Vibroflotation pile composite foundation quality evaluation method based on AHP-entropy weight method

Abstract

The invention discloses a vibroflotation pile composite foundation quality evaluation method based on an AHP-entropy weight method. The method comprises the following steps: constructing a multi-dimensional analysis model; four master control influence factors of quality evaluation are obtained based on the multi-dimensional analysis model; weighting the influence factors based on an AHP subjective weighting method and an entropy weight objective weighting method, and obtaining a combined weight; obtaining a normalized thematic map of each influence factor evaluation index based on a Kriging interpolation method; superposing the normalized thematic maps based on a GIS superposition coupling function to obtain a quality quantification index type partition evaluation map of the whole area of the composite foundation; and carrying out partition evaluation on the quality of the vibro-replacement stone column composite foundation in the whole region. According to the method, the multi-dimensional analysis model is constructed to obtain the combination weight of each index, so that the evaluation is comprehensive, and the error of the evaluation result is greatly reduced; the influence factors are coupled in the same graph and are subjected to partition evaluation, so that the evaluation precision of the processed foundation is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of composite foundation supporting technologies, and particularly to a method for evaluating the quality of vibroflotation stone column composite foundation based on the AHP-entropy weight method. Background Art

[0002] Due to its poor soil mechanical properties, the soft overburden layer cannot meet the requirements as a dam foundation. To improve the bearing capacity of the foundation, vibroflotation stone columns are often used to treat the foundation, and after treatment, it is usually necessary to evaluate the quality of the composite foundation.

[0003] In the conventional evaluation process, tests such as static load tests, dynamic penetration tests, standard penetration tests, and indoor direct shear tests of the composite foundation need to be carried out. When evaluating, only a single index of a certain test result is used to evaluate the quality of the vibroflotation gravel pile composite foundation.

[0004] However, since the existing evaluation method uses a single index, and is affected by the technical level and experience of the evaluator and does not consider the fuzziness and randomness between evaluation indexes, the evaluation result is greatly affected by personal subjectivity, the evaluation is not comprehensive, and the evaluation result is one-sided, resulting in a large error in the evaluation result and being unable to truly reflect the quality of the vibroflotation gravel pile composite foundation based on multiple test information sources. Moreover, the existing evaluation method has a single dimension and cannot carry out zonal evaluation and grading of the quality of the composite foundation in the whole area. Summary of the Invention

[0005] The main purpose of the present invention is to provide a method for evaluating the quality of vibroflotation stone column composite foundation based on the AHP-entropy weight method, aiming to solve the technical problems that the evaluation result of the existing technology often has a large error and cannot carry out zonal evaluation and grading of the quality of the composite foundation in the whole area.

[0006] To achieve the above purpose, the present invention provides a method for evaluating the quality of vibroflotation stone column composite foundation based on the AHP-entropy weight method, and the method includes the following steps: S10, constructing a multi-dimensional analysis model; S20, obtaining four main control influencing factors for quality evaluation based on the multi-dimensional analysis model; S30, assigning weights to the influencing factors based on the AHP subjective weighting method and the entropy weight objective weighting method, and obtaining the combined weight; S40, obtaining the normalized thematic map of each influencing factor evaluation index based on the Kriging interpolation method; S50, superimposing the normalized thematic maps based on the GIS superimposing and coupling function to obtain the quality quantitative index type zonal evaluation map of the whole area of the composite foundation; S60, dividing and grading the quality quantitative index type zonal evaluation map, so as to carry out zonal evaluation on the quality of the vibroflotation gravel pile composite foundation in the whole area.

[0007] Optionally, step S10 includes the following steps: S110, conducting a static load test on the composite foundation; S120, evaluating the integrity and density of the vibroflotation gravel piles; S130, constructing a multi-dimensional analysis model based on the test and evaluation results.

[0008] Optionally, step S30 includes: S310, assigning weights to the influencing factors respectively based on the AHP subjective weighting method and the entropy weight objective weighting method; S320, establishing a formula based on the principle of minimum information entropy and the Lagrange multiplier method, optimizing and solving the weights of the influencing factors, and obtaining the combined weights.

[0009] Optionally, step S40 includes: S410, performing dimensionless and normalized data processing on the influencing factor indicators; S420, multiplying the dimensionless and normalized data processed influencing factor indicators by the combined weights of the determined influencing factors; S430, based on the Kriging interpolation method, using the numerical analysis ability of GIS to obtain the normalized thematic maps of the evaluation indicators of each influencing factor.

[0010] Optionally, step S50 includes: S510, based on the GIS information fusion, overlay and coupling function, overlaying the normalized thematic maps; S520, obtaining the quality quantification index type zoning evaluation map of the entire composite foundation area.

[0011] Optionally, the formula established in step S320 is as follows: (1) In the formula: minF is the combined weight; Q j is the optimal weight of multi-source information of the AHP-entropy weight method; W j is the weight assigned by the AHP method; m is the index value; V j is the objective weight of the entropy weight; s.t. represents the constraint conditions that need to be satisfied during the optimization process.

[0012] Optionally, step S60 includes: S610, grading the index values based on the dynamic natural grading method, and dividing them into five grades according to different thresholds; S620, dividing the quality evaluation map of the entire area into excellent areas, relatively excellent areas, transition areas, general areas and warning areas for foundation treatment quality based on the grading results.

[0013] Optionally, in step S510, the overlay and coupling are performed based on the following formula: (11) In the formula: W is the quality index; W i is the weight of the influencing factor; f i (x,y) is the single-factor influence value function; x,y are geographical coordinates; i is the number of influencing factors.

[0014] In addition, to achieve the above object, an embodiment of the present application further provides a vibroflotation pile composite foundation quality evaluation device based on the AHP-entropy weight method. The device includes: a construction module for constructing a multi-dimensional analysis model; an influencing factor acquisition module for obtaining four main influencing factors for quality evaluation based on the multi-dimensional analysis model; a weight acquisition module for weighting the influencing factors based on the AHP subjective weighting method and the entropy weight objective weighting method, and obtaining a combined weight; a thematic map acquisition module for obtaining a normalized thematic map of each influencing factor evaluation index based on the Kriging interpolation method; a superposition module for superposing the normalized thematic maps based on the GIS superposition coupling function to obtain a quality quantification index type zoning evaluation map of the entire composite foundation area; and a quality evaluation module for classifying and grading the quality quantification index type zoning evaluation map, so as to conduct a zonal evaluation of the quality of the vibroflotation gravel pile composite foundation in the entire area.

[0015] In addition, to achieve the above object, an embodiment of the present application further provides a computer-readable storage medium, which includes instructions that, when running on a computer, cause the computer to execute the vibroflotation pile composite foundation quality evaluation method of any embodiment of the present application.

[0016] In addition, to achieve the above object, an embodiment of the present application further provides a computing device, which includes: at least one processor, a memory, and an input-output unit; wherein, the memory is used to store a computer program, and the processor is used to call the computer program stored in the memory to execute the vibroflotation pile composite foundation quality evaluation method of any embodiment of the present application.

[0017] The vibroflotation pile composite foundation quality evaluation method based on the AHP-entropy weight method provided by the embodiment of the present application constructs a multi-dimensional analysis model to obtain four main influencing factors for quality evaluation, thereby determining the influencing factor weight values required by the influencing factors, and then obtaining the combined weights of each index, making the evaluation comprehensive and greatly reducing the error of the evaluation result, and can truly reflect the quality of the vibroflotation gravel pile composite foundation based on multiple test information sources; through the GIS superposition coupling function, each influencing factor is coupled and zonally evaluated in the same graph, which solves the problem of single quality evaluation dimension to a certain extent, can realize zonal evaluation and grading of the entire area, improves the accuracy of the post-treatment foundation evaluation, provides specific and visual guidance for the acceptance and re-treatment of the composite foundation, and provides a new solution for the evaluation of the composite foundation. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a flowchart of the vibroflotation pile composite foundation quality evaluation method based on the AHP-entropy weight method provided by one or more embodiments of the present application; Figure 2 is a structural block diagram of the vibroflotation pile composite foundation quality evaluation device based on the AHP-entropy weight method provided by one or more embodiments of the present application; Figure 3 The hierarchical structure model for evaluating the quality of vibro-compaction pile composite foundation provided for one or more embodiments of the present application; Figure 4 The zoning map for evaluating the quality of the composite foundation provided for one or more embodiments of the present application; Figure 5 The specific flowchart of the entropy weight objective weighting method provided for one or more embodiments of the present application; Figure 6 The structural schematic diagram of the medium provided for one embodiment of the present application; Figure 7 The structural schematic diagram of the computing device provided for one embodiment of the present application.

[0019] The realization of the purpose of the present application, functional features and advantages will be further described in conjunction with the embodiments with reference to the accompanying drawings. Specific Embodiments

[0020] It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application. On the contrary, these embodiments are provided to make the present disclosure more thorough and complete, and to convey the scope of the present disclosure to those skilled in the art completely.

[0021] Those skilled in the art know that the embodiments of the present application can be implemented as a system, device, equipment, method or computer program product. Therefore, the present application can be specifically implemented in the following forms, namely: complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0022] The embodiments of the present application provide a method for evaluating the quality of vibro-compaction pile composite foundation based on the AHP-entropy weight method, and this method can be executed by a computer, such as Figure 1 As shown, this method may include the following steps: S10, construct a multi-dimensional analysis model.

[0023] In an exemplary embodiment, step S10 may include the following steps: S110, conduct the static load test of the composite foundation; S120, evaluate the integrity and density of the vibro-compacted gravel piles; S130, construct a multi-dimensional analysis model based on the test and evaluation results.

[0024] Specifically, the overall process of the static load test of the composite foundation is as described below: The static load test of the composite foundation is carried out according to the service function of the pile. Axial pressure is applied step by step to the pile top, and the settlement of the corresponding detection points of the pile over time is observed. According to the relationship between the load and displacement (i.e., the Q-S curve), the corresponding vertical compressive bearing capacity is determined. This test method uses various artificial loading methods to simulate the actual working state of the foundation or the foundation, and tests its bearing performance and deformation characteristics after loading. The static load test of the composite foundation is used to determine the bearing capacity and deformation parameters of the composite soil layer within the main stress influence range under the bearing plate. The determination of this influence factor takes the cumulative settlement value of each point under the maximum load condition and the characteristic bearing capacity value determined by each test pile as the analysis index. The composite foundation bearing capacity is the basis for judging the quality of the vibroflotation gravel pile foundation and is positively correlated with the quality of the composite foundation. The cumulative settlement of the pile body under the maximum load is negatively correlated with the quality of the composite foundation.

[0025] Furthermore, the evaluation process of the integrity and density of the vibroflotation gravel pile is as follows: According to the specification standards of the "Technical Specification for Foundation Treatment by Vibroflotation Method in Hydropower and Water Conservancy Projects" (DL / 5214-2005), the "Code for Geotechnical Investigation" (GB50021-2001), and the "Technical Specification for Building Foundation Treatment" (JGJ79-2012), the integrity and density of the enhanced body of the gravel pile granular material composite foundation are inspected by the cone penetration test.

[0026] The cone penetration test uses a certain hammering kinetic energy to drive a cone probe of a certain specification into the soil. According to the resistance of the soil during driving, the change of the soil layer is judged, the soil layer is mechanically stratified, and the physical properties of the soil layer are determined to make an engineering geological evaluation of the foundation soil. In practice, the number of hammer blows for penetrating a certain depth into the soil layer is often used as the test index of the cone penetration test. The pile body density can reflect the integrity of the pile body itself and an important index of the pile body bearing capacity. The greater the pile body density, the higher the pile body bearing capacity. Therefore, the pile body density is positively correlated with the quality of the composite foundation. The pile body integrity is positively correlated with the quality of the composite foundation.

[0027] S20. Obtain four main control influence factors for quality evaluation based on the multi-dimensional analysis model.

[0028] Specifically, the influence factors include the pile body condition B1 of the vibroflotation pile, the treatment effect B2 of the soil between piles, the static load characteristics B3 of the composite foundation, and the engineering geological condition B4.

[0029] Furthermore, the pile body condition B1 of the vibroflotation pile includes the integrity C1 of the pile body size and the number of hammer blows C2 of the dynamic penetration test. The treatment effect B2 of the soil between piles includes the standard penetration number C3. The static load characteristics B3 of the composite foundation include the cumulative settlement C4 of the pile body under the maximum load. The engineering geological condition B4 includes the characteristics C5 of the pile tip bearing layer.

[0030] S30. Obtain the combined weights of each index based on the determined influence factors.

[0031] In an exemplary embodiment, step S30 may include the following steps: S310. Assign weights to the influence factors respectively based on the AHP subjective weighting method and the entropy weight objective weighting method; S320. Establish a formula based on the principle of minimum information entropy and the Lagrange multiplier method, optimize and solve the weights of the influence factors, and obtain the combined weights.

[0032] Specifically, the formula established in step S320 is as follows: (1) In the formula: minF is the minimum information entropy; m is the index value; Q j is the optimal weight of multi-source information of the AHP-entropy weight method; W j is the weight assigned by the AHP method; V j is the objective weight of the entropy weight; s.t. represents the constraint conditions that need to be satisfied during the optimization process.

[0033] Calculating according to the above steps, the optimal weight of multi-source information of the AHP-entropy weight method is obtained, as shown in Table 1.

[0034] Table 1

[0035] Furthermore, the AHP subjective weighting method is abbreviated as the AHP method. Its principle is to decompose the elements related to the decision-making problem into levels such as objectives, criteria, and solutions, and on this basis, a decision-making method for qualitative and quantitative analysis, which belongs to the subjective weighting method.

[0036] Next, the steps of the AHP subjective weighting method will be elaborated in detail with examples: Step 1: Establish the AHP influence factor hierarchical structure model The AHP subjective weighting method is a practical decision-making method that combines qualitative analysis and quantitative analysis. It decomposes complex problems into several levels, forming a progressive hierarchical structure, which greatly simplifies the problem analysis process. It has the advantages of simplicity, systematicness, reliability, etc.

[0037] The main principle of the AHP subjective weighting method is to use the quality evaluation of vibroflotation stone column composite foundation in the study area as the target layer (layer A), the conditions of vibroflotation stone column, the treatment effect of the soil between piles, the static load characteristics of the composite foundation, and the engineering geological conditions as the intermediate layer (layer B) that affect the factors in layer A. Each specific influence factor constitutes the decision-making layer (layer C) of this model according to its subordination relationship to the main control influence factor. Based on this, Figure 3 the shown hierarchical analysis diagram of the influence factors of the quality of vibroflotation gravel pile composite foundation is established.

[0038] Step 2: Establishment and Consistency Test of AHP Judgment Matrix Construct a judgment matrix. Make pairwise judgments on the indicators in the criterion layer to determine the weights of each criterion layer for the target layer. Taking m samples and n evaluation indicators as an example, construct the initial indicator matrix A:

[0039] where i and j are the row and column of the matrix respectively, and the elements in A satisfy the following formula: (2) In the formula: a ij is the index element; a kj is the j-th index element of the k-th layer; w i is the weight of each influencing factor.

[0040] The matrix can be used in the analytic hierarchy process to represent people's relative importance of each factor at each level. These judgments are represented numerically to form the result in matrix form.

[0041] The analytic hierarchy process is a practical decision-making method that combines qualitative analysis and quantitative analysis. It decomposes complex problems into several levels to form a progressive hierarchical structure, greatly simplifying the problem analysis process. It has the advantages of simplicity, systematicness, reliability, etc.

[0042] The main principle of the analytic hierarchy process is to take the quality evaluation of vibroflotation stone column composite foundation in the study area as the target layer (layer A), the vibroflotation stone column body conditions, the treatment effect of the soil between piles, the static load characteristics of the composite foundation, and the engineering geological conditions as the intermediate layer (layer B) that affects the factors at layer A. Each specific influencing factor constitutes the decision-making layer (layer C) of this model according to its subordination relationship to the main control influencing factor. Based on this, establish the Figure 3 shown analytic hierarchy process diagram of the influencing factors of the quality of vibroflotation gravel pile composite foundation.

[0043] The consistency verification formula of the hierarchical total sorting matrix is as follows: (3) In the formula: CR is the consistency ratio of the hierarchical total sorting; CI i is the single sorting consistency index; RI i is the single sorting average random consistency index; w A / B i is the hierarchical total sorting weight.

[0044] According to the consistency determination standard of the set confidence level: If CR < 0.10, it is considered that the determination of the judgment matrix weight coefficient meets the accuracy requirements. After calculation, CR is 0.0145 < 0.10, meeting the accuracy requirements.

[0045] The entropy weight objective weighting method (entropy weight method) is a commonly used comprehensive evaluation method that is not affected by subjective factors and is an objective weighting method. The core idea of the entropy weight method is to determine the objective weight completely through data-driven. Refer to Figure 5 , the specific process of the entropy weight method is introduced as follows: Assume that the data consists of n data samples and m indicators are defined. Let x ij be the indicator element, which can be abstracted into mathematical language as follows: Step 1: Construct the initial data matrix X:

[0046] where x ij is the i-th indicator and the j-th data element of X.

[0047] Step 2: Normalize the indicator data to establish the standard matrix. The indicators are divided into two types: positive indicators and negative indicators.

[0048] The normalization calculation formula for extremely large indicators (positive indicators) is as follows: (4) where Y ij is the normalized value of x ij ; x i is the i-th indicator of x; x ij is the i-th indicator and the j-th data element of x; min(x i ) is the minimum data value in the i-th indicator of x, and max(x i ) is the maximum data value in the i-th indicator of x.

[0049] The normalization calculation method for extremely small indicators (negative indicators): (5) where Y ij is the normalized value of x ij ; x i is the i-th indicator of x; x ij is the i-th indicator and the j-th data element of x; min(x i ) is the minimum data value in the i-th indicator of x, and max(x i ) is the maximum data value in the i-th indicator of x.

[0050] Step 3: Perform positive value processing on the numerical values After normalizing the data set, for the points with a numerical value of 0, these points need to be assigned a very small number similar to 0.00001. This will not affect the final calculation result of the weight value and can avoid the situation of unable to calculate during the calculation of information entropy.

[0051] Step 4: Calculate weights using the entropy weight method (1) Construct a standardized matrix (6) where Y is the standardized matrix; n is the number of data samples; m is the number of indicators.

[0052] (2) Calculate the entropy weight value H j (7) (8) where H j is the entropy weight value; n is the number of data samples, and m is the indicator value.

[0053] (3) Calculate the objective weight V of each evaluation indicator j (9) where V j is the objective weight of the evaluation indicator; n is the number of data samples.

[0054] Calculate the objective weights of each evaluation indicator of the vibro gravel pile composite foundation quality impact factor according to the above steps, as shown in Table 2 specifically.

[0055] Table 2

[0056] S40. Obtain the normalized thematic map of each of the said impact factor evaluation indicators based on the Kriging interpolation method.

[0057] In an exemplary embodiment, step S40 may include the following steps: S410. Perform dimensionless and normalized data processing on the impact factor indicators; S420. Multiply the impact factor indicators after dimensionless and normalized data processing by the combined weights of the determined impact factors; S430. Based on the Kriging interpolation method, use the numerical analysis ability of GIS to obtain the normalized thematic map of each impact factor evaluation indicator.

[0058] Specifically, to eliminate the influence of different dimensions in the quantification process of different influencing factors and facilitate the statistical superposition and comprehensive evaluation of impact factors, the study uses maximum value normalization for dimensionless data processing.

[0059] (10) In the formula: A irepresents the data after dimensionless processing of the data; a and b respectively represent the lower and upper limits of the normalization range, which are taken as 0 and 1 respectively in this exemplary embodiment; x i is the quantization value of each main control factor; minx i , maxx i are respectively the minimum and maximum values of the quantization values of each main control factor.

[0060] In addition, standardization can also be used for dimensionless processing of the data, linearly transforming the data according to the mean and standard deviation, so that the mean of the data is 0 and the standard deviation is 1.

[0061] Further, in this exemplary embodiment, after dimensionless and normalized data processing of the influence factor indicators, the product of the determined combined weights of each influence factor is used, and the Kriging interpolation method is used to utilize the numerical analysis ability of GIS to obtain the normalized thematic map of each influence factor evaluation index.

[0062] The Kriging interpolation method is a spatial interpolation method based on the covariance function, mainly used for spatial modeling and prediction of random processes or random fields.

[0063] S50. Based on the GIS overlay coupling function, overlay the normalized thematic maps to obtain the quality quantization index-type zoning evaluation map of the entire area of the composite foundation.

[0064] In the exemplary embodiment, step S50 may include the following steps: S510. Based on the GIS information fusion overlay coupling function, overlay the normalized thematic maps; S520. Obtain the quality quantization index-type zoning evaluation map of the entire area of the composite foundation.

[0065] Specifically, in step S510, the overlay coupling is performed based on the following formula: (11) In the formula: W is the quality index; W i is the influence factor weight; f i (x, y) is the single-factor influence value function; x and y are geographical coordinates; i is the number of influence factors.

[0066] In this exemplary embodiment, the integrated analysis module of the GIS (Geographic Information System) multiplies the data of the influencing factors affecting the quality of the vibroflotation gravel pile composite foundation by the weights after combined weighting and then performs superposition coupling. The superposition-coupled index value is used to reflect the quality evaluation of the vibroflotation pile composite foundation. The superposition-coupling formula is as described in formula (10), where positive correlation is addition and negative correlation is subtraction. The larger the calculated value W, the better the treatment effect of the vibroflotation gravel pile composite foundation. Thus, it comprehensively reflects the quality evaluation of the vibroflotation pile composite foundation, and based on this, the quality zoning of the vibroflotation gravel pile composite foundation is carried out.

[0067] S60. Divide and grade the quality quantification index-type zoning evaluation map, so as to conduct a zonal evaluation of the quality of the vibroflotation gravel pile composite foundation in the entire region. The composite foundation quality zoning grade map is specifically as Figure 4 shown.

[0068] In the exemplary embodiment, step S60 may include the following steps: S610. Grade the index value based on the dynamic natural grading method, and divide it into five grades according to different thresholds; S620. Based on the grading results, divide the overall region quality evaluation map into an excellent foundation treatment quality area, a relatively excellent area, a transition area, an average area, and a warning area.

[0069] Specifically, in this embodiment, a zonal evaluation is carried out on the uniformity of the quality of the treated composite foundation in this region. By using the powerful data management and spatial analysis functions and information fusion technology of GIS, an information fusion-type composite foundation quality quantification index-type zoning evaluation oriented to GIS is created. Through the vibroflotation gravel pile composite foundation quality index zoning map of this area, the quality balance of the foundation treated by the vibroflotation pile here and the risk of settlement in different areas of the treated foundation can be zoned. According to the results statistically analyzed by the model, the index value is graded based on the dynamic natural grading method and divided into five grades: excellent foundation treatment quality area, relatively excellent area, transition area, average area, and warning area.

[0070] The vibroflotation pile composite foundation quality evaluation method based on the AHP-entropy weight method provided in the above embodiment, by constructing a multi-dimensional analysis model, obtains four main control influencing factors for quality evaluation, thereby determining the influencing factor weight values required for the influencing factors, and thus obtaining the combined weights of each index, making the evaluation comprehensive, greatly reducing the error of the evaluation result, and being able to truly reflect the quality of the vibroflotation gravel pile composite foundation based on multiple test information sources; through the GIS superposition coupling function, each influencing factor is coupled and zoned and evaluated in the same map, which solves the problem of single-dimensional quality evaluation to a certain extent, can realize zonal evaluation and grading of the entire region, improves the accuracy of the evaluation of the treated foundation, provides specific and visual guidance for the acceptance and re-treatment of the composite foundation, and provides a new solution for the evaluation of the composite foundation.

[0071] Based on the above embodiments, with reference to Figure 2 , another embodiment of the present application further provides a vibroflotation pile composite foundation quality evaluation device, and the vibroflotation pile composite foundation quality evaluation device 200 may include the following modules: A construction module 210, configured to construct a multi-dimensional analysis model; An influencing factor acquisition module 220, configured to obtain four main influencing factors for quality evaluation based on the multi-dimensional analysis model; A weight acquisition module 230, configured to assign weights to the influencing factors based on the AHP subjective weighting method and the entropy weight objective weighting method, and obtain a combined weight; A thematic map acquisition module 240, configured to obtain a normalized thematic map of each influencing factor evaluation index based on the Kriging interpolation method; An overlay module 250, configured to overlay the normalized thematic maps based on the GIS overlay coupling function to obtain a quality quantization index type zoning evaluation map for the entire area of the composite foundation; A quality evaluation module 260, configured to classify and grade the quality quantization index type zoning evaluation map, so as to conduct a zoning evaluation on the quality of the vibroflotation gravel pile composite foundation in the entire area.

[0072] With reference to Figure 6 , the computer-readable storage medium shown therein is an optical disc 50, on which a computer program (i.e., a program product) is stored. When the computer program is run by a processor, it will implement the steps described in the above method embodiments, for example, constructing a multi-dimensional analysis model; obtaining four main influencing factors for quality evaluation based on the multi-dimensional analysis model; assigning weights to the influencing factors based on the AHP subjective weighting method and the entropy weight objective weighting method, and obtaining a combined weight; obtaining a normalized thematic map of each influencing factor evaluation index based on the Kriging interpolation method; overlaying the normalized thematic maps based on the GIS overlay coupling function to obtain a quality quantization index type zoning evaluation map for the entire area of the composite foundation; classifying and grading the quality quantization index type zoning evaluation map, so as to conduct a zoning evaluation on the quality of the vibroflotation gravel pile composite foundation in the entire area. The specific implementation manners of each step will not be repeated here.

[0073] It should be noted that examples of computer-readable storage media may also include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory, or other optical and magnetic storage media, which will not be elaborated one by one here.

[0074] In addition, based on the above embodiments, an embodiment of the present application further provides a computing device,Figure 7 FIG. shows a block diagram of an exemplary computing device 60 suitable for implementing embodiments of the present application. The computing device 60 may be a computer system or a server. Figure 7 The shown computing device 60 is merely an example and should not impose any limitation on the functions and scope of use of the embodiments of the present application.

[0075] As Figure 7 shown, the components of the computing device 60 may include, but are not limited to: one or more processors or processing units 601, a system memory 602, and a bus 603 connecting different system components (including the system memory 602 and the processing unit 601).

[0076] The computing device 60 typically includes a variety of computer system-readable media. These media can be any available media accessible by the computing device 60, including volatile and non-volatile media, removable and non-removable media.

[0077] The system memory 602 may include computer system-readable media in the form of volatile memory, such as random access memory (RAM) 6021 and / or cache memory 6022. The computing device 60 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, ROM 6023 can be used to read and write non-removable, non-volatile magnetic media ( Figure 7 not shown in the figure, commonly referred to as a "hard disk drive"). Although not shown in Figure 7 the figure, a disk drive for reading and writing removable non-volatile disks (such as "floppy disks") and an optical disk drive for reading and writing removable non-volatile optical disks (such as CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 603 connecting different system components through one or more data media interfaces. The system memory 602 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present application.

[0078] A program / utility 6025 having a set (at least one) of program modules 6024 may be stored, for example, in the system memory 602, and such program modules 6024 include, but are not limited to: an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include the implementation of a network environment. The program modules 6024 typically perform the functions and / or methods described in the embodiments of the present application.

[0079] The computing device 60 may also communicate with one or more external devices 604 (such as a keyboard, a pointing device, a display, etc.). Such communication may be carried out through the input / output (I / O) interface 605. Moreover, the computing device 60 may also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through the network adapter 606. As Figure 7 shown, the network adapter 606 communicates with other modules (such as the processing unit 601, etc.) of the computing device 60 through the bus 603 that connects different system components. It should be understood that although Figure 7 not shown in the figure, other hardware and / or software modules may be used in combination with the computing device 60.

[0080] The processing unit 601 executes various functional applications and data processing by running programs stored in the system memory 602. For example, it constructs a multi-dimensional analysis model; obtains four main control influencing factors for quality evaluation based on the multi-dimensional analysis model; assigns weights to the influencing factors based on the AHP subjective weighting method and the entropy weight objective weighting method, and obtains the combined weights; obtains the normalized thematic maps of the evaluation indexes of each of the influencing factors based on the Kriging interpolation method; overlays the normalized thematic maps based on the GIS overlay coupling function to obtain the quality quantification index type zoning evaluation map of the entire area of the composite foundation; divides and grades the quality quantification index type zoning evaluation map, so as to conduct a zonal evaluation of the quality of the vibroflotation gravel pile composite foundation in the entire area. The specific implementation manners of each step will not be repeated here. It should be noted that although several units / modules or sub-units / sub-modules of the vibroflotation pile composite foundation quality evaluation device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to the embodiments of the present application, the features and functions of the two or more units / modules described above may be embodied in one unit / module. Conversely, the features and functions of one unit / module described above may be further divided and embodied by multiple units / modules.

[0081] In the description of the present application, it should be noted that the terms "first", "second", and "third" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance.

[0082] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above may refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0083] In several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and there may be other division methods in actual implementation. For another example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some communication interfaces. The indirect coupling or communication connection of devices or units can be in electrical, mechanical, or other forms.

[0084] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0085] In addition, in each embodiment of the present application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0086] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in each embodiment of the present application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0087] Finally, it should be noted that the above embodiments are only specific implementation manners of the present application, used to illustrate the technical solutions of the present application, rather than limiting it. The protection scope of the present application is not limited thereto. Although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that any person skilled in the art within the technical scope disclosed by the present application can still modify the technical solutions recorded in the foregoing embodiments, or can easily think of changes, or perform equivalent replacements on some of the technical features; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

[0088] In addition, although the operations of the method of the present application are described in a specific order in the drawings, however, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step for execution, and / or one step may be decomposed into multiple steps for execution.

Claims

1. A method for evaluating the quality of vibro-compacted pile composite foundation based on AHP-entropy weight method, characterized in that: The method comprises the following steps: S10, construct a multi-dimensional analysis model; S20, obtaining four main influencing factors of quality evaluation based on the multi-dimensional analysis model; S30, weight the influencing factors based on the AHP subjective weighting method and the entropy weight objective weighting method, and obtain the combined weight; S40, obtaining normalized thematic maps of evaluation indicators of each of the impact factors based on the Kriging interpolation method; S50, superimposing the normalized thematic maps based on the GIS superposition coupling function to obtain a quality quantitative index-type zoning evaluation map of the entire composite foundation area; S60, dividing and grading the quality quantitative index type zoning evaluation diagram, thereby performing zoning evaluation on the quality of the vibro-compacted stone pile composite foundation in the entire area.

2. The method for evaluating the quality of vibro-compacted pile composite foundation according to claim 1, characterized in that: Step S10 includes the following steps: S110, conduct static load test on composite foundation; S120, evaluate the integrity and density of vibro-stone columns; S130, constructing a multi-dimensional analysis model based on the test and evaluation results.

3. The method for evaluating the quality of vibro-compacted pile composite foundation according to claim 1, characterized in that: Step S30 includes: S310, assigning weights to the influencing factors based on the AHP subjective weighting method and the entropy weight objective weighting method respectively; S320, based on the minimum information entropy principle and the Lagrange multiplier method, a formula is established to optimize and solve the weights of the influencing factors and obtain the combined weights.

4. The method for evaluating the quality of vibro-compacted pile composite foundation according to claim 1, characterized in that: Step S40 includes: S410, dimensionless and normalized data processing of impact factor indicators; S420, multiplying the impact factor index after dimensionless and normalized data processing by the determined combined weights of each impact factor; S430, based on the Kriging interpolation method, uses the numerical analysis capability of GIS to obtain the normalized thematic maps of the evaluation indicators of each influencing factor.

5. The method for evaluating the quality of vibro-compacted pile composite foundation according to claim 1, characterized in that: Step S50 includes: S510, based on the GIS information fusion overlay coupling function, overlaying the normalized thematic maps; S520, obtaining a quality quantitative index-type zoning evaluation map of the entire composite foundation area.

6. The method for evaluating the quality of vibro-compacted pile composite foundation according to claim 3, characterized in that: The formula established in step S320 is as follows: （1） Where: minF is the combined weight; Q j W is the optimal weighting of multi-source information according to AHP-entropy weight method; j is the weight assigned by AHP method; m is the index value; V j is the objective weight assigned by entropy weight; st represents the constraints that need to be met during the optimization process.

7. The method for evaluating the quality of vibro-compacted pile composite foundation according to claim 1, characterized in that: Step S60 includes: S610, grading the index value based on a dynamic natural grading method, and grading it into five levels according to different thresholds; S620, based on the classification results, the quality evaluation map of the entire area is divided into a foundation treatment quality high-quality area, a relatively high-quality area, a transition area, a general area and a warning area.

8. The method for evaluating the quality of vibro-compacted pile composite foundation according to claim 5, characterized in that: In step S510, superposition coupling is performed based on the following formula: （11） Where: W is the quality index; W i is the weight of influencing factors; f i (x,y) is the single factor influence value function; x, y are geographical coordinates; i is the number of influencing factors.

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