Ground fracture settlement deformation prediction method based on error function

Abstract

The invention discloses a ground fracture settlement deformation prediction method based on an error function, and the method comprises the following steps: firstly, obtaining related parameters of a ground fracture site, including a soil layer profile parameter, a ground fracture basic parameter, a ground fracture strength parameter and a ground fracture and upper and lower disc soil layer interface material strength parameter; then establishing an original site numerical analysis model and simulating ground fracture differential settlement motion to obtain a ground surface differential settlement curve; then, based on the error function, a least square method is adopted to fit soil deformation so as to obtain an error function parameter, and then the incidence relation between the parameter and a ground fracture characteristic parameter is established; and finally, comparing and analyzing the ground surface settlement prediction curve based on the error function with a numerical simulation curve, and evaluating the precision of the prediction curve. According to the method, error function fitting and parameter correlation are utilized, and effective prediction of ground surface settlement of ground fracture activity is achieved.

Description

Technical Field

[0001] This invention relates to the field of geological disaster monitoring and prediction technology, specifically to a method for predicting ground fissure settlement and deformation based on an error function. Background Technology

[0002] Ground fissure subsidence is a common and extremely dangerous geological hazard. In urban environments, surface buildings and underground pipelines are crucial supports for the normal operation of cities, and ground fissure subsidence can cause devastating damage to them. For example, in some cities, ground fissure subsidence has led to cracked and tilted building walls, seriously threatening the safety of residents; ruptured underground pipelines have caused malfunctions in water supply, drainage, and gas systems, affecting residents' lives and the normal operation of the city, and significantly increasing urban maintenance costs. From an urban planning perspective, the uncertainty of ground fissure subsidence areas hinders rational urban planning and sustainable development. If the risks of ground fissure subsidence are not fully considered in the initial planning, large-scale engineering modifications and safety hazards may follow.

[0003] Traditional methods for obtaining ground settlement parameters at ground fissure sites often rely on model tests to construct settlement curves for single models. This process is time-consuming and can only reflect the ground settlement patterns under a single condition. Furthermore, traditional mathematical model prediction methods are limited by their ability to characterize complex geological conditions (such as differences in the properties of different strata and soils, and the complexity of geological structures) and dynamic factors (such as interference from human engineering activities and dynamic changes in groundwater). As a result, they are difficult to accurately simulate the actual ground fissure settlement process, and the prediction results have large errors, failing to provide reliable guidance for engineering practice.

[0004] For example, Chinese patent CN 222211486 U, through the coordinated design of a support platform, adjusting arm, and measuring structure, combined with a level calibrator and settlement observation window, can simultaneously acquire core parameters such as the width, depth, and settlement value of ground fissures. Chinese patent application CN 115468497 A, targeting complex mining environments, utilizes a bidirectional screw-driven ranging plate of the fissure width measuring component, along with infrared sensing and displacement monitoring of the moving block of the settlement measuring component, to achieve automated measurement of fissure width and settlement depth at different locations, featuring a multi-dimensional, multi-point data acquisition mode.

[0005] Chinese patent application CN 118965108 A establishes a correlation between ground fissure monitoring data and risk indicators by extracting change characteristic values ​​from monitoring data, calculating overall impact values, and screening key monitoring data. It also analyzes the data fluctuation patterns and impact weights. Chinese patent application CN 109783947 A uses a passivated fracture zone model to dynamically simulate the occurrence and propagation of ground fissures by dividing the soil failure stages and correcting the stress-strain matrix. It also demonstrates a modeling method for the correlation between soil mechanical behavior and fissure activity. The aforementioned prediction methods based on simple empirical formulas are mostly derived from limited case studies in local areas, lacking solid theoretical support. Furthermore, variations in geological conditions lead to drastic changes in the applicability of these formulas, resulting in poor universality across different geological regions and failing to meet diverse and precise prediction needs. As the geological environment becomes increasingly complex due to natural evolution and intensified human activities, there is an urgent need for a more accurate, reliable, and adaptable method for predicting ground fissure subsidence and deformation to improve geological disaster prevention and control, and ensure the safe development of engineering projects and cities. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for predicting ground fissure settlement and deformation based on an error function. This method can predict the surface settlement pattern of similar sites by obtaining the soil foundation profile parameters and basic parameters of the ground fissures at a specific site. This invention not only proposes a method that can accurately predict the surface settlement pattern of a site, but also enables the construction of a supporting prediction system based on this method.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: The method for predicting ground fissure settlement based on error functions includes the following steps: Step 1.1: Obtain soil profile parameters for the ground fissure site; the soil profile parameters include: the structural composition of the soil layers and the burial depth of each soil layer. H i The physical and mechanical properties of each soil layer; these properties include elastic modulus E, Poisson's ratio μ, unit weight γ, cohesion c, and internal friction angle φ. Step 1.2: Obtain the basic parameters of the ground fissure; the basic parameters include: the dip angle and underground extension depth of the ground fissure; Step 1.3: Obtain the strength parameters of the ground fissure and the strength parameters of the interface materials between the ground fissure profile and the soil layers of the upper and lower plates; the strength parameters include: normal stiffness modulus. K n Shear stiffness modulus K t , cohesion c and internal friction angle φ; Step 1.4: Based on the parameters obtained in steps 1.1, 1.2, and 1.3, establish a numerical analysis model of the original site, including the following steps: ① construct the model geometry, ② assign parameters to the constitutive model, and ③ set boundary conditions. Step 1.5: Simulate differential subsidence movement of ground fissures on the numerical analysis model established in Step 1.4, and obtain the differential subsidence curve of the original site under differential subsidence movement of ground fissures. In step 1.1, the soil profile parameters of the ground fissure site are obtained by drilling at certain intervals using drilling equipment, extracting rock cores, and dividing the soil into layers to determine the soil stratification (such as miscellaneous fill, silty clay, silty sand, etc.). A columnar section of the soil profile is then drawn to clarify the spatial distribution and contact relationship of each soil layer. Indoor geotechnical tests are conducted on each soil sample: the elastic modulus E is determined through static compression tests; Poisson's ratio μ is calculated using triaxial compression test data; the unit weight γ is measured using the ring cutter method; and the cohesion c and internal friction angle φ are obtained through direct shear tests, providing mechanical parameters for numerical simulation.

[0008] In step 1.2, the basic parameters of the ground fissures were determined through geological surveys and explorations.

[0009] In step 1.3, the strength parameters of the ground fissure and the strength parameters of the interface materials between the ground fissure profile and the soil layers of the upper and lower plates are obtained by collecting samples of the ground fissure filling material (fractured rock and soil, clay with gravel, etc.) and conducting stiffness tests (staged loading and unloading). The deformation is measured by applying normal stress, and the normal stiffness modulus is obtained by fitting the slope of the stress-strain curve. K n Similarly, shear loads are applied to obtain the shear stiffness modulus. K t This is to reflect the deformation resistance of ground fissures in the normal and shear directions.

[0010] In step 1.4, the numerical analysis model can be established using finite element software (Midas GTS NX).

[0011] In step 1.4, the model geometry includes: creating model geometry according to the actual soil layer distribution, setting the thickness of each soil layer, and constructing the geometric shape of the ground fissure based on the ground fissure dip angle α and the underground extension depth D; the parameters assigned to the constitutive model include: assigning physical, mechanical, and strength parameters to the interface between the soil layer and the ground fissure, and selecting a suitable constitutive model for the soil; the boundary condition settings include: applying horizontal constraints to the side of the model, applying vertical constraints to the bottom, and the surface being a free boundary without actual constraints.

[0012] In step 1.5, the differential settlement curve is the vertical displacement of the surface nodes of the detection model, and the maximum identification amount and settlement influence range are analyzed.

[0013] Step 2.1: The surface deformation curve caused by normal fault displacement has similar curve characteristics to the error function. Based on the error function, the soil deformation of the ground fissure site is fitted, and it conforms to the shear deformation mechanism of the overlying soil. The expression (1) is as follows: (1), in B, CThese are two parameters that control the shape and position of the error function curve, where h is the settlement depth of the hanging wall of the ground fissure, and X is the distance from the outcrop of the ground fissure.

[0014] Step 2.2: Extract n sets of discrete data points from the original site surface differential settlement curve: {(x1,y1), (x2,y2),…,(x n ,y n ), where x i Let y be the distance from the outcrop of the ground fissure in the i-th data set. i For the corresponding x i The observed surface subsidence values ​​are given, where i is any value from 1 to n. The error function expression is then used as the objective function for fitting, denoted as f(X,B,C)=h, where B and C are the parameters to be solved, and h is the known subsidence depth of the hanging wall of the ground fissure. The sum of squared errors equation is then constructed: Where i represents the i-th set of data from the n sets of discrete data points extracted from the curve. e i Let's define the equation for the sum of squared errors of the i-th group. Finally, we solve for the parameters using the Gauss-Newton iterative method. When the iteratively corrected parameters meet the convergence condition, we can obtain the parameter values ​​for B and C.

[0015] Step 2.3: To predict settlement deformation in different sites and make the error function universal for ground fissure sites, establish the correlation between parameters B and C and the characteristic parameters of ground fissures.

[0016] Step 2.4 involves comparing and analyzing the derived surface subsidence prediction curve based on the error function for ground fissures with the curve obtained from numerical simulation. The differences between the curves are analyzed, and the accuracy of the surface subsidence prediction curve based on the error function for ground fissure activity is comprehensively assessed.

[0017] In step 2.3, the parameter correlation is achieved through parameter sensitivity analysis and correlation modeling to quickly fit the sensitive parameters B and C. First, select the characteristic parameters of the ground fissure, rewrite the value of each characteristic value while keeping other parameters unchanged, and observe the changes in parameters B and C to analyze which characteristic parameters have a greater impact on B and C. Then, select a suitable model to establish the correlation between parameters B and C and the characteristic parameters of the ground fissure.

[0018] In step 2.4, the method for quantifying the accuracy of the model uses variance calculation. The smaller the variance, the lower the degree of dispersion between the predicted value and the actual value, and the higher the model accuracy.

[0019] The beneficial effects of this invention are as follows: Based on the geological profile structure, distribution, and development status of ground fissure sites obtained from geological exploration, a relatively complete geological model of the ground fissure site that can better reflect the actual situation is obtained. Then, based on the error function, the surface subsidence caused by ground fissure activity is described more clearly, and a prediction method based on the basic parameters of ground fissures is established on this basis. This method avoids repetitive data collection and numerical modeling, reduces a lot of workload, truly realizes the prediction of surface subsidence in ground fissure sites, and is fast, simple, and effective. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the process of this invention; Figure 2 It is a finite element calculation model of a ground fissure site at a 70° dip angle; Figure 3 These are curves showing the vertical displacement of soil in ground fissure sites with different inclination angles. Figure 4 These are comparative curves of soil settlement and deformation patterns in ground fissure sites based on error functions. Detailed Implementation

[0021] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0022] The structures, proportions, and sizes illustrated in the accompanying drawings are merely for illustrative purposes and to aid those skilled in the art in understanding and reading the invention. They are not intended to limit the scope of the invention and therefore have no substantial technical significance. Any modifications to the structure, changes in proportions, or adjustments to size, provided they do not affect the effectiveness or purpose of the invention, should still fall within the scope of the technical content disclosed herein. Furthermore, the terms "upper," "lower," "left," "right," "middle," and "one" used in this specification are merely for clarity and not intended to limit the scope of the invention. Changes or adjustments to their relative relationships, without substantially altering the technical content, should also be considered within the scope of the invention's implementation.

[0023] like Figures 1-4 As shown, a method for predicting ground fissure settlement and deformation based on an error function is implemented according to the following steps: Step 1.1: Obtaining Soil Profile Parameters at the Ground Fissure Site: Using drilling equipment, boreholes are drilled at preset intervals (e.g., every 5-10 meters) at the target ground fissure site to extract core samples. Based on the core characteristics, geological expertise is used to divide the strata, clarifying the soil layer composition, such as miscellaneous fill, silty clay, and silty sand layers, and drawing detailed soil profile columnar diagrams to accurately determine the spatial distribution and contact relationships of each soil layer. Representative samples are extracted from each soil layer for indoor geotechnical tests: static compression tests are conducted, and the elastic modulus E is determined by analyzing the test data; Poisson's ratio μ is calculated using data obtained from triaxial compression tests; the unit weight γ is measured using the ring cutter method; and cohesion c and internal friction angle φ are obtained using direct shear tests, providing reliable mechanical parameters for subsequent numerical simulations.

[0024] Step 1.2, Obtaining Basic Parameters of Ground Fissures: Organize a professional geological team to comprehensively utilize geological survey (such as surface geological mapping and geological mapping) and exploration (such as ground-penetrating radar detection and core drilling) methods to determine the basic parameters of the ground fissures in detail, including the dip angle and underground extension depth. Typically, the dip angle of ground fissures is determined to be between 60° and 80°, but it is not limited to this and depends on the actual site conditions. The underground extension depth is related to the dip angle of the ground fissure and its distance from the surface outcrop; the larger the dip angle, the deeper the fissure; and the farther away from the surface outcrop, the deeper the fissure.

[0025] Step 1.3: Obtain the strength parameters of the ground fissure and the interface material: Collect samples of the filling material (such as fractured rock and soil, clay mixed with gravel, etc.) of the ground fissure zone and conduct stiffness tests. The test adopts a staged loading and unloading method. First, normal stress is applied, and the deformation is recorded. The normal stiffness modulus K is obtained by fitting the slope of the stress-strain curve. n Similarly, the shear stiffness modulus is obtained by applying a shear load. K t Meanwhile, cohesion c and internal friction angle φ were determined through relevant tests to comprehensively reflect the deformation resistance of the ground fissure in the normal and shear directions, as well as the strength characteristics of the interface materials between the ground fissure profile and the soil layers of the upper and lower plates.

[0026] Step 1.4: Construct the original site numerical analysis model, as shown in Figure (2). Based on the parameters obtained in Steps 1.1, 1.2, and 1.3, establish the original site numerical analysis model and construct the model geometry in sequence: Based on the actual soil layer distribution, create the model geometry in the software and accurately set the thickness of each soil layer. Based on the dip angle α and underground extension depth D of the ground fissure, construct a ground fissure geometry model that conforms to the actual shape. Parameter assignment and constitutive model: Assign the physical, mechanical, and strength parameters of the soil layer and ground fissure interface obtained in Steps 1.1-1.3 to the corresponding parts of the model, and select a suitable constitutive model (such as the Mohr-Coulomb constitutive model) according to the soil properties. Set boundary conditions: Apply horizontal constraints to the side of the model to limit horizontal displacement; apply vertical constraints to the bottom to limit vertical displacement; set the surface as a free boundary and do not apply actual constraints to simulate the real surface environment.

[0027] Step 1.5, Simulate Differential Subsidence Movement of Ground Fissures: Based on the established numerical analysis model, simulate the differential subsidence movement process of ground fissures. By detecting the vertical displacement of the surface nodes of the model, analyze data such as the maximum subsidence and the range of subsidence influence, and obtain the surface differential subsidence curve of the original site under the differential subsidence movement of ground fissures. Figure 3 ).

[0028] Step 2.1, constructing the error function to fit the predicted surface settlement curve of the ground fissure: Given that the surface deformation curve caused by normal fault slippage has similar curve characteristics to the error function, the soil deformation of the ground fissure site is fitted based on the error function. To fit the shear deformation mechanism of the overlying soil, expression (1) is adopted. (1), in B, C These are two parameters that control the shape and position of the error function curves. h is the settlement depth of the hanging wall of the ground fissure, and X is the distance from the outcrop of the ground fissure.

[0029] Step 2.2: Extract n sets of discrete data points from the original site surface differential settlement curve: {(x1,y1), (x2,y2),…,(x n ,y n ), where x i Let y be the distance from the outcrop of the ground fissure in the i-th data set. i For the corresponding x i The observed surface subsidence values ​​are given, where i is any value from 1 to n. The error function expression is then used as the objective function for fitting, denoted as f(X,B,C)=h, where B and C are the parameters to be solved, and h is the known subsidence depth of the hanging wall of the ground fissure. The sum of squared errors equation is then constructed: Where i represents the i-th set of data from the n sets of discrete data points extracted from the curve. ei Let's define the equation for the sum of squared errors of the i-th group. Finally, we solve for the parameters using the Gauss-Newton iterative method. When the iteratively corrected parameters meet the convergence condition, we can obtain the parameter values ​​for B and C.

[0030] Step 2.3, Establishing Parameter Correlation: Using parameter sensitivity analysis, first select the characteristic parameters of the ground fissure, rewrite the value of each characteristic value while keeping other parameters unchanged, and determine the correlation between parameters B and C and the characteristic parameters of the ground fissure (such as the ground fissure dip angle, underground extension depth, and ground fissure activity depth). Analyze which characteristic parameters have a greater impact on B and C, and then select the corresponding model to establish the correlation between parameters B and C and the characteristic parameters of the ground fissure. This enables rapid fitting of sensitive parameters B and C, making the error function universal for ground fissure sites.

[0031] Step 2.4, evaluate the accuracy of the surface subsidence prediction curve for ground fissure activity: compare and analyze the derived surface subsidence prediction curve based on the error function with the curve obtained from numerical simulation, as shown in Figure (4). Compare and analyze the differences between the curves, and comprehensively analyze the accuracy of the surface subsidence prediction curve under ground fissure activity. Example 1

[0032] The construction site is located in the loess subsidence area of ​​Xi'an, and there are ground fissures in the site.

[0033] Step 1.1: At an engineering site in Xi'an, professional drilling equipment was used to drill 20 boreholes at 8-meter intervals, penetrating the main strata of the site. After extracting core samples, geological engineers, based on the color, structure, texture, and inclusions of the core samples, and combined with the typical stratigraphic distribution patterns in the Xi'an area, divided the site's strata into four main categories: fill, loess, paleosols, and interbedded silt. Simultaneously, a high-precision soil profile columnar section was drawn, clearly showing the spatial distribution and contact relationships of each soil layer.

[0034] Using compression testing equipment, progressively increasing pressures were applied to the samples. Stress-strain curve analysis revealed the following elastic moduli: 26.0 MPa for plain fill, 28.0 MPa for loess, 41.7 MPa for paleosol, and 46.0 MPa for interbedded silt. Based on triaxial compression test data and processed using specialized software, the Poisson's ratio was determined to be 0.35 for plain fill, 0.30 for loess, 0.28 for paleosol, and 0.31 for interbedded silt. Using the ring sampler method, strictly following the "Standard for Geotechnical Testing Methods" (GB / T 50123-2019), the unit weights were measured to be 18.0 kN / m³ for plain fill, 18.5 kN / m³ for loess, 18.6 kN / m³ for paleosol, and 19.5 kN / m³ for interbedded silt. Through direct shear tests, the following parameters were obtained: cohesion of plain fill soil (20 kPa, internal friction angle 15°); cohesion of loess soil (40 kPa, internal friction angle 20°); cohesion of paleosol soil (40 kPa, internal friction angle 21°); and cohesion of silt interbedded soil (40 kPa, internal friction angle 24°).

[0035] Step 1.2 involves a basic investigation of the ground fissures. First, a 1:500 scale surface geological mapping is conducted to identify the surface traces and extension direction of the fissures. Then, ground-penetrating radar is used to probe along the fissure's direction, preliminarily determining its underground distribution. Finally, core drilling is employed for verification. Six exploration boreholes are arranged on both sides of the fissure, reaching a depth of 60 meters underground. Through detailed analysis of the core samples, combined with inclinometer data, the dip angle of the ground fissure is precisely determined to be 70°, with an underground extension depth exceeding 40 meters.

[0036] Step 1.3: Samples of fractured rock and soil, clay mixed with gravel, and other filling materials were collected from five different locations within the ground fissure zone. The normal stiffness modulus K was measured. n It is 6.75×10 4 kPa; apply shear load using a similar method to obtain the shear stiffness modulus K. t Also 6.75×10 4 kPa. Meanwhile, direct shear tests determined the cohesion c of the ground fissure filler to be 10 kPa and the internal friction angle φ to be 12°.

[0037] The final basic parameters of the soil layer and ground fissures at the site of the ground fissure are as follows: Table 1. Geometric relationships of the stratigraphy and basic parameters of the ground fissure site.

[0038] Step 1.4: Establish a numerical analysis model. Using Midas GTS NX finite element software, based on the site's strata distribution and thickness data, sequentially create layers of 8.6m thick plain fill, 41.2m thick loess, 19.5m thick paleosol, and 10.7m thick silt interbedded in the software. Based on the 70° dip angle and underground extension depth of the ground fissures, the geometric morphology of the fissures is precisely constructed. The horizontal range of the model is 50 meters on each side of the fissures, and the vertical depth is 60 meters. Subsequently, the physical and mechanical parameters of each soil layer, such as elastic modulus, unit weight, Poisson's ratio, cohesion, and internal friction angle, as well as the strength parameters Kn, Kt, c, and φ of the ground fissures, are assigned to the corresponding parts of the model. The soil mass adopts a Mohr-Coulomb constitutive model. Finally, horizontal constraints are applied laterally to limit horizontal displacement; vertical constraints are applied at the bottom to limit vertical displacement; the surface is set as a free boundary to simulate real site boundary conditions.

[0039] Step 1.5: Set the settlement of the hanging wall of the ground fissure to 30mm on the constructed model to simulate the differential settlement process of the ground fissure, and record the vertical displacement of the model surface in real time in the software to draw the differential settlement curve of the original site.

[0040] Step 2.1, based on the similarity in morphological characteristics between normal fault displacement and error function, this study adopts the error function expression (1): (1), in B, C These are the parameters controlling the shape and position of the four error function curves, where h is the settlement depth of the hanging wall of the ground fissure, and X is the distance from the outcrop of the ground fissure.

[0041] To achieve accurate fitting, an equation for the sum of squared errors is constructed based on the expression of the error function and the least squares method: Based on the Gauss-Newton iterative method, the parameter values ​​of B and C in the objective function were calculated. Using simulated differential surface subsidence data as constraints, the parameters in the error function were finally obtained when the ground fissure dip angle was 70° and the activity was 0.3m. B =0.0173, C =-0.445.

[0042] Step 2.2 involves sensitivity analysis of the parameters to identify B and C as the main controlling parameters significantly affecting ground fissure subsidence. Subsequently, characteristic parameters of ground fissures (such as fissure dip angle, underground extension depth, and fissure activity depth) are introduced to establish the correlation function of the error function prediction model for ground fissure surface subsidence. The final relationship between B, C and the ground fissure parameters can be obtained as follows: (2), (3), Substituting the functions describing the parameters into equation (1), we can obtain the calculation formula (4) for the curve characterizing the settlement and deformation law of the soil in the ground fissure site: (4), The final prediction model not only quantifies the impact of various parameters on ground fissure subsidence, but can also be applied to surface subsidence caused by uneven subsidence of ground fissures under similar geological conditions, providing a reliable basis for subsequent engineering design.

[0043] Step 2.3, evaluate the accuracy of the surface subsidence prediction curve for ground fissure activity: compare and analyze the derived surface subsidence prediction curve based on the error function with the curve obtained from numerical simulation, as shown in Figure (4). Compare and analyze the differences between the curves, and comprehensively analyze the accuracy of the surface subsidence prediction curve under ground fissure activity.

[0044] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for predicting ground fissure settlement and deformation based on an error function, characterized in that, Includes the following steps: Step 1.1: Obtain relevant parameters of the ground fissure site; Step 1.2: Based on the parameters obtained in Step 1.1, establish a numerical analysis model of the original site; Step 1.3: Simulate the differential settlement movement of ground fissures on the numerical analysis model to obtain the differential settlement curve of the original site; Step 1.4: Fit the soil deformation of the ground fissure site based on the error function. Obtain the error function parameters by fitting the error function expression through the algorithm. Step 1.5: Establish the correlation between the error function parameters and the characteristic parameters of the ground fissure; Step 1.6: Evaluate the accuracy of the surface subsidence deformation prediction curve for ground fissure activity: Compare and analyze the derived surface subsidence deformation prediction curve based on the error function with the curve obtained from numerical simulation, compare and analyze the differences between the curves, and comprehensively analyze the accuracy of the surface subsidence prediction curve under ground fissure activity.

2. The method for predicting ground fissure settlement and deformation based on an error function as described in claim 1, characterized in that, The relevant parameters for the ground fissure site in step 1.1 include: a. Soil profile parameters at the site of the ground fissure; b. Basic parameters of ground fissures; c. Strength parameters of the ground fissures and strength parameters of the interface materials between the ground fissure profile and the soil layers of the upper and lower plates.

3. The method for predicting ground fissure settlement and deformation based on an error function as described in claim 2, characterized in that, The soil profile parameters of the ground fissure site include: the structural composition of the soil layers, the burial depth of each soil layer, and the physical and mechanical properties of each soil layer; the physical and mechanical properties include elastic modulus, Poisson's ratio, unit weight, cohesion, and internal friction angle.

4. The method for predicting ground fissure settlement and deformation based on an error function as described in claim 2, characterized in that, The basic parameters of the ground fissures include: the dip angle and the depth of underground extension.

5. The method for predicting ground fissure settlement and deformation based on an error function as described in claim 2, characterized in that, The strength parameters include: normal stiffness modulus, shear stiffness modulus, cohesion, and internal friction angle.

6. The method for predicting ground fissure settlement and deformation based on an error function as described in claim 1, characterized in that, The numerical analysis model in step 1.2 is established using finite element software; the establishment of the numerical analysis model of the original site includes the following steps: ① constructing the model geometry, ② assigning parameters and constitutive model, ③ setting boundary conditions.

7. The method for predicting ground fissure settlement and deformation based on an error function as described in claim 6, characterized in that, The construction of the model geometry includes: creating model geometry according to the actual soil layer distribution, setting the thickness of each soil layer, and constructing the geometric shape of the ground fissures based on the ground fissure dip angle and underground extension depth; The parameters assigned to the constitutive model include: assigning physical, mechanical, and strength parameters to the interface between the soil layer and the ground fissure, and selecting a corresponding constitutive model for the soil. The boundary conditions are set as follows: horizontal constraints are applied to the sides of the model, vertical constraints are applied to the bottom, and the ground surface is a free boundary with no actual constraints.

8. The method for predicting ground fissure settlement and deformation based on an error function as described in claim 1, characterized in that, In step 1.3, the differential settlement curve represents the vertical displacement of the surface nodes of the detection model, and is used to analyze the maximum identification amount and the range of settlement influence.

9. The method for predicting ground fissure settlement and deformation based on an error function as described in claim 1, characterized in that, In step 1.4, the error function is expressed as: (1)， in B, C These are the parameters that control the shape and position of the error function curves, where h is the settlement depth of the hanging wall of the ground fissure, and X is the distance from the outcrop of the ground fissure. The error function expression in the fixed ground fissure site was fitted by the least squares algorithm, and the B and C parameters of equation (1) were obtained.

10. The method for predicting ground fissure settlement and deformation based on an error function as described in claim 9, characterized in that, In step 1.5, the parameter correlation relationship is established as follows: by using the parameter sensitivity analysis method and combining the correlation model, the correlation relationship between parameters B and C and the characteristic parameters of the ground fissure is determined, so as to achieve rapid fitting of sensitive parameters B and C and make the error function have the universality of ground fissure sites.

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