and the calculation of the difference coefficient ρ is as follows:

Among them, P _i (i=1, 2, 3, ... n) is the vector of the AHP weight values arranged in ascending order, and n is the number of evaluation indicators.

During specific implementation, as a preferred embodiment of the present invention, the basis for dividing the safety level in the step S5 is the probability of risk occurrence and the degree of loss caused by accident damage.

In order to solve the problem of inaccurate quantification standards of monitoring and alarm grading strategies, the monitoring warning value should follow: (1) meet the design calculation requirements, but not the design value; (2) meet the safety requirements of the monitoring object and achieve the purpose of protection; (3) ) For the protection objects under the same conditions, they should be comprehensively determined in combination with the requirements of the surrounding environment and the specific construction conditions; (4) To meet the requirements of the current relevant norms and regulations; (5) To meet the principles of the requirements put forward by the competent authorities of each protection object . By comparing the monitoring and alarm values of the "Technical Standards for Construction Foundation Pit Engineering Monitoring", combined with the probability of risk occurrence and the degree of accident damage loss, a reference index for grade 5 deep foundation pit construction safety status evaluation was established, as shown in Table 3.

Table 3 Reference indexes for the safety status evaluation of deep foundation pit construction

Note: 1.f ₁ - design value of bearing capacity of components, ultimate pull-out bearing capacity of anchor; f _y - design value of steel support and anchor prestress.

2. When the cumulative change of the monitoring items exceeds the specified value or the rate of change exceeds 70% of the specified value in the table for three consecutive times, the disaster warning response should be started immediately.

Risk factors can directly or indirectly lead to the occurrence of engineering safety accidents, and to a certain extent, cause related economic losses to the project itself, materials and equipment, construction equipment, third parties, etc. and the casualties of on-site operators. In order to better manage and control the occurrence of risks, and conduct timely and effective investigation and prevention of major danger sources, the safety and stable state of deep foundation pit engineering is now classified according to the probability of risk occurrence and the degree of loss caused by accident damage. , see Table 4.

Table 4 Risk probability and accident loss level during deep foundation pit construction

Note: EL is the ratio of direct economic loss to total investment; CL is the ratio of lost construction period to planned construction period; MW is the number of minor injuries; SW is the number of serious injuries; D is the number of deaths.

During specific implementation, as a preferred embodiment of the present invention, the implementation process of step S6 is as follows:

S61. Substitute the measured data of the evaluation index into the standard interval of the reference index for the evaluation of the safety state level of deep foundation pit construction, and determine the degree of membership of a single index with respect to each state level, denoted as r _ij ;

S62, forming a judgment set of any single index on all state levels, and determining the safe and stable state level of the evaluation index according to the principle of maximum membership, and the judgment set is as follows:

r _i ={r _i1 , r _i2 , r _i3 ,...r _im }

S63, the fuzzy comprehensive evaluation of the bottom layer is integrated to the upper layer in turn to obtain a total evaluation matrix R':

During specific implementation, as a preferred embodiment of the present invention, the implementation process of step S7 is as follows:

S71. In order to take into account the influence of all evaluation indicators on the safety and stability evaluation process of the deep foundation pit, and to truly reflect the comprehensive stability of the deep foundation pit during the on-site construction process, according to the comprehensive weight w _j of the indicators determined in step S4 and the step From the total evaluation matrix R' obtained in S63, the fuzzy evaluation results are obtained as follows:

B=W×R′=(b ₁ ,b ₂ ,...,b _m )

Among them, B is the fuzzy evaluation result, W is the revised weight matrix, and R' is the membership matrix. According to the maximum membership principle max{b _j }(j=1,2,3,...m), the deep foundation pit is determined. Comprehensive security and stability level;

S72. In order to reflect the comparability of the evaluation objects, select the weight components for each level to perform a weighted average on them to obtain the evaluation score. The formula for the weighted average is as follows:

Among them, b _j represents the level value corresponding to the j-th state level in the evaluation vector B, v _j represents the score of the j-level environmental quality, m is the selected positive real number, and F is the final score value.

Example

This example adopts a deep foundation pit project in Shenzhen, which is located on the southeast side of the intersection of Guangzhou-Shenzhen Yanjiang Expressway and Tinghai Avenue, in the green garden on the south side of Metro Line 5 under construction. The perimeter of the foundation pit is about 317.425m and the area is about 7683m ² . There are three basements with a height of 10.0m and a depth of 18.75m-24.75m. It is supported by an underground diaphragm wall and the thickness of the filling layer is 6.0m- 14.0m. The northwest side of the foundation pit is adjacent to the subway Line 5 extension line tunnel side about 15.0m, and the southwest side is adjacent to the Yanjiang Expressway pile foundation about 30.0m. The site environmental conditions are relatively complex.

Step 1: Build evaluation indicators and systems:

During the construction of the deep foundation pit, the accumulated changes of the surrounding ground surface and pipe trenches are relatively large. According to the actual safety and stability needs of the foundation pit engineering project of the Qianwan Information Hub Center, combined with the construction principles of the index system in Figure 2, the foundation pit structure and surrounding environment are In two aspects, a four-layer security evaluation system is constructed, as shown in Figure 3.

The first layer: U=[B ₁ , B ₂ ];

Second layer: B ₁ =[C ₁ , C ₂ , C ₃ , C ₄ , C ₅ , C ₆ ]; B ₂ =[C ₇ , C ₈ , C ₉ ];

The third layer: C ₁ =[D ₁ ,D ₂ ]; C ₂ =[D ₃ ,D ₄ ];C ₃ =[D ₅ ,D ₆ ];C ₄ =[D ₇ ,D ₈ ];C ₅ =[D ₉ ,D ₁₀ ]; C ₆ =[D ₁₁ ,D ₁₂ ];C ₇ =[D ₁₃ ,D ₁₄ ];C ₈ =[D ₁₅ ,D ₁₆ ];C ₉ =[D ₁₇ ,D ] ₁₈ ].

The second step: determine the weight coefficient of the evaluation index;

Taking the structure of the foundation pit as an example, an Analytic Hierarchy Process (AHP) judgment matrix is constructed according to the 1-9 scaling method, as shown in Tables 5 and 6.

Table 5 Overall Judgment Matrix B-U

Table 6 Pit structure judgment matrix B ₁ -C

According to the consistency index formula, the above judgment matrix is tested for consistency, and the calculated consistency ratios all satisfy CR<0.1, indicating that the consistency of the matrix is good and meets the requirements of deep foundation pit construction.

The third step: entropy weight-AHP method combination weight;

On the basis of the judgment matrix A constructed by the Analytic Hierarchy Process (AHP), according to the formula for calculating the entropy of all the evaluation indexes affecting the stability of deep foundation pits, the standardized judgment matrix is obtained:

According to the calculation of R ₁ , the index entropy E ₁ and deviation degree d ₁ , correction coefficient μ ₁ , corrected weight coefficient θ ₁ , and combined weight w ₁ of foundation pit structure evaluation indexes are obtained.

E ₁ = (0.8759 0.8759 0.8540 0.8540 0.8540 0.9488)

d ₁ = (0.1241 0.1241 0.1460 0.1460 0.1460 0.0512)

μ ₁ = (0.8759 0.8759 0.8540 0.8540 0.8540 0.9488)

θ ₁ = (0.3250 0.3250 0.1387 0.0832 0.0935 0.0346)

w ₁ = (0.3246 0.3246 0.1282 0.0769 0.0864 0.0592)

Step 4: Establish the membership matrix and evaluation model of evaluation indicators at all levels;

The measured data of the project is evaluated according to the reference index of the deep foundation pit construction safety state level, and the membership degree matrix of the pit structure is constructed:

Pit structure:

B ₁ =W ₁ ×R ₁ ′=(0.9057 0.2585 0.0942 0.0766 0)

Overall deep foundation pit:

B=W×R′=(0.5720 0.2681 0.1159 0.0440 0)

Fuzzy subset of the overall safety level of the foundation pit:

B=[0.5720(Class I) 0.2681(Class II) 0.1159(Class III) 0.0440(Class IV) 0(Class V)]

Step 5: Overall assessment of the safety status of the deep foundation pit;

Combined with the above analysis of the evaluation index status of each level of the deep foundation pit, the comprehensive evaluation result of a deep foundation pit project in Shenzhen is obtained according to the weighted average formula, as shown in Table 7.

Table 7 Evaluation results of safety status of deep foundation pit engineering

According to the above data analysis, the deep foundation pit as a whole is in the first-level safety state, and in the first-level safety fuzzy subset, the membership degree belonging to the I-level is 0.572. The score of the surrounding environment is lower than that of the pit structure, indicating that when the horizontal displacement of the wall (pile) and the horizontal displacement of the deep layer during the construction of the foundation pit exceeds the early warning value, the impact on the surrounding environment is greater. In this regard, relevant departments have attached great importance to the on-site construction, and have taken corresponding measures in a timely manner. The evaluation results are consistent with the actual situation of the project, which shows the validity of the foundation pit safety evaluation model, and can better guide the construction process of the foundation pit.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, but not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: The technical solutions described in the foregoing embodiments can still be modified, or some or all of the technical features thereof can be equivalently replaced; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the technical solutions of the embodiments of the present invention. scope.

Claims (4)

1. a deep foundation pit stability assessment method based on entropy weight-analytic hierarchy process fuzzy comprehensive evaluation method, is characterized in that, comprises the steps: S1. Build an evaluation index system; S11. According to the main deformation of the foundation pit during the construction process, determine the index factors affecting the stability of the deep foundation pit, and construct a hierarchical evaluation index system; S12. Set the index probability level, and build a multi-level index evaluation model that affects the safety and stability of the deep foundation pit; S2. Determine the weight of the evaluation index based on the analytic hierarchy process; S3. Based on the entropy weight method, the weight of the evaluation index is revised; S4. Determine the comprehensive weight of the indicators; The weight index difference coefficient ρ is proposed, and the weight W _j and the weight correction coefficient θ _j are combined and calculated by linear weighting to determine the comprehensive index weight w _j : w _j =ρW _j +(1-ρ)θ _j Among them, ρ represents the proportion of the weight determined by the AHP to the combined weight; 1-ρ represents the proportion of the weight calculated by the entropy weight method to the combined weight; The ratio of the weight determined by the AHP to the combined weight, the weight index difference coefficient ρ is determined according to the specific situation required, and the calculation of the difference coefficient ρ is as follows:

Among them, P _i (i=1, 2, 3,...n) is the vector of the weight values of AHP arranged in ascending order, and n is the number of evaluation indicators; S5, the division of security levels; Classify the safety level according to the probability of risk occurrence and the degree of loss caused by accident damage; S6. Determine the security level; S61. Substitute the measured data of the evaluation index into the standard interval of the reference index for the evaluation of the safety state level of deep foundation pit construction, and determine the degree of membership of a single index with respect to each state level, denoted as r _ij ; S62, forming a judgment set of any single index on all state levels, and determining the safe and stable state level of the evaluation index according to the principle of maximum membership, and the judgment set is as follows: r _i ={r _i1 , r _i2 , r _i3 , ... _ri m} S63, the fuzzy comprehensive evaluation of the bottom layer is integrated to the upper layer in turn to obtain the total evaluation matrix R′:

S7. Fuzzy comprehensive evaluation to obtain evaluation scores; S71, according to the comprehensive index weight w _j determined in step S4 and the total evaluation matrix R′ obtained in step S63, obtain a fuzzy evaluation result, as follows: B=W×R′=(b ₁ , b ₂ , . . . , b _m ) Among them, B is the fuzzy evaluation result, W is the revised weight matrix, and R' is the membership matrix. According to the maximum membership principle max{b _j }(j=1,2,3,...m), the deep foundation pit is determined. Comprehensive security and stability level; S72. Select the weight components for each level to perform a weighted average on them to obtain an evaluation score. The formula for the weighted average is as follows:

Among them, b _j represents the level value corresponding to the j-th state level in the evaluation vector B, v _j represents the score of the j-level environmental quality, m is the selected positive real number, and F is the final score value. 2. a kind of deep foundation pit stability assessment method based on entropy weight-AHP fuzzy comprehensive evaluation method according to claim 1, is characterized in that, the realization process of described step S2 is as follows: S21. Use the analytic hierarchy process to compare each index factor in the same level with respect to the upper level, give a certain judgment on the relative importance of each index factor in each level, and combine the 1-9 scaling method to determine the relative importance of each index factor in each level. The importance is scored, and the judgment matrix A of each level is constructed; S22, make assumptions on the judgment matrix A, the assumptions are as follows:

Among them, a _ij is the relative importance ratio of index i and index j; S23. Multiply each row of the judgment matrix A to obtain a new vector

S24, will

Each component is raised to the nth power and normalized, and finally the weight vector Wi is _obtained :

where (i=1,2,...,n) S25. Introduce consistency indicators, as follows:

Among them, _λmax represents the maximum eigenroot of the judgment matrix, and the larger the CI value, the worse the consistency of the judgment matrix; S26. Use the consistency index and the random consistency index RI to perform consistency check: When the consistency ratio

If it passes the test, it is considered that the ranking result of AHP satisfies the consistency, and the eigenvector is the weight vector; if it fails, the judgment matrix is reconstructed or the elements in the matrix are adjusted until the consistency test is met. 3. a kind of deep foundation pit stability assessment method based on entropy weight-AHP fuzzy comprehensive evaluation method according to claim 1, is characterized in that, the realization process of described step S3 is as follows: S31. After passing the consistency check, standardize the judgment matrix A, and denote it as R:

in

S32, after standardizing the judgment matrix A, calculate the entropy E _j of each evaluation index:

S33. Using the deviation d _j of each index, calculate the correction coefficient μ _j of each index:

where d _j =1-E _j S34. Use the correction coefficient μ _j to correct the initial weight W _j calculated by the AHP method, and obtain the weight coefficient θ _j corrected by the entropy weight method:

4. a kind of deep foundation pit stability assessment method based on entropy weight-analytic hierarchy process fuzzy comprehensive evaluation method according to claim 1, is characterized in that, the safety grade that divides in described step S5 sees the following table:

Note: EL is the ratio of direct economic loss to total investment; CL is the ratio of lost construction period to planned construction period; MW is the number of minor injuries; SW is the number of serious injuries; D is the number of deaths.

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