A method, system and device for calculating the instability probability of loess slope

Abstract

The present invention discloses a method, system and device for calculating the instability probability of a loess slope, and relates to the technical field of loess landslide prediction, including the following steps: dividing the profile data of the target loess slope to obtain a plurality of grid units; obtaining the moisture imaging data of the target loess slope in real time under rainfall conditions; obtaining mechanical indicators for characterizing the stability of the target loess, and establishing a correlation between the moisture imaging data and the stability parameters of the target loess through the mechanical indicators; substituting the moisture imaging data of the target loess slope into the correlation to obtain the stability parameter distribution of the target loess slope; obtaining the local safety factor of each grid unit according to the stability parameter distribution of the target loess slope, and obtaining the local instability probability of the target loess slope through the local safety factors of multiple grid units. The greatest advantage of the present invention is that it can monitor and predict the stability state of the slope in a long-term, dynamic and grid-based manner.

Description

Technical Field

[0001] The invention relates to the technical field of loess slope instability prediction, and in particular to a method, system and device for calculating the instability probability of a loess slope. Background Art

[0002] In recent years, affected by extreme climate change, extreme rainfall events have occurred frequently in the Loess Plateau region. As water infiltrates the loess slopes, the soil suction decreases and the strength drops sharply, causing a large number of loess slopes to deform and become unstable, seriously threatening the lives and property of the people. Therefore, real-time and accurate prediction of the location of possible slope damage and the probability of instability during rainfall is of great significance for disaster prevention and mitigation in the Loess Plateau region.

[0003] In the existing research on monitoring and prediction methods of loess landslides, researchers have noticed that the occurrence of loess landslides is closely related to factors such as rainfall infiltration into the slope, changes in soil water retention and permeability characteristics. The researchers first used soil moisture monitoring methods such as time domain reflectometry (TDR), frequency domain reflectometry (FDR) and electrical resistivity tomography (ERT) to monitor slope moisture, and then calculated the probability of slope instability through methods such as collaborative striping, Bishop method and Janbu method, thereby evaluating the state of the slope.

[0004] The existing collaborative striping method, Bishop method, Janbu method and other methods use partial time periods of moisture imaging data for calculation in the specific calculation process. Therefore, they can only obtain the instability probability of the slope at a certain moment, and cannot obtain the instability probability of the slope at any time in real time. It is impossible to establish a continuous connection between moisture imaging data and the probability of slope instability, which easily leads to waste of the collected data. Summary of the invention

[0005] The present invention provides a method, system and device for calculating the instability probability of a loess slope, which solves the problem that the existing instability probability calculation method can only obtain the instability probability of the slope at a certain moment, cannot obtain the instability probability of the slope at any time in real time, cannot establish a continuous connection between moisture imaging data and the instability probability of the slope, and easily causes waste of the collected data.

[0006] In a first aspect, the present invention provides a method for calculating the instability probability of a loess slope, comprising the following steps:

[0007] Dividing the target loess slope profile data to obtain a plurality of grid units; acquiring moisture imaging data of the target loess slope in real time under rainfall conditions, wherein the moisture imaging data is the moisture content of each grid unit;

[0008] Acquire a mechanical index for characterizing the stability of the target loess, and establish a correlation between the moisture imaging data and the stability parameter of the target loess through the mechanical index;

[0009] Substituting the moisture imaging data of the target loess slope into the correlation equation to obtain the stability parameter distribution of the target loess slope;

[0010] The local safety factor of each grid cell is obtained according to the stability parameter distribution of the target loess slope, and the local instability probability of the target loess slope is obtained through the local safety factors of multiple grid cells.

[0011] Preferably, the step of obtaining the moisture content of each grid unit in real time under rainfall conditions comprises the following steps:

[0012] Electrodes are arranged at multiple measuring points of the target loess slope to measure the resistivity of the multiple measuring points; the resistivity at any position of the target loess slope profile is obtained in real time under rainfall conditions;

[0013] The soil of the target loess slope is sampled to obtain a sample; the resistance value corresponding to the sample after suction balance is measured to obtain the corresponding water content and resistance value data;

[0014] The corresponding resistivity is obtained according to the resistance value, and the moisture content and the resistivity are fitted to obtain the corresponding relationship between the resistivity and the moisture content;

[0015] Discretize the resistivity at different locations on the corresponding grid cells to obtain the resistivity corresponding to each grid cell;

[0016] The resistivity of each grid cell is input into the corresponding relationship between resistivity and water content to obtain the water content of each grid cell.

[0017] Preferably, the stability parameter is effective stress.

[0018] Preferably, the establishing of a correlation between the moisture imaging data and the stability parameter of the target loess by means of the mechanical index comprises the following steps:

[0019] The Archie model is used to represent the resistivity of loess soil:

[0020] ;

[0021] In the formula, ρ is the resistivity of loess soil, is the pore water resistivity, S r is the soil saturation, a and b is the soil property parameter, is the cementation coefficient, nis the porosity;

[0022] Fit the Archie model and get the fitting formula:

[0023] ;

[0024] In the formula, K is the comprehensive structural parameter of soil, w is the mass moisture content, G s is the specific gravity, e is the void ratio;

[0025] The relationship between soil resistivity and volumetric water content is obtained through the Archie model and fitting formula:

[0026] ;

[0027] In the formula, is the volumetric water content, is the dry density;

[0028] Introducing soil-water characteristic relationship:

[0029] ;

[0030] In the formula, is the matrix suction, θ is the volumetric water content, θ ( h ) is the soil-water characteristic equation, h is the water head height, θ r is the residual volume moisture content, θ s is the saturated volume water content, and m is an empirical parameter;

[0031] According to the relationship between soil resistivity and volumetric water content and the soil-water characteristic equation, the relationship between matrix suction and soil resistivity is obtained:

[0032] ;

[0033] Introducing suction stress, the relationship between suction stress and water content is obtained:

[0034] ;

[0035] In the formula, is the suction stress, is the effective saturation, u a is the pore pressure, u wis the pore water pressure;

[0036] Get the stress at any position of the target loess slope profile:

[0037] ;

[0038] In the formula, is the stress at different locations, i and j Represents two-dimensional space x and z The subscript of x is the horizontal direction, z is the vertical or gravity direction, is the normal stress in the horizontal direction, is the normal stress in the vertical direction, for xz Shear force in the direction for zx Shear force in direction;

[0039] According to the theory of linear elasticity, stress and strain are expressed by Hooke's law, and the total stress is expressed as follows:

[0040] ;

[0041] In the formula, μ is Poisson's ratio, G is the shear modulus, is the identity matrix, is the horizontal positive strain, is strain in different directions;

[0042] Using suction stress to replace pore pressure, the relationship between suction stress and effective stress is obtained:

[0043] ;

[0044] In the formula, is the effective stress.

[0045] Preferably, the local safety factor of each grid unit is obtained according to the stability parameter distribution of the target loess slope, as shown in the following formula:

[0046] ;

[0047] In the formula, LFS is the local safety factor, is the shear strength, is the shear stress, is the cohesion of the slope material under drainage conditions, is the friction angle of the slope under drainage conditions, is the effective maximum principal stress, is the effective minimum principal stress.

[0048] Preferably, the method of obtaining the local instability probability of the target loess slope through the local safety factors of multiple grid cells comprises the following steps:

[0049] Get the total number of grid cells;

[0050] Count the number of grid cells whose local safety factor is less than 1;

[0051] The percentage of the number of grid cells with a local safety factor less than 1 in the total number of grid cells is obtained and its distribution is analyzed to obtain the local instability probability of the target loess slope.

[0052] In a second aspect, the present invention provides a device for calculating the instability probability of a loess slope, comprising:

[0053] A division module is used to divide the target loess slope profile data into multiple grid units; and obtain moisture imaging data of the target loess slope in real time under rainfall conditions, wherein the moisture imaging data is the moisture content of each grid unit;

[0054] Establishing a module for obtaining mechanical indicators for characterizing the stability of target loess, and establishing a correlation between the moisture imaging data and the stability parameters of the target loess through the mechanical indicators;

[0055] A substitution module is used to substitute the moisture imaging data of the target loess slope into the correlation formula to obtain the stability parameter distribution of the target loess slope;

[0056] The calculation module is used to obtain the local safety factor of each grid unit according to the stability parameter distribution of the target loess slope, and obtain the local instability probability of the target loess slope through the local safety factors of multiple grid units.

[0057] In a third aspect, the present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for calculating the instability probability of a loess slope when executing the program.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] The present invention firstly performs grid division on the target loess slope profile, and obtains the moisture imaging data of the target loess slope in real time under rainfall conditions. With regard to the problem that the existing slope stability calculation method uses a partial time period of the moisture imaging data for calculation, the present invention is based on the basic physical and mechanical indicators of the slope soil, and establishes a correlation between the moisture imaging data and the stability parameters of the target loess according to the mechanical indicators, and substitutes the moisture imaging data of the target loess slope obtained in real time into the correlation, thereby obtaining the stability parameter distribution of the target loess slope. Finally, the local safety factor of each grid unit is obtained according to the stability parameter distribution of the target loess slope, and the local instability probability of the target loess slope is obtained through the local safety factors of multiple grid units. The present invention can obtain the instability probability of the slope at any time in real time, establish a continuous connection between the moisture imaging data of the target loess slope and the instability probability, and will not cause waste of the collected data. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0061] Figure 1 It is a flow chart of a method for calculating the instability probability of a loess slope according to the present invention;

[0062] Figure 2 is a schematic diagram of the high-density electrochemical method of the present invention;

[0063] Figure 3 It is a schematic diagram of calculating the local safety factor based on the unit of the present invention;

[0064] Figure 4 It is a schematic diagram of calculating the instability probability of a loess slope under rainfall according to the present invention;

[0065] Figure 5 Schematic diagram of numerical simulation of an embodiment of the present invention. DETAILED DESCRIPTION

[0066] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0067] Reference Figure 1, a method for calculating the instability probability of a loess slope, comprising the following steps:

[0068] Step 1: Divide the target loess slope profile data into multiple grid cells. Obtain the resistivity of any position of the target loess slope profile in real time under rainfall conditions, and obtain the moisture content of each grid cell through the resistivity of any position.

[0069] The slope network segmentation process divides the target loess slope into many small units, each of which represents a discrete spatial area.

[0070] Reference Figure 2 The present invention adopts the moisture imaging method (high-density electrical method) to invert the moisture content of the target loess slope in a grid-based manner. It includes:

[0071] S1: Multiple electrodes are laid out on the target loess slope, with the electrode spacing ranging from 1m to 10m, to obtain an electrode system. All electrodes are set at the expected measuring points at a certain interval.

[0072] S2: Connect each electrode to an electrode conversion switch (converter). This switch is an automatic electrode switching device controlled by a single-chip microcomputer, which can automatically convert the electrode device form, pole distance and measuring point according to needs.

[0073] S3: The measurement signal (resistivity value of soil at different times) is sent to the high-density host through the electrode conversion switch through the communication equipment, and the measurement signal is stored in the computer in turn through data transmission. The measurement signal is converted, preprocessed and three-dimensionally inverted, and can be expressed as an electrical distribution of an inverted triangle or inverted trapezoidal two-dimensional section.

[0074] S4: Conduct test indoors to measure the resistance value of loess samples after suction balance, and obtain a series of moisture content and resistance data. Then, the corresponding resistivity can be calculated based on the resistance value using the following formula:

[0075] (1);

[0076] in, ρ is the resistivity, R is the resistance, A is the cross-sectional area of ​​the specimen, L is the sample height.

[0077] The moisture content value and the resistivity value are fitted to obtain the corresponding relationship between resistivity and moisture content, which usually presents a logarithmic relationship.

[0078] S5: Obtain the slope moisture distribution map through data inversion (i.e. Figure 2During data inversion, it should be noted that the slope network segmentation process will divide the target loess slope into many small cells, each representing a discrete spatial region. The resistivity of the underground is distributed on the grid and discretized to obtain the resistivity corresponding to each grid cell. This usually involves representing the resistivity distribution within the target loess slope as unknowns at the grid nodes. Common methods include the finite element method or the finite difference method. This gridding is the same grid as the grid involved in the stability analysis.

[0079] Step 2: Derive the relationship between suction stress and moisture content, substitute the moisture content of all grid cells into the relationship between suction stress and moisture content, and obtain the suction stress distribution of the target loess slope.

[0080] The slope stability analysis of seepage-stress coupling includes hydrodynamic analysis and slope stress and stability analysis. In the hydrodynamic analysis, the hydrodynamic field under water infiltration is solved based on the Richard equation. In the slope stress and stability analysis, the total stress field of the slope is calculated based on the stress-strain equilibrium equation. The suction stress parameter is introduced to solve the effective stress field under water infiltration. Finally, based on the local safety field theory, referred to as LSF, the slope safety factor field distribution based on the subdivided unit is calculated. The calculation of the local safety field theory obeys the Moore Coulomb failure criterion, which is defined as the ratio of the current Coulomb stress of the calculation unit to the Coulomb stress at the time of failure. On the basis of the stability analysis of the loess slope, the continuous surface with a safety factor less than 1 is identified, that is, the slope deformation failure surface.

[0081] The Archie model is used to represent the resistivity of loess:

[0082] (2);

[0083] In the formula, ρ is the resistivity of loess soil, is the pore water resistivity, S r is the soil saturation, a and b is the soil property parameter, is the cementation coefficient, n is the porosity.

[0084] For loess samples collected at the same location, their porosity and pore shape and other parameters remain basically unchanged, so the structural parameters basically do not change much and can be considered constants. That is, formula (2) can be extended to:

[0085] (3);

[0086] In the formula, K is the comprehensive structural parameter of soil, w is the mass moisture content,G s is the specific gravity, e is the void ratio.

[0087] The relationship between soil resistivity and volumetric water content can be obtained from equations (2) and (3):

[0088] (4);

[0089] In the formula, is the volumetric water content, is the dry density, converted in the three phases of soil, and Both are mass moisture content. According to the three-phase conversion of soil, mass moisture content and volume moisture content can be calculated by Conversion, dry density is obtained based on test results.

[0090] When sampling loess samples for indoor geotechnical tests, the samples are sampled in accordance with the "Geotechnical Engineering Investigation Code" (GB50021-2001); conventional test methods are used indoors to measure conventional indicators such as moisture content, density, and bulk density of the samples. In addition, the soil suction is measured by the axis translation method.

[0091] The governing equation for transient unsaturated seepage is described by the Richard equation: (The Richard equation is a water transport equation that can describe the movement of water under unsaturated conditions.)

[0092] (5);

[0093] In the formula, Matrix suction, z is the position head [L], θ is the volumetric moisture content [-], t is time [T], K (h) is the permeability coefficient equation.

[0094] The Fredlund-Xing model equation (6) is used to describe the soil water characteristic equation, and the relationship between matrix suction and volumetric water content is obtained:

[0095] (6);

[0096] In the formula, is the volumetric moisture content [-], θ r is the residual volume moisture content [-], θ s is the saturated volumetric water content [-], and m It is an empirical parameter and can be obtained through TRIM test inversion.

[0097] Combining equations (4) and (6), we can get the relationship between matrix suction and resistivity:

[0098] (7).

[0099] Introducing the suction stress, it is expressed by formula (8):

[0100] (8);

[0101] In the formula, is the suction stress, is the effective saturation, u a is the pore pressure, u w is the pore water pressure.

[0102] Substituting the moisture content of all grid cells into the relationship between suction stress and moisture content, the suction stress distribution of the target loess slope is obtained.

[0103] Step 3: Derive the relationship between suction stress and effective stress, substitute the suction stress distribution of the target loess slope into the relationship between suction stress and effective stress, and obtain the effective stress distribution of the target loess slope.

[0104] The stress at any position of the two-dimensional slope is composed of three independent tensors, which can be expressed by formula (9):

[0105] (9);

[0106] in, i and j Represents two-dimensional space x and z The subscript of x is the horizontal direction, z is the vertical or gravity direction, is the normal stress in the horizontal direction, is the normal stress in the vertical direction, for x - z Shear force in the direction for z - x Shear force in the direction and Same size, different direction.

[0107] According to the linear elastic theory, stress and strain are expressed by Hooke's law, and the total stress can be expressed as formula (10):

[0108] (10).

[0109] In the Cartesian coordinate system, , and The specific expression is formula (11)-(13):

[0110] (11);

[0111] (12);

[0112] (13);

[0113] In the formula, μ is the Poisson's ratio, G is the shear modulus, ε xx is the normal strain in the horizontal direction, ε zz is the normal strain in the vertical direction, is the identity matrix, for xz Direction of strain.

[0114] The suction stress is used to replace the pore pressure to calculate the effective stress, formula (14):

[0115] (14);

[0116] In the formula, is the effective stress, For suction stress.

[0117] Substituting the suction stress distribution of the target loess slope into the relationship between suction stress and effective stress, the effective stress distribution of the target loess slope is obtained.

[0118] Step 4: Obtain the local safety factor of each grid cell according to the effective stress distribution of the target loess slope, and obtain the local instability probability of the target loess slope according to the local safety factors of multiple grid cells.

[0119] Reference Figure 3 , the calculation principle of local safety factor based on grid unit is: .

[0120] The local safety factor at any point on the slope can be calculated based on the unit-based local safety factor and expressed as formula (15):

[0121] (15);

[0122] In the formula, LFS is the local safety factor, is the shear strength, is the shear stress, is the cohesion of the slope material under drainage conditions, is the friction angle of the slope under drainage conditions, is the effective maximum principal stress, is the effective minimum principal stress.

[0123] Schematic diagram of the stability calculation process of any loess slope under a given rainfall intensity; According to the above calculation principle and method, for any given loess slope, when the moisture content distribution of the slope is known, as shown in formula (16), the suction stress at any position of the slope can be calculated by formula (8) (17), the effective stress distribution of the slope can be calculated by formula (14), and then the local safety factor distribution of the slope can be calculated by formula (15) (18);

[0124] (16);

[0125] (17);

[0126] (18).

[0127] Reference Figure 4 , the local instability probability of the target loess slope is obtained according to the local safety factors of multiple grid cells.

[0128] The number of grid cells of the target loess slope after gridding is counted, and the total number is recorded as S1.

[0129] Calculate the local safety factor for each mesh element.

[0130] The number of grid cells with a local safety factor less than 1 is counted and recorded as S2.

[0131] The instability probability of loess slope under rainfall is calculated using the following formula: .

[0132] Identify continuous surfaces with a safety factor less than 1, i.e., locations where slope deformation and failure have penetrated.

[0133] Based on the same concept, the present invention also provides a system for calculating the instability probability of a loess slope, including a division module, a building module, a substitution module and a calculation module.

[0134] The division module is used to divide the target loess slope profile data to obtain multiple grid units; and to obtain moisture imaging data of the target loess slope in real time under rainfall conditions, wherein the moisture imaging data is the moisture content of each grid unit.

[0135] The establishment module is used to obtain mechanical indicators for characterizing the stability of the target loess, and establish a correlation between the moisture imaging data and the stability parameters of the target loess through the mechanical indicators.

[0136] The substitution module is used to substitute the moisture imaging data of the target loess slope into the correlation equation to obtain the stability parameter distribution of the target loess slope.

[0137] The calculation module is used to obtain the local safety factor of each grid unit according to the stability parameter distribution of the target loess slope, and obtain the local instability probability of the target loess slope through the local safety factors of multiple grid units.

[0138] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the above-mentioned method for calculating the instability probability of a loess slope is implemented.

[0139] Example

[0140] The safety factor of each grid unit geological body of the gridded slope is obtained by numerical analysis and other methods. Specifically, the following steps are included:

[0141] Establish geological modeling: obtain the basic physical and mechanical indicators of each rock and soil layer of the target geological body, soil absorption stress data and the corresponding geological model through geological surveys and geotechnical engineering investigations.

[0142] Discretization: Discretization of continuous problems In geology, soil is considered as a continuous medium, and the corresponding problem is the problem of continuous geological body. This kind of problem is difficult to solve based on mathematical methods, so it is necessary to discretize it and convert the solution into discrete form, dividing the time and space in the model into discrete steps or units. This involves grid generation and the selection of time step, etc.

[0143] Selection of numerical methods: Select appropriate numerical methods to solve the discretized problem, which may include finite element method, finite difference method and finite volume method. Finite element method, finite difference method and finite volume method are all numerical methods, which require discretization when solving. Appropriate calculation methods need to be selected for specific geological bodies.

[0144] Reference Figure 5 , Initial conditions and boundary conditions setting: determine the initial state of the system at the beginning of the simulation (the geological model is in a geological environment, and its force and seepage boundaries are different. The initial state needs to be set during numerical simulation to fully simulate the state of the geological model in the actual environment) and the boundary conditions during the simulation process.

[0145] Numerical Solving: Solving the mathematical model using the chosen numerical method, meshing the mathematical model and solving the equations. This may involve operations such as iteration, matrix solving and numerical integration.

[0146] Result analysis: Analyze the simulation results, specifically to determine whether the simulation results converge, and evaluate the effectiveness of the model and the accuracy of the simulation.

[0147] Verification and Validation: Ensure the accuracy and reliability of numerical models. Validation is performed by comparing simulation results with actual operating conditions. Validation is the process of ensuring that numerical methods and models are consistent with actual system behavior.

[0148] Post-processing: Post-process the simulation results to meet the requirements.

[0149] Optimization parameters: When necessary, models and numerical methods are optimized to improve computational efficiency or accuracy.

[0150] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0151] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for calculating the instability probability of a loess slope, characterized in that: The following steps are involved: Dividing the target loess slope profile data to obtain a plurality of grid units; acquiring moisture imaging data of the target loess slope in real time under rainfall conditions, wherein the moisture imaging data is the moisture content of each grid unit; Acquire a mechanical index for characterizing the stability of the target loess, and establish a correlation between the moisture imaging data and the stability parameter of the target loess through the mechanical index; the stability parameter is effective stress; Substituting the moisture imaging data of the target loess slope into the correlation equation to obtain the stability parameter distribution of the target loess slope; The local safety factor of each grid unit is obtained according to the stability parameter distribution of the target loess slope, and the local instability probability of the target loess slope is obtained through the local safety factors of multiple grid units; The method of establishing a correlation between the moisture imaging data and the stability parameter of the target loess by using the mechanical index comprises the following steps: The Archie model is used to represent the resistivity of loess soil: Where ρ is the resistivity of loess soil, ρ w is the pore water resistivity, S r is the soil saturation, a and b are soil parameters, κ is the cementation coefficient, and n is the porosity; Fit the Archie model and get the fitting formula: In the formula, K is the comprehensive structural parameter of soil, w is the mass water content, G s is the specific gravity, e is the porosity ratio; The relationship between soil resistivity and volumetric water content is obtained through the Archie model and fitting formula: Where θ is the volumetric water content, ρ d is the dry density; Introducing soil-water characteristic relationship: In the formula, s c is the matrix suction, θ is the volumetric water content, θ(h) is the soil water characteristic equation, h is the water head height, θ r is the residual volume moisture content, θ s is the saturated volumetric water content, α and m are empirical parameters; According to the relationship between soil resistivity and volumetric water content and the soil-water characteristic equation, the relationship between matrix suction and soil resistivity is obtained: Introducing suction stress, the correlation between suction stress and water content is obtained: In the formula, σ s is the suction stress, S e is the effective saturation, u a is the pore pressure, u w is the pore water pressure; Get the stress at any position of the target loess slope profile: In the formula, σ ij is the stress at different positions, i and j represent the subscripts x and z in two-dimensional space, x is the horizontal direction, z is the vertical or gravity direction, σ xx is the normal stress in the horizontal direction, σ zz is the normal stress in the vertical direction, σ xz is the shear force in the xz direction, σ zx is the shear force in the zx direction; According to the theory of linear elasticity, stress and strain are expressed by Hooke's law, and the total stress is expressed as follows: In the formula, μ is Poisson's ratio, G is the shear modulus, δ ij is the identity matrix, ε kk is the normal strain in the horizontal direction, ε ij is strain in different directions; Using suction stress to replace pore pressure, the correlation between suction stress and effective stress is obtained: σ′=σ ij -s s ; Where σ′ is the effective stress.

2. The method for calculating the instability probability of a loess slope according to claim 1, characterized in that: The step of obtaining the moisture content of each grid unit in real time under rainfall conditions comprises the following steps: Electrodes are arranged at multiple measuring points of the target loess slope to measure the resistivity of the multiple measuring points; the resistivity at any position of the target loess slope profile is obtained in real time under rainfall conditions; The soil of the target loess slope is sampled to obtain a sample; the resistance value corresponding to the sample after suction balance is measured to obtain the corresponding water content and resistance value data; The corresponding resistivity is obtained according to the resistance value, and the moisture content and the resistivity are fitted to obtain the corresponding relationship between the resistivity and the moisture content; Discretize the resistivity at different locations on the corresponding grid cells to obtain the resistivity corresponding to each grid cell; The resistivity of each grid cell is input into the corresponding relationship between resistivity and water content to obtain the water content of each grid cell.

3. The method for calculating the instability probability of a loess slope according to claim 1, characterized in that: The local safety factor of each grid unit is obtained according to the stability parameter distribution of the target loess slope, as shown in the following formula: Where LFS is the local safety factor, τ * is the shear strength, τ is the shear stress, c′ is the cohesion of the slope material under drainage conditions, is the friction angle of the slope under drainage conditions, σ′1 is the effective maximum principal stress, and σ′3 is the effective minimum principal stress.

4. The method for calculating the instability probability of a loess slope according to claim 3, characterized in that: The method of obtaining the local instability probability of the target loess slope by using the local safety factors of multiple grid cells comprises the following steps: Get the total number of grid cells; Count the number of grid cells whose local safety factor is less than 1; The percentage of the number of grid cells with a local safety factor less than 1 in the total number of grid cells is obtained and its distribution is analyzed to obtain the local instability probability of the target loess slope.

5. A loess slope instability probability calculation system, characterized in that: include: A division module is used to divide the target loess slope profile data into multiple grid units; and obtain moisture imaging data of the target loess slope in real time under rainfall conditions, wherein the moisture imaging data is the moisture content of each grid unit; Establishing a module for obtaining a mechanical index for characterizing the stability of the target loess, and establishing a correlation between the moisture imaging data and the stability parameter of the target loess through the mechanical index; the stability parameter is effective stress; A substitution module is used to substitute the moisture imaging data of the target loess slope into the correlation formula to obtain the stability parameter distribution of the target loess slope; A calculation module is used to obtain the local safety factor of each grid unit according to the stability parameter distribution of the target loess slope, and obtain the local instability probability of the target loess slope through the local safety factors of multiple grid units; The method of establishing a correlation between the moisture imaging data and the stability parameter of the target loess by using the mechanical index comprises the following steps: The Archie model is used to represent the resistivity of loess soil: Where ρ is the resistivity of loess soil, ρ w is the pore water resistivity, S r is the soil saturation, a and b are soil parameters, κ is the cementation coefficient, and n is the porosity; Fit the Archie model and get the fitting formula: In the formula, K is the comprehensive structural parameter of soil, w is the mass water content, G s is the specific gravity, e is the porosity ratio; The relationship between soil resistivity and volumetric water content is obtained through the Archie model and fitting formula: Where θ is the volumetric water content, ρ d is the dry density; Introducing soil-water characteristic relationship: In the formula, s c is the matrix suction, θ is the volumetric water content, θ(h) is the soil water characteristic equation, h is the water head height, θ r is the residual volume moisture content, θ s is the saturated volumetric water content, α and m are empirical parameters; According to the relationship between soil resistivity and volumetric water content and the soil-water characteristic equation, the relationship between matrix suction and soil resistivity is obtained: Introducing suction stress, the correlation between suction stress and water content is obtained: In the formula, σ s is the suction stress, S e is the effective saturation, u a is the pore pressure, u w is the pore water pressure; Get the stress at any position of the target loess slope profile: In the formula, σ ij is the stress at different positions, i and j represent the subscripts x and z in two-dimensional space, x is the horizontal direction, z is the vertical or gravity direction, σ xx is the normal stress in the horizontal direction, σ zz is the normal stress in the vertical direction, σ xz is the shear force in the xz direction, σ zx is the shear force in the zx direction; According to the theory of linear elasticity, stress and strain are expressed by Hooke's law, and the total stress is expressed as follows: In the formula, μ is Poisson's ratio, G is the shear modulus, δ ij is the identity matrix, ε kk is the normal strain in the horizontal direction, ε ij is strain in different directions; Using suction stress to replace pore pressure, the correlation between suction stress and effective stress is obtained: σ′=σ ij -s s ; Where σ′ is the effective stress.

6. A computer device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the program, the method for calculating the instability probability of a loess slope as described in any one of claims 1 to 4 is implemented.

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