Technology for quantitatively characterizing 3D particle morphology of granite weathered soil body

Abstract

The invention relates to the technical field of geotechnical engineering, and particularly discloses a granite weathered soil 3D particle morphology quantitative characterization technology which comprises a three-dimensional scanning subsystem, an intelligent image processing subsystem, a morphological parameter calculation subsystem, a data mining and machine learning subsystem, a virtual simulation and optimization design subsystem and a user interaction interface subsystem. The three-dimensional scanning subsystem is used for acquiring three-dimensional form information of granite weathered soil particles by using a high-precision three-dimensional scanning technology; according to the technology for quantitatively characterizing the 3D particle morphology of the granite weathered soil body, the particle morphology can be presented in a high-precision mode, researchers can observe and analyze the fine structures and characteristics of the particles more intuitively, the behaviors of the particles in a complex environment can be accurately predicted, and the analysis accuracy of the particles is improved. Reliable reference basis is provided for engineering application, potential risks can be evaluated in advance, and corresponding countermeasures can be formulated.

Description

Technical Field

[0001] The invention belongs to the field of geotechnical engineering technology, and in particular relates to a technology for quantitatively characterizing the 3D particle morphology of weathered granite soil. Background Art

[0002] The technology of quantitatively characterizing the 3D particle morphology of weathered granite soil mainly relies on high-precision CT scanning technology and image processing technology to obtain the three-dimensional morphological information of weathered granite soil particles, and uses methods such as spherical harmonic function sequence to achieve accurate reconstruction of the three-dimensional morphology, and then calculates the morphological characterization parameters such as the surface area, surface curvature, three-dimensional size, three-dimensional sphericity, roundness and elongation of the particles.

[0003] Although the existing 3D particle morphology technology has made certain progress in characterizing weathered granite soil, it still has the disadvantages of insufficient precision, difficulty in intuitively displaying the fine structure of particles, and inability to accurately predict the behavior of particles in complex environments. This limits its in-depth research and wide application in engineering applications, and needs to be improved. To this end, a technology for quantitatively characterizing the 3D particle morphology of weathered granite soil is proposed. Summary of the invention

[0004] The purpose of the present invention is to provide a technology for quantitatively characterizing the 3D particle morphology of weathered granite soil to solve the problems raised in the above background technology.

[0005] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: a technology for quantitatively characterizing the 3D particle morphology of weathered granite soil, including a three-dimensional scanning subsystem, an intelligent image processing subsystem, a morphological parameter calculation subsystem, a data mining and machine learning subsystem, a virtual simulation and optimization design subsystem, and a user interaction interface subsystem. The three-dimensional scanning subsystem uses high-precision three-dimensional scanning technology to obtain the three-dimensional morphological information of weathered granite soil particles; the intelligent image processing subsystem uses image processing technology to pre-process, segment, and extract features of the three-dimensional images obtained by the three-dimensional scanning subsystem; the morphological parameter calculation subsystem, based on the intelligent image processing The data provided by the subsystem is used to calculate various morphological characterization parameters of granite weathered soil particles, such as volume, surface area, sphericity, roundness, and elongation; the data mining and machine learning subsystem uses data mining and machine learning techniques to conduct in-depth analysis and pattern recognition on the morphological characterization parameters provided by the morphological parameter calculation subsystem; the virtual simulation and optimization design subsystem performs virtual simulation and optimization design based on the data and analysis results provided by the morphological parameter calculation subsystem and the data mining and machine learning subsystem; the user interaction interface subsystem is used to provide users with an intuitive and easy-to-use interactive interface, and provides operations such as inputting commands, viewing results, and setting and modifying parameters.

[0006] Preferably, the three-dimensional scanning subsystem includes a scanning device unit, a data acquisition unit, and a data preprocessing unit. The scanning device unit is responsible for performing three-dimensional scanning, and the scanning device unit is a CT scanner or a laser scanner; the data acquisition unit is responsible for collecting data from the scanning device and converting it into a format that can be used for subsequent processing; the data preprocessing unit is used to perform preliminary processing on the collected data.

[0007] Preferably, the intelligent image processing subsystem includes an image segmentation unit, a feature extraction unit, and an image enhancement unit. The image segmentation unit is used to segment the scanned image into separate particle images; the feature extraction unit is used to extract the morphological features of the particles from the segmented image; and the image enhancement unit is used to enhance the image to improve the accuracy of feature extraction.

[0008] Preferably, the morphological parameter calculation subsystem includes a volume calculation unit, a surface area calculation unit, and a morphological characterization parameter calculation unit, wherein the volume calculation unit is used to calculate the volume of particles; the surface area calculation unit is used to calculate the surface area of ​​particles; and the morphological characterization parameter calculation unit is used to calculate characterization parameters.

[0009] Preferably, the data mining and machine learning subsystem includes a pattern recognition unit and an association analysis unit, wherein the pattern recognition unit classifies and identifies particles using a machine learning algorithm; and the association analysis unit is used to discover associations and patterns between morphological parameters.

[0010] Preferably, the virtual simulation and optimization design subsystem includes a virtual model building unit, a simulation unit, and an optimization design unit, wherein the virtual model building unit builds a virtual model of the particles based on the scanned and processed data; the simulation unit is used to simulate the behavior of the particles under different conditions; and the optimization design unit is used to optimize the design of the particles according to the simulation results.

[0011] Preferably, the rendering equation in the virtual simulation and optimization design subsystem is, L(o,ω)=L_e(o,ω)+∫f_rω_iL_i(ω_i,n)L_i(o,ω_i)n·ω_idω_i, wherein L(o,ω) is the radiation intensity in the direction ω at the camera position o, L_e(o,ω) is the radiation intensity from the light source in the scene, f_r is the reflection function of the surface, n is the surface normal, L_i is the radiation intensity from the light source to the surface, and ω_i is the incident direction of the light; the interaction formula is, I_t=F(I_t-1,I_t-2,...,I_t-n), wherein I_t represents the input state of the user at time t; F is an interaction function used to describe the user's operation and feedback effect on the virtual environment.

[0012] Preferably, the user interaction interface subsystem includes an input unit, a display unit, and a control unit, wherein the input unit is used for the user to input instructions and parameters; the display unit is used to display processing results and simulation optimization design results; and the control unit is responsible for the control and interaction logic of the entire interface.

[0013] In summary, compared with the prior art, the present invention has the following beneficial effects:

[0014] 1. Through the 3D scanning subsystem and the intelligent image processing subsystem, this technology can acquire and process the 3D morphological information of granite weathered soil particles in a high-precision manner, allowing researchers to observe and analyze the subtle structure and characteristics of particles more intuitively. For example, through high-resolution 3D scanning, the texture, pores and complex internal structure of the particle surface can be clearly presented. The segmentation and feature extraction functions in the intelligent image processing can accurately separate the particles from the background and extract key morphological features, such as sphericity and roundness. This provides a solid foundation for in-depth research on the physical properties and engineering behavior of granite weathered soil, helps to reveal the relationship between particle morphology and mechanical properties, permeability, etc., and provides more accurate data support for engineering design and geological research.

[0015] 2. The pattern recognition unit uses machine learning algorithms to classify and identify particles, which can quickly and accurately distinguish different types of particles, providing convenience for geological exploration and engineering classification. The association analysis unit can discover the associations and patterns between morphological parameters, such as the relationship between volume, surface area and particle strength, or the relationship between sphericity and particle fluidity, which helps to establish a more accurate mathematical model, predict the behavior of particles under different conditions, and provide a reliable reference for engineering applications.

[0016] 3. The virtual simulation and optimization design subsystem can perform high-precision virtual simulation and optimization design based on the data and analysis results provided by the previous subsystems. The virtual model construction unit can build a realistic virtual model of particles, allowing researchers to conduct various experiments and analyses in a virtual environment without actually operating physical particles, saving time and cost. The simulation unit can simulate the behavior of particles under different conditions, such as deformation under different stress states, movement in water flow, etc., to help researchers assess potential risks in advance. The optimization design unit can optimize the design of particles based on the simulation results, for example, by adjusting the shape, size and other parameters of the particles, the engineering performance of the particles can be improved to meet specific engineering needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a structural diagram of the present invention. DETAILED DESCRIPTION

[0018] 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.

[0019] See also Figure 1 , the present invention provides a technical solution:

[0020] A technology for quantitatively characterizing the 3D particle morphology of weathered granite soil, including a 3D scanning subsystem, an intelligent image processing subsystem, a morphological parameter calculation subsystem, a data mining and machine learning subsystem, a virtual simulation and optimization design subsystem, and a user interaction interface subsystem. The 3D scanning subsystem uses high-precision 3D scanning technology to obtain the 3D morphological information of weathered granite soil particles; the intelligent image processing subsystem uses image processing technology to pre-process, segment, and extract features of the 3D images obtained by the 3D scanning subsystem; the morphological parameter calculation subsystem calculates the morphological parameters based on the data provided by the intelligent image processing subsystem. Various morphological characterization parameters of granite weathered soil particles, such as volume, surface area, sphericity, roundness, and elongation; the data mining and machine learning subsystem, which uses data mining and machine learning techniques to conduct in-depth analysis and pattern recognition on the morphological characterization parameters provided by the morphological parameter calculation subsystem; the virtual simulation and optimization design subsystem, which performs virtual simulation and optimization design based on the data and analysis results provided by the morphological parameter calculation subsystem and the data mining and machine learning subsystem; the user interaction interface subsystem, which is used to provide users with an intuitive and easy-to-use interactive interface, and provides operations such as inputting commands, viewing results, and setting and modifying parameters.

[0021] The three-dimensional scanning subsystem includes a scanning device unit, a data acquisition unit, and a data preprocessing unit. The scanning device unit is responsible for three-dimensional scanning, and the scanning device unit is a CT scanner or a laser scanner; the data acquisition unit is responsible for collecting data from the scanning device and converting it into a format that can be used for subsequent processing; the data preprocessing unit is used to perform preliminary processing on the collected data.

[0022] The intelligent image processing subsystem includes an image segmentation unit, a feature extraction unit, and an image enhancement unit. The image segmentation unit is used to segment the scanned image into separate particle images; the feature extraction unit is used to extract the morphological features of the particles from the segmented image; and the image enhancement unit is used to enhance the image to improve the accuracy of feature extraction.

[0023] The morphological parameter calculation subsystem includes a volume calculation unit, a surface area calculation unit, and a morphological characterization parameter calculation unit. The volume calculation unit is used to calculate the volume of the particles; the surface area calculation unit is used to calculate the surface area of ​​the particles; and the morphological characterization parameter calculation unit is used to calculate the characterization parameters.

[0024] The data mining and machine learning subsystem includes a pattern recognition unit and an association analysis unit. The pattern recognition unit uses a machine learning algorithm to classify and identify particles; the association analysis unit is used to discover the association and rules between morphological parameters.

[0025] The virtual simulation and optimization design subsystem includes a virtual model building unit, a simulation unit, and an optimization design unit. The virtual model building unit builds a virtual model of the particles based on the scanned and processed data; the simulation unit is used to simulate the behavior of the particles under different conditions; and the optimization design unit is used to optimize the design of the particles according to the simulation results.

[0026] The rendering equation in the virtual simulation and optimization design subsystem is, L(o,ω)=L_e(o,ω)+∫f_rω_iL_i(ω_i,n)L_i(o,ω_i)n·ω_idω_i, where L(o,ω) is the radiation intensity in the direction ω at the camera position o, L_e(o,ω) is the radiation intensity from the light source in the scene, f_r is the reflection function of the surface, n is the surface normal, L_i is the radiation intensity from the light source to the surface, and ω_i is the incident direction of the light; the interaction formula is, I_t=F(I_t-1,I_t-2,...,I_t-n), where I_t represents the user's input state at time t; F is the interaction function, which is used to describe the user's operation and feedback effect on the virtual environment.

[0027] The user interaction interface subsystem includes an input unit, a display unit, and a control unit. The input unit is used for the user to input instructions and parameters; the display unit is used to display processing results and simulation optimization design results; and the control unit is responsible for the control and interaction logic of the entire interface.

[0028] Working principle:

[0029] The technology is mainly composed of a 3D scanning subsystem, an intelligent image processing subsystem, a morphological parameter calculation subsystem, a data mining and machine learning subsystem, a virtual simulation and optimization design subsystem, and a user interaction interface subsystem;

[0030] First, the scanning device unit (such as a CT scanner or a laser scanner) in the 3D scanning subsystem performs high-precision 3D scanning on the granite weathered soil particles. The data acquisition unit collects data from the scanning device and converts it into a format that can be used for subsequent processing. Then, the data preprocessing unit performs preliminary processing on the collected data to remove noise, correct deviations, etc., to provide high-quality raw data for subsequent image processing.

[0031] The intelligent image processing subsystem starts to work. The image segmentation unit segments the scanned image into separate particle images in order to analyze individual particles. The feature extraction unit extracts the morphological features of the particles from the segmented images, such as the particle outline and texture. The image enhancement unit enhances the image and improves the accuracy of feature extraction by adjusting contrast, sharpening, and other operations.

[0032] The morphological parameter calculation subsystem performs calculations based on the data provided by the intelligent image processing subsystem. The volume calculation unit calculates the volume of the particles through a specific algorithm, the surface area calculation unit calculates the surface area of ​​the particles, and the morphological characterization parameter calculation unit further calculates the sphericity, roundness, elongation and other characterization parameters. These parameters can quantitatively describe the shape characteristics of the particles.

[0033] The pattern recognition unit in the data mining and machine learning subsystem uses machine learning algorithms to classify and identify particles and divide them into different types according to their morphological characteristics. The association analysis unit deeply mines the data to find the associations and patterns between morphological parameters, such as finding the relationship between volume and surface area, or the potential connection between specific shape parameters and the mechanical properties of particles.

[0034] The virtual simulation and optimization design subsystem works based on the data and analysis results provided by the previous two subsystems. The virtual model construction unit constructs a realistic virtual model of the particles based on the scanned and processed data. The rendering equation L(o,ω)=L_e(o,ω)+∫f_rω_iL_i(ω_i,n)L_i(o,ω_i)n·ω_idω_i is used to determine the radiation intensity in the camera position and direction, thereby achieving high-quality rendering of the virtual model and making it more visually realistic. The simulation unit simulates the behavior of particles under different conditions, such as under different stresses, The optimization design unit optimizes the design of particles according to the simulation results, such as adjusting the shape, size and other parameters of the particles to meet specific engineering requirements. The interaction formula I_t=F(I_t-1, I_t-2,..., I_t-n) describes the interaction process between the user and the virtual environment. The user inputs instructions and parameters through the input unit. The control unit is responsible for the control and interaction logic of the entire interface. The display unit displays the processing results and simulation optimization design results, which is convenient for users to intuitively understand the morphological characteristics and performance of the particles and set and modify parameters.

[0035] Through the collaborative work of this series of subsystems, this technology can achieve quantitative characterization, in-depth analysis, virtual simulation and optimization design of the 3D particle morphology of weathered granite soil, providing strong technical support for geotechnical engineering, geological research and other fields.

[0036] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A technology for quantitatively characterizing the 3D particle morphology of weathered granite soil, comprising a 3D scanning subsystem, an intelligent image processing subsystem, a morphological parameter calculation subsystem, a data mining and machine learning subsystem, a virtual simulation and optimization design subsystem, and a user interaction interface subsystem, characterized in that: The 3D scanning subsystem uses high-precision 3D scanning technology to obtain the 3D morphological information of granite weathered soil particles; the intelligent image processing subsystem uses image processing technology to pre-process, segment, and extract features of the 3D images obtained by the 3D scanning subsystem; The morphological parameter calculation subsystem calculates various morphological characterization parameters of granite weathered soil particles, such as volume, surface area, sphericity, roundness, and elongation, based on the data provided by the intelligent image processing subsystem; the data mining and machine learning subsystem uses data mining and machine learning techniques to conduct in-depth analysis and pattern recognition on the morphological characterization parameters provided by the morphological parameter calculation subsystem; the virtual simulation and optimization design subsystem performs virtual simulation and optimization design based on the data and analysis results provided by the morphological parameter calculation subsystem and the data mining and machine learning subsystem; The user interaction interface subsystem is used to provide users with an intuitive and easy-to-use interactive interface, providing operations for inputting commands, viewing results, and setting and modifying parameters.

2. The quantitative characterization technology for 3D particle morphology of weathered granite soil according to claim 1 is characterized in that: The three-dimensional scanning subsystem includes a scanning device unit, a data acquisition unit, and a data preprocessing unit. The scanning device unit is responsible for three-dimensional scanning, and the scanning device unit is a CT scanner or a laser scanner; the data acquisition unit is responsible for collecting data from the scanning device and converting it into a format that can be used for subsequent processing; the data preprocessing unit is used to perform preliminary processing on the collected data.

3. The quantitative characterization technology for 3D particle morphology of weathered granite soil according to claim 1 is characterized in that: The intelligent image processing subsystem includes an image segmentation unit, a feature extraction unit, and an image enhancement unit. The image segmentation unit is used to segment the scanned image into separate particle images; the feature extraction unit is used to extract the morphological features of the particles from the segmented image; The image enhancement unit is used to perform enhancement processing on the image to improve the accuracy of feature extraction.

4. The quantitative characterization technology for 3D particle morphology of weathered granite soil according to claim 1 is characterized in that: The morphological parameter calculation subsystem includes a volume calculation unit, a surface area calculation unit, and a morphological characterization parameter calculation unit. The volume calculation unit is used to calculate the volume of the particles; the surface area calculation unit is used to calculate the surface area of ​​the particles; The morphological characterization parameter calculation unit is used to calculate the characterization parameters.

5. The quantitative characterization technology for 3D particle morphology of weathered granite soil according to claim 1 is characterized in that: The data mining and machine learning subsystem includes a pattern recognition unit and an association analysis unit. The pattern recognition unit uses a machine learning algorithm to classify and identify particles; the association analysis unit is used to discover the association and rules between morphological parameters.

6. The technology for quantitatively characterizing 3D particle morphology of weathered granite soil according to claim 1, characterized in that: The virtual simulation and optimization design subsystem includes a virtual model building unit, a simulation unit, and an optimization design unit. The virtual model building unit builds a virtual model of the particles based on the scanned and processed data; the simulation unit is used to simulate the behavior of the particles under different conditions; and the optimization design unit is used to optimize the design of the particles according to the simulation results.

7. The quantitative characterization technology for 3D particle morphology of weathered granite soil according to claim 6 is characterized in that: The rendering equation in the virtual simulation and optimization design subsystem is, L(o,ω)=L_e(o,ω)+∫f_rω_iL_i(ω_i,n)L_i(o,ω_i)n·ω_idω_i, where L(o,ω) is the radiation intensity in the direction ω at the camera position o, L_e(o,ω) is the radiation intensity from the light source in the scene, f_r is the reflection function of the surface, n is the surface normal, L_i is the radiation intensity from the light source to the surface, and ω_i is the incident direction of the light; the interaction formula is, I_t=F(I_t-1,I_t-2,...,I_t-n), where I_t represents the input state of the user at time t; F is the interaction function, which is used to describe the user's operation and feedback effect on the virtual environment.

8. The technology for quantitatively characterizing 3D particle morphology of weathered granite soil according to claim 1, characterized in that: The user interaction interface subsystem includes an input unit, a display unit, and a control unit. The input unit is used for the user to input instructions and parameters; the display unit is used to display processing results and simulation optimization design results; and the control unit is responsible for the control and interaction logic of the entire interface.

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