A method for measuring the external accumulation form and internal state parameters of a dam

Abstract

The application discloses a kind of determination method of external accumulation morphology and internal state parameter of barrier body, it is related to model construction field.The present application at least includes the following steps: S1: image information acquisition, the image information acquisition is carried out after barrier body formation;S2: point cloud and grid generation, the point cloud and grid generation are carried out in the image information acquisition;S3: based on S2, reconstruct each block of segmentation body;S4: based on S3, grid assembly is carried out;S5: based on S4, space body reconstruction is carried out;S6: based on S5, external accumulation morphology data is carried out;S7: based on S5, internal state parameter data is obtained.The present application obtains the following advantages by the overall step design: simple implementation step, simple operation method can obtain the data of the external characteristics of landslide barrier body space geometry, internal void ratio and grading, lay data foundation and boundary conditions for quantifying the spatial variation characteristics of landslide barrier body.

Description

Technical Field

[0001] This invention relates to the field of model building, specifically to a method for determining the external accumulation morphology and internal state parameters of a landslide dam. Background Technology

[0002] As a typical major natural flood and drought disaster, landslide dams have occurred frequently in recent years. The formation process of dams inevitably results in the heterogeneity of their materials, and coupled with the lack of prior consolidation, they exhibit significant spatial variability. Due to the short duration of landslide dams and the complex natural geographical environment at the sites, it is difficult to obtain timely and effective data on the morphology, structure, and particle size distribution of landslide dams.

[0003] Remote scanning by drones can only acquire images of the surface of landslide dams, and is insufficient for identifying the internal structural features and particle distribution of landslide dams.

[0004] Currently, the identification of the external morphology of landslide dams is still in the exploratory and developmental stage, and the analysis of internal structural characteristics is relatively scarce.

[0005] Therefore, a new solution is needed to address the above problems. Summary of the Invention

[0006] The purpose of this invention is to provide a method for determining the external accumulation morphology and internal state parameters of a landslide dam. This method utilizes image information collected from the landslide dam to generate point clouds and meshes of complex spatial geometry through SFM geometric reconstruction. Subsequently, a block sampling approach is introduced to discretize the structural features of the landslide dam into blocks of accumulation space, and then geometrically reconstruct the surface contour of the landslide dam after further block division. Through several similar processes, the spatial discretization of the landslide dam can be achieved. Finally, the volume and centroid coordinates of each segment are calculated using the integral of the spatial coordinate system to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a method for determining the external accumulation morphology and internal state parameters of a landslide dam, comprising at least the following steps:

[0008] S1: Image information acquisition, which is carried out after the landslide dam is formed;

[0009] S2: Point cloud and mesh generation, wherein the point cloud and mesh generation is performed on the acquired image information;

[0010] S3: Reconstruct the segmented volume block by block based on S2;

[0011] S4: Mesh assembly based on S3;

[0012] S5: reconstructing the space based on S4;

[0013] S6: accumulating the external form data based on S5, the form data at least including length, width, height and volume;

[0014] S7: obtaining the internal state parameter data based on S5, the internal state parameter at least including porosity and grading.

[0015] Further, the S1 at least includes the following steps:

[0016] Setting the mark points with coordinate information at equidistance at the riverbed position;

[0017] According to the SFM geometric reconstruction, continuously shooting the surface image information of the landslide dam body at different control points, and then performing the discrete segmentation of the dam body by the block sampling method, and after each sampling, the surface image is collected;

[0018] Firstly, the surface image information is shot, and then the dam body is segmented until the last sampling is completed;

[0019] Wherein, the same area between the two continuous images is not less than one fourth of any one image, and at least has 3 same mark points in the same area.

[0020] Further, the S2 at least includes the following steps: setting the actual mark points as the reference, and obtaining the grid and point cloud of the surface contour of the landslide dam body through the SFM reconstruction after the image data fusion and the pose adjustment.

[0021] Further, the S3 at least includes the following steps:

[0022] After S2, in order to ensure that the reconstruction result is more accurate, usually 2-5 initial images are placed in the subsequent grid reconstruction process;

[0023] Through the subsequent point cloud and grid reconstruction process, the segmented surface point cloud and grid before and after different sampling times are obtained.

[0024] Further, the S4 at least includes the following steps: according to S3, multiple segmented images are performed, and the number of times can be set as X, X+1 point clouds and grid data with coordinate information including the river valley are obtained after reconstruction, and the point cloud and the grid are edited and assembled to form the space segmentation surface of the dam body.

[0025] Further, the S5 at least includes the following steps:

[0026] Using the assembled grid file in S4, the space entity, i.e. the dam body model, is generated by the segmentation surface copying and combination;

[0027] Each closed entity is a different segmentation block of the barrier dam, and adjacent spatial entities have the same segmentation surface.

[0028] Further, the S6 at least includes the following steps:

[0029] Initially, the barrier dam is in an undisturbed state, and the image information thereof maximally retains the geometric features and spatial position information of the barrier dam of the landslide;

[0030] Therefore, the initially photographed image is taken as the initial state of the barrier dam of the landslide this time;

[0031] The cross-river width section and the transverse river length section of the initial state are extracted by using the section line, and can be taken as the typical section of the barrier dam of the landslide.

[0032] Further, the S7 at least includes the following steps:

[0033] According to the reconstructed barrier dam model, the surface grid is reconstructed to obtain the surface contour features such as particle distribution, transverse section and longitudinal section;

[0034] In combination with the sampling sequence of the barrier dam of the landslide, the volume and the three-dimensional coordinates of the centroid of each segmentation block are determined;

[0035] According to the mass of each block measured on site, the block porosity is calculated by using the three-phase material composition of the soil, and is taken as the parametric source data of the centroid position;

[0036] Finally, the particle size gradation composition of each block is determined according to the vibration screening result.

[0037] Compared with the prior art, the beneficial effects of the present application are:

[0038] The present application provides a method for measuring the external accumulation morphology (length, width, height and volume) and internal state parameters (porosity and gradation) of the barrier dam of the landslide, image information is collected for SFM geometric reconstruction, and further surface point cloud and grid of the barrier dam of the landslide are generated; the block sampling method is used to obtain different segmentation blocks, and vibration screening and weighing are used to obtain the particle gradation and mass of each segmentation block of the barrier dam of the landslide;

[0039] In order to obtain the volume and centroid coordinates of each block, after the rock-soil body is taken out, SFM geometric reconstruction is used again to construct the surface contour of the barrier dam of the landslide after sampling, Boolean set operation is performed on the surface contour of the barrier dam of the landslide before and after sampling, and the spatial geometric sampling block of each block after sampling is obtained. Repeating the operation several times can disperse the barrier dam structure of the landslide; the volume and centroid coordinates of the segmentation block are calculated by using the defined spatial coordinate system integration, and the porosity of each block is calculated by using the three-phase material composition of the soil.

[0040] The surface profile after the initial SFM geometric reconstruction is taken as the overall volume of the landslide dam, and the data extraction of the river width section and the transverse river length section can be used as the analysis of the typical section characteristics of the landslide dam;

[0041] Thus, the implementation steps of the whole application are simple, the operation method is simple, the data of the spatial geometric body external characteristics, internal porosity ratio and grading of the landslide dam can be obtained, and the data foundation and boundary conditions for quantifying the spatial variation characteristics of the landslide dam are laid. BRIEF DESCRIPTION OF DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0043] Figure 1 The flow chart of the landslide dam structure characteristic parameter measurement method of the present application;

[0044] Figure 2 The reverse modeling flow chart of the SFM geometric reconstruction and block division of the landslide dam of the present application;

[0045] Figure 3 The external profile graph after the SFM geometric reconstruction of the landslide dam of the present application;

[0046] Figure 4 The typical section graph after the SFM geometric reconstruction of the landslide dam of the present application;

[0047] Figure 5 The porosity ratio distribution graph calculated by each sampling block of the landslide dam of the present application;

[0048] Figure 6 The particle grading curve graph of each sampling block of the landslide dam of the present application. DETAILED DESCRIPTION

[0049] The technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all the embodiments. Embodiment one

[0050] Referring to Figure 1 A method for measuring the external accumulation form and internal state parameters of a dam, comprising at least the following steps:

[0051] S1: image information collection, image information collection is carried out after the formation of the landslide dam;

[0052] S2: point cloud and mesh generation, point cloud and mesh generation is carried out in the collected image information;

[0053] S3: piecewise reconstruction of the segmented body based on S2;

[0054] S4: mesh assembly based on S3;

[0055] S5: spatial body reconstruction based on S4;

[0056] S6: external morphological data accumulation based on S5, the morphological data at least including length, width, height and volume;

[0057] S7: internal state parameter data obtained based on S5, the internal state parameters at least including porosity and gradation.

[0058] S1 at least includes the following steps:

[0059] Setting up landmark points with coordinate information at equidistant positions in the riverbed position;

[0060] According to the SFM geometric reconstruction, continuously shooting the landslide dam surface image information at different control points, and then performing block sampling method for dam body discrete segmentation, after each sampling, surface image collection is performed;

[0061] First, shooting surface image information, then segmenting the dam body, until the last sampling is completed;

[0062] Among them, the same area between two consecutive images is not less than one fourth of any one image, and at least has 3 same landmark points in the same area.

[0063] S2 at least includes the following steps: image data needs to set actual landmark points as reference, after image data fusion and pose adjustment, SFM reconstruction is carried out, and the mesh and point cloud of the landslide dam surface contour are obtained.

[0064] S3 at least includes the following steps:

[0065] After S2, in order to ensure that the reconstruction result is more accurate, usually 2-5 initial images are placed in the subsequent mesh reconstruction process;

[0066] Through the subsequent point cloud and mesh reconstruction process, the segmented body surface point cloud and mesh before and after different sampling times are obtained.

[0067] S4 at least includes the following steps: according to the 24 times of segmented image reconstruction in S3, 25 point cloud and mesh data with coordinate information including the river valley are obtained, the point cloud and mesh are edited and assembled, and the landslide dam spatial segmentation surface is formed.

[0068] S5 at least includes the following steps:

[0069] With the assembled grid file in S4, the spatial entity is generated by copying and combining the segmentation surface, that is, the dammed body model;

[0070] Each closed entity is a different segmentation block of the dammed body, and adjacent spatial entities have the same segmentation surface.

[0071] S6 at least includes the following steps:

[0072] Initially, the dammed body is in an undisturbed state, and its image information retains the geometric features and spatial position information of the landslide dammed body to the greatest extent;

[0073] Therefore, the initial image is taken as the initial state of the landslide dammed body this time;

[0074] The cross-river width section and the transverse length section of the initial state are extracted by using the section line, which can be used as the typical section of the landslide dammed body.

[0075] S7 at least includes the following steps:

[0076] According to the reconstructed dammed body model, the surface grid is reconstructed to obtain the surface contour features such as particle distribution, cross section and longitudinal section shape;

[0077] Combined with the sampling sequence of the landslide dammed body block, the volume and the three-dimensional coordinates of the centroid of each segmentation block are determined;

[0078] According to the measured mass of each block on site, the block porosity is calculated by using the three-phase material composition of the soil body, which is used as the parametric source data of the centroid position;

[0079] Finally, according to the vibration sieve analysis results, the particle size gradation composition of each block is determined. Example Two

[0080] Based on the above example one, this example two mainly introduces the physical model test method for quantitatively characterizing the spatial variability of the dammed body material, which details the determination of the volume, centroid spatial coordinates, porosity and particle size gradation of each segmentation block in the discrete process of the landslide dammed body structure, including the following steps:

[0081] Step 1: refer to Figure 2, Image information collection is carried out after the formation of the landslide dam, and mark points with coordinate information are set at equidistant positions in the riverbed. According to the SFM geometric reconstruction, the surface image information of the accumulation body is continuously captured at different control points, and then the dam body is segmented by the block sampling method. After each sampling, the surface image information is collected. Considering the input format of the SFM geometric reconstruction, during the image information collection process, it is necessary to ensure that the same area between two consecutive images is not less than one quarter of any one image, and the same area has at least three same mark points. In this embodiment, the dam body is segmented 24 times.

[0082] Step 2: refer to Figure 2 , Point cloud and mesh generation are carried out after image information collection. The image data needs to set the actual mark points as a reference. After the SFM reconstruction through image data fusion and pose adjustment, the mesh and point cloud of the surface profile of the landslide dam of the segmented block body are obtained 24 times. Combined with the coordinates of the actual mark points and the reconstructed mark points, the effect of the SFM geometric reconstruction is determined.

[0083] Step 3: refer to Figure 2 , Block-by-block reconstruction is carried out after point cloud and mesh generation. After the initial point cloud and mesh reconstruction, in order to ensure that the reconstruction result is more accurate, 2-5 initial images are usually placed in the subsequent mesh reconstruction process. Through the subsequent point cloud and mesh reconstruction process, the surface point cloud and mesh of the segmented body before and after different sampling times are obtained.

[0084] Step 4: refer to Figure 2 , Mesh assembly is carried out after block-by-block reconstruction. According to the 24 times of segmented image reconstruction, 25 point cloud and mesh data including the river valley with coordinate information are obtained. The point cloud and mesh are edited and assembled, and the point cloud and mesh at the same position are taken and set to fuse, until there is only a single mesh surface in a single area, forming the spatial segmentation surface of the landslide dam.

[0085] Step 5: refer to Figure 2 , Spatial body reconstruction is carried out after mesh assembly. Using the assembled mesh file, a closed spatial entity of a single surface is generated by copying and combining the segmentation surface. Each closed entity is a different segmented block body of the landslide dam, and adjacent spatial entities have the same segmentation surface.

[0086] Step 6: refer to Figure 3 , External accumulation morphology data (length, width, height, and volume) is carried out after spatial body reconstruction. Initially, the landslide dam is in an undisturbed state, and the image information retains the geometric features and spatial position information of the landslide dam to the greatest extent. Therefore, the initial image is taken as the initial state of the landslide dam. The riverwise width section and the transverse length section of the initial state are extracted by using the section line, which can be used as the typical section of the landslide dam, refer to Figure 4 .

[0087] Step 7: see Figure 5 , the internal state parameters (porosity and gradation) data are obtained after the spatial body reconstruction; according to the reconstructed dam model, the particle distribution, cross-sectional and longitudinal profile morphology and other surface contour features are obtained by using the reconstructed surface grid. Combined with the sampling sequence of the landslide dam block, the volume and the centroid three-dimensional coordinates of each segmented block are determined. Correspondingly, according to the measured mass of each block on site, the block porosity is calculated by using the three-phase material composition of the soil body, which is used as the parameter source data of the centroid position; finally, according to the vibration sieve analysis results, the particle size gradation composition of each block is determined, see Figure 6 .

[0088] It will be obvious to a person skilled in the art that the application is not limited to the details of the above-described exemplary embodiments, but that the application can be implemented in other concrete forms without departing from the spirit or the essential characteristics of the application. The embodiments should therefore be considered in all respects as illustrative and not restrictive, the scope of the application being defined by the appended claims rather than by the above description, and it is therefore intended that all changes and modifications that fall within the meaning and range of equivalency of the elements of the claims are encompassed by the application. Any reference signs in the claims should not be considered as limiting the claims concerned.

Claims

1. A method for determining the external deposition morphology and internal state parameters of a landslide dam, characterized in that: At least comprising the following steps: S1: image information collection, which is carried out after the formation of the barrier body; S2: point cloud and grid generation, which is carried out in the collected image information; S3: based on S2, the segmented block is reconstructed; S4: based on S3, the grid is assembled; S5: based on S4, the spatial body is reconstructed; S6: based on S5, external morphological data is accumulated, which at least includes length, width, height and volume; S7: based on S5, internal state parameter data is obtained, which at least includes porosity and gradation; The S5 at least comprises the following steps: Using the assembled grid file in S4, the spatial entity is generated by copying and combining the segmentation surface, which is the barrier body model; Each closed entity is a different segmented block of the barrier body, and adjacent spatial entities have the same segmentation surface; The S6 at least comprises the following steps: Initially, the barrier body is in an undisturbed state, and its image information retains the geometric features and spatial position information of the landslide barrier body to the greatest extent; The initial image is taken as the initial state of the landslide barrier body; The cross-river width section and the transverse river length section of the initial state are extracted using the section line, which are used as the typical section of the landslide barrier body; The S7 at least comprises the following steps: According to the reconstructed barrier body model, the particle distribution, cross-sectional and longitudinal morphological surface profile characteristics are obtained using the reconstructed surface grid; Combined with the sampling sequence of the landslide barrier body dam block, the volume and centroid three-dimensional coordinates of each segmented block are determined; According to the measured mass of each block, the block porosity is calculated using the three-phase material composition of the soil body, which is used as the parameter source data of the centroid position; Finally, according to the vibration sieve analysis results, the particle size gradation composition of each block is determined.

2. The method for measuring the external stacking shape and internal state parameters of a damper according to claim 1, characterized in that: The S1 at least comprises the following steps: Setting landmark points with coordinate information at equal intervals at the riverbed position; According to the SFM geometric reconstruction, the surface image information of the landslide barrier body is continuously taken at different control points, and then the dam body is discretely segmented according to the block sampling method; The surface image information is first taken, and then the dam body is segmented until the last sampling is completed; The same area between two consecutive images is not less than one fourth of any one image, and at least has three same landmark points in the same area.

3. The method for measuring the external stacking state of the dam body and the internal state parameter according to claim 2, characterized in that: The S2 at least comprises the following steps: the actual landmark points are set as references in the image data, and the SFM reconstruction after image data fusion and pose adjustment obtains the grid and point cloud of the landslide barrier body surface profile.

4. The method for measuring the external stacking state of the weir and the internal state parameter according to claim 3, characterized in that: The S3 at least comprises the following steps: After S2, 2-5 initial images are placed in the subsequent grid reconstruction process; Through the subsequent point cloud and grid reconstruction process, the segmented body surface point cloud and grid before and after different sampling times are obtained.

5. The method for measuring the external stacking shape and internal state parameters of a weir block according to claim 4, characterized in that: The S4 at least comprises the following steps: according to S3, multiple segmented images are reconstructed, the number of times is set to X, X+1 point cloud and grid data including the river valley with coordinate information are obtained after reconstruction, and the point cloud and grid are edited and assembled to form the spatial segmentation surface of the barrier body.

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