Stability Detection Method for Expansive Soil Slopes Based on Crack Evolution and Intelligent Slip Surface Recognition

Abstract

This invention discloses a method for detecting the stability of expansive soil slopes based on fracture evolution and intelligent identification of sliding surfaces. The method collects soil structure data and primary fracture distribution data of the expansive soil slope to construct a geological model of the fractured slope. It estimates the dynamic characteristics of water infiltration within the slope based on precipitation data to generate the slope's deformation. Combining the geological model and deformation data, it estimates the fracture development trend of the slope, obtaining the changes in the fracture structure. Based on the changes in fracture structure, it searches for the sliding surface within the slope. Based on the stress state of the sliding surface, it predicts the soil sliding change state of the slope. By utilizing soil structure and primary fractures to construct a complete model, the method accurately ensures the geological structure of the slope. Furthermore, it uses the dynamic water infiltration caused by precipitation as the basis for predicting fracture development in the geological model, accurately locating the sliding surface within the slope, and improving the accuracy of slope stability detection.

Description

Technical Field

[0001] This invention relates to the field of soil engineering testing, and in particular to a method for testing the stability of expansive soil slopes based on crack evolution and intelligent identification of sliding surfaces. Background Technology

[0002] Expansive soil is a type of clay that expands upon absorbing water and shrinks upon losing water. Under repeated wet-dry cycles, it develops numerous fissures, easily leading to deformation of expansive soil slopes and subsequently landslides. Slope engineering projects often include a certain amount of expansive soil, and these characteristics inevitably pose a risk of landslides and collapses. To ensure the safety of expansive soil slopes and to implement timely slope reinforcement projects, stability testing of expansive soil slopes is necessary. Existing methods for expansive soil slope stability testing mainly include slope stability analysis based on fitting the unfavorable sliding surface using the circular arc sliding method, or calculating the sliding surface strength based on fissure distribution statistics. However, the method based on fitting the unfavorable sliding surface using the circular arc sliding method fails to reflect the actual situation when the slope becomes unstable, resulting in significant distortion in the analysis results. The method based on calculating the sliding surface strength based on fissure distribution statistics heavily relies on the quantitative statistical results of fissure spatial distribution and does not consider the dynamic influence of precipitation on fissure development and evolution. This shows that existing slope stability testing does not fully consider the effect of precipitation infiltration into the slope on crack development, and cannot form a comprehensive and accurate prediction of crack evolution. This reduces the reliability of locating the sliding surface and identifying the mechanical state inside the slope, thus affecting the accuracy of slope stability testing. Summary of the Invention

[0003] Considering the existing methods for detecting the stability of expansive soil slopes and taking into full account the effect of precipitation infiltration into the slope on crack development, it is impossible to accurately predict the entire process of crack structure evolution. This reduces the reliability of locating the sliding surface inside the slope and identifying soil sliding, thus affecting the accuracy of slope stability detection.

[0004] In view of the above problems, the present invention provides a method for detecting the stability of expansive soil slopes based on crack evolution and intelligent identification of sliding surfaces, characterized in that it includes: Step 1: Collect soil structure data and primary fissure distribution data for expansive soil slopes; Step 2: Preprocess the soil structure data and the original fracture distribution data to construct a geological model of the fractured slope; Step 3: Obtain historical precipitation data for the area where the expansive soil slope is located, and use this data to estimate the dynamic characteristics of water infiltration of the expansive soil slope; Step 4: Based on the dynamic characteristics of water seepage, generate the swelling stress effect of the expansive soil slope; Step 5: Based on the geological model of the fractured slope and the effect of expansion stress, estimate the fracture development trend of the expansive soil slope; Step 6: Estimate the changes in the crack structure of the expansive soil slope based on the crack development trend; Step 7: Search for the sliding surface inside the expansive soil slope based on the changes in the crack structure; predict the soil sliding change state of the expansive soil slope based on the stress state of the sliding surface.

[0005] Preferably, step one specifically includes the following steps: Step 11: Perform ultrasonic scanning on the expansive soil slope, collect and analyze the ultrasonic echo signals of the expansive soil slope, and obtain soil structure data and first primary fissure distribution data; wherein, the soil structure data includes the soil type and soil layer thickness layout inside the expansive soil slope; the first primary fissure distribution data includes the morphology and location of the primary fissures inside the expansive soil slope. Step 12: Perform machine vision recognition on the expansive soil slope to obtain the second primary crack distribution data; wherein, the second primary crack distribution data includes the length, average width, direction, center point coordinates of each crack, and the surface density of all cracks.

[0006] Preferably, step two specifically includes the following steps: Step 21: Perform three-dimensional spatial coordinate unification preprocessing and abnormal data partial removal preprocessing on the soil structure data, the first primary fracture distribution data, and the second primary fracture distribution data; Step 22: Perform three-dimensional spatial modeling on the soil structure data, the first primary fracture distribution data, and the second primary fracture distribution data to obtain a geological model of the fractured slope.

[0007] Preferably, step three specifically includes the following steps: Step 31: Collect historical precipitation data of the area where the expansive soil slope is located, perform multidimensional precipitation feature identification and differentiation on the historical precipitation data, and generate a multidimensional precipitation data sequence; wherein, the multidimensional precipitation features include precipitation type, precipitation duration, precipitation location, and precipitation intensity; the multidimensional precipitation data sequence refers to the time-space sequence data formed by arranging each precipitation event in chronological order and associating it with the spatial distribution of its precipitation intensity; Step 32: Based on the multidimensional precipitation data sequence, determine the spatial distribution of rainfall input flow to the expansive soil slope during each type of precipitation event; Step 33: Estimate the water infiltration dynamic characteristics of the expansive soil slope based on the spatial distribution of rainfall input flow and the second primary fissure distribution data; wherein, the water infiltration dynamic characteristics refer to the flow rate of precipitation infiltrating into the expansive soil slope through the primary fissures on the surface of the expansive soil slope.

[0008] Preferably, step four specifically includes the following steps: Step 41: Based on the dynamic characteristics of water infiltration and the real-time water content distribution of the expansive soil slope, estimate the spatial distribution of the water absorption and swelling deformation of the expansive soil slope; Step 42: Calculate the elastic stress field generated by the spatial distribution of the water absorption and swelling deformation according to the constitutive model of the expansive soil, and obtain the swelling stress effect of the expansive soil slope; wherein, the swelling stress effect refers to the stress distribution formed by the water absorption and swelling deformation inside the expansive soil slope.

[0009] Preferably, step five specifically includes the following steps: Step 51: Based on the expansive stress, generate the stress field inside the expansive soil slope; Step 52: Based on the stress field, perform mechanical response analysis on the geological model of the fractured slope using the finite element method or the discrete element method to obtain the stress vector of the internal fractures of the expansive soil slope; wherein, the stress vector refers to the magnitude and direction of the stress acting on each fracture inside the expansive soil slope. Step 53: Estimate the crack development trend inside the expansive soil slope based on the time-domain variation of the stress vector; wherein, the crack development trend refers to the size variation trend of each crack inside the expansive soil slope in multiple structural dimensions.

[0010] Preferably, step six specifically includes the following steps: Based on the crack development trend, the changes in the internal crack connection relationship caused by the dimensional changes in the structural dimensions of the cracks inside the expansive soil slope are estimated, and this is used as the crack structure change of the expansive soil slope.

[0011] Preferably, step seven specifically includes the following steps: Step 71: Based on the changes in the crack structure, determine all soil bodies in the expansive soil slope that are separated by cracks and are in a state of separation; Step 72: Based on all the soil bodies in the separated state, search for the sliding surface inside the expansive soil slope; wherein, the sliding surface refers to the potential sliding surface formed by the soil bodies in the separated state inside the expansive soil slope; In step 73, based on the stress state of the soil corresponding to the sliding surface, the rigid body limit equilibrium method is used to calculate the sliding force and anti-sliding force of the soil along the sliding surface. When the sliding force is greater than or equal to the anti-sliding force, it is determined that an equilibrium state change event has occurred. When an equilibrium state change event occurs, the sliding change state of the soil is predicted based on the force vector of the stress state.

[0012] Compared with the prior art, the present invention has the following beneficial effects: This invention obtains the stability of expansive soil slopes by collecting and processing soil structure data and primary fissure distribution data. Attached Figure Description

[0013] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a flowchart illustrating the method for detecting the stability of expansive soil slopes based on crack evolution and intelligent identification of sliding surfaces, as provided in this embodiment of the invention.

[0014] Figure 2 It is the process of constructing a geological model of a fractured slope.

[0015] Figure 3 It is the process of estimating the dynamic characteristics of water infiltration.

[0016] Figure 4 It is the process of estimating the development trend of fractures. Detailed Implementation

[0017] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0018] A method for detecting the stability of expansive soil slopes based on crack evolution and intelligent identification of sliding surfaces, specifically including the following steps: Step 1: Collect soil structure data and primary fissure distribution data for expansive soil slopes; Step 2: Preprocess the soil structure data and the original fracture distribution data to construct a geological model of the fractured slope; Step 3: Obtain historical precipitation data for the area where the expansive soil slope is located, and use this data to estimate the dynamic characteristics of water infiltration of the expansive soil slope; Step 4: Based on the dynamic characteristics of water seepage, generate the swelling stress effect of the expansive soil slope; Step 5: Based on the geological model of the fractured slope and the effect of expansion stress, estimate the fracture development trend of the expansive soil slope; Step 6: Estimate the changes in the crack structure of the expansive soil slope based on the crack development trend; Step 7: Search for the sliding surface inside the expansive soil slope based on the changes in the crack structure; predict the soil sliding change state of the expansive soil slope based on the stress state of the sliding surface.

[0019] Step one specifically includes the following steps: Step 11: Perform ultrasonic scanning on the expansive soil slope, collect and analyze the ultrasonic echo signals of the expansive soil slope, and obtain soil structure data and first primary fissure distribution data; wherein, the soil structure data includes the soil type and soil layer thickness layout inside the expansive soil slope; the first primary fissure distribution data includes the morphology and location of the primary fissures inside the expansive soil slope. Step 12: Perform machine vision recognition on the expansive soil slope to obtain the second primary crack distribution data; wherein, the second primary crack distribution data includes the length, average width, direction, center point coordinates of each crack, and the surface density of all cracks.

[0020] Expansive soil slopes, primarily composed of expansive soil, develop internal fissures due to the consolidation and expansion / contraction properties of the soil itself. These fissures can be considered primary fissures within the slope. These primary fissures are widely distributed both within and on the slope surface, and are numerous. Some internal and surface fissures connect and merge. When rainfall reaches the slope surface, it first enters the slope interior through surface fissures, then diffuses into the interior through these connected internal fissures. This infiltration creates hydrostatic pressure on the internal fissures, causing them to expand in width and depth, thus influencing the development and evolution of fissures in the expansive soil slope. Furthermore, the soil composition within an expansive soil slope is not solely expansive soil; several layers of soil with varying compositions and thicknesses can be distributed along the slope's depth. Understandably, these soil layers are mainly composed of expansive soil, and may also contain other components such as sand. The composition and thickness of each soil layer affect the infiltration and diffusion range and rate of rainwater within the slope, and play a decisive role in the development and evolution of fissures.

[0021] As described above, the soil structure and primary fissure distribution of expansive soil slopes form a crucial foundation for fissure development and evolution. Therefore, soil structure and primary fissure distribution must be considered as modeling factors in the modeling process. To ensure the accuracy and reliability of the modeling, it is necessary to obtain soil structure data and primary fissure distribution data for expansive soil slopes. Specifically, ultrasonic scanning can be performed on the expansive soil slope along multiple directions, collecting ultrasonic echo signals generated along each direction. It is understandable that ultrasonic waves travel at different speeds in soil and air. During ultrasonic scanning of the expansive soil slope, ultrasonic waves propagating within the slope are reflected at the interface between adjacent soil layers, generating ultrasonic echoes. These ultrasonic echoes travel along paths containing fissures of varying numbers and sizes, causing them to not reach the slope surface synchronously. In fact, the arrival time of ultrasonic echoes from different areas to the slope surface varies, resulting in a cluster of ultrasonic echoes on the slope surface. By analyzing the ultrasonic velocity and return delay of the collected ultrasonic echo signals, soil structure data and the distribution data of the first primary fissures can be obtained. This provides a comprehensive characterization of the soil type and thickness of each soil layer within the expansive soil slope, as well as the shape, size, and location of the primary fissures within the slope. Furthermore, the shape, size, and location of the primary fissures on the surface of the expansive soil slope affect the efficiency and flow rate of external precipitation infiltration into the slope. Therefore, machine vision identification is performed on the surface of the expansive soil slope to obtain the shape, size, and location of the primary fissures, providing a basis for subsequent estimation of the dynamics of water infiltration caused by precipitation.

[0022] Ultrasonic scanning detection can also be replaced by existing technologies such as surface wave method and ground-penetrating radar.

[0023] Step 12 specifically includes the following steps: Step 121: Use a camera to collect full-coverage, multi-view images of the expansive soil slope surface to obtain the original digital image of the slope surface; Step 122: By setting up ground control points, complete the calibration of the camera's interior and exterior orientation elements, establish the mapping relationship between pixel coordinates and actual physical coordinates, and determine the pixel-to-actual size conversion factor. , in, This is a size conversion factor. The actual physical length of the calibration part. The pixel length of the calibration component image; Step 123: Preprocess the original digital image of the slope surface to obtain the preprocessed image. To improve the recognizability of fracture features, the following steps are included: Step 1231, Grayscale processing: , Steps 1, 2, 3, and 2: [Regarding...] Gaussian filtering is performed to remove noise, resulting in the filtered image. ; Steps 1, 2, 3, and 3: [Regarding...] Histogram equalization is performed to enhance contrast, resulting in a preprocessed image. ; Step 124: Adaptive threshold segmentation is used to achieve binarization separation of the cracks and the soil background, obtaining an approximate crack profile, as shown in the following formula: , in, This is a locally adaptive threshold; Step 125: Extract the approximate crack outline obtained in step 124 using Canny edge detection, and use morphological opening and closing operations to remove isolated noise and connect fracture segments to obtain the complete crack and its location. Step 126: Calculate each crack Geometric parameters: (1) No. Crack length : , Here is the size conversion factor, and n is the nth dimensional conversion factor. The total number of pixels along the crack outline. Let J be the image coordinates of the j-th pixel on the i-th crack contour line; (2) Average width of the crack : , in, Let be the number of sampling points for the width of the i-th crack. For the first Crack number The width in pixels of each sampling point; (3) Fracture orientation : , The actual value is the angle. For the first The coordinates of the starting pixel of the crack outline. For the first The coordinates of the terminal pixel of the crack outline.

[0024] (4) Coordinates of the fracture center point ( ): , For the first The total number of pixels along the outline of the crack; Step 127: Calculate the areal density of all cracks. The formula is as follows: , Where S is the area of ​​the statistical region.

[0025] Step two specifically includes the following steps: Step 21: Perform three-dimensional spatial coordinate unification preprocessing and abnormal data partial removal preprocessing on the soil structure data, the first primary fracture distribution data, and the second primary fracture distribution data; Step 22: Perform three-dimensional spatial modeling on the soil structure data, the first primary fracture distribution data, and the second primary fracture distribution data to obtain a geological model of the fractured slope.

[0026] In this embodiment, soil structure data and the first primary fracture distribution data are obtained through ultrasonic scanning, while the second primary fracture distribution data is obtained through machine vision recognition. For a unified representation of soil thickness distribution and structural morphology within and on the surface of expansive soil slopes in the same space, please refer to [link to relevant documentation]. Figure 2 Based on the operational space coordinate system of ultrasonic scanning and machine vision recognition, spatial coordinate system transformation is performed. This involves unified 3D spatial coordinate preprocessing and outlier removal preprocessing (e.g., removing data with excessively large or small values) of the layer construction data, first primary fracture distribution data, and second primary fracture distribution data. A CNN neural network model can then be used to perform 3D spatial modeling of the preprocessed soil structure data, first primary fracture distribution data, and second primary fracture data to obtain a fractured slope geological model. This fractured slope geological model comprehensively represents the soil layer layout and fracture structure of expansive soil slopes, providing a model basis for subsequent simulations of precipitation infiltration dynamics.

[0027] Step three specifically includes the following steps: Step 31: Collect historical precipitation data of the area where the expansive soil slope is located, perform multidimensional precipitation feature identification and differentiation on the historical precipitation data, and generate a multidimensional precipitation data sequence; wherein, the multidimensional precipitation features include precipitation type, precipitation duration, precipitation location, and precipitation intensity; the multidimensional precipitation data sequence refers to the time-space sequence data formed by arranging each precipitation event in chronological order and associating it with the spatial distribution of its precipitation intensity; Step 32: Based on the multidimensional precipitation data sequence, determine the spatial distribution of rainfall input flow to the expansive soil slope during each type of precipitation event; Step 33: Estimate the water infiltration dynamic characteristics of the expansive soil slope based on the spatial distribution of rainfall input flow and the second primary fissure distribution data; wherein, the water infiltration dynamic characteristics refer to the flow rate of precipitation infiltrating into the expansive soil slope through the primary fissures on the surface of the expansive soil slope.

[0028] Rainfall in the area of ​​expansive soil slopes enters the slope interior through surface fissures and diffuses along these fissures into different areas within the slope. This diffusion and infiltration generates hydrostatic pressure within the slope, which in turn causes the fissures to develop and evolve in terms of size, width, and depth. Understandably, the intensity and duration of rainfall determine the magnitude of this hydrostatic pressure. Obtaining rainfall data can provide a basis for determining the rainfall infiltration status and the resulting hydrostatic pressure.

[0029] Please see Figure 3 First, historical precipitation data of the area where the expansive soil slope is located is collected. Multidimensional precipitation features are extracted from the above historical precipitation data to obtain precipitation type (such as rain, snow, etc.), precipitation duration, precipitation location (such as spatial range coordinates of precipitation occurrence, etc.), and precipitation intensity (such as precipitation per unit time, etc.). Then, the above multidimensional precipitation features are integrated to generate a multidimensional precipitation data sequence, thereby accurately representing the time-space sequence data of each precipitation event arranged in chronological order and the spatial distribution of precipitation intensity.

[0030] It is understandable that the precipitation events occurring in the area of ​​expansive soil slopes are directly related to the rainwater flow input to the slopes. Based on the aforementioned multidimensional precipitation data series, determining the spatial distribution of rainfall input flow to the expansive soil slopes during each type of precipitation event allows for a preliminary determination of the rainwater flow to the slope surface. Furthermore, by combining the spatial distribution of rainfall input flow and the distribution data of secondary primary fissures, the flow rate of precipitation infiltrating into the expansive soil slope through the primary fissures on the slope surface can be estimated, providing a basis for subsequently determining the deformation stress formed by precipitation within the expansive soil slope.

[0031] Step four specifically includes the following steps: Step 41: Based on the dynamic characteristics of water infiltration and the real-time water content distribution of the expansive soil slope, estimate the spatial distribution of the water absorption and swelling deformation of the expansive soil slope; Step 42: Calculate the elastic stress field generated by the spatial distribution of the water absorption and swelling deformation according to the constitutive model of the expansive soil, and obtain the swelling stress effect of the expansive soil slope; wherein, the swelling stress effect refers to the stress distribution formed by the water absorption and swelling deformation inside the expansive soil slope.

[0032] Expansive soil exhibits the characteristics of absorption expansion and water loss shrinkage. The greater the water absorption of expansive soil, the greater its expansion rate, and the greater the deformation within the expansive soil slope. When deformation occurs within the expansive soil slope, the expansive soil particles compress each other and change relative positions, thus creating a global stress effect within the slope. The magnitude and direction of this stress effect depend on the deformation amount and direction within the slope. As the above analysis shows, during the diffusion and infiltration of rainwater within the slope, expansive soil absorbs rainwater and undergoes expansion deformation, thereby creating a multi-dimensional stress effect throughout the slope. The water absorption rate of expansive soil is related to its real-time moisture content; the higher the real-time moisture content, the lower the water absorption rate, and the smaller the corresponding deformation; conversely, the lower the real-time moisture content and the higher the water absorption rate, the greater the corresponding deformation. Specifically, based on the aforementioned dynamic characteristics of water infiltration and the real-time moisture content distribution of expansive soil slopes, the water absorption rate of the expansive soil inside the slope is estimated. Combined with the water absorption-swelling rate of the expansive soil (i.e., the volumetric expansion of the expansive soil when absorbing a unit volume of rainwater), the spatial distribution of the water absorption and swelling deformation of the expansive soil inside the slope is estimated; that is, the swelling deformation of the expansive soil in each grid region inside the slope after water absorption. Then, using a nonlinear elastic constitutive model of expansive soil (such as the Duncan-Chang model) or a temperature stress analogy method considering swelling strain, the elastic stress field generated inside the slope due to deformation constraint is calculated based on the aforementioned spatial distribution of water absorption and swelling deformation. The magnitude of this stress field is related to the deformation and the elastic modulus of the soil, and its direction is opposite to the direction of the deformation constraint. This stress field is used as the swelling stress effect of the expansive soil slope to characterize the mechanical effects of water absorption and swelling on the interior of the slope.

[0033] In another embodiment, based on a geological model of the fractured slope and the effect of expansive stress, the fracture development trend of the expansive soil slope is estimated, including: Step five specifically includes the following steps: Step 51: Based on the expansive stress, generate the stress field inside the expansive soil slope; Step 52: Based on the stress field, perform mechanical response analysis on the geological model of the fractured slope using the finite element method or the discrete element method to obtain the stress vector of the internal fractures of the expansive soil slope; wherein, the stress vector refers to the magnitude and direction of the stress acting on each fracture inside the expansive soil slope. Step 53: Estimate the crack development trend inside the expansive soil slope based on the time-domain variation of the stress vector; wherein, the crack development trend refers to the size variation trend of each crack inside the expansive soil slope in multiple structural dimensions.

[0034] It is understandable that the stress generated by the expansion of expansive soil due to water absorption within the slope creates a stress field. This stress field exhibits irregular distribution in magnitude and direction, resulting in significant differences in the magnitude and direction of stress experienced by each crack within the slope. Furthermore, this stress field is not static but varies with the temporal changes in rainwater diffusion and infiltration within the slope. As the above analysis shows, the stress field directly affects the changes in the size of crack structures within the slope, thereby promoting the development and evolution of internal cracks. Please refer to [link / reference]. Figure 4 Based on the stress generated within the expansive soil slope due to water absorption and expansion deformation, a stress field (i.e., the magnitude and direction distribution of stress in each grid region within the slope) is generated. Using finite element software (such as ABAQUS, PLAXIS) or discrete element software (such as PFC3D), the geological model of the fractured slope is discretized. The stress field formed by the expansion stress is applied as the initial load, and the mechanical parameters of the soil (elastic modulus, Poisson's ratio, shear strength, etc.) are set for quasi-static mechanical response analysis. The stress tensor at each fracture element node is calculated, and the stress vectors (magnitude and direction) in the normal and tangential directions of each fracture surface are extracted. Furthermore, based on the time-domain variation of the stress field, the dimensional variation trend of each fracture within the slope in multiple structural dimensions such as width and depth is estimated.

[0035] As an optional embodiment, estimating the crack development trend of the expansive soil slope can be performed as follows: Step A1: Based on the expansive stress, generate the stress field inside the expansive soil slope; wherein the stress field includes the stress tensor of each spatial point inside the slope; Step A2: Based on the stress field, perform mechanical response analysis on the geological model of the fractured slope using the finite element method or discrete element method to obtain the stress vector on each fracture surface inside the expansive soil slope, and decompose the stress vector into normal stress perpendicular to the fracture surface. and tangential stress parallel to the crack surface ; in, and The units are all kilopascals (kPa), with subscripts. Indicates the normal direction of the fracture surface; Step A3: Based on the water permeation flow rate in the aforementioned water permeation dynamic characteristics, combined with the fracture geometry parameters (including fracture width and length) and Darcy's law, calculate the fracture water pressure inside each fracture. ; The unit is kilopascal (kPa), with subscript. It represents water; Step A4: Obtain the initial width of each crack. and the crack width at the previous moment. ,Will As the current crack width Approximate values; simultaneously obtain the current volumetric moisture content. and initial volumetric moisture content ; in, Defined as the average volumetric water content of a slope at a corresponding depth under natural conditions (without recent precipitation events), expressed as a percentage (%). Step A5: Calculate the crack propagation driving force exponent for each crack. The formula is used to evaluate the potential driving force for further propagation of the fracture under the coupling effect of water absorption expansion stress and seepage.

[0036] in, It is a dimensionless number; k This is the reference coefficient for crack propagation, dimensionless, with a range of values. The preferred value is 0.5; This reflects the inherent ease or difficulty of crack propagation in expansive soil under standard reference conditions where the ratio of shear stress to effective normal stress is 1, crack width does not expand, and water content remains unchanged. It comprehensively reflects the soil's intrinsic sensitivity to crack initiation. It indicates that it is easily expandable. (This indicates that the crack is difficult to propagate); the method for obtaining this information can be through in-situ or indoor crack propagation tests to determine the initial state ( The critical effective stress ratio at which the lower crack just begins to propagate and order ,but ; The tangential stress at the current fracture surface represents the stress component acting parallel to the fracture surface. The normal stress of the current fracture surface is represented by the stress component acting perpendicular to the fracture surface. The current fracture water pressure inside the fracture can be calculated using the dynamic characteristics of water seepage combined with Darcy's law, and satisfies... (If not satisfied, then take) (to avoid division by zero) The shear stress sensitivity index is dimensionless and reflects the sensitivity of crack propagation to changes in shear stress relative to the effective normal stress. It is a preset value with a range of values. The preferred value is 0.8; This is the width expansion feedback coefficient, dimensionless, reflecting the positive feedback strength of the existing crack width relative to the expansion amount on further expansion. It is a preset value, with a range of values. The preferred value is 2.0; The current width of the current crack is taken from the crack width calculation result or the initial width at the previous moment; This represents the initial width of the current crack; The moisture content influence coefficient is dimensionless and reflects the exponential effect of changes in volumetric moisture content on crack propagation. It is a preset value with a range of values. The preferred value is 3.0; This represents the current volumetric water content of the soil at the location of the current crack; The initial volumetric water content of the soil at the current location of the crack is defined as the average volumetric water content of the soil at that location under natural conditions (without recent precipitation events). Let be a natural constant; where, It can be a negative value, in which case... This reflects the inhibitory effect of water loss shrinkage on the current crack propagation; Step A6: Based on the fracture propagation driving force index The size of the crack can be used to determine its propagation trend: when At that time, it was determined that the crack would significantly expand, and The larger the value, the higher the risk of expansion; when When the crack is slow to propagate or tends to stabilize, it is determined that the crack is slow to propagate or tends to stabilize. Step A7: Summarize the propagation trends of all cracks to obtain the crack development trend of the expansive soil slope.

[0037] The above technical solution constructs a crack propagation driving force index based on the local stress state of the crack surface, the water pressure inside the crack, the relative change between the current and initial crack widths, and the change in soil moisture content at the crack location. Specifically, the index takes into account the following physical mechanisms: using tangential stress on the fracture surface. With effective normal stress ( The ratio of shear stress to water pressure reflects the driving force of the shear stress relative to the compaction-hydraulic coupling effect on the fracture surface, resulting in shear slip and tensile propagation. As the effective normal stress increases, the ratio decreases, making the cracks easier to propagate, which conforms to the physical law of seepage-induced slippage; introducing... The term characterizes the amplification effect of the existing width expansion on subsequent expansion: the wider the crack, the easier it is for moisture to enter, and the more obvious the stress concentration, thus accelerating the expansion; an exponential term is used. Describe the nonlinear effect of soil moisture content changes on the swelling and shrinkage properties of expansive soil: wetting ( When the index is greater than 1, it promotes fracture propagation and water loss. When the index is less than 1, it inhibits expansion, reflecting the true effect of the wet-dry cycle. This is achieved by multiplying the above three terms and introducing an empirical coefficient related to soil type. Finally, the dimensionless crack propagation driving force index was obtained. .when At that time, it is determined that the crack will expand significantly.

[0038] Step six specifically includes the following steps: Based on the development trend of cracks, the changes in the internal crack connection relationship caused by the size changes of the structural dimensions of the cracks in the expansive soil slope are estimated, and this is used as the crack structure change of the expansive soil slope.

[0039] Understandably, as fissures develop and evolve within the slope, their width and / or depth increase. Previously unconnected fissures become connected, creating soil fragmentation within the slope. This means that the originally monolithic soil within the slope is divided into separate soil masses, which become potential sliding masses, with their bases forming the sliding surface within the slope. Based on fissure development trends, estimating the changes in the internal fissure connection relationships caused by dimensional variations in the structural dimensions of expansive soil slopes can provide a basis for subsequently determining the soil fragmentation caused by fissures within the slope.

[0040] Step seven specifically includes the following steps: Step 71: Based on the changes in the crack structure, determine all soil bodies in the expansive soil slope that are separated by cracks and are in a state of separation; Step 72: Based on all the soil bodies in the separated state, search for the sliding surface inside the expansive soil slope; wherein, the sliding surface refers to the potential sliding surface formed by the soil bodies in the separated state inside the expansive soil slope; In step 73, based on the stress state of the soil corresponding to the sliding surface, the rigid body limit equilibrium method is used to calculate the sliding force and anti-sliding force of the soil along the sliding surface. When the sliding force is greater than or equal to the anti-sliding force, it is determined that an equilibrium state change event has occurred. When an equilibrium state change event occurs, the sliding change state of the soil is predicted based on the force vector of the stress state.

[0041] As discussed earlier, as internal fissures develop and evolve within a slope, the width and / or depth of some fissures increase, leading to their interconnection. This interconnection of fissures divides the slope, forming separate soil masses that are potentially susceptible to sliding within the slope. When the sliding force and frictional force acting on these separated soil masses cannot maintain equilibrium, they slide downwards, causing a landslide. Specifically, based on changes in fissure structure, all soil masses within an expansive soil slope that are divided by fissures and are in a separated state are identified. This allows for the search for potential sliding surfaces formed within the expansive soil slope by these separated soil masses. Using the rigid body limit equilibrium method, the sliding force (composed of the soil's own weight and the tangential component of the external load along the sliding surface) and the resisting force (composed of the cohesion and frictional force generated by the normal pressure on the sliding surface) of each separated soil mass are calculated along its bottom sliding surface. The safety factor Fs is defined as: Resisting force / Sliding force. When Fs < 1.0, meaning the sliding force is greater than the resisting force, an equilibrium state change event is identified. When Fs ≥ 1.0, no equilibrium state change event is identified. When an equilibrium state change event occurs, the sliding direction and sliding velocity of the soil are predicted based on the force vector of the stress state (i.e., the vector difference between the sliding force and the resisting force), enabling reliable and accurate detection of slope stability.

[0042] As an optional embodiment, predicting the soil sliding change state of the expansive soil slope based on the stress state of the sliding surface can be specifically implemented as follows: Step B1: Based on the changes in the fracture structure, identify all soil masses within the expansive soil slope that are separated by fractures and are in a state of separation, and search for the potential sliding surface corresponding to each separated soil mass; wherein, each potential sliding surface extends along the bottom boundary of the soil mass, dividing the sliding surface into... A strip of earth, Number the soil strips. ; Step B2: Obtain the following parameters for each soil strip: No. The weight of a soil strip The unit is kilonewtons (kN), which is calculated from soil structure data and soil unit weight. Soil unit weight is determined by on-site ring sample weighing or empirical value. The unit is degrees (°); it is directly measured from the geometry of the sliding surface. The unit is kilonewtons (kN); determined based on the actual conditions of the slope on site. The unit is meters (m); it is calculated from the geometry of the sliding surface. The unit is kilopascal (kPa); it can be measured directly by pore water pressure gauges installed on site, or estimated based on water content distribution and water level lines; The unit is kilopascal (kPa); it is determined by in-situ testing (such as static cone penetration test, CPT) or by consulting the experience values ​​of expansive soil engineering in the region, with a typical range of 10~30 kPa. The unit is degrees (°); the value is determined by on-site in-situ testing or regional experience, with a typical range of 15° to 25°. The unit is meters (m); it is the sum of the arc lengths of the bases of all soil strips. ; The unit is millimeters (mm); obtained from the changes in the crack structure (machine vision or ultrasonic measurement); The unit is meters (m); calculated from soil structure data (ultrasonic scanning); The unit is kilopascal (kPa); calculated based on the water seepage flow rate in the aforementioned water seepage dynamic characteristics, combined with fracture geometry and Darcy's law, subscript... It represents water. Indicates the soil strip number; Dimensionless; values ​​are determined empirically based on the degree of fracture connectivity: 0.3 for poor fracture connectivity, 0.5 for moderate connectivity, and 0.8 for good connectivity. Dimensionless; based on the relative width of the crack Based on experience: hour , hour , hour ; Step B3: Calculate the width (per unit width), the pore water pressure at the bottom of each soil strip Converted into the form of force The unit is kilonewtons (kN); the increment of fissure water pressure at the bottom of each soil strip. Converted into the form of force The unit is kilonewtons (kN). Step B4: Calculate the slip surface instability risk coefficient This formula is used to evaluate the comprehensive risk of unstable sliding along the potential sliding surface of an isolated soil mass separated by cracks.

[0043] Among them, when Immediately determine soil instability and sliding; For the first The force (kN) corresponding to the increase in fissure water pressure at the bottom of each soil strip. ; To calculate the width, take The unit is meters (m); For the first The force (kN) corresponding to the pore water pressure at the bottom of each soil strip. ; The crack width attenuation coefficient is dimensionless and ranges from 0.1 to 0.4. To take the larger value between the value in parentheses and 0, when the effective normal force is negative, the contribution of frictional anti-slip force is taken as 0; Trigonometric functions; This is the tangent of the internal friction angle.

[0044] Constraints must be met If not satisfied, then take If the denominator is zero, it indicates that the anti-slip force is completely lost; if the denominator is zero, then it is directly determined that... This indicates that the soil has completely lost its ability to resist sliding. Step B5: Based on the slip surface instability risk coefficient Determine the soil equilibrium state: when When the sliding force is determined to be greater than or equal to the anti-sliding force, an equilibrium state change event occurs, and the soil will slide along the sliding surface; when At that time, the soil is determined to be in a stable state; Step B6: When an equilibrium state change event occurs, based on the vector difference between the sliding force and the anti-slip force... Predicting the sliding change state of the soil: Let the total mass of the separated soil be... ,in The acceleration due to gravity is taken as 9.8 m / s². 2 Then the sliding acceleration By integrating the acceleration over time to obtain the sliding velocity, and then integrating the velocity to obtain the sliding displacement, the sliding change state of the soil can be predicted.

[0045] The above technical solution, based on the rigid body limit equilibrium method, introduces the dynamic increment of fracture water pressure and the weakening effect of fracture width on shear strength, and constructs a sliding surface instability risk coefficient. Specifically, this coefficient divides the potential sliding surface into n soil strips and calculates: the numerator (sliding force) includes the tangential component of the soil strip's gravity. External loads And the driving force of the increased fissure water pressure transmitted to the bottom of the soil strip. ,in Increase in fissure water pressure caused by precipitation infiltration Multiply by the arc length of the bottom of the soil strip and the unit width to obtain the result. The transfer coefficient reflects the effect of fracture connectivity on water pressure transmission efficiency; the denominator (anti-slip force) includes the contribution of cohesion. ( (unit width), and the frictional anti-sliding force generated by the effective normal force of each soil strip. Then multiply by the crack width weakening factor ,in The case where the effective normal force is negative (i.e., the pore water pressure exceeds the normal component of the soil strip's self-weight) is addressed, and the friction contribution is set to zero. The weakening factor reflects the crack width on the sliding surface. Relative to soil thickness The larger the value, the more severe the loss of shear strength. When When the sliding force is greater than or equal to the resisting force, the soil becomes unstable and slides. Furthermore, the acceleration is calculated based on the vector difference between the sliding force and the resisting force, and the velocity and displacement are obtained by integration, enabling dynamic prediction of the sliding process.

[0046] Compared with existing technologies, the above-mentioned technical solution dynamically considers the driving force of fracture water pressure, which is more in line with precipitation conditions. Traditional rigid body limit equilibrium methods usually use steady-state pore water pressure, while the above-mentioned technical solution introduces the increment of fracture water pressure generated by precipitation infiltration. And through the transfer coefficient Distinguishing the impact of different degrees of fracture connectivity allows for real-time reflection of the dynamic amplification effect of water pressure on sliding forces during rainfall. For the first time, the weakening effect of fracture width on anti-sliding forces is quantified. Factor, representing the measured width of the crack on the sliding surface. With soil thickness The ratio is directly coupled to the calculation of anti-sliding force, overcoming the shortcomings of traditional methods that ignore the influence of crack geometry on strength, and improving the accuracy of stability evaluation of expansive soil slopes. This method avoids the erroneous negative value of frictional anti-sliding force due to excessive pore water pressure, conforming to the fundamental mechanical principle that soil cannot withstand tensile stress, and provides dynamic prediction capabilities for the sliding process. It not only provides an instability assessment but also calculates acceleration, velocity, and displacement based on Newton's second law, offering quantitative time-dimensional data for landslide early warning and reinforcement design, which is superior to traditional methods that only provide static evaluations of the safety factor.

[0047] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. This disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims. Thus, if these modifications and variations of the invention fall within the scope of the claims of the invention and their equivalents, the invention is also intended to include these modifications and variations.

Claims

1. A method for detecting the stability of expansive soil slopes based on crack evolution and intelligent identification of sliding surfaces, characterized in that, include: Step 1: Collect soil structure data and primary fissure distribution data for expansive soil slopes; Step 2: Preprocess the soil structure data and the original fracture distribution data to construct a geological model of the fractured slope; Step 3: Obtain historical precipitation data for the area where the expansive soil slope is located, and use this data to estimate the dynamic characteristics of water infiltration of the expansive soil slope; Step 4: Based on the dynamic characteristics of water seepage, generate the swelling stress effect of the expansive soil slope; Step 5: Based on the geological model of the fractured slope and the effect of expansion stress, estimate the fracture development trend of the expansive soil slope; Step 6: Estimate the changes in the crack structure of the expansive soil slope based on the crack development trend; Step 7: Search for the sliding surface inside the expansive soil slope based on the changes in the crack structure; predict the soil sliding change state of the expansive soil slope based on the stress state of the sliding surface.

2. The method for detecting the stability of expansive soil slopes based on crack evolution and intelligent identification of sliding surfaces as described in claim 1, characterized in that: Step one specifically includes the following steps: Step 11: Perform ultrasonic scanning on the expansive soil slope, collect and analyze the ultrasonic echo signals of the expansive soil slope, and obtain soil structure data and first primary fissure distribution data; wherein, the soil structure data includes the soil type and soil layer thickness layout inside the expansive soil slope; the first primary fissure distribution data includes the morphology and location of the primary fissures inside the expansive soil slope. Step 12: Perform machine vision recognition on the expansive soil slope to obtain the second primary crack distribution data; wherein, the second primary crack distribution data includes the length, average width, direction, center point coordinates of each crack, and the surface density of all cracks.

3. The method for detecting the stability of expansive soil slopes based on crack evolution and intelligent identification of sliding surfaces as described in claim 2, characterized in that: Step two specifically includes the following steps: Step 21: Perform three-dimensional spatial coordinate unification preprocessing and abnormal data partial removal preprocessing on the soil structure data, the first primary fracture distribution data, and the second primary fracture distribution data; Step 22: Perform three-dimensional spatial modeling on the soil structure data, the first primary fracture distribution data, and the second primary fracture distribution data to obtain a geological model of the fractured slope.

4. The method for detecting the stability of expansive soil slopes based on crack evolution and intelligent identification of sliding surfaces as described in claim 2, characterized in that: Step three specifically includes the following steps: Step 31: Collect historical precipitation data of the area where the expansive soil slope is located, perform multidimensional precipitation feature identification and differentiation on the historical precipitation data, and generate a multidimensional precipitation data sequence; wherein, the multidimensional precipitation features include precipitation type, precipitation duration, precipitation location, and precipitation intensity; the multidimensional precipitation data sequence refers to the time-space sequence data formed by arranging each precipitation event in chronological order and associating it with the spatial distribution of its precipitation intensity; Step 32: Based on the multidimensional precipitation data sequence, determine the spatial distribution of rainfall input flow to the expansive soil slope during each type of precipitation event; Step 33: Estimate the water infiltration dynamic characteristics of the expansive soil slope based on the spatial distribution of rainfall input flow and the second primary fissure distribution data; wherein, the water infiltration dynamic characteristics refer to the flow rate of precipitation infiltrating into the expansive soil slope through the primary fissures on the surface of the expansive soil slope.

5. The method for detecting the stability of expansive soil slopes based on crack evolution and intelligent identification of sliding surfaces as described in claim 4, characterized in that: Step four specifically includes the following steps: Step 41: Based on the dynamic characteristics of water infiltration and the real-time water content distribution of the expansive soil slope, estimate the spatial distribution of the water absorption and swelling deformation of the expansive soil slope; Step 42: Calculate the elastic stress field generated by the spatial distribution of the water absorption and swelling deformation according to the constitutive model of the expansive soil, and obtain the swelling stress effect of the expansive soil slope; wherein, the swelling stress effect refers to the stress distribution formed by the water absorption and swelling deformation inside the expansive soil slope.

6. The method for detecting the stability of expansive soil slopes based on crack evolution and intelligent identification of sliding surfaces as described in claim 1, characterized in that: Step five specifically includes the following steps: Step 51: Based on the expansive stress, generate the stress field inside the expansive soil slope; Step 52: Based on the stress field, perform mechanical response analysis on the geological model of the fractured slope using the finite element method or the discrete element method to obtain the stress vector of the internal fractures of the expansive soil slope; wherein, the stress vector refers to the magnitude and direction of the stress acting on each fracture inside the expansive soil slope. Step 53: Estimate the crack development trend inside the expansive soil slope based on the time-domain variation of the stress vector; wherein, the crack development trend refers to the size variation trend of each crack inside the expansive soil slope in multiple structural dimensions.

7. The method for detecting the stability of expansive soil slopes based on crack evolution and intelligent identification of sliding surfaces as described in claim 6, characterized in that: Step six specifically includes the following steps: Based on the crack development trend, the changes in the internal crack connection relationship caused by the dimensional changes in the structural dimensions of the cracks inside the expansive soil slope are estimated, and this is used as the crack structure change of the expansive soil slope.

8. The method for detecting the stability of expansive soil slopes based on crack evolution and intelligent identification of sliding surfaces as described in claim 1, characterized in that: Step seven specifically includes the following steps: Step 71: Based on the changes in the crack structure, determine all soil bodies in the expansive soil slope that are separated by cracks and are in a state of separation; Step 72: Based on all the soil bodies in the separated state, search for the sliding surface inside the expansive soil slope; wherein, the sliding surface refers to the potential sliding surface formed by the soil bodies in the separated state inside the expansive soil slope; In step 73, based on the stress state of the soil corresponding to the sliding surface, the rigid body limit equilibrium method is used to calculate the sliding force and anti-sliding force of the soil along the sliding surface. When the sliding force is greater than or equal to the anti-sliding force, it is determined that an equilibrium state change event has occurred. When an equilibrium state change event occurs, the sliding change state of the soil is predicted based on the force vector of the stress state.

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