A method, device, storage medium and equipment for searching potential failure path of a heap body slope

Abstract

This invention relates to the field of search technology, and particularly to a method, apparatus, storage medium, and device for searching potential failure paths of boulders slopes. The technical solution of this invention includes the following steps: constructing a boulders slope model with a random block structure, storing it as a CAD file, wherein the constructed boulders slope model must meet the set orientation requirements; exporting the CAD file of the boulders slope model as an image, and then discretizing the pixels within the image model area using digital image binarization; according to the instability mode of the boulders slope, setting the leading edge shear exit position and the trailing edge tensile fracture position in the discretized pixels; and using A... * The algorithm searches for potential failure paths of the accumulated slope and identifies the shortest path distance as the optimal failure path. It then calculates the length of the optimal failure path and the enclosed area between the optimal failure path and the soil failure path to characterize the stability of the accumulated slope.

Description

A method, apparatus, storage medium, and equipment for searching potential failure paths of accumulated slopes. Technical Field

[0001] This invention relates to the field of search technology, and in particular to a method, apparatus, storage medium, and device for searching potential failure paths of accumulated slopes. Background Technology

[0002] Accumulated slopes are essentially a non-homogeneous mixture of soil and rock, exhibiting high structural randomness and spatial variability. Therefore, the stability and internal structure of accumulated slopes are difficult to determine. The stability of accumulated slopes depends not only on the mechanical properties of the internal soil and rock but also on the distribution characteristics of the internal rock, including rock content, surface roughness of boulders, boulder size, and boulder inclination distribution.

[0003] Quantitatively describing the failure paths of complex aggregate slopes based on existing research findings remains a challenging research problem. Using artificial intelligence algorithms to accurately search for failure paths can provide a new approach to stability analysis of aggregate slopes. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for searching potential failure paths of accumulated slopes, thereby solving the problem that existing methods for identifying potential failure paths of accumulated slopes are difficult to implement.

[0005] The technical solution adopted in this invention is as follows: A method for searching potential failure paths of accumulated body slopes, comprising the following steps:

[0006] (1) Construct a slope model with random block stone structure and save it as a CAD file. The constructed slope model must meet the set orientation requirements.

[0007] (2) After exporting the CAD file of the accumulated slope model as an image, the pixels in the image model area are discretized by digital image binarization.

[0008] (3) Based on the instability mode of the accumulation body slope, set the position of the leading edge shear outlet and the position of the trailing edge tensile crack in the discrete pixels;

[0009] (4) In the discretized pixels, A is used * The algorithm searches for potential failure paths of the accumulated slope and identifies the shortest path distance as the optimal failure path.

[0010] (5) Calculate the length of the optimal failure path and the closed area between the optimal failure path and the soil failure path to characterize the stability of the accumulated slope.

[0011] Preferably, in step (1), the orientation requirement is that the slope model with a random block structure needs to be generated within a set area of ​​the slope according to the random block generation algorithm.

[0012] Preferably, in step (2), after the pixels in the image model area are discretized, the black points of the boulders have a value of 1, representing that the path is impassable; the white points of the soil area have a value of 0, representing that the path is passable; during the digital image binarization process, a grayscale threshold needs to be set in advance to satisfy the following formula:

[0013]

[0014] In the formula, f(x,y) is the gray value of a pixel after binarization of the digital image; g(x,y) is the initial gray value of the pixel; and k is the gray threshold.

[0015] Preferably, in step (3), the location of the leading edge shear exit and the location of the trailing edge tensile crack are determined based on the failure path when the slope is pure soil. This failure path is obtained by calculating and analyzing the pure soil slope using the limit equilibrium method.

[0016] Preferably, in step (4), the use of A * The algorithm searches for potential disruptive paths. The search steps are as follows:

[0017] (4.1) Set the leading edge shear exit position of the potential failure path as the starting point n. s and its value f(n) s )=g(n s Add it to the Open list;

[0018] (4.2) Set the trailing edge fracture location of the potential failure path as the target node n. g ;From the starting point n s First, determine if the current node n is the target node n. g If yes, output the path coordinates; otherwise, proceed to the next step.

[0019] (4.3) Search for all nodes that belong to the neighborhood of the current node n, ignoring pixels that are already in the Closed list and those that cannot be passed through, and calculate the cost value f(n); select the node corresponding to the smallest f(n) and store it in the Closed list;

[0020] (4.4) Connect the current node n with the node corresponding to the minimum f(n), set the node corresponding to the minimum f(n) as the next current node n, and repeat step (2).

[0021] Preferably, in step (4), the path distance is calculated using Euclidean distance as the calculation standard, according to the following formula:

[0022]

[0023] In the formula: (x s ,y s ) and (x g ,y g (n) represents the starting point. s and target node n g The coordinates.

[0024] Preferably, in step (5), the optimal failure path length and the closed area between the optimal failure path and the soil failure path are obtained by statistical analysis of the output path coordinate information.

[0025] The present invention also provides a potential failure path search device for a slab slope, comprising:

[0026] The model generation module is used to generate a slope model with a random block stone structure within a defined area of ​​the slope, and save it as a CAD file.

[0027] The image processing module is used to export CAD files as images and discretize the pixels within the image model area through digital image binarization.

[0028] The search module is used to search for the coordinate information of pixels within the discretized model region to obtain the optimal destruction path.

[0029] The statistical analysis module is used to perform calculations and analyses on pure soil slopes, obtain the shear exit location and trailing edge tensile crack location of the soil failure path, output them to the search module, and calculate the closed area of ​​the optimal failure path and the soil failure path based on the optimal failure path obtained by the search module.

[0030] The present invention also provides a storage medium storing a computer program executable by a processor, characterized in that: when the computer program is executed, it implements the steps of the method for searching potential failure paths of the accumulated slope.

[0031] The present invention also provides a computer device having a memory and a processor, wherein the memory stores a computer program that can be executed by the processor, characterized in that: when the computer program is executed, it implements the steps of the method for searching potential failure paths of the accumulated slope.

[0032] The beneficial effects of this invention are: it provides new technical guidance for the stability analysis of accumulated slopes, constructs accumulated slopes with complex random structures based on a random block generation algorithm, introduces the A* algorithm to search for potential failure paths, and realizes the identification of potential failure paths of complex accumulated slopes with random structures. Attached Figure Description

[0033] Figure 1 shows an embodiment of the present invention, A * Flowchart of the algorithm for searching the shortest distance.

[0034] Figure 2 is a diagram of the initially constructed accumulation body slope model in an embodiment of the present invention.

[0035] Figure 3 is a binarized model of the accumulation body slope in an embodiment of the present invention.

[0036] Figure 4 is a schematic diagram of potential destruction path search results in an embodiment of the present invention.

[0037] Figure 5 is a schematic diagram of the statistical analysis of the shortest destruction path characteristics in an embodiment of the present invention. Detailed Implementation

[0038] To enable those skilled in the art to more clearly understand the purpose, technical solution and advantages of the present invention, the present invention will be further described below in conjunction with the accompanying drawings and embodiments, but the present invention is not limited to the following embodiments.

[0039] The present invention provides a method for searching potential failure paths of a slab slope, comprising the following steps:

[0040] Step 1: Construct a slope model with a random block structure and save it as a CAD file. The constructed slope model must meet the set orientation requirements.

[0041] First, based on the random stone generation algorithm, random stones are randomly placed in the model according to the requirements of the accumulated slope model. Attention must be paid to the intrusion judgment between points, lines, and lines. Second, key model construction information such as stone content, stone tendency, and stone size are set to effectively consider the characteristics of stones in the accumulated slope and reflect the real slope characteristics.

[0042] Step 2: After exporting the CAD file of the accumulated slope model as an image, perform digital image binarization to discretize the pixels within the model area. Specifically:

[0043] Images discretized using digital image binarization are decomposed as follows: black dots representing rocks have a value of 1, indicating an impassable path; white dots representing soil have a value of 0, indicating a passable path. A grayscale threshold needs to be pre-set during digital image binarization, satisfying the following formula:

[0044]

[0045] In the formula, f(x,y) is the gray value of the digital image after binarization; g(x,y) is the initial gray value of the pixel; and k is the gray threshold.

[0046] Step 3: Based on the instability mode of the accumulation body slope, set the position of the leading edge shear outlet and the position of the trailing edge tensile crack in the discretized pixels.

[0047] Specifically, the location of the leading shear exit and the trailing tensile crack exit needs to be determined based on the failure path when the slope is pure soil. The limit equilibrium method can be used to calculate and analyze the pure soil slope.

[0048] Step 4: Among the discretized pixels, use A * The algorithm searches for potential failure paths on the slope of the accumulation body and considers the shortest path distance as the optimal failure path.

[0049] Using A * The algorithm searches for potential disruptive paths, and the specific process is shown in Figure 1. The search steps can be described as follows:

[0050] (4.1) Set the leading edge shear exit position of the potential failure path as the starting point n. s and its value f(n) s )=g(n s Add it to the Open list; in A * In the algorithm, cost refers to the path distance between two points;

[0051] (4.2) Set the trailing edge fracture location of the potential failure path as the target node n. g ;From the starting point n s Initially, determine whether the current node n is the target node n by using the path distance. g If yes, output the path coordinates; otherwise, proceed to the next step.

[0052] (4.3) Search for all nodes that belong to the neighborhood of the current node n, ignoring pixels that are already in the Closed list and those that cannot be passed through, and calculate the cost value f(n); select the node corresponding to the smallest f(n) and store it in the Closed list;

[0053] (4.4) Connect the current node n with the node corresponding to the minimum value f(n), set the node corresponding to the minimum cost f(n) as the next current node n, and repeat step (2).

[0054] Preferably, the path distance is calculated using Euclidean distance as the calculation standard, according to the following formula:

[0055]

[0056] In the formula: (x s ,y s ) and (x g ,y g (n) represents the starting point.s and target node n g The coordinates.

[0057] (5) Calculate the shortest path length and the enclosed area between the shortest path and the soil failure path to characterize the stability of the embankment slope. The shortest path length and the enclosed area between the shortest path and the soil failure path can be obtained by statistical analysis of the extracted path coordinate information.

[0058] Example:

[0059] 1. Based on the random boulders generation system, a CAD file for the accumulated slope model was constructed, as shown in Figure 2. The model includes soil and boulders, with boulder gradation sizes ranging from 30cm to 90cm, a boulder dip angle of 45°, a stone content of 30%, and 5-6 boulder edges.

[0060] 2. Export the accumulated slope model from the CAD file as an image and perform digital image binarization. The image will contain 420*180 pixels. Black areas (rocks) will have a value of 1, indicating the search distance will be blocked; white areas (soil) will have a value of 0, indicating the search distance will be allowed. Output a bmp image to complete the digital image binarization, resulting in the corresponding binary file, as shown in Figure 3.

[0061] 3. The failure path for pure soil was searched using the limit equilibrium method, as shown by the dashed line in Figure 4. The shear exit location and the trailing tensile fracture location were determined sequentially. The shear exit location is at the slope toe, and the trailing tensile fracture location is 3.5m to the right of the slope crest. Then, the A* algorithm was used to search for the shortest Euclidean distance between the two points, as shown by the solid line in Figure 4. It can be seen that the failure path bypasses the boulders and only passes through the soil, thus allowing the search for the shortest failure path for a slope with a random structure.

[0062] 4. The shortest path length and the area enclosed by the shortest path and the soil failure path are calculated to characterize the stability of the embankment slope, as shown in Figure 5. The enclosed area is 1.33 m², and the failure path length is 14.11 m.

[0063] The present invention also provides a potential failure path search device for a slab slope, comprising:

[0064] The model generation module is used to generate a slope model with a random block stone structure within a defined area of ​​the slope, and save it as a CAD file.

[0065] The image processing module is used to export CAD files as images and discretize the pixels within the image model area through digital image binarization.

[0066] The search module is used to search for the coordinate information of pixels within the discretized model region to obtain the optimal destruction path.

[0067] The statistical analysis module is used to perform calculations and analyses on pure soil slopes, obtain the shear exit location and trailing edge tensile crack location of the soil failure path, output them to the search module, and calculate the closed area of ​​the optimal failure path and the soil failure path based on the optimal failure path obtained by the search module.

[0068] The present invention also provides a storage medium storing a computer program executable by a processor, wherein the computer program, when executed, performs the steps of the above-described method for searching potential failure paths of accumulated body slopes.

[0069] The present invention also provides a computer device having a memory and a processor, wherein the memory stores a computer program that can be executed by the processor, and the computer program, when executed, implements the steps of the above-described method for searching potential failure paths of accumulated slopes.

[0070] The above description is merely a preferred embodiment of the present invention. For those skilled in the art, the present invention can have various modifications and variations. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for searching potential failure paths of a slab slope, characterized in that... Includes the following steps: (1) Construct a slope model with a random block stone structure and store it as a CAD file. The constructed slope model must meet the set orientation requirements. (2) Export the CAD file of the slope model as an image and then discretize the pixels in the image model area using digital image binarization. (3) Based on the slope instability mode, set the leading edge shear exit position and the trailing edge tensile crack position in the discretized pixels. (4) In the discretized pixels, use A * The algorithm searches for potential failure paths of the embankment slope and identifies the shortest path distance as the optimal failure path; (5) the length of the optimal failure path and the closed area between the optimal failure path and the soil failure path are statistically analyzed to characterize the stability of the embankment slope; in step (4), the A algorithm is used. * The algorithm performs a potential destruction path search. The search steps are as follows: (4.1) Set the leading edge shear exit position of the potential destruction path as the starting point. and its value Add to the Open list; (4.2) Set the trailing edge fracture location of the potential failure path as the target node. From the starting point Begin by determining the current node. Is it the target node? If yes, output the path coordinates; otherwise, proceed to the next step; (4.3) Search for nodes belonging to the current node Calculate the cost value for all nodes in the neighborhood, ignoring pixels already in the Closed list and those that cannot be accessed. Select the smallest The corresponding node is stored in the Closed list; (4.4) Connect the current node With minimum The corresponding node will be the smallest The corresponding node is set as the next current node. Repeat step (2).

2. The method for searching potential failure paths of a slab slope according to claim 1, characterized in that: In step (1), the orientation requirement is that the slope model with a random block structure needs to be generated within a set area of ​​the slope according to the random block generation algorithm.

3. The method for searching potential failure paths of a slab slope according to claim 2, characterized in that: In step (2), after the pixels in the image model area are discretized, the black points of the stone block have a value of 1, which means that the path is not passable; the white points of the soil area have a value of 0, which means that the path is passable. In the process of digital image binarization, a grayscale threshold needs to be set in advance, satisfying the following formula: In the formula, The grayscale value of a pixel after binarization of a digital image; The initial grayscale value of the pixel; This is the grayscale threshold.

4. The method for searching potential failure paths of a slab slope according to claim 3, characterized in that: In step (3), the positions of the leading shear exit and the trailing tensile crack are determined based on the soil failure path when the slope is pure soil. The soil failure path is obtained by calculating and analyzing the pure soil slope using the limit equilibrium method. The leading shear exit position of the soil failure path is used as the starting point of the potential failure path, and the trailing tensile crack position is used as the ending point of the potential failure path.

5. The method for searching potential failure paths of a slab slope according to claim 1, characterized in that: In step (4), the path distance is calculated using Euclidean distance as the calculation standard, according to the following formula: In the formula: and Divided into starting points and target node The coordinates.

6. The method for searching potential failure paths of a slab slope according to claim 1, characterized in that: In step (5), the optimal failure path length and the closed area between the optimal failure path and the soil failure path are obtained by statistical analysis of the output path coordinate information.

7. A potential failure path search device for an accumulation slope, characterized in that, include: The model generation module is used to generate a slope model with a random block stone structure within a defined area of ​​the slope, and save it as a CAD file. The image processing module is used to export CAD files as images and discretize the pixels within the image model area through digital image binarization. The search module is used to search for the coordinate information of pixels within the discretized model region to obtain the optimal destruction path. The statistical analysis module is used to perform calculations and analyses on pure soil slopes, obtain the shear exit location and trailing edge tensile crack location of the soil failure path, output them to the search module, and calculate the closed area of ​​the optimal failure path and the soil failure path based on the optimal failure path obtained by the search module.

8. A storage medium storing a computer program executable by a processor, characterized in that: When the computer program is executed, it implements the steps of the potential failure path search method for the accumulated slope as described in any one of claims 1 to 6.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program executable by the processor, characterized in that: When the computer program is executed, it implements the steps of the potential failure path search method for the accumulated slope as described in any one of claims 1 to 6.

Images