A system for predicting the interfacial shear instability of a base coating

Abstract

The present invention provides a shear instability prediction system for a base-cover interface, and relates to the technical field of marine base-cover interfaces. The present invention divides a predicted marine rock slope area into multiple sub-areas through a region division module, obtains a three-dimensional model, analyzes the generated surface height and base height, and calculates an undulation contribution index based on this, thereby evaluating the proportion of the marine rock slope base-cover layer, and further generating the variance roughness of the surface and base. The roughness interference analysis module combines the roughness index to evaluate the degree of interference between the sliding slope and the rock slope. The water level impact module analyzes the impact of the water level on shear strength and generates a water level strength variation index. The comprehensive analysis module performs correlation analysis on each item to generate a shear instability coefficient, which reflects the shear resistance of the sub-area when considering external loads, water levels and roughness. By comparing with a threshold, the shear resistance strength level of the sub-area is output, providing a basis for risk assessment and prevention.

Description

Technical Field

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

[0002] As a secondary accumulation, rock mass landslide deposits primarily have surface-to-surface contact with the underlying bedrock, with a distinct interface known as the base-cover interface, also known as the sliding surface. Rock mass landslide deposits are deposits formed after rock and soil slide due to factors such as gravity, geological conditions, rainfall, and earthquakes during a landslide. The formation of landslide deposits is closely related to their characteristics, structure, and stability. Landslides are a common geological disaster, occurring when rock, soil, or other materials slide along an inclined surface under the influence of gravity.

[0003] In the ocean, the base-cover interface phenomenon causes slope landslides, which in turn leads to the collapse of buildings or projects on them, creating dangers. Therefore, it is very important to evaluate the stability of rock slopes in the ocean.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the Invention

[0005] The object of the present invention is to provide a system for predicting shear instability of a substrate-cladding interface to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A base-cover interface shear instability prediction system, specifically comprising:

[0008] A region division module is used to determine the predicted area of the marine rock mass slope, divide the predicted area into N sub-areas, monitor and map the slip slope of each sub-area, and generate a three-dimensional model, wherein the three-dimensional model includes a slip surface model and a surface model;

[0009] The undulation contribution index analysis module performs correlation analysis on the three-dimensional model to generate the surface height and base height, and performs correlation analysis on the surface height and base height to generate the undulation contribution index;

[0010] A roughness analysis module is used to perform correlation analysis on the three-dimensional model to generate an average roughness, wherein the average roughness includes surface variance roughness and substrate variance roughness;

[0011] Roughness interference analysis module, used to perform correlation analysis on surface variance roughness, substrate variance roughness and undulation contribution index to generate roughness interference index;

[0012] The shear strength analysis module is used to drill in the sub-area, extract soil samples, conduct experimental tests, obtain soil sample parameters, perform correlation analysis on the soil sample parameters, and generate shear strength;

[0013] 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;

[0014] 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-region shear capacity strength grade.

[0015] Furthermore, the surface rock point data of each sub-area is collected, and the drawn sliding slope and the collected surface rock point data are entered 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, and the surface variance roughness is used to reflect the average height of the surface rock 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 maps the sliding slope of each sub-region through acoustic detection technology.

[0016] Furthermore, the three-dimensional model is placed in a coordinate system, and 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, wherein 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 base height is obtained by averaging. , height of substrate and surface height Conduct correlation analysis to generate fluctuation contribution index , based on the formula: ;

[0017] Among them, the fluctuation contribution index Used to reflect the proportion of the base covering layer on the marine rock slope in the sub-area.

[0018] Furthermore, the three-dimensional model is subjected to correlation analysis to generate surface variance roughness and base variance roughness , based on the formula:

[0019] ;

[0020] 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.

[0021] Furthermore, the surface variance roughness, substrate variance roughness and undulation contribution index are correlated and the roughness interference index is generated. , based on the formula:

[0022] ;

[0023] 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.

[0024] Furthermore, the correlation analysis of soil sample parameters was performed to generate the shear strength, based on the formula:

[0025] ;

[0026] 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 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.

[0027] Furthermore, the water level of the sub-area is collected, and the correlation analysis between the water level and shear strength is performed to generate the water level strength change index , based on the formula: ;

[0028] 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.

[0029] Furthermore, the water level intensity change index , shear strength , roughness interference index Perform correlation analysis to generate shear instability coefficients , based on the formula: ;

[0030] 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, the risk of shear instability in the sub-region is relatively high, and reinforcement 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.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] The present invention divides the marine rock slope prediction area into multiple sub-areas through the regional division module, obtains a three-dimensional model to reflect the sliding slope and rock surface characteristics of each sub-area, analyzes the generated surface height and base height, and calculates the undulation contribution index to evaluate the proportion of the base covering layer of the marine rock slope, and further generates the variance roughness of the surface and base to reflect the roughness level of each model. The roughness interference analysis module combines the roughness index to evaluate the degree of interference between the sliding slope and the rock slope. Soil samples are obtained by drilling and their shear parameters are tested to generate the maximum shear stress. The water level impact module analyzes the impact of the water level on the shear strength and generates the water level strength change index. The comprehensive analysis module performs correlation analysis on each item to generate a shear instability coefficient, which reflects the shear capacity of the sub-area when considering external loads, water levels and roughness. By comparing with the threshold, the shear capacity strength level of the sub-area is output, providing a basis for risk assessment and prevention. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 This is a schematic diagram of the overall system flow of the present invention;

[0034] Figure 2 The distribution diagram of cohesion, pore water pressure and shear strength of the present invention;

[0035] Figure 3 This is the distribution diagram of the minimum water level, maximum water level, and water level intensity change index of the present invention;

[0036] Figure 4 is a fitting diagram of the roughness interference index-shear instability coefficient of the present invention;

[0037] Figure 5 This is a fitting diagram of shear strength-shear instability coefficient of the present invention;

[0038] Figure 6 It is a fitting diagram of the water level strength change index-shear instability coefficient of the present invention. DETAILED DESCRIPTION

[0039] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to specific embodiments.

[0040] It should be noted that, unless otherwise defined, the technical or scientific terms used in the present invention should have the usual meanings understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative position relationships. When the absolute position of the object being described changes, the relative position relationship may also change accordingly.

[0041] Example:

[0042] See also Figure 1 , the present invention provides a technical solution:

[0043] A base-cover interface shear instability prediction system, specifically comprising:

[0044] A region division module is used to determine a predicted marine rock slope area, divide the predicted area into N sub-areas, monitor and map the slip slope of each sub-area, collect surface rock point data of each sub-area, enter the mapped slip slope and the collected surface rock point data into a three-dimensional design software and generate a three-dimensional model. The three-dimensional model includes a slip surface model and a surface model. The slip surface model is used to reflect the shape characteristics of the slip slope of the sub-area, and the surface model is used to reflect the surface shape characteristics of the surface rock of the sub-area.

[0045] The regionalization module uses acoustic detection technology to monitor and map the landslide surface in each sub-region. Acoustic detectors are deployed within each sub-region to form a monitoring network, ensuring coverage of every sub-region. Drones equipped with high-resolution cameras and lidar equipment acquire surface rock mass point data. Signal processing software is used to denoise and enhance the acoustic data, extracting the characteristics of the landslide surface. The landslide surface data obtained from acoustic detection and the point cloud data acquired by the drone are then input into 3D design software, where the data from these different sources is integrated to create a complete 3D model.

[0046] A relief contribution index analysis module is used to place the three-dimensional model in a coordinate system, perform correlation analysis on the three-dimensional model, generate surface height and base height, wherein 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 sliding slope in the sub-region. Correlation analysis is performed on the surface height and base height to generate a relief contribution index, wherein the relief contribution index is used to reflect the proportion of the base cover layer on the marine rock mass slope in the sub-region;

[0047] 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 values 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 base height is obtained by averaging. , height of substrate and surface height Conduct correlation analysis to generate fluctuation contribution index , based on the formula: ;

[0048] Among them, the marine rock mass slope is unidirectionally inclined as a whole. In order to determine the proportion of the marine rock mass slope base cover in each sub-area, the surface height is used to determine the proportion of the marine rock mass slope base cover. and base height The ratio of the ratio of the fluctuation contribution index is used to determine its proportion. Reflects the proportion of the base covering layer on the current sub-region's marine rock mass slope and the undulation contribution index The larger the value is, the greater the proportion of the base covering layer on the marine rock slope in the sub-region. By performing a difference analysis on the undulation contribution index of adjacent sub-regions, the degree of undulation between the sub-regions can be obtained.

[0049] A roughness analysis module is used to perform correlation analysis on the three-dimensional model to generate average roughness, which includes surface variance roughness and base variance roughness. 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.

[0050] The three-dimensional model is used for correlation analysis to generate surface variance roughness and base variance roughness , based on the formula:

[0051] ;

[0052] The sliding surface model and surface model of the i-th sub-region are both sampled at nine points, using Indicates 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, 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.

[0053] A roughness interference analysis module is used to perform correlation analysis on the surface variance roughness, the base variance roughness and the undulation contribution index to generate a roughness interference index, which is used to reflect the degree of roughness interference between the sliding slope and the rock slope;

[0054] Correlation analysis is performed on the surface variance roughness, substrate variance roughness and undulation contribution index to generate the roughness interference index. , based on the formula:

[0055] ;

[0056] The sub-regions are arranged from top to bottom, and the adjacent sub-regions from top to bottom are indexed with subscripts i-1, i, and i+1. For example, among three adjacent sub-regions, the ups and downs contribution index of the topmost sub-region is The fluctuation contribution index of the middle side is expressed as Indicates that the bottom side of the fluctuation contribution index is expressed as Indicates. Among them, is the fluctuation weight factor, and its value range is The fluctuation weight factor is determined by experiment. The fluctuation weight factor is used to reflect the degree of interference of the roughness interference index by the shear strength. The larger the fluctuation weight factor, the greater the degree of interference of the roughness interference index by the shear strength. Used to reflect the degree of roughness interference between the sliding slope and the rock slope, the roughness interference index The larger the value is, the higher the fluctuation between sub-regions is, which makes the prediction region more stable. It is used to indicate the degree of undulation of adjacent sub-regions. It is used to indicate the contribution degree of roughness of sliding slope and rock slope. The larger the value, the greater the contribution of the roughness of the sliding slope and rock slope. The contact tightness between the base and the surface is reflected in the base variance roughness, so the base variance roughness plays a decisive role in the contribution. The exponential growth is adopted. The larger the surface variance roughness, base variance roughness and undulation contribution index are, the greater the roughness interference index is. The bigger.

[0057] The shear strength analysis module is used to drill in the sub-area, extract soil samples, and conduct tests to obtain soil sample parameters, including cohesion and friction angle. The soil sample parameters are then subjected to correlation analysis to generate shear strength, which reflects the maximum shear stress that the sub-area can withstand under the action of shear force.

[0058] Correlation analysis of soil sample parameters was performed to generate shear strength, based on the following formula:

[0059] ;

[0060] 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 volume of the i-th sub-region, is the density of the ith sub-region, and the pore water pressure is measured by the pore water pressure gauge. is the shear strength of the i-th subregion. Shear strength reflects the maximum shear stress a subregion can withstand under shear force. External load, cohesion, friction angle, and pore water pressure are average values. Greater cohesion, density, and volume are associated with greater subregion mass, load, and cohesion, resulting in a positive correlation between the shear strength and the shear strength. Greater pore water pressure leads to lower shear strength, resulting in a negative correlation. In slope stability analysis, an increase in external load, such as the deadweight of a building, can reduce the effective stress in the soil, thereby lowering its shear strength.

[0061] The water level impact module is used to collect the water level of the sub-area, perform correlation analysis on the water level and shear strength, and generate a water level strength change index, which is used to reflect the degree to which the shear strength of the sub-area is affected by the water level;

[0062] Collect sub-area water levels, conduct correlation analysis between water levels and shear strength, and generate a water level strength change index , based on the formula: ;

[0063] The collection period is one month. is the minimum water level depth of the ith sub-area, is the maximum water level depth in the ith sub-area, and the water level intensity change index Used to reflect the impact of water level changes on shear strength. is the minimum amount of shear strength, The maximum shear strength is determined by comparing the ratio of the change in shear strength to determine the water level strength change index. , water level intensity change index The larger the value, the more the sub-area is affected by the water level and the more unstable its shear resistance is.

[0064] Statistical sub-area maximum water level , minimum water level The relationship with the water level intensity change index is shown in Table 1:

[0065] Table 1: Maximum water levels , minimum water level Table of water level intensity change index

[0066] ;

[0067] Reference Figure 2 and Figure 3 , Figure 2 The horizontal axis is the sub-region number, and the vertical axis is the pressure. The distribution values of cohesion, pore water pressure, and shear strength are displayed intuitively through this table. Figure 3The distribution diagrams of maximum water level, minimum water level and water level intensity change index are drawn.

[0068] The comprehensive analysis module is used to perform correlation analysis on the water level intensity change index, shear strength, and roughness interference index to generate a shear instability coefficient. 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 shear instability coefficient is compared with the threshold value to output the shear capacity strength level of the sub-region.

[0069] Water level intensity change index , shear strength , roughness interference index Perform correlation analysis to generate shear instability coefficients , based on the formula: ;

[0070] 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 larger the size, the better the shear resistance of the sub-region. The larger the value, the greater the contribution of roughness to anti-shear capacity, indicating that the sub-region has better anti-shear capacity. Its weight ratio has an upper limit, so the logarithmic function is used to limit its numerical growth. The water level intensity change index The larger the value is, the more the sub-region is affected by the water level, and the more unstable the shear resistance of the sub-region is. It is used to reflect the stability of the shear strength of the corresponding sub-area. The water level strength change index is positively correlated with it, and the shear strength and roughness interference index are negatively correlated with it. The shear instability coefficient is generated by fitting, and the shear instability coefficient is compared with the threshold. Compare, threshold is the demarcation value of the shear instability coefficient of the sub-region, the threshold Through experimental analysis, it is obtained that When the shear strength of the sub-region is level 2, the risk of shear instability in the sub-region is relatively high, and reinforcement 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.

[0071] The data table of roughness interference index, shear strength, water level strength change index and shear instability coefficient is shown in Table 2:

[0072] Table 2: Data table of roughness interference index, shear strength, water level strength change index and shear instability coefficient

[0073] ;

[0074] Reference Figures 4 to 6 , Figure 4 The middle is the fitting image of the roughness interference index-shear instability coefficient, Figure 5 is the fitting image of shear strength-shear instability coefficient, Figure 6 This is the fitting image of the water level strength change index-shear instability coefficient. It can be seen from the figure that the water level strength change index is positively correlated with the shear instability coefficient. The larger the water level strength change index, the larger the shear instability coefficient. The shear strength and roughness interference index are negatively correlated with the shear instability coefficient. The larger the shear strength and roughness interference index, the smaller the shear instability coefficient. The larger the shear instability coefficient, the greater the risk of shear instability in the sub-region, and the predicted area needs to be reinforced and maintained.

[0075] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0076] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other 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 each example described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software depends on the specific application and design constraints of the technical solution.

[0077] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, and may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment as needed.

[0078] The above is only a specific implementation method of the present application, but the scope of protection of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the scope of protection of the present application.

Claims

1. A system for predicting shear instability of a base-cover interface, characterized in that: Specifically include: A region division module is used to determine the predicted area of the marine rock mass slope, divide the predicted area into N sub-areas, monitor and map the slip slope of each sub-area, and generate a three-dimensional model, wherein the three-dimensional model includes a slip surface model and a surface model; The undulation contribution index analysis module performs correlation analysis on the three-dimensional model to generate the surface height and base height, and performs correlation analysis on the surface height and base height to generate the undulation contribution index; A roughness analysis module is used to perform correlation analysis on the three-dimensional model to generate an 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 to generate roughness interference index; The shear strength analysis module is used to drill in the sub-area, extract soil samples, conduct experimental tests, 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; Comprehensive analysis module, used to perform correlation analysis on water level intensity variation index, shear strength, and roughness interference index, generate shear instability coefficient, compare the shear instability coefficient with the threshold, and output the shear strength grade of the sub-region; 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 values 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 base height is obtained by averaging. , height of substrate and surface height Conduct correlation analysis to generate fluctuation contribution index , based on the formula: Among them, the fluctuation contribution index To reflect the The proportion of the marine rock slope base cover in each sub-region, where i is the sub-region number, which is used to index the sub-region; Perform correlation analysis on the 3D model to generate surface variance roughness and base variance roughness , based on the formula: 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; Correlation analysis is performed on the surface variance roughness, substrate variance roughness and undulation contribution index to generate the roughness interference index. , based on the formula: 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; Correlation analysis of soil sample parameters was performed to generate shear strength, based on the following 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 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; Collect sub-area water levels, conduct correlation analysis between water levels and shear strength, and generate a water level strength change index , based on the formula: The collection period is one month. is the minimum water level depth of the ith sub-area, is the maximum water level depth in the ith sub-area, and the water level intensity change index Used to reflect the impact of water level changes on shear strength; Water level intensity change index , shear strength , roughness interference index Perform correlation analysis to generate shear instability coefficients , based on the formula: .

2. The system for predicting shear instability of a substrate-cladding interface 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 entered 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 variation 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 maps the sliding slope of each sub-region through acoustic detection technology.

3. The system for predicting shear instability of a substrate-cladding interface according to claim 1, characterized in that: 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, the risk of shear instability in the sub-region is relatively high, and reinforcement 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.

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