Rock mass quality grade evaluation method based on fracture image

Abstract

The invention discloses a fracture image-based rock mass quality grade evaluation method, which belongs to the field of intelligent mines, and specifically comprises the following steps: sampling and selecting a representative image acquisition area according to rock mass characteristics, acquiring a joint fracture close-range two-dimensional image, digitally processing and correcting a fracture image according to a built-in rectangular plastic plate with a fixed size, and evaluating the rock mass quality grade. And extracting basic geometric feature parameters of the fracture image, quantitatively calculating a rock incomplete degree index according to the extracted feature parameters, and finally performing addition calculation to obtain a rock mass evaluation index RMR value according to each parameter scoring standard so as to determine the rock mass grade. The method can automatically identify and evaluate the grade of the rock mass by taking the digital image shot on site as a medium and combining with the image processing technology to obtain the joint fissure image information, has the characteristics of high information acquisition speed, small workload, high accuracy and small influence of human or environmental factors, is easy to carry out detailed investigation work, and is suitable for popularization and application. And a more accurate scientific basis is provided for mine technical work.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent mines, and particularly relates to a method for evaluating the quality grade of rock masses based on the extraction and calculation of geometric feature parameters of fracture images. Background Art

[0002] Precisely identifying the structural plane information of two-dimensional fracture patterns can achieve a rapid and effective evaluation of the quality grade of rock masses. Among them, joint fracture parameters are the most basic structural plane information. Based on this information, the quality grade of rock masses and the rock mass structure can be divided, providing favorable technical data support for mine exploitation design and construction plans. The more accurate the joint fracture parameters are, the more accurate the division is and the stronger the guidance is.

[0003] Traditional fracture identification and measurement techniques rely on manual on-site measurements through survey work, which are inefficient, time-consuming, difficult to ensure accuracy, and have limited guidance for mine exploitation work. Therefore, how to quickly, safely, and accurately obtain joint fracture information and then accurately evaluate the quality grade of rock masses is the main exploration direction of the present invention. Summary of the Invention

[0004] The purpose of the present invention is to propose a method for evaluating the quality grade of rock masses based on fracture images to solve the problems of low efficiency, high danger, and difficult accuracy guarantee in obtaining traditional joint fracture parameters.

[0005] The present invention is realized through the following technical solutions:

[0006] The present invention proposes a method for evaluating the quality grade of rock masses based on fracture images, including the following steps:

[0007] S1, Select the image acquisition area: Initially divide multiple areas according to the similarity of rock mass characteristics in the mining area, and use the rock mass fault, dike strike, and shear zone as the area boundaries. Different sections are divided within each area, and the section with the most significant rock mass characteristics is selected as the representative image acquisition area;

[0008] S2, Collect close-range images of joint fractures: Place a rectangular plastic plate with a known fixed size in the image acquisition area selected in step S1, and conduct orthographic photography at predetermined points to collect close-range two-dimensional fracture images. Each fracture image contains the same rectangular plastic plate with a fixed size; at the same time, obtain the rock block strength Rc, structural plane condition R4, and groundwater condition R5 information at each collection point, and generate the corresponding relationship R6 between the structural plane occurrence and the engineering trend based on the obtained information;

[0009] S3. Image preprocessing: Import the collected fissure images into Matlab software. Using the rectangular plastic plate in the fissure image as a reference object, construct the pixel-length scale (cm / pixel) of the fissure image. According to the angular variation relationship between any point within the rectangular plastic plate and the perpendicular projection lines of other points on the image with respect to the shooting point, obtain the correction coefficient of the coordinate of any point and the pixel-length scale, and correct the coordinates of each pixel point in each fissure image.

[0010] S4. Extract geometric feature parameters of joint fissure images: Identify and select the two end points of each fissure in the corrected image to obtain the end point coordinates. Quantify the feature parameters of each fissure according to the end point coordinates and the scale. The feature parameters include geometric center coordinates, fissure length, and fissure dip angle.

[0011] S5. Calculate the weighted fissure spacing S: Group the fissures in each fissure image according to the angle with the horizontal plane, calculate the weight P(i) of the number of fissures in the group relative to the total number of fissures in the image. Take the groups with P(i)>10% as valid groups. Calculate the spacing between any two adjacent fissures and its average value in the valid groups as the fissure spacing S(i) of the valid groups. Calculate the weighted fissure spacing S of the image based on the fissure spacing S(i) of the valid groups and the weight P(i). The calculation method is shown in formula (5-1):

[0012]

[0013] S6. Quantify the index of rock integrity degree: Directly obtain the number of joints in the whole image from the fissure image, and quantify and calculate the volumetric joint count Jv, rock quality designation RQD, and rock mass integrity index Kv according to the number of joints and the size of the fissure image.

[0014] S7. Quantify and obtain the rock mass quality grade: Using the rock quality designation RQD and the weighted fissure spacing S as input parameters, and the rock block strength Rc, structural plane condition R4, groundwater condition R5, and the relationship between the structural plane attitude and the engineering strike R6 as correction parameters, formulate the scoring criteria for each parameter, sum up the scores of each parameter to obtain the RMR value, and obtain the rock mass quality grade according to the corresponding relationship between the RMR value and the rock mass quality grade, and complete the rock mass quality evaluation of the corresponding area.

[0015] Based on the above method, two-dimensional close-range fissure images of different regions are collected through on-site photography. Based on the digital processing of the collected images, geometric characteristic parameters of joint fissures such as the endpoints, geometric centers, lengths, dips, and joint spacings of each fissure are quantified. Furthermore, the rock integrity degree index and the rock mass quality grade are quantified, and a rock mass grade automatic evaluation system with digital images as the medium is constructed. Based on this system, only by collecting the images of the to-be-evaluated area exposed in the mining area, the surrounding rock grade of the corresponding area can be automatically identified, which has the characteristics of fast information collection speed, small on-site workload, can quickly identify, quantify, and extract the rock mass quality characteristic parameters through two-dimensional fissure graphics, is not affected by human subjective and technical experience judgments, and is easy to conduct a detailed investigation of a certain area, can store the original data for a long time, has strong traceability, and can provide favorable technical data support for mine exploitation design and construction plans.

[0016] Furthermore, the rock mass characteristics in step S1 include rock type, rock mass cutting degree, joint occurrence, hydrogeological conditions, and weathering and alteration states. The comprehensive multi-dimensional similarity of rock mass characteristics is used as the regional division standard, which is conducive to enhancing the representativeness of the image acquisition area and improving the accuracy of rock mass quality grade evaluation.

[0017] Furthermore, the orthographic photography method in step S2 is that when photographing the structural plane of the fissured rock mass, keep the lens main axis of the image acquisition device along the normal direction of the photographing target to form orthographic photography, so as to ensure that the photographed digital image is a front view and reduce the error caused by the camera attitude.

[0018] Furthermore, when collecting close-range two-dimensional fissure images in the same investigation area, the image acquisition device is the same image acquisition device with high pixels, and the same posture is maintained during shooting to ensure that the field target corresponding to each pixel of the image is fine enough.

[0019] Furthermore, the method for obtaining the rock block strength Rc in step S2 is as follows: use a point load test instrument to detect the rock block strength at each image acquisition point respectively, and perform conversion and correction of the rock mass quality index to obtain the standard rock sample load strength Rc. The calculation method of the standard rock sample point load strength index is shown in formulas (2-1)-(2-3):

[0020]

[0021] Among them, I s is the rock sample point load strength index (MPa);

[0022] P is the maximum applied load (kN);

[0023] D is the distance between the two cone head endpoints, that is, the equivalent core diameter of the specimen, in mm;

[0024] I s(50)is the point load strength index of the standard rock sample with a diameter of φ50mm;

[0025] m is the correction index, which is determined according to the lithology and is a constant.

[0026] Further, the image preprocessing steps in step S3 are specifically as follows:

[0027] S301: Select the rectangular plastic plate as a reference object. According to the actual size and pixel size of the rectangular plastic plate, calculate the pixel-length scale λ of this fracture image E , and the calculation method is shown in formula (3-1):

[0028]

[0029] where A1 and B1 are the actual length and width values of the reference object, and a1 and b1 are the pixel length and width values of the reference object;

[0030] S302: According to the pixel-length scale λ E calculate the geometric dimensions A and B of the actual shooting area corresponding to the fracture image respectively. The calculation formulas are shown in (3-2) and (3-3):

[0031] A = A1 / a1 × a (3-2)

[0032] B = B1 / b1 × b (3-3)

[0033] where a and b are the pixel length and width values of this fracture image;

[0034] S303: Denote the actual geometric center point of the shooting area as O′(1 / 2A, 1 / 2B), and the pixel geometric center of the fracture image as O″(1 / 2a, 1 / 2b). Measure the vertical projection distance L of the shooting lens O relative to the shooting area. According to the angle value between the center point E(x1, y1) of the reference object and the vertical projection line of any point P(x i , y i ) in the area and the Pythagorean theorem, calculate the correction coefficient K of any point P(x i , y i ) relative to the center point E(x1, y1) of the reference object. The specific calculation method is shown in formulas (3-4) to (3-7):

[0035]

[0036]

[0037] where λ is the standard pixel-length scale (cm / pixel) at the vertical shooting point, λ pis the pixel-length scale (cm / pixel) at any point P, (x1, y1) is the coordinate point of the center point E of the reference object in the fracture image, and (x i , y i ) is the coordinate point of any point P in the fracture image;

[0038] S304, traverse all pixel points outside the reference object area in the image, and correct the coordinate values of each pixel point one by one according to the corresponding K value of the point.

[0039] Further, the method for calculating the fracture spacing in step S5 is as follows: If two adjacent fractures do not intersect, the midpoint spacing of the line connecting the fracture endpoints is used as the fracture spacing; if two adjacent fractures intersect, the geometric center spacing is calculated based on the geometric center coordinates obtained in step S4 as the fracture spacing.

[0040] Further, the calculation methods of the volumetric joint number Jv and the rock mass rating RQD in step S6 are shown in formulas (6-1)-(6-2):

[0041]

[0042] RQD = 115 - 3.3J v (6-2)

[0043] where K is the conversion coefficient for converting the two-dimensional areal joint number to the three-dimensional volumetric joint number, with a value range of 1.15 to 1.35;

[0044] n is the total number of joints in each fracture image;

[0045] A is the actual area corresponding to each fracture image.

[0046] Further, the rock mass integrity index Kv in step S6 is quantified through its corresponding relationship table with the volumetric joint number Jv. The BQ value is quantified through the rock mass integrity index Kv, and the rock mass quality grade is obtained according to the BQ classification method, which is used to assist in determining the accuracy of the rock mass quality grade obtained in step S7. The calculation method of the BQ value is shown in formula (8):

[0047] BQ = 100 + 3Rc + 250Kv (8)

[0048] where Rc is the uniaxial compressive strength of the rock block, that is, the rock block strength.

[0049] The purpose of this step is to: integrate the RMR classification evaluation method and the BQ classification evaluation method, verify the accuracy with each other, further eliminate the error in the evaluation of the rock mass quality grade, improve the accuracy of the rock mass quality classification structure, and provide a basic basis for the mutual conversion between the indexes of the RMR classification evaluation method and the BQ classification evaluation method.

[0050] Beneficial effects

[0051] The beneficial effects of the present invention are as follows:

[0052] 1) By collecting two-dimensional close-range fissure images of different regions through on-site shooting, digitizing and quantifying the geometric characteristic parameters of each joint fissure such as the endpoints, geometric centers, lengths, dips, and joint spacings of the fissures based on the collected images, and then quantifying and calculating the rock integrity degree index and the rock mass quality grade according to the obtained geometric characteristic parameters, an automatic evaluation system for rock mass grade using digital images as a medium is constructed. Based on this system, only by collecting the images of the exposed areas to be evaluated in the mining area, the surrounding rock grade of the corresponding area can be automatically identified. It has the characteristics of fast information collection speed, small on-site workload, can quickly identify, quantify, and extract the rock mass quality characteristic parameters through two-dimensional fissure graphics, is not affected by human subjective and technical experience judgments, and is easy to conduct a detailed investigation of a certain area. The original data is easy to store for a long time and has strong traceability, which can provide favorable technical data support for mine exploitation design and construction plans, effectively avoiding the problems existing in the traditional method for collecting joint fissure parameters, such as long operation time, many environmental interference factors, low data processing efficiency, and being greatly affected by human experience, judgment criteria and other subjective factors, and greatly improving the efficiency and accuracy of the rock mass quality grade evaluation work.

[0053] 2) By determining the image acquisition area through multi-dimensional rock mass characteristic parameters and collecting images at predetermined points within the acquisition area, the representativeness of the collected images is effectively guaranteed, the influence of human factors is eliminated, and the credibility of the later-stage quantitative data collection is improved.

[0054] 3) By obtaining digitizable close-range two-dimensional fissure images through orthophotography and constructing a specific scale for each image through a rectangular plastic plate with known dimensions included in the image to complete the image correction, it not only effectively eliminates the data loss caused by the inaccessibility of the exposed rock mass, but also effectively eliminates the data error caused by the deformation of the photographic image, further ensuring the accuracy of the data collection information.

[0055] 4) By constructing an image processing and automatic calculation program based on the common mathematical processing software Matlab, including identifying, quantifying, and extracting the basic geometric characteristic parameters of the fissures by identifying the key features of the close-range two-dimensional fissure images, and quantifying and calculating the joint weighted spacing S, volumetric joint count Jv, rock quality designation RQD, rock mass integrity index Kv and other rock mass integrity degree index parameters of all digital close-range photographic photos accordingly, and then quantifying the RMR value and BQ value of the rock mass to complete the evaluation of the rock mass quality grade, it has the characteristics of high accessibility of processing means, simple data processing method, fast data extraction, and can automatically evaluate the rock mass quality grade. Description of the drawings

[0056] Other features, objectives, and advantages of the present invention will become more apparent by reading the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0057] Figure 1 Schematic diagram of the close-range two-dimensional fissure image of the present invention;

[0058] Figure 2 Schematic diagram of the correction of the image point coordinates and scale of the present invention;

[0059] Figure 3 Schematic diagram of the image processing working interface of the present invention Figure 1 ;

[0060] Figure 4 Schematic diagram of the image processing working interface of the present invention Figure 2 。 Detailed implementation manners

[0061] The present invention will be further described in detail below in conjunction with embodiments, but the implementation manners of the present invention are not limited thereto.

[0062] The present invention provides a method for evaluating the rock mass quality grade based on fissure images, including the following steps:

[0063] S1. Select an image acquisition area: Initially divide multiple areas according to the similarity degree of rock mass characteristics in the mining area, and use the rock mass faults, dike trends, and shear zones as the area boundaries. Different sections are divided within each area, and the section with the most significant rock mass characteristics is selected as the representative image acquisition area, and the structural plane information such as the structural plane condition R4, groundwater condition R5, and the relationship R6 between the structural plane occurrence and the engineering trend is synchronously collected;

[0064] Among them, the rock mass characteristics include rock type, rock mass cutting degree, joint occurrence, hydrogeological conditions, weathering and alteration status, etc. The comprehensive multi-dimensional similarity of rock mass characteristics is used as the area division standard to determine the engineering geological conditions of the area to be investigated, which is beneficial to enhancing the representativeness of the image acquisition area and improving the accuracy of the rock mass quality grade evaluation

[0065] S2. Collect close-range images of joint fissures: Place a rectangular plastic plate with a known fixed size (as shown in Figure 1 in the image acquisition area selected in step S1, and conduct orthographic photography at the predetermined points to collect close-range two-dimensional fissure images. Each fissure image contains the same rectangular plastic plate with a fixed size; at the same time, obtain the rock block strength RC, structural plane condition R4, and groundwater condition R5 information at each acquisition point, and generate the corresponding relationship R6 between the structural plane occurrence and the engineering trend according to the obtained information;

[0066] Among them, the orthographic photography method refers to that when photographing the structural plane of fractured rock mass, the lens main axis of the image acquisition device is kept along the normal direction of the photographing target to form orthographic photography, so as to ensure that the photographed digital image is a front view. When collecting close-range two-dimensional fracture images in the same investigation area, image acquisition devices such as digital cameras with the same altitude pixel are used, and the same posture is maintained during photographing to ensure that the field target corresponding to each pixel of the image is fine enough for subsequent image processing.

[0067] Among them, the method for obtaining the rock block strength Rc is as follows: The rock block strength is detected at each image acquisition point by using a point load test instrument, and the rock mass quality index conversion and correction are carried out to obtain the standard rock sample load strength Rc. The calculation method of the standard rock sample point load strength index is shown in formulas (2-1)-(2-3):

[0068]

[0069] Among them, I s is the point load strength index of the rock sample (MPa);

[0070] P is the maximum applied load (kN);

[0071] D is the distance between the two cone head endpoints, that is, the equivalent core diameter of the specimen, in mm; I s(50) is the point load strength index of the standard rock sample of φ50mm; m is the correction index, which is determined according to the lithology and is a constant. In this embodiment, the value is 0.42.

[0072] S3. Image preprocessing: Import the collected fracture images into the matlab software. Taking the rectangular plastic plate in the fracture image as a reference object, construct the pixel-length scale (cm / pixel) of the fracture image, and obtain the correction coefficient of the coordinate of any point and the pixel-length scale according to the angular change relationship between any point in the rectangular plastic plate and the vertical projection line of other points on the image to the photographing point, and correct the coordinates of each pixel point of each fracture image.

[0073] Among them, as Figure 2 shown, the specific process of image preprocessing is as follows:

[0074] S301. Select the rectangular plastic plate as a reference object, and calculate the pixel-length scale λ E of the fracture image according to the actual size and pixel size of the rectangular plastic plate. The calculation method is shown in formula (3-1):

[0075]

[0076] Among them, A1 and B1 are the actual length and width values of the reference object, and a1 and b1 are the pixel length and width values of the reference object;

[0077] S302. Calculate the geometric dimensions A and B of the actual shooting area corresponding to the fracture image respectively according to the pixel-length scale λ E As shown in formulas (3-2) and (3-3), the calculation formulas are as follows:

[0078] A = A1 / a1×a (3-2)

[0079] B = B1 / b1×b (3-3)

[0080] where a and b are the pixel length and width values of the fracture image;

[0081] S303. Denote the actual geometric center point of the shooting area as O′(1 / 2A, 1 / 2B), and the pixel geometric center of the fracture image as O″(1 / 2a, 1 / 2b). Measure the vertical projection distance L of the shooting lens O relative to the shooting area. According to the angle value between the reference object center point E(x1, y1) and the vertical projection line of any point P(x i , y i ) within the area and the Pythagorean theorem, calculate the correction coefficient K of any point P(x i , y i ) relative to the reference object center point E(x1, y1). The specific calculation method is as shown in formulas (3-4) to (3-7):

[0082]

[0083] where λ is the standard pixel-length scale (cm / pixel) at the vertical shooting point, λ p is the pixel-length scale (cm / pixel) at any point P, (x1, y1) is the coordinate point of the reference object center point E in the fracture image, and (x i , y i ) is the coordinate point of any point P in the fracture image;

[0084] S304. Traverse all pixel points outside the reference object area in the image, and correct the coordinate values of each pixel point one by one according to the corresponding K value of the point to eliminate the error caused by image deformation.

[0085] S4. Extract the geometric feature parameters of the joint fracture image: As Figure 3 shown, identify and select the two end points of each fracture in the corrected image to obtain the end point coordinates; Quantify the feature parameters of each fracture according to the end point coordinates and the scale to form a distribution map. The feature parameters include geometric center coordinates, fracture length, and fracture dip angle (i.e., joint dip angle). As Figure 4 shown is the joint dip angle rose diagram formed based on the fracture image;

[0086] S5. Calculate the weighted fracture spacing S: Group the fractures in each fracture image according to the angle with the horizontal plane, calculate the weight P(i) of the number of fractures in the group relative to the total number of fractures in the image, and use the groups with P(i) > 10% as the effective groups; calculate the spacing between any two adjacent fractures in the effective group and its average value as the fracture spacing S(i) of the effective group, and calculate the weighted fracture spacing S of the image based on the fracture spacing S(i) and the weight P(i) of the effective group. The calculation method is shown in formula (5-1):

[0087]

[0088] Among them, the fracture spacing calculation method in step S5 is as follows: If two adjacent fractures do not intersect, use the midpoint spacing of the line connecting the fracture endpoints as the fracture spacing; if two adjacent fractures intersect, calculate the geometric center spacing based on the geometric center coordinates obtained in step S4 as the fracture spacing;

[0089] Among them, the inclination angle range for grouping is reasonably determined according to actual needs. When fine grouping is required, a relatively narrow inclination angle range can be selected; when only rough grouping is required, a relatively wide inclination angle range can be selected.

[0090] S6. Quantify the rock integrity index: Directly obtain the number of joints in the entire image from the fracture image, and quantitatively calculate the volumetric joint number Jv, rock quality designation RQD, and rock mass integrity index Kv based on the number of joints and the size of the fracture image;

[0091] Among them, the calculation methods of the volumetric joint number Jv and the rock quality designation RQD are shown in formulas (6-1)-(6-2):

[0092]

[0093] RQD = 115 - 3.3J v (6-2)

[0094] Among them, K is the conversion coefficient for converting the two-dimensional areal joint number to the three-dimensional volumetric joint number, with a value range of 1.15 - 1.35;

[0095] n is the total number of joints in each fracture image;

[0096] A is the actual area corresponding to each fracture image;

[0097] Among them, the rock mass integrity index Kv is quantitatively obtained through its corresponding relationship table with the volumetric joint number Jv:

[0098] Table 1 Corresponding relationship table between Jv and Kv

[0099] <![CDATA[Jv (strip / m 3 )]]> <3 3～10 10～20 20～35 ≥35 Kv >0.75 0.75～0.55 0.55～0.33 0.35～0.15 ≤0.15

[0100] S7, Quantify and obtain the rock mass quality grade: Using the rock quality designation RQD and the weighted fracture spacing S as input parameters, and the rock block strength Rc, the structural plane condition R4, the groundwater condition R5, and the relationship R6 between the structural plane attitude and the engineering strike as correction parameters, formulate the scoring criteria for each parameter, sum up the scores of each parameter to obtain the RMR value, and obtain the rock mass quality grade according to the corresponding relationship between the RMR value and the rock mass quality grade, thereby completing the rock mass quality evaluation of the corresponding area;

[0101] The present invention will be further described below in conjunction with actual application scenarios:

[0102] S1, In combination with the construction situation of the mine entity project, the staff enter the mine for on-site investigation, initially divide the investigation area into several regions, and use existing geological features such as rock mass faults, dike strikes, and shear zones as the regional boundaries, so that the main rock mass features of each region, such as rock type, rock mass cutting degree, joint attitude, and hydrogeological conditions and weathering and alteration, are more or less the same. Each region is divided into multiple segments, and the segment with the most representative structural plane features is selected as the image acquisition area;

[0103] S2, Place a rectangular plastic plate with a known fixed size in the selected image acquisition area, and conduct orthographic photography at predetermined points to collect near - view two - dimensional fracture images. Each fracture image contains the same rectangular plastic plate with a fixed size; at the same time, obtain the rock block strength Rc, the structural plane condition R4, and the groundwater condition R5 information at each acquisition point, and generate the corresponding relationship R6 between the structural plane attitude and the engineering strike based on the obtained information;

[0104] In this embodiment, according to the application of the mine entity, 110 fracture images are selected at the levels of +0m, +18m, +54m, +72m, +90m in the west area, and 44 fracture images are selected at the levels of +115m, +130m, +145m, +160m, +175m, +190m in the middle area, for a total of 154 fracture images. The styles of the collected fracture images are as Figure 1 shown;

[0105] Meanwhile, rock samples are collected at the corresponding collection points at the selected levels of +0m, +18m, +54m, +72m, and +90m in the west area. The strike of the roadway, the dip and inclination of the dominant joint set, the structural plane condition R4, the groundwater condition R5, and other structural plane information are specifically investigated and measured, and an evaluation table of the influence of joint strike and dip on roadway engineering is generated (that is, the relationship R6 between the occurrence of the structural plane and the engineering strike is obtained, see Table 2); among them, the structural plane condition is divided into five grades A, B, C, D, and E, which are "discontinuous, tight, very rough rock wall, unweathered rock wall", "slightly rough rock wall, width < 1mm, slightly weathered rock wall", "slightly rough rock wall, width < 1mm, severely weathered rock wall", "smooth surface or soft interlayer thickness < 5mm, width 1 - 5mm, continuous", "smooth surface or soft interlayer thickness > 5mm or aperture > 5mm, continuous", respectively; the groundwater condition is also divided into five grades A, B, C, D, and E, which represent "completely dry", "humid", "wet cave wall", "dripping water", "flowing water", respectively; the collected rock samples are respectively detected on-site using a point load test instrument. Specifically: the rock sample is placed between the two spherical cone heads of the point load test instrument and a load is applied until the rock sample is broken, and the point load strength index of the standard rock sample with a diameter of φ50mm corresponding to each rock sample is calculated according to formulas (2)-(3), and the I corresponding to the rock samples at each collection point S(50) After removing three maximum values and three minimum values (to eliminate the influence of the dispersion of rock samples), regression analysis is carried out, and the rock mass strength Rc at this collection point is obtained by conversion and correction according to formula (4) (see Table 3):

[0106] Table 2 Evaluation Table of the Influence of Joint Strike and Dip on Roadway Engineering

[0107]

[0108] Table 3 Results of Rock Point Load Tests at Some Collection Points

[0109] Sampling point Average value / MPa Maximum value / MPa Standard deviation / MPa <![CDATA[Variance / MPa 2 > Coefficient of variation D1 5.5603 8.1680 1.6189 2.6208 26.98％ D2 3.7806 4.8752 1.0163 1.0328 16.94％ D3 4.8621 6.0226 1.0998 1.2095 18.33％ D4 6.1333 6.9313 0.9405 0.8845 15.67％ D5 4.5665 5.8593 1.0310 1.0631 17.18％ D6 2.2478 2.8250 0.3697 0.1367 6.16％ D7 3.9447 5.1303 1.1114 1.2353 18.52％ D8 7.0046 8.0001 0.8684 0.7542 14.47％ D9 6.3558 7.2423 0.8580 0.7362 14.30％

[0110] According to the aforementioned steps S3 and S4, the 154 fracture images collected are processed one by one, and the fracture parameters of the close-range images shown in Table 4 are obtained:

[0111] Table 4 Fracture Parameters of Some Close-Range Images

[0112]

[0113]

[0114] According to the foregoing step S5, the weighted fracture spacing S was calculated for 154 fracture images respectively, and the fracture spacing was obtained by using the traditional measurement method for the image acquisition areas corresponding to 10 of the fracture images as the comparison standard to review the accuracy of the weighted fracture spacing S. The review results are shown in Table 5. The calculated fracture spacing error is not greater than 7% and is acceptable.

[0115] Table 5 Table of manual review of fracture spacing

[0116] Number Calculated value Measured value Error Number Calculated value Measured value Error 1 20.30 21.70 6.45％ 11 36.13 34.65 4.27％ 2 22.10 20.10 9.95％ 12 40.03 39.26 1.96％ 3 20.40 23.50 13.19％ 13 40.32 40.85 1.30％ 4 24.50 26.10 6.13％ 14 18.09 17.37 4.15％ 5 29.50 28.30 4.24％ 15 37.34 36.10 3.43％ 6 22.30 21.60 3.24％ 16 20.81 19.56 6.39％ 7 13.10 15.10 13.25％ 17 31.82 29.79 6.81％ 8 16.80 15.20 10.53％ 18 40.03 39.85 0.45％ 9 19.39 18.53 4.64％ 19 66.55 62.68 6.17％ 10 23.09 24.09 4.15％ 20 9.20 9.01 2.11％

[0117] According to the foregoing step S6, the volumetric joint number Jv and the rock mass quality index RQD were calculated for 154 fracture images respectively. According to the foregoing step S7, according to the RMR system classification index scoring standard table (Table 6), the RMR value was calculated by summation. According to the corresponding table of RMR value and rock mass grade (Table 7), the evaluation of the rock mass quality grade was completed, and technical work such as roadway engineering construction, surrounding rock support scheme design, rock drilling optimization scheme design, and blasting scheme design was carried out according to the rock mass quality grade.

[0118] The calculation method of the RMR value is shown in formula (7-1):

[0119] RMR = S + RQD + Rc + R4 + R5 + R6 (7-1)

[0120] Table 6 RMR system classification index scoring standard table

[0121]

[0122] Table 7 Corresponding table of RMR value and rock mass grade

[0123] 100～81 80～61 60～41 40～21 <21 Classification Ⅰ Ⅱ Ⅲ Ⅳ Ⅴ Description Very good rock mass Good rock mass Average rock mass Poor rock mass Very poor rock mass

[0124] Finally, the rock mass quality grades of the selected areas obtained according to all the foregoing steps are generally grade III, and some are grade IV, which is consistent with the actual rock mass situation, and the evaluation results are credible.

[0125] Furthermore, the rock mass integrity index Kv obtained through step S6 is quantified through its corresponding relationship table with the volumetric joint number Jv. The BQ value is quantified through the rock mass integrity index Kv, and the rock mass quality grade is obtained according to the BQ classification method to assist in determining the accuracy of the rock mass quality grade obtained in step S7. The calculation method of the BQ value is shown in formula (8):

[0126] BQ = 100 + 3Rc + 250Kv (8)

[0127] Among them, Rc is the uniaxial compressive strength of the rock block, that is, the rock block strength.

[0128] The rock mass quality grades are obtained by the RMR grading evaluation method and the BQ grading evaluation method respectively. The two calculated values are subjected to data fitting, and the accuracy is mutually verified according to the correlation and the goodness of fit, further eliminating the error in the evaluation of the rock mass quality grade and improving the accuracy of the rock mass quality grading structure. In this embodiment, linear fitting and exponential fitting are used to verify the accuracy of the two evaluation methods. The fitting results show that among the gradings of 110 measurement sections, the grades of 93 measurement sections are the same or only differ by one level, and the coincidence rate is 85.4%. There is a significant correlation between BQ and RMR. The rock mass quality grade obtained according to the RMR grading evaluation method of the present invention has high accuracy.

[0129] The above are only preferred embodiments of the present invention, and do not impose any limitation on the technical scope of the present invention. Therefore, any minor modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention still fall within the protection scope of the present invention.

Claims

1. A method for evaluating the rock mass quality grade based on fracture images, characterized in that: It includes the following steps: S1. Select the image acquisition area: Initially divide multiple areas according to the similarity of rock mass characteristics in the acquisition area, and use rock mass faults, dike trends, and shear zones as the boundaries of the areas. Different sections are divided within each area, and the section with the most prominent rock mass characteristics is selected as the representative image acquisition area; S2. Collect close-range images of joint fissures: Place a rectangular plastic plate with a known fixed size in the image acquisition area selected in step S1, and conduct orthogonal photography at predetermined points to collect close-range two-dimensional fissure images. Each fissure image contains the same rectangular plastic plate of a fixed size; meanwhile, obtain the information of rock block strength Rc, structural plane condition R4, and groundwater condition R5 at each acquisition point, and generate the corresponding relationship R6 between the structural plane occurrence and the engineering trend based on the obtained information; S3. Image preprocessing: Import the collected fissure images into the matlab software. Taking the rectangular plastic plate in the fissure image as a reference object, construct the pixel-length scale (cm / pixel) of this fissure image, and obtain the correction coefficient of the coordinate of any point and the pixel-length scale according to the angular variation relationship between any point within the rectangular plastic plate and the perpendicular projection line of other points on the image to the shooting point, and correct the coordinates of each pixel point of each fissure image; S4. Extract the geometric feature parameters of the joint fissure images: Identify and select the two end points of each fissure in the corrected image to obtain the end point coordinates; Quantify the feature parameters of each fissure according to the end point coordinates and the scale. The feature parameters include geometric center coordinates, fissure length, and fissure dip angle; S5. Calculate the weighted fissure spacing S: Group the fissures in each fissure image according to the angle with the horizontal plane, calculate the weight P(i) of the number of fissures in the group relative to the total number of fissures in this image. The groups with P(i)>10% are used as effective groups; Calculate the spacing between any adjacent fissures and its average value within the effective group as the fissure spacing S(i) of the effective group. Calculate the weighted fissure spacing S of this image based on the fissure spacing S(i) of the effective group and the weight P(i). The calculation method is shown in formula (5-1): S6. Quantify the rock integrity index: Directly obtain the number of joints of the entire image from the fissure image, and quantify and calculate the volumetric joint number Jv, rock quality designation RQD, and rock mass integrity index Kv according to the number of joints and the size of the fissure image; S7. Quantify and obtain the rock mass quality grade: Taking the rock quality designation RQD and the weighted fissure spacing S as input parameters, and using the rock block strength Rc, structural plane condition R4, groundwater condition R5, and the relationship R6 between the structural plane occurrence and the engineering trend as correction parameters, formulate the scoring criteria for each parameter, sum the scores of each parameter to obtain the RMR value, and obtain the rock mass quality grade according to the corresponding relationship between the RMR value and the rock mass quality grade, and complete the rock mass quality evaluation of the corresponding area.

2. The method for evaluating the rock mass quality grade based on fracture images according to claim 1, characterized in that: The rock mass characteristics in step S1 include rock type, rock mass cutting degree, joint occurrence, hydrogeological conditions, and weathering and alteration status.

3. A method for evaluating the rock mass quality grade based on fracture images according to claim 1, characterized in that: The orthogonal photography method in step S2 is that when shooting the structural plane of the fissured rock mass, keep the lens main axis of the image acquisition device along the normal direction of the shooting target to form orthogonal photography.

4. A method for evaluating the rock mass quality grade based on fracture images according to claim 3, characterized in that: When collecting the close-range two-dimensional fracture images within the same survey area, the image acquisition device is the same high-pixel image acquisition device, and the images are acquired while maintaining the same posture during shooting.

5. A method for evaluating the quality grade of rock mass based on fracture images according to claim 1, characterized in that: The method for obtaining the rock block strength Rc in step S2 is as follows: Use a point load test instrument to detect the rock block strength at each image acquisition point respectively, and perform conversion and correction of the rock mass quality index to obtain the standard rock sample load strength Rc. The calculation method of the standard rock sample point load strength index is shown in formulas (2-1)-(2-3): Wherein, I s is the point load strength index of the rock sample (MPa); P is the maximum applied load (kN); D is the distance between the two cone tip endpoints of the point load test instrument, that is, the equivalent core diameter of the specimen, in mm; I s(50) is the point load strength index of a standard rock sample with a diameter of φ50mm; m is the correction index, determined according to the lithology, and is a constant.

6. The method for evaluating the rock mass quality grade based on the fracture image according to claim 1, wherein: The specific steps of image preprocessing in step S3 are as follows: S301, Select the rectangular plastic plate as a reference object. According to the actual size and pixel size of the rectangular plastic plate, calculate the pixel-length scale λ of this fracture image E , and the calculation method is shown in formula (3-1): Among them, A1 and B1 are the actual length and width values of the reference object, and a1 and b1 are the pixel length and width values of the reference object; S302, according to the pixel-length scale λ e Calculate the geometric dimensions A and B of the actual shooting area corresponding to the fracture image respectively, and the calculation formulas are as shown in (3-2) and (3-3): A = A1 / a1 × a (3-2) B = B1 / b1 × b (3-3) Among them, a and b are the pixel length and width values of this fracture image; S303. The actual geometric center point of the shooting area is denoted as O′(1 / 2A, 1 / 2B), and the pixel geometric center of the fissure image is denoted as O″(1 / 2a, 1 / 2b). Measure the vertical projection distance L of the shooting lens O relative to the shooting area. According to the angle value between the center point E(x1, y1) of the reference object and the vertical projection line of any point P(x i , y i ) in the area and the Pythagorean theorem, calculate the correction coefficient K of any point P(x i , y i ) relative to the center point E(x1, y1) of the reference object. The specific calculation method is shown in formulas (3-4) to (3-7) as follows: where λ is the standard pixel-length scale (cm / pixel) at the vertical shooting point, and λ p is the pixel-length scale (cm / pixel) at any point P, (x1, y1) is the coordinate point of the center point E of the reference object in the fracture image, and (x i , y i ) is the coordinate point of any point P in the fracture image; S304, traverse all pixel points outside the reference object area in the image, and correct the coordinate values of each pixel point one by one according to the corresponding K value of this point.

7. A method for evaluating the rock mass quality grade based on fracture images according to claim 1, characterized in that: The calculation method of the fracture spacing in step S5 is as follows: If two adjacent fractures do not intersect, use the midpoint spacing of the line connecting the fracture endpoints as the fracture spacing; if two adjacent fractures intersect, calculate the geometric center spacing based on the geometric center coordinates obtained in step S4 as the fracture spacing.

8. A method for evaluating the rock mass quality grade based on fracture images according to claim 1, characterized in that: The calculation methods of the volumetric joint number Jv and the rock quality designation RQD in step S6 are shown in formulas (6-1)-(6-2): RQD = 115 - 3.3J v (6 - 2) Among them, K is the conversion coefficient for converting the two-dimensional areal joint number to the three-dimensional volumetric joint number, with a value range of 1.15 - 1.35; n is the total number of joints in each fracture image; A is the actual area corresponding to each fracture image.

9. A method for evaluating the rock mass quality grade based on fracture images according to claim 1, characterized in that: The rock mass integrity index Kv in step S6 is quantified through its corresponding relationship table with the volumetric joint number Jv. The BQ value is quantified through the rock mass integrity index Kv, and the rock mass quality grade is obtained according to the BQ classification method, which is used to assist in determining the accuracy of the rock mass quality grade obtained in step S7. The calculation method of the BQ value is shown in formula (8): BQ = 100 + 3Rc + 250Kv (8) Among them, Rc is the uniaxial compressive strength of the rock block, that is, the rock block strength.

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