Underground disease body dynamic evolution and three-dimensional visualization method based on CIM

Abstract

The invention relates to an underground disease body dynamic evolution and three-dimensional visualization method based on CIM, and the method comprises the steps: carrying out the slicing of collected multi-source data, and generating a three-dimensional point cloud model, so as to recognize the features of an underground disease body; secondly, screening out points on the surface of the disease body by adopting a point vector method, generating a three-dimensional attribute cloud picture by adopting a space fitting technology, and realizing accurate superposition of a three-dimensional point cloud model and the cloud picture based on a unified coordinate system; based on engineering practice and real-time data, carrying out real-time adjustment on boundary points of the disease body; meanwhile, dynamically generating a three-dimensional point cloud model and an attribute cloud picture so as to realize dynamic evolution of the model; and finally, calculating the volume of the disease body based on plane segmentation and a ray collision method, and performing spatial geometric analysis on the disease body and the underground structure body to evaluate the influence of the disease body on the underground structure, thereby providing decision support for actual engineering application. The method has the advantages of rapidness and high efficiency; accuracy and quality are guaranteed; the application range is wide; and the visualization effect is good.

Description

Technical Field

[0001] The present invention relates to the technical field of digital analysis of underground diseased bodies, and in particular to a CIM-based method for dynamic evolution and three-dimensional visualization of underground diseased bodies. Background Art

[0002] Underground disease bodies refer to unfavorable geological bodies such as cavities, loose soil, and water-rich soil in urban underground spaces, which are formed due to natural factors or human activities. These disease bodies are hidden and sudden, and may cause safety accidents such as road collapse, posing a threat to urban road safety and citizens' travel. With the acceleration of urbanization, the intensity of underground space development and utilization has continued to increase, and the problem of underground disease bodies has become increasingly prominent.

[0003] The underground disease body model can help determine the type, scale and location of the disease body, and provide specific technical guidance and decision-making support for the management and restoration of underground disease bodies. However, at present, underground disease bodies are generally processed in a sliced ​​manner, and a two-dimensional plane is used to express the local underground disease body, which cannot intuitively display the true form of the disease body, affecting the use of subsequent projects. Therefore, it is necessary to parse multi-source data and realize the expression and analysis of the three-dimensional distribution form of complex disease bodies, so as to provide more refined digital results data for underground disease detection, collapse disaster prevention and management. Summary of the invention

[0004] The purpose of the present invention is to provide a CIM-based method for dynamic evolution and three-dimensional visualization of underground diseased bodies in light of the deficiencies of the above-mentioned prior art, to slice the collected multi-source data and generate a three-dimensional point cloud model to identify the characteristics of the underground diseased body; then, the point vector method is used to screen out the points on the surface of the diseased body, and the space fitting technology is used to generate a three-dimensional attribute cloud map, and the three-dimensional point cloud model and the cloud map are accurately superimposed based on a unified coordinate system; based on engineering practice and real-time data, the boundary points of the diseased body are adjusted in real time, and a three-dimensional point cloud model and an attribute cloud map are dynamically generated to realize the dynamic evolution of the model; finally, the volume of the diseased body is calculated based on the plane segmentation and ray collision method, and the diseased body and the underground structure are spatially geometrically analyzed to evaluate the impact of the diseased body on the underground structure, so as to provide decision support for practical engineering applications.

[0005] The purpose of the present invention is achieved by the following technical solutions:

[0006] A method for dynamic evolution and three-dimensional visualization of underground disease bodies based on CIM, characterized in that the method comprises the following steps:

[0007] S1. Obtain a three-dimensional point cloud model of the underground or the surface of an object;

[0008] S2. Based on the three-dimensional point cloud model, point cloud data of the surface of the diseased body is screened out by point cloud vector method;

[0009] S3, based on the point cloud data of the surface of the diseased body, a nonlinear difference algorithm is used to achieve spatial fitting of the diseased body attributes and cloud map display;

[0010] S4. Based on engineering practice and real-time data, the boundary points of the diseased body are adjusted in real time, and a three-dimensional point cloud model and an attribute cloud map are dynamically generated;

[0011] S5. Calculate the volume of the diseased body based on plane segmentation and ray collision method;

[0012] S6. Integrate the three-dimensional model of the damaged body and the underground structure model based on a unified coordinate system, and conduct spatial geometric analysis to evaluate the impact of the damaged body on the underground structure.

[0013] In step S1, physical data of the underground or the surface of an object are obtained through geophysical exploration equipment (such as digital seismographs, ground penetrating radars, three-dimensional laser scanners, etc.), which usually include response information of reflected waves, electromagnetic waves, sound waves, etc. Then, the processed data is sliced, and the spatial data is divided into several slices along the detection direction according to certain rules. The depth of each slice remains consistent, and the slice contains several data points. The amount of data in each slice is the same. The point data contains information such as the horizontal coordinate (X), the vertical coordinate (Y), the depth (Z), and attributes. The point cloud data is a collection of a series of discrete points in space. Finally, a three-dimensional point cloud model is generated based on the parsed geophysical exploration data.

[0014] In step S2, based on the three-dimensional point cloud data, the point cloud on the surface of the diseased body is screened out from the massive point cloud data by the point cloud vector method. These point clouds can not only reveal the morphological characteristics of the disease, but also reflect the development trend of the disease and the potential damage mode.

[0015] First, the point cloud needs to be preprocessed to remove outliers or noise points in the point cloud. Then, for each point in the point cloud, search for its K nearest neighboring points and calculate the local plane of these points in the least squares sense. For each point, calculate the angle between its normal vector and the neighboring points. If the angle is greater than a certain threshold, the point is considered to be a boundary point.

[0016] In step S3, a nonlinear interpolation algorithm is used based on the point cloud data of the surface of the diseased body to achieve spatial fitting of the diseased body attributes and cloud map display. At the same time, the refined three-dimensional point cloud model is used as the information carrier, and the cloud map and the three-dimensional point cloud model are accurately superimposed based on a unified coordinate system.

[0017] In step S4, based on engineering practice and real-time data, the boundary points of the diseased body are adjusted in real time, and a three-dimensional point cloud model and attribute cloud map are dynamically generated to enable the model to be adaptively updated when the diseased body environment changes, ensuring its accuracy and practicality. Boundary points can be moved and deleted in batches. After the modification is completed, click OK, and the three-dimensional point cloud model and attribute cloud map will be recreated. Through this dynamic evolution mechanism, the model can reflect the most realistic state of the underground diseased body. This dynamic adjustment not only improves the accuracy of the model, but also enhances its application value in engineering decision-making and risk assessment.

[0018] In step S5, the projection surface of the diseased body is divided into a number of quadrilateral areas at a certain interval, and the center point of the area is calculated according to the four corner points of the area; then the ray collision method is used to obtain the points on the upper and lower surfaces of the diseased body at the center point respectively, the height of the diseased body at the center point is obtained by subtracting the elevations of the two points, the area of ​​the quadrilateral area multiplied by the height is the volume of the area, and the sum of all volumes is the volume of the diseased body.

[0019] In step S6, the underground engineering design scheme and the construction scheme are compared and selected based on the analysis results of the three-dimensional defect body model to provide decision support for actual engineering applications.

[0020] The advantages of the present invention are:

[0021] 1) Fast and efficient: It realizes the processing and analysis of multi-source data, converts geophysical data into three-dimensional point clouds, and improves the efficiency of model processing.

[0022] 2) Accuracy and quality assurance: geophysical data of different levels, sources and precision can be used to express underground disease bodies, thus improving the accuracy and rationality of the model.

[0023] 3) Wide range of applications: The three-dimensional underground disease model contains a lot of information, which can not only evaluate the impact of the disease body on the underground structure, but also can be used for other subsequent applications.

[0024] 4) Good visualization effect: The underground disease body is displayed in three-dimensional form to facilitate communication among all parties involved in the project. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is the slice processing diagram of underground disease volume data;

[0026] Figure 2 This is a schematic diagram for calculating the volume of underground diseased bodies;

[0027] Figure 3 It is a flow chart of the working principle of the present invention;

[0028] Figure 4The three-dimensional point cloud data effect diagram of the underground diseased body provided by the embodiment of the present invention;

[0029] Figure 5 A three-dimensional visualization diagram (thickness cloud diagram) of underground diseased bodies according to an embodiment of the present invention;

[0030] Figure 6 A three-dimensional visualization map (depth cloud map) of underground diseased bodies according to an embodiment of the present invention;

[0031] Figure 7 This is a diagram of the integration of the loose belt and the pile foundation model when the embodiment provided by the present invention is applied. DETAILED DESCRIPTION

[0032] The features of the present invention and other related features are further described in detail below through embodiments in conjunction with the accompanying drawings to facilitate understanding by those skilled in the art:

[0033] Example: Figures 1 to 7 As shown, the CIM-based method for dynamic evolution and three-dimensional visualization of underground disease bodies in this embodiment includes the following steps:

[0034] (1) Analyze multi-source data and generate a 3D point cloud model:

[0035] The detection data of the loose zone is obtained through the digital seismograph, including response information such as reflection waves, and the collected raw data is processed by noise reduction and filtering, and then the processed data is further analyzed to identify and mark the characteristics of the underground diseased body. Finally, three-dimensional point cloud data is generated based on the analyzed geophysical data, such as Figure 4 shown.

[0036] (2) Use the point vector method to filter out the point cloud on the surface of the diseased body:

[0037] First, the point cloud is preprocessed to remove outliers in the point cloud, such as points with large deviations. Then, for each point in the point cloud, its K nearest neighboring points are searched, and the local planes of these points in the least squares sense are calculated. For each point, the angle between its normal vector and the neighboring points is calculated. If the angle is greater than a certain threshold, the point is considered a boundary point.

[0038] (3) Generate three-dimensional attribute cloud map using spatial fitting technology:

[0039] Based on the point cloud data of the surface of the diseased body, a nonlinear interpolation algorithm is used to achieve spatial fitting of the diseased body attributes and cloud map display. At the same time, the refined three-dimensional point cloud model is used as the information carrier, and the cloud map and the three-dimensional point cloud model are accurately superimposed based on a unified coordinate system, such as Figure 5 and Figure 6 As shown, Figure 5 The legend on the right shows the thickness of the three-dimensional disease body. Figure 6 The legend on the right shows the depth of the three-dimensional disease body from the bottom of the pit, in meters.

[0040] In this embodiment, the nonlinear interpolation formula is:

[0041] p i (t) = A 1 +A 2 (xx i )+A 3 (xx i ) 2 ;

[0042] In the formula, A 1 , A 2 , A 3 is the coefficient of the expression and is in the form of a three-dimensional vector; x is a node, x i is the starting point of the i-th segment.

[0043] (4) Model adjustment and dynamic update:

[0044] Based on engineering practice and real-time data, the boundary points of the diseased body are adjusted in real time, and the 3D point cloud model and attribute cloud map are dynamically generated until the actual needs of the project are met. Boundary points can be moved and deleted in batches. After the modification is completed, click OK, and the 3D point cloud model and attribute cloud map will be recreated.

[0045] (5) Calculate the volume of the diseased body based on plane segmentation and ray collision method:

[0046] The projection surface of the diseased body is divided into several quadrilateral areas at intervals of 10m, and the center point of the area is calculated based on the four corner points of the area. Then the ray collision method is used to obtain the points on the upper and lower surfaces of the diseased body at the center point. The difference between the two points is the height of the diseased body at the center point. The area of ​​the quadrilateral area multiplied by the height is the volume of the area, and the sum of all volumes is the volume of the diseased body.

[0047] (6) Model integration and application:

[0048] Based on the 3D graphics platform and the unified coordinate system, the loose belt model and the pile foundation model are integrated. The cast-in-place piles that pass through the loose belt are screened out through the collision analysis algorithm and distinguished by different colors, such as Figure 7 Finally, according to the results of the collision analysis, the underground engineering design scheme and construction scheme are compared and selected to provide decision support for actual engineering applications.

[0049] Although the above embodiments have described in detail the concepts and embodiments of the present invention with reference to the accompanying drawings, ordinary technicians in this field can recognize that various improvements and changes can still be made to the present invention without departing from the scope of the claims, so they are not described one by one here.

Claims

1. A CIM-based method for dynamic evolution and three-dimensional visualization of underground disease bodies, characterized by: The method comprises the following steps: S1. Obtain a three-dimensional point cloud model of the underground or the surface of an object; S2. Based on the three-dimensional point cloud model, point cloud data of the surface of the diseased body is screened out by point cloud vector method; S3, based on the point cloud data of the surface of the diseased body, a nonlinear difference algorithm is used to achieve spatial fitting of the diseased body attributes and cloud map display; S4. Based on engineering practice and real-time data, the boundary points of the diseased body are adjusted in real time, and a three-dimensional point cloud model and an attribute cloud map are dynamically generated; S5. Calculate the volume of the diseased body based on plane segmentation and ray collision method; S6. Integrate the three-dimensional model of the damaged body and the underground structure model based on a unified coordinate system, and conduct spatial geometric analysis to evaluate the impact of the damaged body on the underground structure.

2. The method for dynamic evolution and three-dimensional visualization of underground disease bodies based on CIM according to claim 1, characterized in that: In step S1, geophysical data of the underground or the surface of an object is obtained by geophysical equipment; the processed geophysical data is divided into a number of slices along the detection direction according to certain rules, each slice contains a number of data points with the same data volume, and the three-dimensional point cloud model is generated according to the parsed geophysical data.

3. The method for dynamic evolution and three-dimensional visualization of underground disease bodies based on CIM according to claim 2, characterized in that: The data of the data point includes the abscissa, ordinate, depth and attributes of the data point in the slice.

4. The method for dynamic evolution and three-dimensional visualization of underground disease bodies based on CIM according to claim 1, characterized in that: In step S2, the point cloud data of the surface of the diseased body is preprocessed to remove outliers or noise points in the point cloud. Then, for each point in the point cloud data, its K nearest neighboring points are searched, and the local planes of these points in the least squares sense are calculated. For each point, the angle between its normal vector and the neighboring points is calculated; if the angle is greater than a certain threshold, the point is considered to be a boundary point on the surface of the diseased body.

5. The method for dynamic evolution and three-dimensional visualization of underground disease bodies based on CIM according to claim 1, characterized in that: In step S3, the three-dimensional point cloud model is used as an information carrier, and the cloud map and the three-dimensional point cloud model are accurately superimposed based on a unified coordinate system.

6. The method for dynamic evolution and three-dimensional visualization of underground disease bodies based on CIM according to claim 1, characterized in that: In step S5, the projection surface of the diseased body is divided into a number of quadrilateral areas at a certain interval, and the center point of the area is calculated according to the four corner points of the area; then the ray collision method is used to obtain the points on the upper and lower surfaces of the diseased body at the center point respectively, the height of the diseased body at the center point is obtained by subtracting the elevations of the two points, the area of ​​the quadrilateral area multiplied by the height is the volume of the area, and the sum of all volumes is the volume of the diseased body.

7. The method for dynamic evolution and three-dimensional visualization of underground disease bodies based on CIM according to claim 1, characterized in that: In step S6, the underground engineering design scheme and the construction scheme are compared and selected based on the analysis results of the three-dimensional defect body model to provide decision support for actual engineering applications.

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