A modeling method and system based on two-dimensional slope

Abstract

The present invention discloses a modeling method and system based on a two-dimensional slope, the method comprising: S1. Analyzing and obtaining the structural features of the two-dimensional slope; S2. Classifying the structural features of the slope; S3. Replacing the classified features with straight lines or arcs to achieve simplified slope modeling. The core purpose of the present invention is to reproduce the key features of the slope in a targeted manner during the two-dimensional slope modeling process, ignore the irrelevant features of the slope without affecting the stability of the slope itself, speed up the modeling speed, and improve the efficiency of slope stability analysis. The present invention eliminates the interference of a large number of small features on the slope modeling during the slope modeling process, and significantly reduces the difficulty of slope modeling without affecting the stability of the slope. The present invention processes the slope model while retaining the key feature structure, eliminates abnormal features such as discontinuity and non-differentiability, and improves the convergence of the model.

Description

Technical Field

[0001] The invention belongs to the technical field of two-dimensional plane modeling, and in particular relates to a modeling method and system based on two-dimensional slopes. Background Art

[0002] Transmission lines are usually composed of poles, conductors, insulators, line fittings, guy wires, pole foundations, grounding devices, etc., and are erected on the ground. During the construction process, transmission lines will inevitably be built on complex geological environments, such as slopes, waters, hillsides, mountaintops, hollowed-out areas, karst caves, etc. Since overhead lines are exposed to the outside world all year round and are easily affected by weather and the environment, the pole foundations are subjected to alternating loads in the vertical direction (downward pressure, upward pull) and horizontal direction. These complex geological environments bring more severe tests to the transmission line towers.

[0003] In recent years, tower foundation instability incidents caused by slope damage have occurred from time to time. In order to reasonably evaluate the safety status of the transmission line tower foundation, it is necessary to analyze the stability of the slope. Slope stability analysis methods are usually divided into qualitative analysis, quantitative analysis and uncertainty analysis. Uncertainty analysis is based on qualitative analysis and quantitative analysis, and has developed some new stability analysis methods such as reliability analysis, fuzzy grading evaluation method, system engineering geological analysis method, and gray system theory analysis method. Qualitative analysis refers to a method that analyzes the causes and evolution history of slopes through engineering geological surveys, analyzes factors that affect slope stability, possible forms of slope damage, and mechanical mechanisms of instability, and qualitatively analyzes and explains the stability of slopes and their possible development trends. Commonly used quantitative analysis methods mainly include limit equilibrium method and numerical simulation method. Among them, numerical simulation method is more in line with reality, and the first condition for the analysis results of numerical simulation method to be in line with reality is that the model is accurate.

[0004] In actual engineering projects, the existing method is to convert the numerical analysis cases of slope stability into two-dimensional planes for analysis, so it is necessary to establish a two-dimensional slope model with appropriate accuracy. Based on high-precision data collection methods, a large number of features will be obtained, such as large-span convex and concave rock and soil, as well as small-span earth bags. Some cases reproduce the slope environment according to reality, and the modeling workload is huge. Many structural features that have little effect on slope stability seriously restrict the efficiency of slope modeling; some cases do not screen various features, simplify and omit them all, and the credibility of the analysis results obtained is questionable.

[0005] The results of literature search show that there are few studies on the simplification strategies adopted in the process of two-dimensional slope modeling. Therefore, it is urgent to propose a method to simplify slope modeling while ensuring the accuracy of slope stability analysis results, so as to better meet practical needs. Summary of the invention

[0006] The purpose of the present invention is to overcome the defects of the prior art. The present invention provides a modeling simplification method and system based on two-dimensional slopes. In view of the problem of lack of opinions on the selection of slope structural features, the present invention performs feature analysis on the slope contour, sets feature types and corresponding feature classification basis, simplifies irrelevant features, retains important features, and establishes slope modeling simplification criteria. While ensuring the credibility of the stability analysis structure, the slope modeling speed is accelerated and the efficiency of slope stability analysis is improved.

[0007] In order to achieve the expected effect, the present invention adopts the following technical solutions:

[0008] The present invention also discloses a modeling method based on a two-dimensional slope, comprising:

[0009] S1. Analyze and obtain the two-dimensional slope structure characteristics;

[0010] S2. Classify the structural characteristics of the slope;

[0011] S3. Replace the classified features with straight lines or arcs to achieve simplified slope modeling.

[0012] Furthermore, the S1 specifically includes: based on the least squares method, in combination with the two-dimensional slope scattered point data set, the slope scattered point contour line is calculated, and the local characteristics of the slope and the overall characteristics of the slope are analyzed through the slope scattered point contour line.

[0013] Furthermore, S2 specifically includes: comparing the local features of the slopes adjacent to each other, integrating similar features into one, grouping the local features with large differences, and classifying all the features on the slope one by one.

[0014] Furthermore, the local features of the slopes adjacent to each other are compared, similar features are integrated into one group, local features with large differences are grouped separately, and all features on the slope are classified one by one, specifically including:

[0015] Based on the layer-by-layer progressive strategy, the curvature radius of the slope scattered point contour line is calculated;

[0016] Compare the curvature radius of each contour line and merge the contour lines with similar curvature radius into a group;

[0017] Calculate the span of each section of the contour line and the slope span based on the ideal flat slope contour line;

[0018] The groups with infinite curvature radius or much larger than the slope span are set as flat straight lines, and then other groups are compared with the slope span. The slope features with curvature radius much smaller than the slope span are classified as Class A, the slope features with large curvature radius but small ratio to slope span are classified as Class B, and the slope features with large curvature radius and large ratio to slope span are classified as Class C.

[0019] Furthermore, the comparing the curvature radii of each segment of the contour line and merging the contour lines with similar curvature radii into a group specifically includes: when the curvature radii of two adjacent contour lines satisfy the following formula, merging the two contour lines into a group;

[0020]

[0021] Wherein, R2 and R1 are the curvature radii of two adjacent contour lines, and t1 is the first threshold.

[0022] Furthermore, the step of classifying the slope features whose curvature radius is much smaller than the slope span as Class A specifically includes: when a set of curvature radii When the following formula is satisfied, the group is classified as Class A;

[0023]

[0024] Where d is the span of the set of features, and t2 is the second threshold.

[0025] Furthermore, the method of classifying the slope features with a large curvature radius but a small ratio to the slope span as Class B specifically includes: when a set of curvature radii When the following formula is satisfied, the group is classified as Class B;

[0026]

[0027] Where d is the span of the feature set, D is the slope span, t2 is the second threshold, and t3 is the third threshold.

[0028] Furthermore, the step of classifying the slope features with a larger curvature radius and a larger ratio to the slope span as Class C specifically includes: when a set of curvature radii When the following formula is satisfied, the group is classified as Class C;

[0029]

[0030] Where d is the span of the feature set, D is the slope span, t2 is the second threshold, and t3 is the third threshold.

[0031] Furthermore, the S3 specifically includes: replacing the A-type and B-type slope features with straight line segments, and replacing the C-type slope features with arcs.

[0032] The present invention also discloses a modeling system based on two-dimensional slope, comprising:

[0033] Acquisition module, used to obtain various data required for modeling;

[0034] A modeling module is used to perform modeling according to any of the above methods.

[0035] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention provides a modeling method and system based on two-dimensional slopes. The core purpose of the present invention is to reproduce the key features of the slope in a targeted manner during the two-dimensional slope modeling process, ignore the irrelevant features of the slope without affecting the stability of the slope itself, speed up the modeling speed, and improve the efficiency of slope stability analysis. The present invention eliminates the interference of a large number of small features on slope modeling during the slope modeling process, and significantly reduces the difficulty of slope modeling without affecting the stability of the slope. The present invention processes the slope model while retaining the key feature structure, eliminates abnormal features such as discontinuity and non-differentiability, and improves the convergence of the model. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0037] Figure 1 It is a flow chart of a modeling method based on two-dimensional slope provided by an embodiment of the present invention.

[0038] Figure 2 It is a schematic diagram of a two-dimensional slope scattered point data set provided by an embodiment of the present invention.

[0039] Figure 3 It is an equivalent schematic diagram of an ideal flat slope provided by an embodiment of the present invention.

[0040] Figure 4 It is a schematic diagram of slope grouping provided by an embodiment of the present invention.

[0041] Figure 5 It is a schematic diagram of slope classification results provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] There are two main types of traditional two-dimensional slope modeling strategies: 1. Equivalent slope to an idealized inclined plane model. This type of model oversimplifies the slope structure characteristics, ignores the structural characteristics that affect the slope stability, and its analysis structure is questionable; 2. Fine model based on actual data. This type of model over-details the structural characteristics of the slope and adds many features that have little effect on the slope stability, and its analysis efficiency is low. Both methods are not conducive to the development of slope stability research based on numerical analysis.

[0044] See also Figures 1 to 5 The present invention also discloses a modeling method based on two-dimensional slope, comprising:

[0045] S1. Analyze and obtain the two-dimensional slope structure characteristics;

[0046] In a preferred embodiment, S1 specifically includes: based on the least squares method, combined with a two-dimensional slope scattered point data set, the slope scattered point contour line is calculated, and through the slope scattered point contour line, the local characteristics of the slope (i.e., the curvature radius and corresponding span of all curved areas, the slope and span of the straight area) and the overall characteristics of the slope (i.e., the slope and span when the overall slope is equivalent to a flat slope) are analyzed. The local limitation depends on the grouping result, and one group is considered as one local.

[0047] For example, based on the least squares method, combined with the two-dimensional slope scattered point data set S = {(x i ,y i )|i=1,2,3,…N}, an ideal flat slope contour line is calculated by fitting, such as Figure 3 The contour line is calculated for use in calculating the characteristic span of the slope in the subsequent steps. The specific calculation method is as follows:

[0048] y=kx+h

[0049]

[0050] Among them, k is the slope of the contour line, and h is the intercept of the contour line. The purpose of k and h is to calculate the span of each group (essentially the projection length of each group on the ideal slope).

[0051] S2. Classify the structural characteristics of the slope;

[0052] In one embodiment, S2 specifically includes: comparing two adjacent local features of the slope, integrating similar features into one, grouping local features with large differences, and classifying all features on the slope one by one.

[0053] Furthermore, the local features of the slopes adjacent to each other are compared, similar features are integrated into one group, local features with large differences are grouped separately, and all features on the slope are classified one by one, specifically including:

[0054] Based on the layer-by-layer progressive strategy, the curvature radius of the slope scattered point contour line is calculated;

[0055] Compare the curvature radius of each contour line and merge the contour lines with similar curvature radius into a group;

[0056] Calculate the span of each section of the contour line and the slope span based on the ideal flat slope contour line;

[0057] The groups with infinite curvature radius or much larger than the slope span are set as flat straight lines, and then other groups are compared with the slope span. The slope features with curvature radius much smaller than the slope span are classified as Class A, the slope features with large curvature radius but small ratio to slope span are classified as Class B, and the slope features with large curvature radius and large ratio to slope span are classified as Class C.

[0058] Furthermore, the comparing the curvature radii of each segment of the contour line and merging the contour lines with similar curvature radii into a group specifically includes: when the curvature radii of two adjacent contour lines satisfy the following formula, merging the two contour lines into a group;

[0059]

[0060] Wherein, R2 and R1 are the curvature radii of two adjacent contour lines, and t1 is the first threshold.

[0061] Preferably, analyzing the two-dimensional slope contour line features specifically includes: calculating the curvature radius R from the two-dimensional slope contour line based on a layer-by-layer progressive strategy.

[0062] Specifically, since the contour line of the slope is composed of a set of scattered points, the method for solving the curvature radius of each point in the present invention is to solve the radius of the circle based on the least squares method. If the three points are collinear, there is no solution, that is, the radius of the circle is infinite. Here, taking the starting point of the slope as an example, the coordinates of the three adjacent points are (x1, y1), (x2, y2), and (x3, y3), respectively. The curvature radius of the point (x1, y1) is calculated as follows:

[0063]

[0064] Preferably, after solving the curvature radius of the three points (x1, y1), (x2, y2), and (x3, y3), the next adjacent point is added to solve the curvature radius R2 of the four points. If the curvature radius changes slightly after adding a point and satisfies Then you can combine this point with (x1, y1), (x2, y2), (x3, y3) into a group, record and update the corresponding radius value, continue to add the next point, and calculate the radius value in a loop. Then all the points before this point are merged into one group, and the next point is set as the new calculation starting point, and the judgment is repeated until all scattered points are divided into the corresponding group P. j (j=1, 2, 3, ...), such as Figure 4 shown.

[0065] Furthermore, the two-dimensional slope scattered point data set S = {(x i ,y i )|i=1,2,3,…N} sort by the horizontal coordinate x, and take the first and last two points (x min ,y min )、(x max ,y max ), then the slope span is:

[0066]

[0067] in, is the vector formed by the first and last points, is the direction vector of an ideal flat slope.

[0068] Similarly, based on the merged scattered point groups, the span d of each group on the ideal flat slope is solved.

[0069] Specifically, classification is performed according to the divided groups. The group whose curvature radius is infinite or much larger than the slope span is set as a flat straight line. Other groups are classified by comparing their span and curvature radius. When the grouping is completed, no data points can be added to the calculation, and there are no remaining points; when a group adds a new data point, its curvature radius changes significantly and exceeds the threshold, then the previous points are packaged and grouped, and the added data point is used as the new starting point.

[0070] Furthermore, the step of classifying the slope features whose curvature radius is much smaller than the slope span as Class A specifically includes: when a set of curvature radii When the following formula is satisfied, the group is classified as Class A;

[0071]

[0072] Where d is the span of the set of features, and t2 is the second threshold.

[0073] Class A indicates that this group belongs to relatively sharp protrusions or depressions in the slope structure. The local derivative values ​​of such features will change dramatically, but because the features are too small, they are not enough to affect the stability of the slope.

[0074] Furthermore, the method of classifying the slope features with a large curvature radius but a small ratio to the slope span as Class B specifically includes: when a set of curvature radii When the following formula is satisfied, the group is classified as Class B;

[0075]

[0076] Where d is the span of the feature set, D is the slope span, t2 is the second threshold, and t3 is the third threshold.

[0077] Class B indicates that this group is a relatively gentle convex or concave feature in the slope structure. The derivative value of this type of feature changes slowly, but because the feature coverage is too small, it is not enough to affect the stability of the slope.

[0078] Furthermore, the step of classifying the slope features with a larger curvature radius and a larger ratio to the slope span as Class C specifically includes: when a set of curvature radii When the following formula is satisfied, the group is classified as Class C;

[0079]

[0080] Where d is the span of the feature set, D is the slope span, t2 is the second threshold, and t3 is the third threshold.

[0081] Category C indicates that this group of features is a relatively gentle convex or concave feature in the slope structure. This type of feature covers a large area and will affect the stability of the slope. Figure 5 as shown.

[0082] S3. Replace the classified features with straight lines or arcs to achieve simplified slope modeling.

[0083] In one embodiment, S3 specifically includes: replacing the A-type and B-type slope features with straight line segments, and replacing the C-type slope features with circular arcs.

[0084] In another embodiment, for features of type A and B, a line segment is drawn to replace the two end points of the features of that type, while features of type C retain the original features.

[0085] The core purpose of the present invention is to reproduce the key features of the slope in a targeted manner during the two-dimensional slope modeling process, ignore the irrelevant features of the slope without affecting the stability of the slope itself, speed up the modeling speed, and improve the efficiency of slope stability analysis. The present invention eliminates the interference of a large number of small features on slope modeling during the slope modeling process, and significantly reduces the difficulty of slope modeling without affecting the stability of the slope. The present invention processes the slope model while retaining the key feature structure, eliminates abnormal features such as discontinuity and non-differentiability, and improves the convergence of the model.

[0086] The present invention also discloses a modeling system based on two-dimensional slope, comprising:

[0087] Acquisition module, used to obtain various data required for modeling;

[0088] A modeling module is used to perform modeling according to any of the above methods.

[0089] The system embodiments can be implemented one-to-one with the aforementioned method embodiments, and will not be described in detail here.

[0090] Based on the same inventive concept, the present invention also discloses an electronic device, which may include: a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus. The processor may call the logic instructions in the memory to execute a modeling method based on a two-dimensional slope, including:

[0091] S1. Analyze and obtain the two-dimensional slope structure characteristics;

[0092] S2. Classify the structural characteristics of the slope;

[0093] S3. Replace the classified features with straight lines or arcs to achieve simplified slope modeling.

[0094] In addition, the logic instructions in the above-mentioned memory can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0095] On the other hand, an embodiment of the present invention further provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, and when the program instructions are executed by a computer, the computer can execute a modeling method based on a two-dimensional slope provided by the above-mentioned method embodiments, including:

[0096] S1. Analyze and obtain the two-dimensional slope structure characteristics;

[0097] S2. Classify the structural characteristics of the slope;

[0098] S3. Replace the classified features with straight lines or arcs to achieve simplified slope modeling.

[0099] In another aspect, an embodiment of the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the computer program is implemented to execute a modeling method based on a two-dimensional slope provided in the above embodiments, including:

[0100] S1. Analyze and obtain the two-dimensional slope structure characteristics;

[0101] S2. Classify the structural characteristics of the slope;

[0102] S3. Replace the classified features with straight lines or arcs to achieve simplified slope modeling.

[0103] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0104] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A modeling method based on two-dimensional slope, characterized in that: include: S1. Analyze and obtain the two-dimensional slope structure characteristics; The S1 specifically includes: based on the least squares method, combined with the two-dimensional slope scattered point data set, calculating the slope scattered point contour line, and analyzing the slope scattered point contour line to obtain the local characteristics and the overall characteristics of the slope; S2. Classify the structural features of the slope; S2 specifically includes: comparing the local features of the slopes adjacent to each other, integrating similar features into one group, setting up separate groups for local features with large differences, and classifying all the features on the slope one by one; The comparison of the local features of the slopes adjacent to each other, integrating similar features into one group, setting up separate groups for local features with large differences, and classifying all the features on the slope one by one specifically includes: based on a layer-by-layer progressive strategy, calculating the curvature radius of the slope scattered point contour line; comparing The curvature radius of each contour line, and the contour lines with similar curvature radius are merged into groups; the span of each contour line and the slope span are calculated based on the ideal flat slope contour line; the group with infinite curvature radius or much larger than the slope span is set as a flat straight line, and then the other groups are compared with the slope span, and the slope features with curvature radius much smaller than the slope span are classified as Class A, the slope features with large curvature radius but small ratio to slope span are classified as Class B, and the slope features with large curvature radius and large ratio to slope span are classified as Class C; S3. Replace the classified features with straight lines or arcs to achieve simplified slope modeling; S3 specifically includes: replacing Class A and Class B slope features with straight line segments, and replacing Class C slope features with arcs; The step of comparing the curvature radii of each segment of contour lines and merging contour lines with similar curvature radii into a group specifically includes: merging the two contour lines into a group when the curvature radii of two adjacent contour lines satisfy the following formula; ； In the formula, are the curvature radii of two adjacent contour lines, is the first threshold; The method of classifying the slope characteristics whose curvature radius is much smaller than the slope span as Class A specifically includes: when a set of curvature radii When the following formula is satisfied, the group is classified as Class A; ； Where d is the span of the set of features, is the second threshold; The method of classifying the slope features with a large curvature radius but a small ratio to the slope span as Class B specifically includes: when a set of curvature radii When the following formula is satisfied, the group is classified as Class B; ； Where d is the span of the feature group, D is the slope span, is the second threshold, is the third threshold; the slope characteristics with a large curvature radius and a large ratio to the slope span are classified as Class C specifically including: when a group of curvature radii When the following formula is satisfied, the group is classified as Class C; ； Where d is the span of the feature group, D is the slope span, is the second threshold, is the third threshold.

2. A modeling system based on two-dimensional slope, characterized in that: include: Acquisition module, used to obtain various data required for modeling; A modeling module, used for performing modeling according to the method of claim 1.

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