A method, device, equipment and readable storage medium for predicting peak shear strength of rock joint

Abstract

The application provides a method, device, equipment and readable storage medium for predicting peak shear strength of rock joints, the method comprising: scanning joint data of a rock to be predicted by a three-dimensional laser scanner, wherein the joint data comprises a plurality of joint point cloud data; converting a joint surface of the rock to be predicted into triangular microelements through the plurality of joint point cloud data; obtaining parameter data of the joint surface through the triangular microelements, wherein the parameter data comprises a plurality of normal stresses, a basic friction angle, a joint micro-asperity inclination angle, a uniaxial compressive strength and an average inclination angle of all microelements in an effective contact part of the joint surface of the rock to be predicted; and inputting the parameter data into a preset strength model to predict the peak shear strength of the joint of the rock to be predicted, wherein the strength model is obtained by predicting parameter data of different rocks under different stress states. The method can accurately predict the peak shear strength of the rock joint under high stress.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of rock shear strength prediction, in particular, to a method, device, equipment and readable storage medium for predicting rock joint peak shear strength. BACKGROUND

[0002] Rock mechanics and engineering geology is a discipline that studies the physical properties and mechanical behavior of rock and rock mass composed of rock, and is particularly concerned with the influence of the structural characteristics of rock mass on its mechanical properties. In the field of engineering geology, rock mass is usually not regarded as a homogeneous and continuous material, because the existence of internal structural surfaces (such as joints, cracks, etc.) in rock mass makes the rock mass exhibit anisotropic physical and mechanical behavior.

[0003] The existing model can reflect the anisotropy of joint shear strength, but the physical meaning of the fitting parameters is not clear, the joint dilatancy is limited by the normal stress, the convex body is seriously degenerated, and the shear failure becomes the main form of rock joint shear failure, resulting in inaccurate prediction of rock shear strength.

[0004] Therefore, how to accurately predict the joint peak shear strength of rock under high stress state is a technical problem to be solved. SUMMARY

[0005] The purpose of the embodiments of the present application is to provide a method for predicting the peak shear strength of rock joints, which can accurately predict the peak shear strength of rock joints under high stress state through the technical solutions of the embodiments of the present application.

[0006] In a first aspect, the embodiments of the present application provide a method for predicting the peak shear strength of rock joints, comprising: scanning joint data of a rock to be predicted by a three-dimensional laser scanner, wherein the joint data comprises a plurality of joint point cloud data; converting the joint surface of the rock to be predicted into triangular microelements through the plurality of joint point cloud data; obtaining parameter data of the joint surface through the triangular microelements, wherein the parameter data comprises a plurality of normal stresses, a basic friction angle, a joint micro-convex body inclination angle, a uniaxial compressive strength of the rock to be predicted, and an average inclination angle of all microelements in the effective contact part of the joint surface; inputting the parameter data into a preset strength model to predict the peak shear strength of the joint of the rock to be predicted, wherein the strength model is obtained by predicting the parameter data of different rocks under different stress states.

[0007] In the above embodiments, the conversion of joint point cloud data considers the influence of various normal stresses on the multi-factor characteristics of rock, and comprehensively predicts the peak shear strength of rock joints by considering various factors, which can accurately predict the peak shear strength of rock joints under high stress state.

[0008] In some embodiments, the parameter data of the joint surface is acquired by the triangular microelement, including: setting a plurality of normal stresses, and acquiring a plurality of uniaxial compressive strengths and a plurality of basic friction angles corresponding to the plurality of normal stresses under the plurality of normal stresses; calculating the average inclination of all microelements in the effective contact part of the joint surface based on the joint inclination distribution function and the minimum inclination of the effective contact part of the joint surface; and calculating the joint micro-asperity inclination of the joint surface under different normal stresses by the plurality of preset normal stresses, the plurality of uniaxial compressive strengths and the average inclination of all microelements in the effective contact part of the joint surface.

[0009] In the above embodiments, the compression damage model is corrected by the plurality of preset normal stresses, the plurality of uniaxial compressive strengths and the average inclination of all microelements in the effective contact part of the joint surface, so that the joint micro-asperity inclination of the rock can be accurately determined under the influence of a plurality of factors and the relationship between the inclination and the normal stress.

[0010] In some embodiments, the parameter data is input into a preset strength model to predict the joint peak shear strength of the rock to be predicted, including: predicting the joint peak shear strength by the joint micro-asperity inclination of the joint surface under the plurality of normal stresses, the plurality of normal stresses and the plurality of basic friction angles.

[0011] In the above embodiments, different shear strengths can be predicted under different normal stresses, and thus the peak shear strength of the rock can be accurately determined.

[0012] In some embodiments, the joint surface of the rock to be predicted is converted into a triangular microelement by a plurality of joint point cloud data, including: converting the joint surface of the rock to be predicted into a triangular microelement according to a preset interval by the plurality of joint point cloud data.

[0013] In the above embodiments, the joint surface obtained by laser scanning can accurately acquire the triangular microelement data.

[0014] In a second aspect, the embodiments of the present application provide a device for predicting the joint peak shear strength of rock, including:

[0015] The scanning module is configured to scan joint data of the rock to be predicted by a three-dimensional laser scanner, wherein the joint data includes a plurality of joint point cloud data.

[0016] The conversion module is configured to convert the joint surface of the rock to be predicted into a triangular microelement by the plurality of joint point cloud data.

[0017] The acquisition module is configured to acquire parameter data of the joint surface by the triangular microelement, wherein the parameter data includes a plurality of normal stresses, basic friction angles, joint micro-asperity inclinations, uniaxial compressive strengths and average inclinations of all microelements in the effective contact part of the joint surface of the rock to be predicted.

[0018] The prediction module is configured to input the parameter data into a preset strength model to predict the joint peak shear strength of the rock to be predicted, wherein the strength model is obtained by predicting parameter data of different rocks under different stress states.

[0019] Optionally, the acquisition module is specifically configured to:

[0020] a plurality of normal stresses are set, and a plurality of uniaxial compressive strengths corresponding to the plurality of normal stresses and a plurality of basic friction angles are acquired under the plurality of normal stresses;

[0021] based on the joint dip angle distribution function and the minimum dip angle of the effective contact part of the joint surface, the average dip angle of all microelements in the effective contact part of the joint surface is calculated;

[0022] the average dip angle of all microelements in the effective contact part of the joint surface, the plurality of normal stresses, and the plurality of uniaxial compressive strengths are preset, and the joint micro asperity dip angle of the joint surface under different normal stresses is calculated.

[0023] Optionally, the prediction module is specifically configured to:

[0024] the joint micro asperity dip angle of the joint surface under the plurality of normal stresses, the plurality of normal stresses, and the plurality of basic friction angles are used to predict the joint peak shear strength.

[0025] Optionally, the conversion module is specifically configured to:

[0026] the joint surface of the rock to be predicted is converted into triangular microelements according to a preset interval based on the plurality of joint point cloud data.

[0027] In a third aspect, an embodiment of the present application provides an electronic device, including a processor and a memory, the memory stores computer readable instructions, when the computer readable instructions are executed by the processor, the steps in the method provided in the first aspect are executed.

[0028] In a fourth aspect, an embodiment of the present application provides a readable storage medium, which stores a computer program, when the computer program is executed by a processor, the steps in the method provided in the first aspect are executed.

[0029] Other features and advantages of the present application will be described in the following description, and some will become apparent from the description, or will be understood from the practice of the present application. The purpose and other advantages of the present application can be achieved and obtained by the structures specifically pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF DRAWINGS

[0030] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly introduced as follows. It should be understood that the following drawings only show some of the embodiments of the present application, and therefore should not be regarded as a limitation on the scope, and for those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0031] Figure 1 A flow chart of a method for predicting peak shear strength of rock joint provided by the embodiments of the present application;

[0032] Figure 2 A rock joint point cloud digital model provided by the embodiments of the present application;

[0033] Figure 3 A schematic diagram of effective shear angle of jointed rock provided by the embodiments of the present application;

[0034] Figure 4 A schematic block diagram of a device for predicting peak shear strength of rock joint provided by the embodiments of the present application;

[0035] Figure 5 A structural schematic block diagram of a device for predicting peak shear strength of rock joint provided by the embodiments of the present application. DETAILED DESCRIPTION

[0036] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. The components of the embodiments of the present application described and shown in the drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of the present application.

[0037] It should be noted that: similar reference numerals and letters represent similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. Meanwhile, in the description of the present application, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0038] First, some terms involved in the embodiments of the present application will be explained in order to facilitate the understanding of those skilled in the art.

[0039] Rock shear strength refers to the maximum shear stress that can be resisted by rock under the action of shear load when it is broken. Rock shear strength is divided into rock direct shear strength and rock triaxial shear strength according to different test methods. Rock direct shear strength is divided into shear strength and shear (friction) strength. Shear strength refers to the strength of rock when it is broken by shear, and shear (friction) strength is the shear strength of rock when it is subjected to friction test after shear.

[0040] The present application is applied to the scene of rock shear strength prediction, and the specific scene is to predict the shear strength of rock under different normal stresses by converting rock point cloud data, considering different factors affecting the shear strength of rock, and accurately determining the peak shear strength of rock joints.

[0041] Rock mechanics and engineering geology is a discipline that studies the physical properties and mechanical behavior of rock and rock mass composed of rock. It is particularly concerned with the influence of the structural characteristics of rock mass on its mechanical properties. In the field of engineering geology, rock mass is not usually considered as a homogeneous and continuous material because of the existence of internal structural planes (such as joints, cracks, etc.) in rock mass, which makes rock mass exhibit anisotropic physical and mechanical behavior. Existing models can reflect the anisotropy of joint shear strength, but the physical meaning of the fitting parameters is not clear, the joint dilatancy is limited by the normal stress, the convex body is severely degraded, and shear failure becomes the main form of rock joint shear failure, resulting in inaccurate prediction of rock shear strength.

[0042] Therefore, the present application scans the joint data of the rock to be predicted by a three-dimensional laser scanner, wherein the joint data includes a plurality of joint point cloud data; converts the joint surface of the rock to be predicted into a triangular microelement through the plurality of joint point cloud data; obtains parameter data of the joint surface through the triangular microelement, wherein the parameter data includes a plurality of normal stresses, a basic friction angle, a joint micro-convex body inclination angle, a uniaxial compressive strength of the rock to be predicted, and an average inclination angle of all microelements in the effective contact part of the joint surface; inputs the parameter data into a preset strength model to predict the peak shear strength of the joint of the rock to be predicted, wherein the strength model is obtained by predicting different parameter data of different rocks under different stress states. By converting the joint point cloud data, considering the influence of various normal stresses on the multi-factor characteristics of rock, and comprehensively predicting the peak shear strength of rock joint, the peak shear strength of rock joint under high stress state can be accurately predicted.

[0043] In the embodiment of the present application, the execution subject can be a rock joint peak shear strength prediction device in a rock joint peak shear strength prediction system. In actual application, the rock joint peak shear strength prediction device can be a terminal device and a server, etc. electronic device, which is not limited here.

[0044] The following will be described in combination withFigure 1 The method for predicting the peak shear strength of rock joints according to the embodiments of the present application is described in detail.

[0045] Referring to Figure 1 , Figure 1 A flowchart of the method for predicting the peak shear strength of rock joints according to the embodiments of the present application is shown in Figure 1 The method for predicting the peak shear strength of rock joints includes the following steps.

[0046] Step 110: scanning the joint data of the rock to be predicted by a three-dimensional laser scanner.

[0047] The joint data includes a plurality of joint point cloud data. The joint point cloud data includes the position coordinates of all point clouds in the three-dimensional space of the rock. The rock to be predicted can be various types of rocks or rock groups.

[0048] Specifically, the joint point cloud digital model obtained by scanning the joint by the three-dimensional laser scanner can be obtained by Figure 2 .

[0049] Referring to Figure 2 , Figure 2 A rock joint point cloud digital model is provided according to the present application, which includes the three-dimensional coordinates of each point cloud of the rock.

[0050] Step 120: converting the joint surface of the rock to be predicted into triangular microelements by the plurality of joint point cloud data.

[0051] In some embodiments of the present application, converting the joint surface of the rock to be predicted into triangular microelements by the plurality of joint point cloud data includes: converting the joint surface of the rock to be predicted into triangular microelements according to a preset interval by the plurality of joint point cloud data.

[0052] In the above process, the joint surface obtained by laser scanning can accurately obtain the triangular microelement data.

[0053] The preset interval can be set according to requirements. After converting the joint surface of the rock to be predicted into triangular microelements according to the preset interval by the plurality of joint point cloud data, the effective shear inclination angle can be directly obtained by the joint point cloud data, and the relationship between the microelement area and the total area of the effective shear inclination angle can also be calculated by the plurality of joint point cloud data, as follows:

[0054] tanθ * =-tanθcosα;

[0055]

[0056] Wherein, cosθ = nn0 / |n||n0|cosα = tn1 / |t||n1| θ is the inclination of the joint microelement, θ * is the effective inclination of the joint microelement, α is the angle between the joint surface and the shear direction, t is the shear direction vector, n is the unit outer normal vector, n0 is the shear plane outer normal vector, n1 is the projection vector of the shear direction in the shear plane. A θ* represents the total area of the joint microelement, A0 is the ratio of the total area of all joint microelements with an inclination greater than 0 to the total area of the joint surface, θ * max is the maximum value of the effective inclination of the joint microelement, C is the fitting coefficient of the formula, and the point cloud data can be fitted into triangular microelement data through the fitting coefficient.

[0057] Optionally, the method for obtaining the triangular microelement can be obtained through Figure 3 the effective shear angle diagram shown in the figure.

[0058] Please refer to Figure 3 , Figure 3 is an effective shear angle diagram of joint rock provided by the present application, which comprises:

[0059] Figure 3 (a) joint morphology reconstruction diagram, Figure 3 (b) joint morphology local enlarged view, Figure 3 (c) triangular microelement. From Figure 3 (a) joint morphology, shear in the shear direction as shown in the figure can be obtained Figure 3 (b) joint morphology local, triangular microelement in the shear plane in (c) is obtained from the joint morphology local. Figure 3 (c).

[0060] Wherein, θ is the inclination of the joint microelement, θ * is the effective inclination of the joint microelement, α is the angle between the joint surface and the shear direction, t is the shear direction vector, n is the unit outer normal vector, n0 is the shear plane outer normal vector, n1 is the projection vector of the shear direction in the shear plane. A, B and C are respectively the vertices of the triangular microelement.

[0061] Step 130: obtaining the parameter data of the joint surface through the triangular microelement.

[0062] Wherein, the parameter data includes various normal stresses, basic friction angles, joint microconvex body inclinations, uniaxial compressive strengths and average inclinations of all microelements in the effective contact part of the joint surface of the rock to be predicted.

[0063] In some embodiments of the present application, the parameter data of the joint surface is obtained by the triangular microelement, including: setting a plurality of normal stresses, and obtaining a plurality of uniaxial compressive strengths and a plurality of basic friction angles corresponding to the plurality of normal stresses under the plurality of normal stresses; calculating the average inclination of all microelements in the effective contact part of the joint surface based on the joint inclination distribution function and the minimum inclination of the effective contact part of the joint surface; and calculating the joint micro asperity inclination of the joint surface under different normal stresses by the plurality of preset normal stresses, the plurality of uniaxial compressive strengths, and the average inclination of all microelements in the effective contact part of the joint surface.

[0064] In the above process, the compression damage model is corrected by the plurality of preset normal stresses, the plurality of uniaxial compressive strengths, and the average inclination of all microelements in the effective contact part of the joint surface, so that the joint micro asperity inclination of the rock can be accurately determined under the influence of various factors and the relationship between the inclination and the normal stress.

[0065] The plurality of normal stresses include a high normal stress, for example, a normal stress that can deform the rock.

[0066] Optionally, the average inclination of all microelements in the effective contact part of the joint surface can be obtained based on the joint inclination distribution function and the minimum inclination of the effective contact part of the joint surface by the following formula:

[0067]

[0068]

[0069]

[0070]

[0071] A θ* represents the total area of the joint microelement, A0 is the ratio of the total area of all joint microelements with an inclination greater than 0 to the total area of the joint surface, θ * max is the maximum value of the effective inclination of the joint microelement, C is a formula fitting coefficient, A c is the actual contact area, N is the normal load on the joint surface, σ c is the uniaxial compressive strength of the rock, A is the nominal area of the joint surface, σ n is the normal stress θ * cr1 represents the minimum inclination of all contact micro asperities, is the average inclination of all microelements in the actual contact part of the rough joint.

[0072] Step 140: inputting the parameter data into a preset strength model to predict the joint peak shear strength of the rock to be predicted.

[0073] The strength model is predicted by parameter data of different rocks under different stress states, including high normal stress state.

[0074] In some embodiments of the present application, the parameter data is input into a preset strength model to predict the joint peak shear strength of the rock to be predicted, including predicting the joint peak shear strength by the joint asperity inclination angle under multiple normal stresses, the multiple normal stresses and the multiple basic friction angles.

[0075] In the above process, the present application can predict different shear strengths under different normal stresses, and thus accurately determine the peak shear strength of the rock.

[0076] Optionally, predicting the joint peak shear strength by the joint asperity inclination angle under multiple normal stresses, the multiple normal stresses and the multiple basic friction angles includes predicting the joint shear strength corresponding to each normal stress by the joint asperity inclination angle under multiple normal stresses, the multiple normal stresses and the multiple basic friction angles, and thus determining the joint peak shear strength.

[0077] Specifically, predicting the joint peak shear strength by the joint asperity inclination angle under multiple normal stresses, the multiple normal stresses and the multiple basic friction angles can be obtained by the following formula:

[0078]

[0079]

[0080] wherein τ p is the peak shear strength, σ n is the normal stress, is the basic friction angle, i p is the joint asperity inclination angle, is the average inclination angle of all microelements of the actual contact part of the rough joint.

[0081] In the above Figure 1In the process shown, this application scans the joint data of the rock to be predicted using a 3D laser scanner. The joint data includes multiple joint point cloud data. Using these multiple joint point cloud data, the joint surfaces of the rock to be predicted are converted into triangular micro-elements. Through these triangular micro-elements, parameter data of the joint surfaces is obtained. This parameter data includes various normal stresses of the rock to be predicted, the basic friction angle, the dip angle of the joint micro-protrusions, the uniaxial compressive strength, and the average dip angle of all micro-elements within the effective contact portion of the joint surface. The parameter data is then input into a preset strength model to predict the peak joint shear strength of the rock to be predicted. By converting the joint point cloud data, considering multiple rock characteristics and combining the influence of various normal stresses, the peak joint shear strength of the rock can be predicted comprehensively, achieving the effect of accurately predicting the peak joint shear strength of the rock under high stress conditions.

[0082] The previous text passed Figure 1 A method for predicting the peak shear strength of rock joints is described below, in conjunction with... Figures 4-5 A device for predicting the peak shear strength of rock joints.

[0083] Please refer to Figure 4 This is a schematic block diagram of a device 400 for predicting the peak shear strength of rock joints provided in an embodiment of this application. The device 400 can be a module, program segment, or code on an electronic device. This device 400 is related to the above... Figure 1 The method implementation corresponds to this and can be executed. Figure 1 The various steps involved in the method embodiment, and the specific functions of the device 400, can be found in the following description. To avoid repetition, detailed descriptions are omitted here.

[0084] Optionally, the device 400 includes:

[0085] The scanning module 410 is used to scan the joint data of the rock to be predicted using a three-dimensional laser scanner, wherein the joint data includes multiple joint point cloud data;

[0086] The conversion module 420 is used to convert the joint surfaces of the rock to be predicted into triangular micro-elements using multiple joint point cloud data.

[0087] The acquisition module 430 is used to acquire parameter data of the joint surface through triangular micro-elements. The parameter data includes various normal stresses of the rock to be predicted, basic friction angle, joint micro-protrusion dip angle, uniaxial compressive strength, and average dip angle of all micro-elements in the effective contact part of the joint surface.

[0088] The prediction module 440 is used to input parameter data into a preset strength model to predict the peak joint shear strength of the rock to be predicted. The strength model is obtained by predicting the parameter data of different rocks under different stress states.

[0089] Optionally, the acquisition module 430 is specifically configured to:

[0090] a plurality of normal stresses are set, and a plurality of uniaxial compressive strengths and a plurality of basic friction angles corresponding to the plurality of normal stresses are acquired under the plurality of normal stresses; based on the joint dip angle distribution function and the minimum dip angle of the effective contact part of the joint surface, the average dip angle of all microelements in the effective contact part of the joint surface is calculated; the joint microconvex dip angle of the joint surface under different normal stresses is calculated through the plurality of normal stresses, the plurality of uniaxial compressive strengths and the average dip angle of all microelements in the effective contact part of the joint surface.

[0091] Optionally, the prediction module 440 is specifically configured to:

[0092] The joint peak shear strength is predicted through the joint microconvex dip angle of the joint surface under the plurality of normal stresses, the plurality of normal stresses and the plurality of basic friction angles.

[0093] Optionally, the conversion module 420 is specifically configured to:

[0094] The joint surface of the rock to be predicted is converted into triangular microelements according to the preset interval through the plurality of joint point cloud data.

[0095] Please refer to Figure 5 The structure of the device for predicting the peak shear strength of the rock joint provided in the embodiments of the present application is shown in the schematic block diagram, which can include a memory 510 and a processor 520. Optionally, the device can also include a communication interface 530 and a communication bus 540. The device corresponds to the above-mentioned Figure 1 method embodiments, and can execute Figure 1 the steps involved in the method embodiments. The specific functions of the device can be referred to the description in the following.

[0096] Specifically, the memory 510 is configured to store computer readable instructions.

[0097] The processor 520 is configured to process the readable instructions stored in the memory, and can execute Figure 1 each step in the method.

[0098] The communication interface 530 is configured to communicate with other node devices for signaling or data communication. For example, it is used for communication with a server or a terminal, or communication with other device nodes, which is not limited in the embodiments of the present application.

[0099] The communication bus 540 is configured to realize the direct connection communication of the above-mentioned components.

[0100] The communication interface 530 of the device in the embodiments of the present application is configured to communicate signaling or data with other node devices. The memory 510 can be a high-speed RAM memory or a non-volatile memory such as at least one disk memory. The memory 510 can alternatively be at least one storage device located away from the aforementioned processor. The memory 510 stores computer-readable instructions that, when executed by the processor 520, cause the electronic device to perform the method processes described above. Figure 1 The processor 520 can be used in the device 400 and configured to perform the functions in the embodiments of the present application. By way of example, the processor 520 described above can be a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, and the embodiments of the present application are not limited thereto.

[0101] The embodiments of the present application further provide a readable storage medium. When the computer program is executed by the processor, the method processes performed by the electronic device in the method embodiments described above are performed. Figure 1 The embodiments of the present application further provide a readable storage medium. When the computer program is executed by the processor, the method processes performed by the electronic device in the method embodiments described above are performed.

[0102] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the device described above can refer to the corresponding processes in the foregoing method, and will not be described in detail herein.

[0103] In summary, the embodiments of the present application provide a method, device, electronic device and readable storage medium for predicting the peak shear strength of rock joints. The method includes: scanning joint data of a rock to be predicted by a three-dimensional laser scanner, wherein the joint data includes a plurality of joint point cloud data; converting a joint surface of the rock to be predicted into a triangular microelement through the plurality of joint point cloud data; obtaining parameter data of the joint surface through the triangular microelement, wherein the parameter data includes a plurality of normal stresses, a basic friction angle, a joint micro-convex body inclination angle, a uniaxial compressive strength and an average inclination angle of all microelements in the effective contact part of the joint surface of the rock to be predicted; inputting the parameter data into a preset strength model to predict the peak shear strength of the joint of the rock to be predicted, wherein the strength model is obtained by predicting the parameter data of different rocks under different stress states. This method can accurately predict the peak shear strength of the rock joint under high stress state.

[0104] In several embodiments provided in the present application, it should be understood that the disclosed apparatus and method can also be implemented by other means. The apparatus embodiments described above are only illustrative, for example, the flowcharts and block diagrams in the drawings show the possible implementation architecture, function and operation of the apparatus, method and computer program product according to the embodiments of the present application. In this regard, each block in the flowchart or block diagram can represent a module, a program segment or a part of code, which contains one or more executable instructions for implementing the specified logic function. It should also be noted that in some alternative implementations, the functions noted in the blocks can occur in different order from that shown in the drawings. For example, two consecutive blocks can actually be executed substantially in parallel, and sometimes they can be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system for performing the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions.

[0105] In addition, the functional modules in the embodiments of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0106] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various program code storage media.

[0107] The above merely provides an example of the present application and is not intended to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application. It should be noted that similar reference numerals and letters represent similar items in the following drawings, and thus, once an item is defined in one drawing, it need not be further defined and explained in subsequent drawings.

[0108] The above merely provides an example of the present application and is not intended to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application. It should be noted that similar reference numerals and letters represent similar items in the following drawings, and thus, once an item is defined in one drawing, it need not be further defined and explained in subsequent drawings.

[0109] It should be noted that the relational terms herein such as first and second and the like are used solely to distinguish one from another entity or action without necessarily requiring or implying any actual relationship or order between such entities or actions. Moreover, the terms "comprises", "comprising", or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a" does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

Claims

1. A method for predicting the peak shear strength of rock joints, characterized in that, include: The joint data of the rock to be predicted is scanned using a three-dimensional laser scanner, wherein the joint data includes multiple joint point cloud data; Using the multiple joint point cloud data, the joint surfaces of the rock to be predicted are converted into triangular micro-elements; The parameter data of the joint surface is obtained through the triangular micro-element, wherein the parameter data includes various normal stresses, basic friction angles, joint micro-protrusion dip angles, uniaxial compressive strengths, and the average dip angle of all micro-elements within the effective contact portion of the joint surface of the rock to be predicted; The parameter data is input into a preset strength model to predict the peak joint shear strength of the rock to be predicted. The strength model is obtained by predicting the parameter data of different rocks under different stress states. The step of obtaining parameter data of the joint surface through the triangular micro-element includes: The various normal stresses are set, and under the various normal stress conditions, the various uniaxial compressive strengths and multiple basic friction angles corresponding to the various normal stresses are obtained; Based on the joint dip angle distribution function and the minimum dip angle of the effective contact portion of the joint surface, the average dip angle of all micro-elements within the effective contact portion of the joint surface is calculated; By using the preset multiple normal stresses, multiple uniaxial compressive strengths, and the average tilt angle of all micro-elements within the effective contact portion of the joint surface, the tilt angle of the joint micro-protrusions under different normal stresses is calculated.

2. The method according to claim 1, characterized in that, The step of inputting the parameter data into a preset strength model to predict the peak joint shear strength of the rock to be predicted includes: The peak shear strength of the joint is predicted by the joint micro-protrusion inclination angle, the various normal stresses, and the multiple basic friction angles under the various normal stresses.

3. The method according to any one of claims 1-2, characterized in that, The step of converting the joint surfaces of the rock to be predicted into triangular micro-elements using the multiple joint point cloud data includes: Using the multiple joint point cloud data, the joint surfaces of the rock to be predicted are converted into triangular micro-elements according to a preset spacing.

4. A device for predicting the peak shear strength of rock joints, characterized in that, include: The scanning module is used to scan the joint data of the rock to be predicted using a three-dimensional laser scanner, wherein the joint data includes multiple joint point cloud data; The conversion module is used to convert the joint surfaces of the rock to be predicted into triangular micro-elements using the multiple joint point cloud data. The acquisition module is used to acquire parameter data of the joint surface through the triangular micro-element, wherein the parameter data includes various normal stresses, basic friction angles, joint micro-protrusion dip angles, uniaxial compressive strengths, and the average dip angle of all micro-elements within the effective contact portion of the joint surface of the rock to be predicted; The prediction module is used to input the parameter data into a preset strength model to predict the peak joint shear strength of the rock to be predicted, wherein the strength model is obtained by predicting the parameter data of different rocks under different stress states; The acquisition module is specifically used for: The various normal stresses are set, and under the various normal stress conditions, the various uniaxial compressive strengths and multiple basic friction angles corresponding to the various normal stresses are obtained; Based on the joint dip angle distribution function and the minimum dip angle of the effective contact portion of the joint surface, the average dip angle of all micro-elements within the effective contact portion of the joint surface is calculated; By using the preset multiple normal stresses, multiple uniaxial compressive strengths, and the average tilt angle of all micro-elements within the effective contact portion of the joint surface, the tilt angle of the joint micro-protrusions under different normal stresses is calculated.

5. The apparatus according to claim 4, characterized in that, The prediction module is specifically used for: The peak shear strength of the joint is predicted by the joint micro-protrusion inclination angle, the various normal stresses, and the multiple basic friction angles under the various normal stresses.

6. The apparatus according to any one of claims 4-5, characterized in that, The conversion module is specifically used for: Using the multiple joint point cloud data, the joint surfaces of the rock to be predicted are converted into triangular micro-elements according to a preset spacing.

7. An electronic device, characterized in that, include: A memory and a processor, the memory storing computer-readable instructions that, when executed by the processor, perform the steps of the method as described in any one of claims 1-3.

8. A computer-readable storage medium, characterized in that, include: A computer program that, when run on a computer, causes the computer to perform the method as described in any one of claims 1-3.

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