Substrate-covering interface shear instability prediction system

Abstract

The invention provides a foundation-covering interface shear instability prediction system, and relates to the technical field of ocean foundation-covering interfaces, an ocean rock mass slope prediction region is divided into a plurality of sub-regions through a region division module, a three-dimensional model is obtained, and the generated surface height and foundation height are analyzed, so that a fluctuation contribution index is calculated; a roughness interference analysis module combines a roughness index to evaluate the interference degree between a slip slope and a rock mass slope, and a water level influence module analyzes the influence of a water level on shear strength, generates a water level strength change index, and analyzes the water level change index. And the comprehensive analysis module performs correlation analysis on the various items, generates an anti-shearing instability coefficient, reflects the anti-shearing capability of the sub-region when the external load, the water level and the roughness are considered, and outputs the strength grade of the anti-shearing capability of the sub-region through comparison with a threshold value, so that a basis is provided for risk assessment and prevention and treatment.

Description

Technical Field

[0001] The present invention relates to the technical field of marine base-overlying interface, and particularly to a prediction system for shear instability of the base-overlying interface. Background Art

[0002] As a secondary accumulation body, the rock mass landslide accumulation body mostly has a surface-to-surface contact with the underlying bedrock, and has a clear interface, that is, the base-overlying interface, also known as the sliding surface. The rock mass landslide accumulation body refers to the accumulation formed after the sliding of rock and soil masses due to factors such as gravity, geological conditions, rainfall, and earthquake during the landslide process. The formation of the landslide accumulation body is closely related to its characteristics, structure, and stability. A landslide is a common geological disaster, which refers to the phenomenon that rocks, soil, or other materials slide along a certain inclined plane under the action of gravity.

[0003] In the ocean, the base-overlying interface phenomenon causes slope landslides, which in turn lead to the collapse of buildings or projects on it, resulting in danger. Therefore, it is very important to evaluate the stability of the rock slope in the ocean.

[0004] The above information disclosed in the background art section is only used to enhance the understanding of the background of the present disclosure. Therefore, it may include information that does not constitute the prior art known to those of ordinary skill in the art. Summary of the Invention

[0005] The purpose of the present invention is to provide a prediction system for shear instability of the base-overlying interface to solve the problems raised in the above background art.

[0006] To achieve the above purpose, the present invention provides the following technical solutions: A prediction system for shear instability of the base-overlying interface specifically includes: A regional division module for determining the prediction area of the marine rock slope, dividing the prediction area into N sub-areas, monitoring and mapping the sliding slopes of each sub-area, and generating a three-dimensional model, where the three-dimensional model includes a sliding surface model and a surface model; An undulation contribution index analysis module for performing a correlation analysis on the three-dimensional model to generate a surface height and a base height, and performing a correlation analysis on the surface height and the base height to generate an undulation contribution index; A roughness analysis module for performing a correlation analysis on the three-dimensional model to generate an average roughness, where the average roughness includes a surface variance roughness and a base variance roughness; A roughness interference analysis module for performing a correlation analysis on the surface variance roughness, the base variance roughness, and the undulation contribution index to generate a roughness interference index; The shear strength analysis module is used to drill in the sub-region, extract soil samples, conduct test measurements, obtain soil sample parameters, perform correlation analysis on the soil sample parameters, and generate the shear strength; The water level influence module is used to collect the water level in the sub-region, perform correlation analysis on the water level and the shear strength, and generate the water level strength change index; The comprehensive analysis module is used to perform correlation analysis on the water level strength change index, the shear strength, and the roughness interference index, generate the shear instability coefficient, compare the shear instability coefficient with the threshold value, and output the shear resistance ability strength grade of the sub-region.

[0007] Furthermore, collect the surface rock mass point data of each sub-region, input the drawn slip slope surface and the collected surface rock mass point data into 3D design software to generate a 3D model. The slip surface model is used to reflect the shape characteristics of the slip slope surface of the sub-region, the surface model is used to reflect the surface shape characteristics of the surface rock mass in the sub-region, the surface height is used to reflect the average height of the surface rock mass in the sub-region, the base height is used to reflect the average height of the slip slope surface in the sub-region, the undulation contribution index is used to reflect the proportion of the base-overlying layer of the marine rock mass slope surface in the sub-region, the surface variance roughness is used to reflect the average height of the surface rock mass, the base variance roughness is used to reflect the roughness of the slip slope surface, the roughness interference index is used to reflect the roughness interference degree between the slip slope surface and the rock mass slope surface, the soil sample parameters include cohesion and friction angle, the shear strength is used to reflect the maximum shear stress that the sub-region can withstand under the action of shear force, the water level strength change index is used to reflect the influence degree of the water level on the shear strength of the sub-region, the shear instability coefficient is used to reflect the shear resistance ability index of the sub-region considering external load force, water level, and roughness comprehensively. The regional division module monitors and draws the slip slope surface of each sub-region through acoustic detection technology.

[0008] Furthermore, place the 3D model in a coordinate system. All the points of the 3D model are located above the XOY plane. The coordinate system is a three-dimensional coordinate system of XYZ axes. Among them, the XOY plane is parallel to the ground surface, and the Z axis is perpendicular to the ground surface. At equal intervals and on average, collect the Z-axis coordinates of nine points on the surface model in each sub-region and perform averaging processing on them to obtain the surface height , at equal intervals and on average, collect the Z-axis coordinates of nine points on the slip surface model in each sub-region and perform averaging processing on them to obtain the base height , perform correlation analysis on the base height and the surface height to generate the undulation contribution index , and the formula based on is: ; Among them, the undulation contribution index Used to reflect the proportion of the base and overlying layers of the marine rock slope in the sub-region.

[0009] Furthermore, a correlation analysis is performed on the 3D model to generate the surface variance roughness and the base variance roughness , and the formula used is: ; Nine-point sampling is performed on both the slip surface model and the surface model of each sub-region. is the Z-axis coordinate of the j-th sampling point of the surface model of the i-th sub-region. is the Z-axis coordinate of the j-th sampling point of the slip surface model of the i-th sub-region. i is used to index the sub-regions, and j is used to index the sampling points. The surface variance roughness is used to reflect the average height of the surface rock mass, and the base variance roughness is used to reflect the roughness of the sliding slope surface.

[0010] Furthermore, a correlation analysis is performed on the surface variance roughness, the base variance roughness, and the undulation contribution index to generate the roughness interference index , and the formula used is: ; Among them, is the undulation weight factor, and its value range is . The roughness interference index is used to reflect the roughness interference degree between the sliding slope surface and the rock slope surface.

[0011] Furthermore, a correlation analysis is performed on the soil sample parameters to generate the shear strength, and the formula used is: ; Among them, is the cohesion of the i-th sub-region, is the friction angle of the i-th sub-region, F is the external load force, is the pore water pressure, is the shear strength of the i-th sub-region. The shear strength is used to reflect the maximum shear stress that the sub-region can withstand under the action of shear force.

[0012] Furthermore, the water level of the sub-region is collected, and a correlation analysis is performed on the water level and the shear strength to generate the water level strength change index , and the formula used is: ; Among them, the collection period is one month. is the minimum value of the water level depth of the i-th sub-region. is the maximum value of the water level depth in the $i$-th sub-region, and the water level intensity change index is used to reflect the influence degree of water level change on the anti-shear strength.

[0013] Furthermore, for the water level intensity change index , the anti-shear strength , and the roughness interference index , a correlation analysis is carried out to generate the anti-shear instability coefficient , and the formula based on is: ; The anti-shear instability coefficient is used to reflect the anti-shear ability index of the sub-region considering external load force, water level, and roughness. The anti-shear instability coefficient is compared with the threshold to output the anti-shear ability strength level of the sub-region. When , the anti-shear ability strength of the sub-region is level two, and the anti-shear instability risk of the sub-region is relatively large, and it is necessary to reinforce and maintain the prediction area; when , the anti-shear ability strength of the sub-region is level one, and the anti-shear instability risk of the sub-region is relatively small, and it is necessary to continuously monitor the prediction area.

[0014] Compared with the prior art, the beneficial effects of the present invention are: Through the regional division module, the prediction area of the marine rock slope is divided into multiple sub-regions, and a three-dimensional model is obtained to reflect the slip slope and rock surface characteristics of each sub-region. The generated surface height and base height are analyzed to calculate the undulation contribution index, so as to evaluate the proportion of the base and overlying layers of the marine rock slope. Further, the variance roughness of the surface and the base is generated to reflect the roughness level of each model. The roughness interference analysis module combines the roughness index to evaluate the interference degree between the slip slope and the rock slope. Soil samples are obtained through drilling and their anti-shear parameters are tested to generate the maximum shear stress. The water level influence module analyzes the influence of the water level on the anti-shear strength to generate the water level intensity change index. The comprehensive analysis module conducts a correlation analysis on each item to generate the anti-shear instability coefficient, which reflects the anti-shear ability of the sub-region considering external load, water level, and roughness. By comparing with the threshold, the anti-shear ability strength level of the sub-region is output, providing a basis for risk assessment and prevention. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a schematic diagram of the overall system flow of the present invention; Figure 2 is a distribution diagram of the cohesion, pore water pressure, and anti-shear strength of the present invention; Figure 3 is a distribution diagram of the minimum water level, maximum water level, and water level intensity change index of the present invention; Figure 4It is the fitting graph of the roughness interference index - shear instability coefficient of the present invention; Figure 5 It is the fitting graph of the shear strength - shear instability coefficient of the present invention; Figure 6 It is the fitting graph of the water level strength change index - shear instability coefficient of the present invention. Specific Embodiments

[0016] To make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to specific embodiments.

[0017] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should have the ordinary meanings understood by those with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar terms used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. The terms such as "including" or "comprising" mean that the elements or objects appearing before this word cover the elements or objects listed after this word and their equivalents, without excluding other elements or objects. The terms such as "connected" or "linked" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The terms such as "upper", "lower", "left" and "right" are only used to represent relative position relationships, and when the absolute position of the object being described changes, the relative position relationship may also change accordingly.

[0018] Embodiment: Please refer to Figure 1 , the present invention provides a technical solution: A base - covering interface shear instability prediction system, specifically including: A region - division module, used to determine the prediction region of the marine rock - mass slope surface, divide the prediction region into N sub - regions, monitor and draw the sliding slope surfaces of each sub - region, collect the surface rock - mass point - position data of each sub - region, input the drawn sliding slope surfaces and the collected surface rock - mass point - position data into 3D design software and generate a 3D model. The 3D model includes a sliding - surface model and a surface model. The sliding - surface model is used to reflect the shape characteristics of the sliding slope surface of the sub - region, and the surface model is used to reflect the surface shape characteristics of the surface rock - mass of the sub - region; The area division module monitors and maps the slip slopes of each sub-region through acoustic wave detection technology. Acoustic wave detectors are arranged in each sub-region to form a monitoring network to ensure coverage of each sub-region. The unmanned aerial vehicle is equipped with a high-resolution camera and lidar equipment to obtain the point data of the surface rock mass. Using signal processing software, the acoustic wave data is denoised, enhanced, etc., and the slip slope characteristics are extracted. The slip slope data obtained from acoustic wave detection and the point cloud data obtained by the unmanned aerial vehicle are input into 3D design software. In the 3D design software, the data from different sources are integrated to create a complete 3D model.

[0019] The undulation contribution index analysis module is used to place the 3D model in a coordinate system, perform correlation analysis on the 3D model, generate the surface height and the base height. The surface height is used to reflect the average height of the surface rock mass in the sub-region, and the base height is used to reflect the average height of the slip slope in the sub-region. Correlation analysis is performed on the surface height and the base height to generate the undulation contribution index. The undulation contribution index is used to reflect the proportion of the base-covering layer of the marine rock mass slope in the sub-region; Place the 3D model in a coordinate system. All the points of the 3D model are located above the XOY plane. The coordinate system is a three-dimensional coordinate system of the XYZ axes. Among them, the XOY plane is parallel to the ground surface, and the Z axis is perpendicular to the ground surface. Nine points on the surface model in each sub-region are evenly collected at equal intervals along the Z-axis coordinate, and they are averaged to obtain the surface height Nine points on the slip surface model in each sub-region are evenly collected at equal intervals along the Z-axis coordinate, and they are averaged to obtain the base height For the base height and the surface height perform correlation analysis to generate the undulation contribution index The formula is as follows: ; Among them, the overall marine rock mass slope is unidirectionally inclined. In order to determine the proportion of the base-covering layer of the marine rock mass slope in each sub-region, the ratio of the surface height and the base height is used to determine the proportion it occupies, and the undulation contribution index is used to reflect the proportion of the base-covering layer of the marine rock mass slope in the current sub-region. The larger the value of the undulation contribution index , the larger the proportion of the base-covering layer of the marine rock mass slope in the sub-region. By performing difference analysis on the undulation contribution indices of adjacent sub-regions, the undulation degree between sub-regions can be obtained.

[0020] The roughness analysis module is used to perform a correlation analysis on a 3D model to generate an average roughness, where the average roughness includes a surface variance roughness and a substrate variance roughness. The surface variance roughness is used to reflect the average height of the surface rock mass, and the substrate variance roughness is used to reflect the roughness of the sliding slope surface; Perform a correlation analysis on the 3D model to generate a surface variance roughness And a substrate variance roughness , and the formula is: ; Nine-point sampling is performed on both the sliding surface model and the surface model of the i-th sub-region. Use To represent the Z-axis coordinate point of the j-th sampling point, Is the Z-axis coordinate of the j-th sampling point of the surface model of the i-th sub-region, Is the Z-axis coordinate of the j-th sampling point of the sliding surface model of the i-th sub-region. i is used to index the sub-region, and j is used to index the sampling point. The surface variance roughness Is used to reflect the average height of the surface rock mass, and the substrate variance roughness Is used to reflect the roughness of the sliding slope surface.

[0021] The roughness interference analysis module is used to perform a correlation analysis on the surface variance roughness, the substrate variance roughness, and the undulation contribution index to generate a roughness interference index, where the roughness interference index is used to reflect the roughness interference degree between the sliding slope surface and the rock slope surface; Perform a correlation analysis on the surface variance roughness, the substrate variance roughness, and the undulation contribution index to generate a roughness interference index , and the formula is: ; The sub-regions are arranged in order from top to bottom. The adjacent sub-regions from top to bottom are indexed by subscripts i - 1, i, i + 1. For example, among three adjacent sub-regions, the undulation contribution index of the uppermost side is represented by , the undulation contribution index of the middle side is represented by , and the undulation contribution index of the lowermost side is represented by . Among them, Is the undulation weight factor, and its value range is . The size of the undulation weight factor is determined through experiments. The undulation weight factor is used to reflect the degree of interference of the roughness interference index by the shear strength. The larger the undulation weight factor, the greater the degree of interference of the roughness interference index by the shear strength. The roughness interference index Is used to reflect the roughness interference degree between the sliding slope surface and the rock slope surface. The roughness interference index The larger it is, the higher the undulation degree between sub-regions, and thus the more stable the prediction region. In the formula, is used to represent the undulation degree between adjacent sub-regions, is used to represent the contribution degree of roughness of the sliding slope surface and the rock slope surface, The larger it is, the greater the contribution degree of roughness of the sliding slope surface and the rock slope surface. The contact tightness between the base and the surface is reflected as the base variance roughness. Therefore, the base variance roughness plays a decisive contribution role and increases exponentially. The larger the surface variance roughness, the base variance roughness, and the undulation contribution index are, the larger the roughness interference index is.

[0022] The shear strength analysis module is used to drill in the sub-region, extract soil samples, and conduct test measurements to obtain soil sample parameters. The soil sample parameters include cohesion and friction angle. Correlation analysis is performed on the soil sample parameters to generate shear strength, which is used to reflect the maximum shear stress that the sub-region can withstand under the action of shear force; Correlation analysis is performed on the soil sample parameters to generate shear strength, and the formula is: ; Among them, is the cohesion of the i-th sub-region, is the friction angle of the i-th sub-region, F is the external load force, is the pore water pressure, is the volume of the i-th sub-region, is the density of the i-th sub-region. The pore water pressure is measured by a pore water pressure gauge, is the shear strength of the i-th sub-region, which is used to reflect the maximum shear stress that the sub-region can withstand under the action of shear force. The external load force, cohesion, friction angle, and pore water pressure are mean data. The larger the cohesion, density, and volume are, the greater the mass and load of the sub-region are, and the larger the cohesion is, the greater the shear strength of the sub-region is, which is a positive correlation. The larger the pore water pressure is, the smaller the shear strength is, which is a negative correlation. In the analysis of soil slope stability, if the external load force, such as the self-weight of a building, increases, it will cause a decrease in the effective stress of the soil mass, and thus reduce its shear strength.

[0023] The water level influence module is used to collect the water level of the sub-region, conduct correlation analysis on the water level and shear strength, and generate a water level strength change index, which is used to reflect the degree of influence of the water level on the shear resistance of the sub-region; Collect the water level of the sub-region, conduct correlation analysis on the water level and shear strength, and generate a water level strength change index , and the formula is: ; Among them, the acquisition period is one month, is the minimum value of the water level depth in the i-th sub-region, is the maximum value of the water level depth in the i-th sub-region, and the water level intensity change index is used to reflect the influence degree of water level change on the anti-shear strength, is the minimum amount of anti-shear strength, is the maximum amount of anti-shear strength. The water level intensity change index is determined by comparing the ratio of the change amount of anti-shear strength , and the water level intensity change index The larger the value, the higher the degree of influence of the sub-region by the water level and the more unstable the anti-shear ability.

[0024] Statistical sub-region maximum water level , minimum water level and the relationship with the water level intensity change index, as shown in Table 1: Table 1: Maximum water level , minimum water level and the water level intensity change index table ; Refer to Figure 2 and Figure 3 , Figure 2 in which the abscissa is the sub-region number and the ordinate is the pressure. The distribution values of cohesion, pore water pressure, and anti-shear strength are visually displayed through this table, and Figure 3 in which the distribution maps of the maximum water level, minimum water level, and water level intensity change index are drawn.

[0025] A comprehensive analysis module is used to perform a correlation analysis on the water level intensity change index, anti-shear strength, and roughness interference index to generate an anti-shear instability coefficient. The anti-shear instability coefficient is used to reflect the anti-shear ability index of the sub-region when comprehensively considering external load forces, water level, and roughness. The anti-shear instability coefficient is compared with a threshold value to output the anti-shear ability strength level of the sub-region.

[0026] Perform a correlation analysis on the water level intensity change index , anti-shear strength , roughness interference index to generate an anti-shear instability coefficient , and the formula based on is: ; The anti-shear instability coefficient is used to reflect the anti-shear ability index of the sub-region when comprehensively considering external load forces, water level, and roughness. The anti-shear strength The larger it is, the better the anti-shear ability of the sub-region, and the roughness interference index The larger the value, the greater the contribution of roughness to the anti-shearing ability, indicating better anti-shearing ability of the sub-region. Its weight ratio has an upper limit, so a logarithmic function is used to limit the numerical growth. The water level intensity change index The larger it is, the higher the degree of influence of the water level on the sub-region, indicating that the anti-shearing ability of the sub-region is more unstable. The anti-shear instability coefficient is used to reflect the stability degree of the anti-shearing strength of the corresponding sub-region. There is a positive correlation between the water level intensity change index and it, and a negative correlation between the anti-shearing strength and the roughness interference index and it. The anti-shear instability coefficient is generated by fitting. Compare the anti-shear instability coefficient with the threshold The threshold is the demarcation value of the anti-shear instability coefficient of the sub-region. The threshold is obtained through experimental analysis. When , the anti-shearing ability strength of the sub-region is at the second level, and the risk of anti-shear instability of the sub-region is relatively large. It is necessary to reinforce and maintain the prediction area; when , the anti-shearing ability strength of the sub-region is at the first level, and the risk of anti-shear instability of the sub-region is relatively small. It is necessary to continuously monitor the prediction area.

[0027] The data table of the roughness interference index, anti-shearing strength, water level intensity change index and anti-shear instability coefficient is shown in Table 2: Table 2: Data table of roughness interference index, anti-shearing strength, water level intensity change index and anti-shear instability coefficient ; Refer to Figures 4 to 6 , Figure 4 in which is the fitting image of the roughness interference index - anti-shear instability coefficient, Figure 5 is the fitting image of the anti-shearing strength - anti-shear instability coefficient, Figure 6 is the fitting image of the water level intensity change index - anti-shear instability coefficient. It can be seen from the figure that there is a positive correlation between the water level intensity change index and the anti-shear instability coefficient. The larger the water level intensity change index, the larger the anti-shear instability coefficient. There is a negative correlation between the anti-shearing strength, roughness interference index and anti-shear instability coefficient. The larger the anti-shearing strength and roughness interference index, the smaller the anti-shear instability coefficient. The larger the anti-shear instability coefficient, the greater the risk of anti-shear instability of the sub-region. It is necessary to reinforce and maintain the prediction area.

[0028] The above formulas are all dimensionless and take their numerical calculations. The formulas are obtained by collecting a large amount of data for software simulation to get a formula closest to the actual situation. The preset parameters in the formulas are set by technicians in this field according to the actual situation.

[0029] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. Those skilled in the art will appreciate that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0030] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units. They may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0031] As described above, the specific implementation manners of the present application are only described, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in the present application, and all of them should be covered by the protection scope of the present application.

Claims

1. A shear instability prediction system for a base-cover interface, characterized in that: Specifically include: A region division module is used to determine the predicted region of the marine rock mass slope, divide the predicted region into N sub-regions, monitor and draw the sliding slope of each sub-region, and generate a three-dimensional model, wherein the three-dimensional model includes a sliding surface model and a surface model; The fluctuation contribution index analysis module performs correlation analysis on the three-dimensional model to generate the surface height and base height, performs correlation analysis on the surface height and base height, and generates the fluctuation contribution index; A roughness analysis module, used for performing correlation analysis on the three-dimensional model to generate average roughness, wherein the average roughness includes surface variance roughness and substrate variance roughness; Roughness interference analysis module, used to perform correlation analysis on surface variance roughness, substrate variance roughness and undulation contribution index, and generate roughness interference index; The shear strength analysis module is used to drill in the sub-area, extract soil samples, and conduct experimental tests to obtain soil sample parameters, perform correlation analysis on the soil sample parameters, and generate shear strength; The water level impact module is used to collect the water level in the sub-area, conduct correlation analysis between the water level and shear strength, and generate a water level strength change index; The comprehensive analysis module is used to perform correlation analysis on the water level intensity change index, shear strength, and roughness interference index, generate the shear instability coefficient, compare the shear instability coefficient with the threshold, and output the sub-area shear capacity strength grade.

2. A base-cover interface shear instability prediction system according to claim 1, characterized in that: The surface rock point data of each sub-area is collected, and the drawn sliding slope and the collected surface rock point data are input into the three-dimensional design software to generate a three-dimensional model. The sliding surface model is used to reflect the shape characteristics of the sliding slope of the sub-area, the surface model is used to reflect the surface shape characteristics of the surface rock of the sub-area, the surface height is used to reflect the average height of the surface rock of the sub-area, the base height is used to reflect the average height of the sliding slope of the sub-area, the undulation contribution index is used to reflect the proportion of the base covering layer of the marine rock slope of the sub-area, the surface variance roughness is used to reflect the average height of the surface rock, and the The base variance roughness is used to reflect the roughness of the sliding slope, the roughness interference index is used to reflect the degree of roughness interference between the sliding slope and the rock slope, the soil sample parameters include cohesion and friction angle, the shear strength is used to reflect the maximum shear stress that the sub-region can withstand under the action of shear force, the water level strength change index is used to reflect the degree to which the shear strength of the sub-region is affected by the water level, and the shear instability coefficient is used to reflect the shear capacity index of the sub-region when the external load, water level and roughness are comprehensively considered. The regional division module monitors and draws the sliding slope of each sub-region through acoustic wave detection technology.

3. A base-cover interface shear instability prediction system according to claim 2, characterized in that: The three-dimensional model is placed in a coordinate system. All points of the three-dimensional model are located on the upper side of the XOY plane. The coordinate system is an XYZ axis three-dimensional coordinate system, where the XOY plane is parallel to the surface and the Z axis is perpendicular to the surface. In each sub-area, the Z axis coordinates of nine points on the surface model are collected at equal intervals and averaged, and the averaged coordinates are processed to obtain the surface height. In each sub-area, the Z-axis coordinates of nine points on the sliding surface model are collected at equal intervals and averaged, and the averaged coordinates are processed to obtain the base height. , height to base and surface height Conduct correlation analysis to generate fluctuation contribution index , the formula based on is: ; Among them, the fluctuation contribution index To reflect the The proportion of the base covering layer of the marine rock slope in each sub-area, where i is the number of the sub-area, which is used to index the sub-area.

4. A base-cover interface shear instability prediction system according to claim 3, characterized in that: Perform correlation analysis on the 3D model to generate surface variance roughness and base variance roughness , the formula based on is: ； Nine points are sampled for the sliding surface model and surface model of each sub-area. is the Z-axis coordinate of the j-th sampling point of the surface model of the i-th sub-region, is the Z-axis coordinate of the j-th sampling point of the sliding surface model of the i-th sub-region, i is used to index the sub-region, j is used to index the sampling point, and the surface variance roughness Used to reflect the average height of the surface rock mass and the base variance roughness Used to reflect the roughness of the sliding slope.

5. A base-cover interface shear instability prediction system according to claim 4, characterized in that: Correlation analysis is performed on the surface variance roughness, substrate variance roughness and undulation contribution index to generate the roughness interference index. , the formula based on is: ； in, is the fluctuation weight factor, and its value range is , roughness interference index Used to reflect the degree of roughness interference between the sliding slope and the rock slope.

6. A base-cover interface shear instability prediction system according to claim 5, characterized in that: Correlation analysis of soil sample parameters was performed to generate shear strength based on the formula: ； in, is the cohesion of the ith sub-region, is the friction angle of the ith sub-region, F is the external load force, is the pore water pressure, is the shear strength of the ith sub-region, and the shear strength is used to reflect the maximum shear stress that the sub-region can withstand under the action of shear force.

7. A base-cover interface shear instability prediction system according to claim 6, characterized in that: Collect sub-area water levels, conduct correlation analysis between water levels and shear strength, and generate a water level strength change index , the formula based on is: ; The collection period is one month. is the minimum water level depth of the ith sub-area, is the maximum water level depth of the ith sub-area, and the water level intensity change index Used to reflect the impact of water level changes on shear strength.

8. A base-cover interface shear instability prediction system according to claim 7, characterized in that: Water level intensity change index , shear strength , Roughness Interference Index Perform correlation analysis to generate shear instability coefficients , the formula based on is: ; The shear instability coefficient is used to reflect the shear capacity index of the sub-region when the external load, water level and roughness are comprehensively considered. Compare and output the shear strength grade of the sub-region. When , the shear strength of the sub-region is level 2, and the risk of shear instability in the sub-region is relatively high, and reinforcement and maintenance of the predicted area is required; when When the shear strength of the sub-region is level one, the risk of shear instability in the sub-region is small, and continuous monitoring of the predicted area is required.

Images