Visual measurement device and method for global strain field of rock-soil sample

Abstract

The invention discloses a rock-soil sample global strain field vision measurement device and method, and relates to the field of geotechnical engineering testing, and multiple groups of industrial cameras of an image acquisition module are used for shooting multi-angle images of a rock-soil sample in a pressure chamber; the mechanical adjustment modules are in one-to-one correspondence with the industrial cameras; in the mechanical adjustment module, a left-right movement adjustment device and a front-back movement adjustment device are arranged on a cross fine adjustment platform; the cross fine adjustment platform is arranged on the vertical slide rail; the left-right movement adjusting device and the front-back movement adjusting device are used for moving the industrial camera in the horizontal direction; the vertical slide rail is used for moving the industrial camera in the vertical direction; the cross fine adjustment platform is used for adjusting the industrial camera in the horizontal direction; the image processing module is used for carrying out preprocessing according to the image shot by the industrial camera and carrying out three-dimensional reconstruction on the rock-soil sample; and the strain field analysis module is used for carrying out strain field analysis according to the rock-soil sample subjected to three-dimensional reconstruction. According to the invention, the measurement accuracy can be improved.

Description

Technical Field

[0001] This application relates to the field of geotechnical engineering testing, and in particular to a visual measurement device and method for the full-domain strain field of geotechnical samples. Background Technology

[0002] Triaxial testing of soil samples is a core experimental method for studying the shear strength, deformation characteristics, and constitutive relations of soil. Local and global deformation of soil samples plays a crucial role in understanding the anisotropic and nonlinear characteristics of soil materials. Analyzing non-uniform deformation, shear band evolution, and localized failure characteristics of soil is also essential for theoretical modeling and numerical simulation in soil mechanics. Traditional triaxial apparatuses typically rely on contact sensors, which can only acquire the total volume change and total vertical deformation of the soil sample. They have significant limitations in measuring local and global deformation of soil samples and struggle to capture the dynamic evolution of non-uniform deformation and shear bands.

[0003] With the development of computer vision technology and the widespread use of digital cameras, digital image measurement technology has gradually attracted attention. Therefore, how to achieve precise measurement and intelligent analysis of the full-domain strain field of soil samples under non-contact conditions is a technical problem that urgently needs to be solved in the field of geotechnical engineering testing. Summary of the Invention

[0004] The purpose of this application is to provide a visual measurement device and method for the global strain field of soil and rock samples, which can improve the accuracy of the measurement.

[0005] To achieve the above objectives, this application provides the following solution.

[0006] In a first aspect, this application provides a visual measurement device for the full-domain strain field of a soil and rock sample, comprising: an image acquisition module, a mechanical adjustment module, an image processing module, and a strain field analysis module; the image acquisition module includes multiple sets of industrial cameras; the industrial cameras are evenly distributed outside the pressure chamber; the industrial cameras are used to capture images of the soil and rock sample from multiple angles inside the pressure chamber; the mechanical adjustment module corresponds one-to-one with each of the industrial cameras; the mechanical adjustment module includes a cross-shaped fine-tuning platform, a left-right movement adjustment device, a front-back movement adjustment device, and a vertical slide rail; the left-right movement adjustment device and the front-back movement adjustment device are both mounted on the cross-shaped fine-tuning platform; The cross-shaped fine-tuning platform is mounted on the vertical slide rail; the left-right movement adjustment device and the front-back movement adjustment device are used to move the industrial camera horizontally; the vertical slide rail is used to move the industrial camera vertically; the cross-shaped fine-tuning platform is used to adjust the industrial camera horizontally; the industrial camera, the image processing module, and the strain field analysis module are connected in sequence; the image processing module is used to preprocess the images captured by the industrial camera and perform three-dimensional reconstruction of the soil and rock samples; the strain field analysis module is used to perform strain field analysis on the three-dimensionally reconstructed soil and rock samples.

[0007] In one embodiment, the mechanical adjustment module further includes: a vertical support; the vertical slide rail is disposed on the vertical support.

[0008] In one embodiment, the mechanical adjustment module further includes a vertical slide rail stopping device; the vertical slide rail stopping device is used to fix the cross fine-tuning platform on the vertical slide rail stopping device.

[0009] In one embodiment, the mechanical adjustment module further includes a support base; the support base is used to fix the vertical support; the support base is provided with a straight groove; the straight groove is used to fix it to the test bench table.

[0010] In one embodiment, the visual measurement device for the global strain field of the soil and rock sample further includes an optical environment module; the optical environment module is disposed outside the pressure chamber; the optical environment module is used to provide supplemental lighting for the pressure chamber.

[0011] In one embodiment, the visual measurement device for the global strain field of the soil and rock sample further includes a data management module; the data management module is connected to the image acquisition module and the image processing module respectively.

[0012] In one embodiment, the number of industrial cameras is six; the six industrial cameras are evenly arranged outside the pressure chamber at a 60° angle.

[0013] In one embodiment, the pressure chamber is made of quartz glass.

[0014] In one embodiment, the optical environment module includes multiple sets of LED fill light strips.

[0015] Secondly, this application provides a visual measurement method for the global strain field of a soil and rock sample. This method is applied to the aforementioned visual measurement device for the global strain field of a soil and rock sample. The method includes: acquiring a three-dimensionally reconstructed soil and rock sample; the three-dimensionally reconstructed soil and rock sample is obtained by preprocessing and three-dimensional reconstruction of multi-angle images of the soil and rock sample captured by an industrial camera; processing the three-dimensionally reconstructed soil and rock sample using a sub-pixel digital image correlation algorithm to obtain sub-pixel precision global displacement data; determining the nonlinear strain field using a Green-Lagrange strain calculation model based on the global displacement data; and determining the strain deformation using an LSTM neural network based on the nonlinear strain field.

[0016] Based on the specific embodiments provided in this application, the following technical effects are disclosed.

[0017] This application provides a visual measurement device and method for the full-domain strain field of soil and rock samples. Multiple industrial cameras are used, each with an angle adjustable via a mechanical adjustment module. The left-right and forward-backward adjustment devices move the industrial cameras horizontally; a vertical slide rail moves the industrial cameras vertically; and a cross-shaped fine-tuning platform adjusts the industrial cameras horizontally. The industrial cameras, image processing module, and strain field analysis module are connected sequentially. The image processing module preprocesses the images captured by the industrial cameras and performs three-dimensional reconstruction of the soil and rock samples. The strain field analysis module performs strain field analysis on the reconstructed soil and rock samples. The mechanical adjustment module allows for precise control of the industrial camera's position, installation angle, and height, as well as precise adjustment of the camera's focus distance according to the shooting position requirements, ensuring clear and high-fidelity images and thus improving measurement accuracy. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is an overall diagram of the visual measurement device for the global strain field of a soil and rock sample.

[0020] Figure 2This is a top view of the visual measurement device for the global strain field of a soil and rock sample.

[0021] Figure 3 This is a schematic diagram of the image acquisition module and the mechanical adjustment module.

[0022] Figure 4 This is a cross-sectional view of the optical environment module.

[0023] Figure 5 This is a hardware system framework diagram.

[0024] Figure 6 This is a software system framework diagram.

[0025] Reference numerals: 1-Vertical support, 2-Cross fine-tuning platform, 3-Vertical slide rail parking device, 4-Front-back movement adjustment device, 5-Left-right movement adjustment device, 6-Power supply device, 7-Industrial camera, 8-Straight groove, 9-Vertical slide rail, 10-LED supplementary light strip, 11-High-transparency quartz glass pressure chamber, 12-Grid geomembrane, 13-Soil and rock sample. Detailed Implementation

[0026] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0027] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0028] like Figure 1 and Figure 2As shown, this application provides a visual measurement device for the full-domain strain field of a soil and rock sample, comprising: an image acquisition module, a mechanical adjustment module, an image processing module, and a strain field analysis module; the image acquisition module includes multiple sets of industrial cameras 7; the industrial cameras 7 are evenly distributed outside the pressure chamber; the industrial cameras 7 are used to capture images of the soil and rock sample 13 from multiple angles inside the pressure chamber; the mechanical adjustment module corresponds one-to-one with the industrial cameras 7; the mechanical adjustment module includes a cross-shaped fine-tuning platform 2, a left-right movement adjustment device 5, a front-back movement adjustment device 4, and a vertical slide rail 9; the left-right movement adjustment device 5 and the front-back movement adjustment device 4 are both mounted on the cross-shaped fine-tuning platform 2; The cross-shaped fine-tuning platform 2 is mounted on the vertical slide rail 9; the left-right movement adjustment device 5 and the front-back movement adjustment device 4 are used to move the industrial camera 7 horizontally; the vertical slide rail 9 is used to move the industrial camera 7 vertically; the cross-shaped fine-tuning platform 2 is used to adjust the industrial camera 7 horizontally; the industrial camera 7, the image processing module, and the strain field analysis module are connected in sequence; the image processing module is used to preprocess the images captured by the industrial camera 7 and perform three-dimensional reconstruction of the soil and rock sample 13; the strain field analysis module is used to perform strain field analysis on the three-dimensionally reconstructed soil and rock sample 13.

[0029] like Figure 5 and Figure 6 As shown, the visual measurement device for the full-domain strain field of soil and rock samples includes a hardware system and a software system. The hardware system includes an image acquisition module, an optical environment module, a mechanical adjustment module, and a data management module. The software system includes an image processing module and a strain field analysis module.

[0030] In practical applications, such as Figure 3 As shown, the mechanical adjustment module further includes: a vertical support 1; the vertical slide rail 9 is mounted on the vertical support 1. The mechanical adjustment module also includes: a vertical slide rail stopping device 3; the vertical slide rail stopping device 3 is used to fix the cross-shaped fine-tuning platform 2 on the vertical slide rail stopping device 3. The mechanical adjustment module also includes a support base; the support base is used to fix the vertical support 1; the support base is provided with a straight groove 8; the straight groove 8 is used to fix it to the test bench table. The mechanical adjustment module also includes a power supply device 6.

[0031] The mechanical adjustment module combines a fine-tuning slide rail with a cross-shaped fine-tuning platform 2. The slide rail and movable base provide precise control over the camera's horizontal and vertical movement, while the cross-shaped fine-tuning platform 2 enables ultra-high precision adjustment of the camera in the horizontal direction. The camera in this application is an industrial camera 7. The mechanical adjustment module, combining a fine-tuning slide rail with a cross-shaped fine-tuning platform 2, allows for pitch angle adjustment and displacement adjustment in the X, Y, and Z directions. The fine-tuning slide rail consists of a vertical slide rail stopping device 3 and a vertical slide rail 9, providing precise control over the camera's vertical movement. Its high-precision slide rail structure ensures the stability and accuracy of the camera during vertical displacement adjustment. Screws are used to fix the straight groove 8 of the vertical support 1 base to the test bench table, enabling horizontal displacement adjustment of the camera. The cross-shaped fine-tuning platform 2 further enhances the camera's adjustment flexibility, achieving ultra-high precision adjustment of the camera in the horizontal direction through its fine adjustment mechanism. This combination allows the camera to precisely adjust its installation angle and height according to the sample size and position, and at the same time, to accurately adjust the lens's focusing distance according to the image shooting position requirements, ensuring the acquisition of clear and accurate sample images, and providing a high-quality data foundation for subsequent image analysis.

[0032] In practical applications, such as Figure 4As shown, the visual measurement device for the full-domain strain field of soil and rock samples also includes an optical environment module; the optical environment module is located outside the pressure chamber; the optical environment module is used to supplement the lighting of the pressure chamber. The optical environment module includes multiple sets of LED supplementary light strips 10. The optical environment module is based on a high-transmittance quartz glass pressure chamber 11, which has extremely high transmittance and low refractive index. Its high transmittance, especially in the visible and ultraviolet light regions, far surpasses that of ordinary glass. The low and stable refractive index reduces light refraction errors, and excellent thermal and chemical stability ensures stable light transmission characteristics, providing high-precision conditions for visual measurement. In addition, six sets of LED supplementary light strips 10 are arranged on each of the upper and lower sides of the outer edge of the pressure chamber, for a total of twelve sets. The brightness of the LED supplementary light strips 10 can be adjusted according to experimental needs to ensure the reliability and accuracy of experimental data, reduce the influence of external lighting factors on the accuracy of experimental results, and reduce errors caused by flicker, color temperature, and color difference. Compared with traditional supplementary light sources, this LED supplementary light strip 10 shows significant advantages in many aspects. First, the flicker characteristics are greatly optimized, providing stable and continuous illumination output. This effectively avoids the instability in imaging caused by flicker in the industrial camera 7, ensuring that the clarity and consistency of the image remain unaffected during high-speed or long-term continuous shooting. Second, the color temperature and color difference are precisely controlled. The light emitted by the LED supplementary light strip 10 has a stable color temperature and low color difference, providing uniform and accurate illumination for the sample under different environmental conditions. This reduces interference caused by changes in light color temperature and color difference on the color reproduction accuracy of the industrial camera 7, thereby improving the color fidelity of the image. This is particularly important for the industrial camera 7 to identify the detection points of the geomembrane 12 on the sample surface. Third, the thermal radiation characteristics are excellent. The LED supplementary light strip 10 generates relatively little heat during operation, having a smaller impact on the ambient temperature and effectively reducing measurement errors caused by changes in ambient temperature.

[0033] The optical environment module, centered on a high-transmittance quartz glass pressure chamber 11, minimizes measurement errors caused by factors such as light refraction, providing favorable conditions for visual measurement. High-transmittance quartz glass possesses extremely high light transmittance, especially in the visible and ultraviolet light regions, where its transmittance far surpasses that of ordinary glass. This allows a large amount of light to penetrate the pressure chamber, thereby reducing measurement errors caused by light loss. The low and stable refractive index of quartz glass results in weak refraction as light passes through, reducing image distortion or displacement caused by refraction and thus improving the accuracy of visual measurement. Simultaneously, quartz glass also exhibits excellent thermal and chemical stability, maintaining stable physical and chemical properties over a wide temperature range to ensure stable light transmission characteristics during measurement.

[0034] In practical applications, the visual measurement device for the whole-domain strain field of soil and rock samples also includes a data management module; the data management module is connected to the image acquisition module and the image processing module respectively.

[0035] The data management module rapidly and accurately transmits large amounts of image data acquired by multiple industrial cameras (7 sets) to a computer for processing and storage. This module employs high-speed data transmission interfaces, namely Gigabit Ethernet and USB 3.2, to ensure real-time performance and stability. Given the massive data volume generated by multiple cameras operating simultaneously, the module is equipped with larger-capacity storage devices. To ensure secure data storage and easy retrieval, the storage devices utilize high-performance hard drive arrays and cloud storage systems. Furthermore, the module also features data distribution and integration capabilities, enabling effective management and processing of image data from different cameras.

[0036] In practical applications, the number of industrial cameras 7 is six; these six industrial cameras 7 are evenly arranged at a 60° angle outside the pressure chamber. The image acquisition module employs six (or more) sets of high-resolution, high-frame-rate industrial cameras 7, enabling rapid and clear capture of the specimen's surface image during triaxial geotechnical testing, ensuring that no subtle changes in the specimen during stress deformation are missed. The system is also equipped with lenses with focusing capabilities, suitable for both overall and detailed imaging of specimens of different sizes. To ensure high-quality image capture, the component incorporates a light source system that provides stable lighting conditions, preventing image data distortion due to insufficient or uneven lighting. The image acquisition module employs six (or more) sets of high-resolution, high-frame-rate industrial cameras 7, evenly distributed around the transparent pressure chamber at a 60° (or other angle), and each industrial camera 7 is equipped with a lens with focusing capabilities, allowing for both overall and detailed imaging of specimens of different sizes. This unique distribution method has significant advantages. On the one hand, it can simultaneously photograph the soil and rock sample 13 from multiple angles to obtain more comprehensive information about the sample surface and avoid information loss or deviation caused by shooting from a single perspective. On the other hand, by fusing image data from different angles, the displacement and deformation of each point on the surface of the soil and rock sample 13 can be calculated more accurately, improving the accuracy and reliability of the measurement.

[0037] In practical applications, the pressure chamber is made of quartz glass. The soil and rock sample 13 is placed in the pressure chamber and wrapped with a geomembrane 12.

[0038] In practical applications, the image processing module supports global optimization and hardware-triggered synchronization of multi-view camera parameters, enabling it to perform denoising, enhancement, and geometric correction on the acquired raw images to improve image quality and clarity. Furthermore, this module utilizes the CUDA-accelerated SGM stereo matching algorithm and Poisson surface reconstruction technology to achieve real-time generation of sub-millimeter-level 3D point clouds on the sample surface, thereby reconstructing the 3D spatial morphology of the photographed object.

[0039] The implementation process mainly includes the following four stages: 1. Multi-camera synchronous acquisition and global calibration; 2. Image preprocessing and optimization; 3. Stereo matching and depth calculation; 4. 3D point cloud generation and surface reconstruction. The specific implementation details for each step are as follows: Phase 1: Synchronous acquisition and global calibration of multiple cameras.

[0040] The core of this stage lies in ensuring the spatiotemporal consistency of multi-view image data. The system achieves synchronization through hardware triggering, with a synchronization controller sending precise microsecond-level pulse signals to all cameras, forcing them to expose simultaneously and fundamentally eliminating image misalignment caused by object movement or vibration. After acquisition, global optimization and calibration of camera parameters are required. A high-precision calibration board is used to acquire images and extract feature points from multiple perspectives. Then, the nonlinear optimization algorithm of bundle adjustment is applied to jointly optimize the internal parameters (such as focal length and distortion) and external parameters (position and attitude) of all cameras in the same global coordinate system. The ultimate goal is to minimize the error of reprojecting 3D feature points back to each image, thereby establishing a high-precision multi-view imaging geometric model and laying a solid foundation for subsequent 3D calculations.

[0041] Phase 2: Image preprocessing optimization.

[0042] Before stereo matching, the original image needs to be preprocessed to improve its quality. The denoising stage employs edge-preserving algorithms such as bilateral filtering to smooth noise while preserving the edge and texture information crucial for matching. The enhancement stage uses techniques like histogram equalization to improve image contrast and illumination uniformity, enhancing feature discrimination. Geometric correction, based on lens distortion parameters obtained from calibration, corrects image distortion using a mapping table to ensure the image conforms to the pinhole camera model. These processing operations are inherently highly parallel, and therefore all rely on CUDA acceleration technology. By performing parallel computation on massive numbers of pixels on the GPU, the preprocessing speed is greatly improved, providing high-quality data input for subsequent real-time matching.

[0043] Phase 3: Stereo matching and depth calculation.

[0044] This stage is the core of 3D information restoration, converting the 2D image into a disparity map with depth information. The system employs a highly efficient semi-global matching (SGM) algorithm, accelerated on a GPU using CUDA. The process consists of four steps: First, the matching cost (e.g., Census transform) under all possible disparities is calculated for each pixel; this step has extremely high parallelism. Second, the costs are aggregated along multiple paths, and constraints (P1 and P2 penalty terms) are introduced to make the costs more reliable—this is the essence of the SGM algorithm. Then, the disparity of each pixel is initially determined using a winner-take-all (WTA) strategy. Finally, optimization is performed, including left-right consistency checks to eliminate mismatches at occluded points, and sub-pixel interpolation to improve accuracy beyond the pixel level. The final output is a high-precision, high-density sub-millimeter level disparity map.

[0045] Phase 4: 3D point cloud generation and surface reconstruction.

[0046] This stage transforms the disparity map into the final 3D model. First, a 3D point cloud is generated—a direct geometric back-projection process. Using the disparity *d* obtained in the previous stage, and the calibrated and optimized camera parameters (focal length *f*, baseline *B*), the depth value *Z* = (*f**B) / d for each pixel is calculated based on the principle of triangulation. Then, its 3D spatial coordinates (X, Y, Z) are calculated, generating a dense 3D point cloud with sub-millimeter precision. Subsequently, Poisson surface reconstruction technology is used to transform the discrete point cloud into a continuous, smooth, and closed triangular mesh surface. This algorithm treats the point cloud and its normal vectors as samples of the gradient of an indicator function. By constructing and solving a large Poisson equation, it reconstructs a surface model that best fits this gradient field. This model is robust to noise and can generate watertight solid models, accurately reconstructing the 3D spatial morphology of objects.

[0047] In practical applications, the strain field analysis module integrates the sub-pixel DIC algorithm with the Green-Lagrange strain field calculation model. Through an LSTM neural network, this module can analyze volumetric deformation, shear band evolution, local failure, and non-uniform deformation, and dynamically display real-time deformation images through a visual interface.

[0048] Specifically, the sub-pixel DIC algorithm can accurately capture minute displacement changes on the material surface, providing high-precision displacement field data for subsequent strain calculations. The Green-Lagrange strain field calculation model, based on this displacement data, calculates the strain at different locations, thus generating the overall strain distribution. The introduction of the LSTM neural network enables the module to process time-series data, capturing the dynamic deformation characteristics of the material during loading, and achieving real-time monitoring and analysis of the deformation process. Finally, through a visualization interface, the real-time deformation images of the material during the stress process can be intuitively observed.

[0049] The strain field analysis module first processes continuously acquired image pairs based on the subpixel digital image correlation (DIC) algorithm. By performing cross-correlation calculations on sub-regions in the reference image and the deformed image, and employing iterative optimization methods such as the inverse combined Gauss-Newton (IC-GN) method, subpixel-precision full-field displacement data U is obtained. Subsequently, this displacement field data is input into a Green-Lagrange strain calculation model, and numerical differentiation is performed through local least squares fitting to obtain the displacement gradient tensor, thereby calculating the nonlinear strain field reflecting the finite deformation of the material. To further analyze the temporal evolution characteristics, the time-series displacement and strain data are input into an LSTM neural network, which learns the long-term dependencies of historical data to achieve intelligent identification and trend prediction of dynamic processes such as shear band initiation and localized deformation. Finally, all data is fused by a visualization engine, and the strain field is superimposed on the deformed image in real time in pseudo-color image form, dynamically displaying the entire material deformation process and analysis results.

[0050] In this application, the image acquisition module can simultaneously capture images of the soil and rock sample 13 from multiple angles, ensuring full-coverage high-definition capture of the dynamic deformation process of the sample; the mechanical adjustment module can perform multi-angle and omnidirectional pose adjustment of the image acquisition module; the optical environment module minimizes measurement errors caused by factors such as light refraction, and the large number of acquired images are quickly and accurately uploaded to the hard disk array and cloud storage system through the data management module. Through intelligent software system operations such as image processing, 3D reconstruction, and deformation analysis, experimental observation and intelligent analysis of the volume deformation, shear band evolution, and local failure of the soil and rock sample 13 are achieved.

[0051] This application achieves rapid, clear, and precise image capture of the sample surface by coordinating hardware and software systems, while minimizing the influence of factors such as light refraction. The images are then uploaded to a hard disk array and cloud storage system in real time. Sub-millimeter-level three-dimensional point clouds are generated in real time through three-dimensional morphology reconstruction technology, reconstructing the three-dimensional spatial morphology of the photographed object. Through data analysis, the experimental observation and intelligent analysis of the full-domain strain field of the soil and rock sample 13 are realized.

[0052] Specifically, by uniformly arranging multiple sets of high-resolution, high-frame-rate industrial cameras 7 around the transparent pressure chamber, overall and detailed imaging of the soil and rock sample 13 is achieved; the camera's pitch angle and displacement along the X, Y, and Z axes are precisely adjusted through a mechanical adjustment module, enabling the multiple sets of industrial cameras 7 to accurately adjust their installation angle and height according to the sample size and position; at the same time, the lens's focusing distance is precisely controlled according to the image shooting position requirements to ensure the clarity and high fidelity of the captured images.

[0053] Among them, based on the accurately measured object distance (Obtained by high-precision mechanical positioning or laser ranging) and lens focal length The system is based on the Gaussian lens formula. Real-time calculation of target image distance This formula establishes a quantitative control relationship between spatial positioning requirements and optical adjustment amounts. Subsequently, the control system drives the industrial lens's built-in focusing motor or external servo mechanism to precisely adjust the position of the focusing lens group or the entire lens, ensuring that the image distance strictly matches the calculated value. This ensures that the sample surface is clearly imaged on the image sensor. In addition, the focusing strategy takes into account the depth of field effect, usually focusing on the first third of the sample's depth of field to ensure that the entire sample is within the sharp range, ultimately achieving high-fidelity image acquisition.

[0054] The transparent pressure chamber is made of high-transmittance quartz glass (other high-transmittance materials can also be used, but their strength must also be high; typically, the pressure chamber must withstand a strength greater than 2 MPa). Its extremely high transmittance effectively reduces measurement errors caused by light loss. Its low refractive index minimizes image distortion or displacement caused by light refraction. Its excellent thermal and chemical stability ensures stable light transmission characteristics during measurement. The 12 LED supplementary lighting strips 10 on the outer edge of the pressure chamber effectively prevent image instability in the industrial camera 7 caused by flicker, significantly reduce interference from changes in light color temperature and color difference on the color reproduction accuracy of the industrial camera 7, and effectively reduce measurement errors caused by changes in ambient temperature.

[0055] High-precision image acquisition is achieved through hardware devices, transmitting the captured surface images of the test blocks to the software system in real time. The software then processes the acquired raw images through denoising, enhancement, and geometric correction, and employs advanced 3D morphology reconstruction technology to accurately construct the 3D spatial morphology of the soil sample. During this process, various optimization algorithms and error calibration mechanisms ensure that the error between the reconstructed model and the actual object is controlled at the sub-millimeter level, enabling refined visual measurement of the global strain field and intelligent analysis of soil sample volume deformation, shear band evolution, local failure, and non-uniform deformation.

[0056] In another exemplary embodiment, this application also provides a visual measurement method for the global strain field of a soil and rock sample, wherein the visual measurement method for the global strain field of a soil and rock sample is applied to the visual measurement device for the global strain field of a soil and rock sample, and the method includes the following steps.

[0057] A three-dimensional reconstructed soil and rock sample is obtained; the three-dimensional reconstructed soil and rock sample is obtained by preprocessing and three-dimensional reconstruction of multi-angle images of the soil and rock sample taken by an industrial camera.

[0058] Based on the three-dimensional reconstructed soil and rock sample, subpixel digital image correlation algorithm is used to process the sample to obtain full-field displacement data with subpixel accuracy.

[0059] The nonlinear strain field is determined using the Green-Lagrange strain calculation model based on the full-field displacement data.

[0060] The strain deformation is determined using an LSTM neural network based on the nonlinear strain field.

[0061] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0062] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A visual measurement device for the entire strain field of a soil and rock sample, characterized in that, include: Image acquisition module, mechanical adjustment module, image processing module, and strain field analysis module; The image acquisition module includes multiple sets of industrial cameras, which are evenly distributed outside the pressure chamber. Each industrial camera captures multi-angle images of the soil and rock samples inside the pressure chamber. A mechanical adjustment module corresponds to each industrial camera. The mechanical adjustment module includes a cross-shaped fine-tuning platform, a left-right movement adjustment device, a front-back movement adjustment device, and a vertical slide rail. The left-right and front-back movement adjustment devices are both mounted on the cross-shaped fine-tuning platform, which is mounted on the vertical slide rail. The left-right and front-back movement adjustment devices are used to move the industrial cameras horizontally. The vertical slide rail is used to move the industrial cameras vertically. The cross-shaped fine-tuning platform is used to adjust the industrial cameras horizontally. The industrial cameras, the image processing module, and the strain field analysis module are connected sequentially. The image processing module preprocesses the images captured by the industrial cameras and performs three-dimensional reconstruction of the soil and rock samples. The strain field analysis module is used to perform strain field analysis on the three-dimensional reconstructed soil and rock samples.

2. The visual measurement device for the whole-domain strain field of soil and rock samples according to claim 1, characterized in that, The mechanical adjustment module also includes: a vertical support frame; The vertical slide rail is mounted on the vertical support.

3. The visual measurement device for the whole-domain strain field of soil and rock samples according to claim 1, characterized in that, The mechanical adjustment module also includes: a vertical slide rail parking device; The vertical slide rail stopping device is used to fix the cross fine-tuning platform on the vertical slide rail stopping device.

4. The visual measurement device for the whole-domain strain field of soil and rock samples according to claim 2, characterized in that, The mechanical adjustment module also includes a support base; the support base is used to fix the vertical support; a straight groove is provided on the support base; the straight groove is used to fix it to the test bench table.

5. The visual measurement device for the whole-domain strain field of soil and rock samples according to claim 1, characterized in that, It also includes an optical environment module; The optical environment module is located outside the pressure chamber; the optical environment module is used to provide supplemental lighting for the pressure chamber.

6. The visual measurement device for the whole-domain strain field of soil and rock samples according to claim 1, characterized in that, It also includes a data management module; The data management module is connected to both the image acquisition module and the image processing module.

7. The visual measurement device for the whole-domain strain field of soil and rock samples according to claim 1, characterized in that, The number of industrial cameras is six; The six industrial cameras are evenly arranged at a 60° angle outside the pressure chamber.

8. The visual measurement device for the whole-domain strain field of soil and rock samples according to claim 1, characterized in that, The pressure chamber is made of quartz glass.

9. The visual measurement device for the whole-domain strain field of a soil and rock sample according to claim 5, characterized in that, The optical environment module includes multiple sets of LED fill light strips.

10. A method for visually measuring the global strain field of a soil and rock sample, characterized in that, The visual measurement method for the whole-domain strain field of soil and rock samples is applied to the visual measurement device for the whole-domain strain field of soil and rock samples according to any one of claims 1-9, and the method includes: A three-dimensional reconstructed soil and rock sample was obtained; the three-dimensional reconstructed soil and rock sample was obtained by preprocessing and three-dimensional reconstruction of multi-angle images of the soil and rock sample taken by an industrial camera. Based on the three-dimensional reconstructed soil and rock sample, subpixel digital image correlation algorithm is used to process the sample to obtain full-field displacement data with subpixel accuracy. The nonlinear strain field is determined using the Green-Lagrange strain calculation model based on the full-field displacement data. The strain deformation is determined using an LSTM neural network based on the nonlinear strain field.

Images