Multi-dimensional block deconstruction and fragmentation degree quantitative assessment method and system for fractured rock mass

Abstract

The present invention proposes a method and system for quantitatively evaluating the multi-dimensional block size deconstruction and fragmentation degree of fractured rock mass, and relates to the technical field of engineering geological survey. It includes obtaining the geometric distribution information of the tunnel face; constructing the original rock mass joint network model based on the geometric distribution information of the tunnel face to achieve the true reproduction of the distribution morphology of the structural surface of the jointed surrounding rock mass; performing image processing on the rock mass joint network model to form a regular network; searching, selecting and analyzing the independent blocks in the original rock mass joint network model and the image in the regular network, establishing an area equivalent statistical model for the selected independent blocks, and performing block size grading, and performing quantitative normalization with the relative content of the selected independent blocks as parameters; judging the degree of fragmentation of the fractured rock mass based on the results of quantitative normalization. The present invention breaks the industry barriers between many specifications, provides a unified quantitative evaluation method for determining the degree of fragmentation of fractured rock mass, and provides strong support for geological surveys in engineering construction.

Description

Technical Field

[0001] The invention belongs to the technical field of engineering geological survey, and in particular relates to a method and system for quantitatively evaluating the multi-dimensional block deconstruction and fragmentation degree of a fractured rock mass. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] Fractured rock mass can be regarded as a complex block structure system composed of rock blocks of different sizes, and the size and combination of the rock blocks are precisely the "root cause" that affects the degree of fragmentation of the rock mass itself.

[0004] For the analysis and evaluation of the block structure system of fractured rock mass, there are many block size indicators. b , rock mass integrity index Kv, volume joint number Jv, rock mass structure grade (SR) and Q system method, RMR method and quantitative and semi-quantitative indicators in domestic industry standards, which also produced a series of research on the correlation model between various rock mass integrity measurement indicators and between different surrounding rock grade assessment standards. However, the inventors found that there are many rock mass structure classification standards in the prior art, and different industries have different research focuses, and the classification standards for rock mass structures are also different. In addition, there are a large number of qualitative descriptions. In applied research, many scholars generally select standards from the perspective of their respective research object needs, resulting in industry barriers in the data conclusions obtained, which are difficult to be universal. Summary of the invention

[0005] In order to overcome the shortcomings of the above-mentioned prior art, the present invention provides a method and system for quantitative assessment of multi-dimensional block deconstruction and fragmentation degree of fractured rock mass, breaking the industry barriers between numerous specifications, providing a unified quantitative assessment method for determining the fragmentation degree of fractured rock mass, and providing strong support for geological surveys in engineering construction.

[0006] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions:

[0007] The first aspect of the present invention provides a method for quantitatively evaluating the multi-dimensional block deconstruction and fragmentation degree of a fractured rock mass.

[0008] The method for quantitatively evaluating the multi-dimensional block deconstruction and fragmentation degree of fractured rock mass includes the following steps:

[0009] Obtaining the geometric layout information of the tunnel face;

[0010] Based on the geometric distribution information of the tunnel face, the original rock mass joint network model is constructed to achieve the true reproduction of the distribution morphology of the joint surrounding rock mass structure surface;

[0011] Performing image processing on the rock mass joint network model to form a regular network;

[0012] Search, select and analyze the independent blocks in the original rock mass joint network model and the regular network image, establish an area equivalent statistical model for the selected independent blocks, and perform block size grading, and use the relative content of the selected independent blocks as a parameter for quantitative normalization;

[0013] Based on the results of quantitative normalization, the degree of fragmentation of the fractured rock mass is determined.

[0014] Optionally, construct a rock mass joint network model (X1, X2, ..., X i ,...,X n ), where Xi refers to the i-th rock mass joint network model, X i Each joint group x in the model i The spacing, inclination and trace length of (i=1, 2, 3, ..., n) all conform to a given profile, which includes normal distribution, log-normal distribution, uniform distribution and exponential distribution.

[0015] Optional, X i Each joint group x in the model i The spacing, inclination and trace length of (i=1,2,3,...,n) all conform to the given profile, including:

[0016] Select the specific type of a given probability pattern and generate spacing and angles that conform to the given distribution probability pattern;

[0017] Randomly select an endpoint based on the spacing and angle, and use the endpoint as the rotation center;

[0018] Calculate the distance between the endpoint and the boundary intersection point according to the endpoint position and angle to obtain the intersection point spacing;

[0019] Generate a trace length that conforms to a given distribution profile and adapts to the intersection point spacing;

[0020] Assign the track length and direction according to the distance between the endpoint and the intersection point;

[0021] The end point is calculated based on the angle, endpoint, trace length, and strike, and the drawing of the rock joint network model is completed.

[0022] Optionally, pixel point cloud data is added to the original rock mass joint network model so that each trace length in the original rock mass joint network model image is extended until a new intersection appears, thereby forming a regular network.

[0023] Optionally, the original rock mass joint network model and the independent blocks in the regular network image are searched, selected and analyzed, and an area equivalent statistical model is established for the selected independent blocks, specifically:

[0024] Selecting the original closed blocks formed in the image of the original rock mass joint network model;

[0025] Eliminate the original closed blocks in the regularized network image, then identify the closed blocks therein to obtain the later closed blocks;

[0026] Set the threshold and select the valid blocks in the later closed blocks;

[0027] In the image of the regular network from which the original closed blocks have been removed, effective blocks in the later closed blocks are further removed, and overall nearby search and analysis are performed to select the reconstructed effective blocks;

[0028] An area equivalent statistical model is established, in which the selected original closed blocks are equivalent to the same area, and the effective blocks and reconstructed effective blocks in the later closed blocks are enlarged and equivalent to the area.

[0029] Optionally, a threshold C is set for the later closed block, where C = Σthe length of the newly added trace in the closed block / the perimeter of the closed block formed by it. Blocks larger than the threshold C are regarded as invalid blocks, and blocks smaller than the threshold C are regarded as valid blocks.

[0030] Optionally, a block size gradation interval is set, and block size gradation is performed on the area equivalent statistical model based on the block size gradation interval;

[0031] Taking the relative content of each block size as the main parameter, define:

[0032] RBI 2D =S1+2S2+3S3+4S4+5S5

[0033] Among them, S1, S2, S3, S4, S5 are: less than 0.01m 2 , 0.01~0.1m 2 , 0.1~0.5m 2 , 0.5~1.0m 2 , greater than 1.0m 2 Relative content of block size; RBI 2D The smaller the value, the more fragmented the fractured rock mass.

[0034] The second aspect of the present invention provides a system for quantitatively evaluating the multi-dimensional block deconstruction and fragmentation degree of fractured rock mass.

[0035] The multi-dimensional block deconstruction and fragmentation degree quantitative assessment system of fractured rock mass includes:

[0036] The tunnel face information acquisition module is configured to: acquire tunnel face geometric distribution information;

[0037] The original rock mass joint network model construction module is configured to: construct the original rock mass joint network model based on the geometric distribution information of the tunnel face, so as to realize the true reproduction of the distribution morphology of the joint surrounding rock mass structure surface;

[0038] The regular network acquisition module is configured to: perform image processing on the rock mass joint network model to form a regular network;

[0039] The independent block selection and quantitative normalization module is configured to: search, select and analyze the independent blocks in the original rock mass joint network model and the regular network image, establish an area equivalent statistical model for the selected independent blocks, and perform block size grading, and perform quantitative normalization with the relative content of the selected independent blocks as a parameter;

[0040] The evaluation and judgment module is configured to: judge the degree of fragmentation of the fractured rock mass based on the result of quantitative normalization.

[0041] The third aspect of the present invention provides a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps in the method for multi-dimensional block deconstruction and quantitative assessment of the degree of fragmentation of fractured rock mass as described in the first aspect of the present invention.

[0042] The fourth aspect of the present invention provides an electronic device, including a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, the steps in the method for multi-dimensional block deconstruction and quantitative assessment of the degree of fragmentation of fractured rock mass as described in the first aspect of the present invention are implemented.

[0043] One or more of the above technical solutions have the following beneficial effects:

[0044] The present invention proposes a method and system for multi-dimensional block deconstruction and quantitative assessment of the degree of fragmentation of fractured rock mass, and provides a universal processing method for analyzing and assessing the degree of fragmentation of fractured rock mass. The core technology is: based on the "intelligent interpretation of rock mass structure information and cloud-based interactive surrounding rock classification system", the geometric distribution information data of the tunnel face is automatically obtained, and then the joint network simulation model is constructed for the distribution data through programming technology. After image processing, the block size is analyzed, equivalent, screened, and calculated, and RBI is set. 2D , with RBI 2D Realize the quantitative normalization of the discrete degree of block rock mass. Through efficient network circulation and utilization, the block size of fractured rock mass can be deconstructed quickly and accurately. 2D The proposal makes up for the problem that different industries have different research focuses and classification standards on rock structure, resulting in industry barriers and difficulty in universal application of the data conclusions obtained.

[0045] The processing method of the present invention provides another powerful support for determining the degree of fragmentation of fractured rock mass, brings great convenience to tunnel construction, and can shorten the construction period and save costs.

[0046] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0048] Figure 1 This is an overall flow chart of Embodiment 1 of the present invention;

[0049] Figure 2(a) is a schematic diagram of automatically obtaining the geometric distribution information data of the tunnel face based on the "intelligent interpretation of rock mass structure information and cloud-based interactive surrounding rock classification system";

[0050] FIG2( b ) is a schematic diagram of the acquired tunnel face geometric distribution information data;

[0051] Figure 3 This is a schematic diagram of the original rock mass joint network model;

[0052] Figure 4 This is a schematic diagram of the regular network of the original rock mass joint network model after image processing;

[0053] Figure 5(a) is the first batch of equivalent schematic diagrams during the independent block search process;

[0054] Figure 5(b) is a schematic diagram of the second batch of equivalents during the independent block search process;

[0055] Figure 5(c) is a schematic diagram of the third batch of equivalents in the overall proximity search process;

[0056] Figure 6 This is the actual application effect diagram of a certain fractured rock mass. DETAILED DESCRIPTION

[0057] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0058] It should be noted that the terms used herein are for describing specific embodiments only and are not intended to be limiting of exemplary embodiments according to the present invention.

[0059] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0060] Overall concept:

[0061] The present invention discloses a method for multi-dimensional block deconstruction and unified quantitative assessment of the degree of fragmentation of fractured rock mass. It uses the independent "intelligent interpretation of rock mass structure information and cloud-interactive surrounding rock classification system" to automatically obtain the geometric distribution information data of the tunnel face, and then uses C++ to build a joint network simulation model for the distribution data. Finally, image processing is used to perform block analysis, equivalence and screening on the established simulation model, and a unified quantitative assessment method for the degree of fragmentation of fractured rock mass is proposed based on the relative content of each block contained in the model. The efficient networked circulation and utilization in this processing method can quickly and accurately deconstruct the block of fractured rock mass, provide another strong support for determining the degree of fragmentation of fractured rock mass, bring great convenience to tunnel construction, shorten construction period and save costs.

[0062] Embodiment 1

[0063] This embodiment discloses a method for quantitatively evaluating the multi-dimensional block deconstruction and fragmentation degree of a fractured rock mass.

[0064] like Figure 1 As shown in the figure, the method for quantitatively evaluating the multi-dimensional block deconstruction and fragmentation degree of fractured rock mass includes the following steps:

[0065] Obtaining the geometric layout information of the tunnel face;

[0066] Based on the geometric distribution information of the tunnel face, the original rock mass joint network model is constructed to achieve the true reproduction of the distribution morphology of the joint surrounding rock mass structure surface;

[0067] Performing image processing on the rock mass joint network model to form a regular network;

[0068] Search, select and analyze the independent blocks in the original rock mass joint network model and the regular network image, establish an area equivalent statistical model for the selected independent blocks, and perform block size grading, and use the relative content of the selected independent blocks as a parameter for quantitative normalization;

[0069] Based on the results of quantitative normalization, the degree of fragmentation of the fractured rock mass is determined.

[0070] The meaning of the distribution morphology of the structural surface of the jointed surrounding rock mass is: using the geometric distribution information of the tunnel face to construct a rock mass joint network model to achieve the true reproduction of the distribution morphology of the structural surface of the jointed surrounding rock mass, which is the inverse process explained below.

[0071] Generally speaking, researchers go to the site to collect statistics on the geometric distribution information (data) of the tunnel face based on its morphological characteristics - a positive process;

[0072] Based on statistical information (geometric distribution information of the tunnel face), a model is constructed on the computer, and the tunnel face morphological characteristics are restored on the computer - the inverse process.

[0073] like Figure 1 As shown, the present invention discloses a method for unified quantitative assessment of multi-dimensional block deconstruction and fragmentation degree of fractured rock mass, which can be applied to the analysis and assessment of the fragmentation degree of underground fractured rock mass in different industries. Figure 1 , a method for unified quantitative assessment of multi-dimensional block deconstruction and fragmentation degree of fractured rock mass in this embodiment is described in detail, which specifically includes the following steps:

[0074] Step S01, as shown in FIG. 2(a) and FIG. 2(b), automatically obtain the geometric distribution information data of the tunnel face based on the "intelligent interpretation of rock structure information and cloud-based interactive surrounding rock classification system".

[0075] In Figure 2(a), the text on the left side of the image is the content of the "Rock Mass Structure Information Intelligent Interpretation and Cloud Interactive Surrounding Rock Classification System" in the prior art, from top to bottom:

[0076] Home page, image processing, image interpretation, quick overview of image translation, quick overview of interpretation, rock mass home page, BQ algorithm, BQ classification, RMR method, Q method.

[0077] Automatically obtain the geometric distribution information data of the tunnel face, mainly to obtain the geometric distribution form (spacing, inclination, trace length, etc.) of the tunnel face in groups.

[0078] Step S02: Figure 3 As shown, the geometric distribution information data obtained in step S01 is used to construct a rock mass joint network model to achieve true reproduction of the distribution morphology of the joint surrounding rock mass structural surface.

[0079] In the batch construction of rock mass joint network model, the model (X1, X2, ..., X i ,...,X n ).

[0080] Where X i Each joint group x in the model i The spacing, inclination and trace length of (i=1,2,3,...,n) can be selected from normal distribution, lognormal distribution, uniform distribution and exponential distribution. The specific implementation steps include:

[0081] A1. Generate spacing and angles that conform to a given distribution profile;

[0082] A2. Randomly select an endpoint (rotation center) based on the spacing and angle;

[0083] A3. Calculate the distance to the boundary intersection point based on the endpoint position and angle;

[0084] A4, generate a trace length that conforms to a given distribution profile and is adapted to the intersection point spacing;

[0085] A5. Allocate the length and direction of the trace according to the distance between the endpoint and the intersection point;

[0086] A6. Calculate the end point based on the angle, endpoint, trace length, and direction;

[0087] A8. Draw the network model.

[0088] Step S03: Figure 4 As shown, the model image is processed. Pixel point cloud data is added to the model drawn based on matlab, so that each trace in the model image is extended to a new intersection to form a more regular network.

[0089] Step S04: Analyze, equalize, screen and calculate the processed image. Specifically, step S04 includes steps S041 to S044.

[0090] Step S041: Search and analyze each independent block:

[0091] B1. The first batch of equivalents: As shown in Figure 5(a), the formed relatively regular network is searched for each independent block, and the closed block that has been formed without adding pixel point cloud data is identified, that is, the original closed block K1, and the same area is equivalent to each original closed block K1 in the equivalent statistical model, S = S K1 ;

[0092] B2, the original closed block K1 after equivalent completion is eliminated, and the K1 after equivalent completion is no longer searched;

[0093] B3. The second batch of equivalents: As shown in Figure 5(b), continue to search for each independent block in the relatively regular network (K1 has been eliminated), identify the closed block formed by adding pixel point cloud data, that is, the later closed block K2; set a threshold C (C = Σ newly added trace length in the closed block / the perimeter of the closed block formed by it) for the later closed block, and blocks greater than the threshold C = 0.2 are considered invalid blocks, and blocks less than the threshold C are considered valid blocks K3. In the equivalent statistical model, enlarge the area of ​​each valid block K3 formed later, S = (1 + C)S K3 ;

[0094] B4. Continue to remove the effective block K3 after equivalent completion, and K3 after equivalent completion will no longer be searched.

[0095] S042. Conduct an overall nearby search and analysis on the joint network excluding K1 and K3:

[0096] B5. As shown in Figure 5(c), the breadth-first search algorithm is optimized to perform an overall nearby search on the joint network with only the remaining independent invalid block K2. After iterative calculations, if independent invalid blocks are combined into a valid block, that is, the reconstructed valid block K4, then the area of ​​the reconstructed valid block K4 is also enlarged in the equivalent statistical model, S = (1 + C) S K4 .

[0097] S043. According to the area equivalent statistical model, the block size is graded and the relative content of each block size is used as the main parameter to calculate the RBI. 2D .

[0098] RBI in this embodiment 2D Blockness index 2D .

[0099] B6. Set block size gradation interval (<0.01m 2 , 0.01~0.1m 2 , 0.1~0.5m 2 , 0.5~1.0m 2 、>1.0m 2 ), block size grading is performed on the area equivalent statistical model;

[0100] B7. Calculate RBI using the relative content of each size (S1, S2, S3, S4, S5) as the main parameter 2D Value (RBI 2D =S1+2S2+3S3+4S4+5S5, RBI 2D ∈[1,5]), the smaller its value is, the more broken the fractured rock mass is.

[0101] The present invention is a method for unified quantitative evaluation of multi-dimensional block deconstruction and fragmentation degree of fractured rock mass, using RBI 2D The values ​​are uniformly quantified to determine the degree of fragmentation of the fractured rock mass, such as Figure 6 The figure shows the result of the method described in this embodiment in actual engineering application.

[0102] Embodiment 2

[0103] This embodiment discloses a system for quantitatively evaluating the multi-dimensional block deconstruction and fragmentation degree of fractured rock mass.

[0104] The multi-dimensional block deconstruction and fragmentation degree quantitative assessment system of fractured rock mass includes:

[0105] The tunnel face information acquisition module is configured to: acquire tunnel face geometric distribution information;

[0106] The original rock mass joint network model construction module is configured to: construct the original rock mass joint network model based on the geometric distribution information of the tunnel face, so as to realize the true reproduction of the distribution morphology of the joint surrounding rock mass structure surface;

[0107] The regular network acquisition module is configured to: perform image processing on the rock mass joint network model to form a regular network;

[0108] The independent block selection and quantitative normalization module is configured to: search, select and analyze the independent blocks in the original rock mass joint network model and the regular network image, establish an area equivalent statistical model for the selected independent blocks, and perform block size grading, and perform quantitative normalization with the relative content of the selected independent blocks as a parameter;

[0109] The evaluation and judgment module is configured to: judge the degree of fragmentation of the fractured rock mass based on the result of quantitative normalization.

[0110] Embodiment 3

[0111] The purpose of this embodiment is to provide a computer-readable storage medium.

[0112] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the method for multi-dimensional block deconstruction and quantitative assessment of the degree of fragmentation of a fractured rock mass as described in Example 1 of the present disclosure.

[0113] Embodiment 4

[0114] The purpose of this embodiment is to provide an electronic device.

[0115] An electronic device includes a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, the steps in the method for multi-dimensional block deconstruction and quantitative assessment of the degree of fragmentation of fractured rock mass as described in Example 1 of the present disclosure are implemented.

[0116] The steps involved in the apparatuses of the above embodiments 2, 3 and 4 correspond to the method embodiment 1, and the specific implementation methods can refer to the relevant description part of embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood to include any medium that can store, encode or carry an instruction set for execution by a processor and enable the processor to execute any method in the present invention.

[0117] Those skilled in the art should understand that the modules or steps of the present invention described above can be implemented by a general-purpose computer device, or alternatively, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. The present invention is not limited to any specific combination of hardware and software.

[0118] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. A method for quantitatively evaluating the multi-dimensional block deconstruction and fragmentation degree of fractured rock mass, characterized in that: The following steps are involved: Obtaining the geometric layout information of the tunnel face; Based on the geometric distribution information of the tunnel face, the original rock mass joint network model is constructed to achieve the true reproduction of the distribution morphology of the joint surrounding rock mass structure surface; Performing image processing on the rock mass joint network model to form a regular network; Search, select and analyze the independent blocks in the original rock mass joint network model and the regular network image, establish an area equivalent statistical model for the selected independent blocks, and perform block size grading, and use the relative content of the selected independent blocks as a parameter for quantitative normalization; Based on the results of quantitative normalization, the degree of fragmentation of the fractured rock mass is determined; The rock mass joint network model (X1, X2, ..., X i ,...,X n ), where X i Each joint group x in the model i The spacing, inclination and trace length of (i=1, 2, 3, ..., n) all conform to a given probability profile, wherein the given probability profile includes normal distribution, lognormal distribution, uniform distribution and exponential distribution; X i Each joint group x in the model i The spacing, inclination and trace length of (i=1,2,3,...,n) all conform to the given profile, including: Select the specific type of a given probability pattern and generate spacing and angles that conform to the given distribution probability pattern; Randomly select an endpoint based on the spacing and angle, and use the endpoint as the rotation center; Calculate the distance between the endpoint and the boundary intersection point according to the endpoint position and angle to obtain the intersection point spacing; Generate a trace length that conforms to a given distribution profile and adapts to the intersection point spacing; Assign the track length and direction according to the distance between the endpoint and the intersection point; The end point is calculated based on the angle, endpoint, trace length, and strike, and the drawing of the rock joint network model is completed.

2. The method for quantitatively evaluating the multi-dimensional block deconstruction and fragmentation degree of fractured rock mass according to claim 1, characterized in that: Adding pixel point cloud data to the original rock mass joint network model makes each trace length in the original rock mass joint network model image extend to the appearance of new intersections, thus forming a regular network.

3. The method for quantitatively evaluating the multi-dimensional block deconstruction and fragmentation degree of fractured rock mass according to claim 2, characterized in that: The original rock mass joint network model and the independent blocks in the regular network image are searched, selected and analyzed, and the area equivalent statistical model is established for the selected independent blocks, specifically: Selecting the original closed blocks formed in the image of the original rock mass joint network model; Eliminate the original closed blocks in the regularized network image, then identify the closed blocks therein to obtain the later closed blocks; Set the threshold and select the valid blocks in the later closed blocks; In the image of the regular network from which the original closed blocks have been removed, effective blocks in the later closed blocks are further removed, and overall nearby search and analysis are performed to select the reconstructed effective blocks; An area equivalent statistical model is established, in which the selected original closed blocks are equivalent to the same area, and the effective blocks and reconstructed effective blocks in the later closed blocks are enlarged and equivalent to the area.

4. The method for quantitatively evaluating the multi-dimensional block deconstruction and fragmentation degree of fractured rock mass according to claim 3, characterized in that: A threshold C is set for the later closed blocks, where C = Σthe length of the newly added trace in the closed block / the perimeter of the closed block formed by it. Blocks larger than the threshold C are considered invalid blocks, and blocks smaller than the threshold C are considered valid blocks.

5. The method for quantitatively evaluating the multi-dimensional block deconstruction and fragmentation degree of a fractured rock mass according to claim 1, characterized in that: Set the block size gradation interval, and perform block size gradation on the area equivalent statistical model based on the block size gradation interval; Taking the relative content of each block size as the main parameter, define: RBI 2D =S1+2S2+3S3+4S4+5S5 Among them, S1, S2, S3, S4, S5 are: less than 0.01m 2 , 0.01~0.1m 2 , 0.1~0.5m 2 , 0.5~1.0m 2 , greater than 1.0m 2 Relative content of block size; RBI 2D The smaller the value, the more fragmented the fractured rock mass.

6. A multi-dimensional block deconstruction and fragmentation degree quantitative assessment system for fractured rock mass, characterized by: The method for quantitatively evaluating the multi-dimensional block deconstruction and fragmentation degree of a fractured rock mass according to any one of claims 1 to 5 is implemented, comprising: The tunnel face information acquisition module is configured to: acquire tunnel face geometric distribution information; The original rock mass joint network model construction module is configured to: construct the original rock mass joint network model based on the geometric distribution information of the tunnel face, so as to realize the true reproduction of the distribution morphology of the joint surrounding rock mass structure surface; The regular network acquisition module is configured to: perform image processing on the rock mass joint network model to form a regular network; The independent block selection and quantitative normalization module is configured to: search, select and analyze the independent blocks in the original rock mass joint network model and the regular network image, establish an area equivalent statistical model for the selected independent blocks, and perform block size grading, and perform quantitative normalization with the relative content of the selected independent blocks as a parameter; The evaluation and judgment module is configured to: judge the degree of fragmentation of the fractured rock mass based on the result of quantitative normalization.

7. A computer-readable storage medium having a program stored thereon, characterized in that: When the program is executed by a processor, the steps in the method for multi-dimensional block deconstruction and quantitative assessment of the degree of fragmentation of fractured rock mass as described in any one of claims 1 to 5 are implemented.

8. An electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps in the method for multi-dimensional block deconstruction and quantitative assessment of the degree of fragmentation of fractured rock mass as described in any one of claims 1 to 5 are implemented.

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