In-situ structural plane feature rapid acquisition and its influence on rock mechanics property comprehensive test method

Abstract

The present application relates to the technical field of rock mechanics, especially to a comprehensive testing method for quickly obtaining in-situ structural plane features and their influence on rock mechanical properties, comprising the following steps: obtaining three-dimensional topographic features of in-situ structural planes in a study area, and storing the three-dimensional topographic features as three-dimensional point cloud data; correcting the three-dimensional point cloud data to obtain point cloud coordinates; taking Sq parameter as a roughness representation parameter of the three-dimensional topographic features, and combining the Sq parameter with the point cloud coordinates to obtain Sq representation parameters; sampling in the study area and conducting mechanical tests on the samples; and analyzing the correlation between the in-situ structural plane features and the rock mechanical properties according to the in-situ structural plane features of the damaged samples and the corresponding mechanical tests. The present application realizes quick and high-precision acquisition of three-dimensional features of in-situ structural planes, and can quantitatively analyze the relationship between the in-situ structural plane features and the rock mechanical properties.

Description

Technical Field

[0001] This invention relates to the field of rock mechanics, and in particular to a comprehensive testing method for rapidly acquiring in-situ structural surface features and their impact on rock mechanical properties. Background Technology

[0002] The three-dimensional morphological features of macroscopic undulations and micro-convexities of structural surfaces directly affect the mechanical properties of rocks. In engineering practice, obtaining high-precision three-dimensional morphological features of structural surfaces and performing quantitative characterization, while quantitatively correlating them with rock mechanical properties, is crucial for predicting rock mass engineering behavior, assessing rock mass stability, designing support schemes, and preventing geological disasters. Currently, the most commonly used three-dimensional morphological feature characterization is the structural surface roughness parameter. Methods for measuring the three-dimensional roughness of rock mass structural surfaces include stylus profilometry, white light interferometric profilometry, 3D laser scanners, and digital image processing techniques. Portable 3D laser scanners, with their advantages of rapid non-contact acquisition of 3D point clouds and high anti-interference capabilities, are suitable for complex in-situ information acquisition. Currently, the process generally involves the following steps: acquiring the morphological data of rock structural surfaces; preprocessing the 3D point cloud data; performing mesh thinning on the point cloud data; performing regular sorting on the coordinate data; calculating the JRC values ​​of all structural surface contour lines in the point cloud data; and plotting a histogram of the frequency distribution of JRC values.

[0003] Existing solutions involve mesh thinning of point cloud data. However, the deletion and reconstruction of point cloud data inherently present accuracy control issues, and key data features, especially in areas of rapid change, may be missing. Furthermore, the reconstructed point cloud may deviate from the original data. Additionally, existing solutions calculate roughness based on statistical analysis of multiple contour lines (JRCs). This involves first calculating the roughness information of a single contour line and then statistically deriving the complete 3D structural surface information. This process is relatively complex and based on discrete data statistics, failing to fully describe the data's distribution characteristics. Summary of the Invention

[0004] To address the aforementioned issues, this invention provides a comprehensive testing method for rapidly acquiring in-situ structural surface features and their impact on rock mechanical properties. This method enables rapid and high-precision acquisition of three-dimensional features of in-situ structural surfaces and allows for quantitative analysis of the relationship between in-situ structural surface features and rock mechanical properties.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] A comprehensive testing method for rapidly acquiring in-situ structural surface features and their impact on rock mechanical properties includes the following steps:

[0007] S1. Obtain the three-dimensional morphological features of the in-situ structural surface in the study area, and store the three-dimensional morphological features as three-dimensional point cloud data;

[0008] S2. Perform reference plane correction on the three-dimensional point cloud data to obtain point cloud coordinates;

[0009] S3. The Sq parameter is used as the roughness characterization parameter of the three-dimensional topography feature, and the Sq parameter is combined with the point cloud coordinates to calculate the Sq characterization parameter, so as to obtain the in-situ structural surface feature.

[0010] S4. Take samples in the study area and conduct mechanical tests on the samples to obtain damaged samples after mechanical testing. Use the damaged surface of the damaged sample as the study area, and perform steps S1-S3 on the damaged surface of each damaged sample to obtain the in-situ structural surface features of the damaged sample.

[0011] S5. Based on the in-situ structural surface characteristics of the damaged specimen and the corresponding mechanical test, analyze the correlation between the in-situ structural surface characteristics and the rock mechanical properties.

[0012] Further, in step S1, the study area is scanned by a three-dimensional laser scanner to obtain the three-dimensional topographic features, and the three-dimensional topographic features are stored as a three-dimensional point cloud data file in STL format.

[0013] Further, in step S2, the three-dimensional point cloud data obtained by the three-dimensional laser scanner is processed to remove the three-dimensional point cloud data located outside the study area.

[0014] Furthermore, in step S2, the three-dimensional point cloud data is fitted with a plane using the least squares method to obtain a corrected reference plane.

[0015] Further, in step S2, the reference plane is exported as a reference plane file, which is an .asc format file with point cloud coordinate information.

[0016] Further, in step S3, the point cloud coordinates in the reference plane file and the Sq parameter are used to calculate the Sq characterization parameter using Matlab software.

[0017] Furthermore, the method for calculating the Sq characterization parameter is as follows:

[0018]

[0019] in, Sq represents the parameter; The projected area of ​​the point cloud data of the in-situ structural surface; The height is perpendicular to the reference plane, and the height of the reference plane is a horizontal coordinate. and vertical coordinates The function; The horizontal coordinates of the point cloud; The vertical coordinates of the point cloud coordinates.

[0020] The beneficial effects of this invention are:

[0021] A portable handheld 3D laser scanner was used to scan the in-situ structural surfaces in the study area, thereby acquiring point cloud information. The point cloud data used for calculating the Sq characterization parameters was the full data after coordinate calibration of the study area, and the calculation was performed automatically using software written in MATLAB, achieving rapid and high-precision acquisition of the 3D features of the in-situ structural surfaces. By combining the quantitative calculation of the Sq characterization parameters with the rock mechanical property parameters measured by indoor experiments, a quantitative analysis of the relationship between the in-situ structural surface features and the rock mechanical properties was achieved. The point cloud data information of this invention is a non-destructive 3D structural surface morphology feature characterization parameter, which improves the accuracy of quantitative characterization; moreover, the 3D structural surface morphology feature characterization parameters of this invention are directly calculated based on the full amount of point cloud data, which is more efficient and more accurate. Attached Figure Description

[0022] Figure 1 This is a flowchart of a preferred embodiment of the present invention, which describes a comprehensive testing method for rapidly acquiring in-situ structural surface features and their impact on rock mechanical properties.

[0023] Figure 2 This is a fitting curve of the in-situ structural surface feature rapid acquisition method and its comprehensive testing method on rock mechanical properties according to a preferred embodiment of the present invention. Detailed Implementation

[0024] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0025] Please also see Figure 1 and Figure 2 A preferred embodiment of the present invention provides a method for rapid acquisition of in-situ structural surface features and a comprehensive testing method for their impact on rock mechanical properties, comprising the following steps:

[0026] S1. Obtain the three-dimensional morphological features of the in-situ structural surfaces in the study area and store the three-dimensional morphological features as three-dimensional point cloud data.

[0027] In step S1, the study area is scanned by a 3D laser scanner to obtain 3D topographic features, and the 3D topographic features are stored as a 3D point cloud data file in STL format.

[0028] S2. Perform reference plane correction on the 3D point cloud data to obtain the point cloud coordinates.

[0029] In step S2, the 3D point cloud data obtained by the 3D laser scanner is processed to remove the 3D point cloud data located outside the study area.

[0030] In step S2, the three-dimensional point cloud data is fitted to a plane using the least squares method to obtain a corrected reference plane.

[0031] In step S2, the reference plane is exported as a reference plane file, which is an .asc format file containing point cloud coordinate information.

[0032] S3. The Sq parameter is used as the roughness characterization parameter of the three-dimensional topography feature, and the Sq parameter is combined with the point cloud coordinates to calculate the Sq characterization parameter in order to obtain the in-situ structural surface features.

[0033] In step S3, the point cloud coordinates and Sq parameters in the reference plane file are used to calculate the Sq characterization parameters using Matlab software.

[0034] The method for calculating the Sq characterization parameter is as follows:

[0035]

[0036] in, Sq represents the parameter; The projected area of ​​the point cloud data of the in-situ structural surface; The height is perpendicular to the reference plane, and the height of the reference plane is a horizontal coordinate. and vertical coordinates The function; The horizontal coordinates of the point cloud; The vertical coordinates of the point cloud coordinates.

[0037] In this embodiment, the Sq parameter is calculated using full-volume in-situ scanned 3D point cloud data as a characteristic parameter for the 3D structural surface, improving calculation accuracy and efficiency. Furthermore, the calculation is fully automated using software written in MATLAB, enabling rapid and high-precision acquisition of the 3D features of the in-situ structural surface. Moreover, the point cloud data information in this embodiment is a lossless representation of the 3D structural surface morphology, improving the accuracy of quantitative characterization. Simultaneously, the 3D structural surface morphology characteristic parameters of this application are calculated directly based on the full volume of point cloud data, resulting in faster efficiency and higher accuracy. This overcomes the drawbacks of potential information loss in drastically changing areas and the deviation between the reconstructed point cloud and the original data.

[0038] S4. Take samples in the study area and conduct mechanical tests on the samples to obtain the damaged samples after the mechanical tests. Use the damaged surface of the damaged sample as the study area, and perform steps S1-S3 on the damaged surface of each damaged sample to obtain the in-situ structural surface characteristics of the damaged sample.

[0039] S5. Based on the in-situ structural features of the damaged specimens and the corresponding mechanical tests, analyze the correlation between the in-situ structural features and the rock mechanical properties.

[0040] The mechanical tests in this embodiment can be conducted in various indoor settings as needed. By using the calculated Sq characterization parameter values ​​and the rock mechanical property values ​​measured in indoor tests, a quantitative correlation analysis between in-situ structural surface characteristics and rock mechanical properties is performed, achieving a quantitative analysis of the relationship between the two. For example... Figure 2 As shown, the curves represent the fitting relationship between the uniaxial compressive strength of rock and the Sq characterization parameter, where the Y-axis represents the uniaxial compressive strength of rock and the X-axis represents the Sq characterization parameter, i.e., the X-axis represents the roughness characterization parameter.

Claims

1. A comprehensive testing method for rapidly acquiring in-situ structural surface features and their impact on rock mechanical properties, characterized in that... Includes the following steps: S1. Obtain the three-dimensional morphological features of the in-situ structural surface in the study area, and store the three-dimensional morphological features as three-dimensional point cloud data; In step S1, the study area is scanned by a 3D laser scanner to obtain the 3D topographic features, and the 3D topographic features are stored as a 3D point cloud data file in STL format. S2. Perform reference plane correction on the three-dimensional point cloud data to obtain point cloud coordinates; In step S2, the three-dimensional point cloud data is fitted with a plane using the least squares method to obtain a corrected reference plane; S3. The Sq parameter is used as the roughness characterization parameter of the three-dimensional topography feature, and the Sq parameter is combined with the point cloud coordinates to calculate the Sq characterization parameter, so as to obtain the in-situ structural surface feature. The method for calculating the Sq characterization parameter is as follows: in, Sq represents the parameter; The projected area of ​​the point cloud data of the in-situ structural surface; The height is perpendicular to the reference plane, and the height of the reference plane is a horizontal coordinate. and vertical coordinates The function; The horizontal coordinates of the point cloud; S4. Take samples in the study area and conduct mechanical tests on the samples to obtain the damaged samples after the mechanical tests. Take the damaged surface of the damaged samples as the study area and perform steps S1-S3 on the damaged surfaces of each damaged sample to obtain the in-situ structural surface features of the damaged samples. S5. Based on the in-situ structural surface characteristics of the damaged specimen and the corresponding mechanical test, establish a functional relationship between the uniaxial compressive strength of the rock obtained from the indoor uniaxial compression test and the Sq characterization parameter. Combined with the in-situ structural surface characteristics, quickly predict the uniaxial compressive strength of the engineering rock mass.

2. The method for rapid acquisition of in-situ structural surface features and its comprehensive testing effect on rock mechanical properties according to claim 1, characterized in that: In step S2, the three-dimensional point cloud data obtained by the three-dimensional laser scanner is processed to remove the three-dimensional point cloud data located outside the study area.

3. The method for rapid acquisition of in-situ structural surface features and its comprehensive testing effect on rock mechanical properties according to claim 1, characterized in that: In step S2, the reference plane is exported as a reference plane file, which is an .asc format file with point cloud coordinate information.

4. The method for rapid acquisition of in-situ structural surface features and comprehensive testing of their influence on rock mechanical properties according to claim 3, characterized in that: In step S3, the point cloud coordinates and the Sq parameters in the reference plane file are used to calculate the Sq characterization parameters using Matlab software.

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