Method and system for predicting breaking degree of tunnel face surrounding rock suitable for tunnel excavation

Abstract

The invention discloses a tunnel face surrounding rock crushing degree prediction method and system suitable for tunnel excavation, and the method comprises the steps: obtaining first data corresponding to tunnel excavation in real time, and preprocessing the first data; wherein the first data comprises drilling depth data and thrust data; creating a single-tooth thrust theoretical model, and generating second data corresponding to rock in tunnel excavation according to the single-tooth thrust theoretical model and based on the first data; wherein the second data comprises rock physical and mechanical parameter data and rock crushing degree data; according to the second data, third data corresponding to tunnel excavation are generated in real time; wherein the third data is tunnel face surrounding rock crushing degree prediction data corresponding to tunnel excavation, and the system corresponding to the method can predict the tunnel face surrounding rock crushing degree through the drilling depth, thrust and other data, and provides accurate surrounding rock crushing degree prediction for tunnel engineering construction.

Description

Technical Field

[0001] The present invention belongs to the technical field of tunnel construction treatment, and particularly relates to a prediction method and system for the degree of fragmentation of the face rock mass suitable for tunnel excavation. Background Technique

[0002] At present, during tunnel excavation, accurately predicting the degree of fragmentation of the face rock mass is crucial for ensuring construction safety and engineering quality. However, the degree of fragmentation of the rock mass is affected by various factors, such as the physical and mechanical properties of the rock, geological structures, excavation methods, and in-situ stresses. Current prediction methods often have difficulty comprehensively considering these factors, resulting in inaccurate prediction results.

[0003] In addition, digital advanced drilling relies on establishing a quantitative relationship between drilling parameters and rock mass characteristics. However, existing research mainly focuses on qualitative relationships, and there is little research on rock layers with different degrees of fragmentation.

[0004] Therefore, aiming at the technical problem defects that the current prediction methods for the degree of fragmentation of the face rock mass often have difficulty comprehensively considering factors such as the physical and mechanical properties of the rock, geological structures, excavation methods, and in-situ stresses, resulting in inaccurate prediction results, it is urgent to design and develop a prediction method, system, and platform for the degree of fragmentation of the face rock mass suitable for tunnel excavation. Summary of the Invention

[0005] To overcome the deficiencies and difficulties of the above-mentioned prior art, the purpose of the present invention is to provide a prediction method and system for the degree of fragmentation of the face rock mass suitable for tunnel excavation, so as to predict the degree of fragmentation of the face rock mass through data such as drilling depth and thrust, and provide an accurate prediction of the degree of fragmentation of the rock mass for tunnel engineering construction.

[0006] The first object of the present invention is to provide a prediction method for the degree of fragmentation of the face rock mass suitable for tunnel excavation; the second object of the present invention is to provide a prediction system for the degree of fragmentation of the face rock mass suitable for tunnel excavation; the third object of the present invention is to provide a prediction platform for the degree of fragmentation of the face rock mass suitable for tunnel excavation.

[0007] The first object of the present invention is achieved as follows: The method includes the following steps:

[0008] Obtain first data corresponding to tunnel excavation in real time and preprocess the first data; wherein, the first data includes: drilling depth data and thrust data;

[0009] Create a single-tooth thrust theoretical model, and based on the single-tooth thrust theoretical model and the first data, generate second data corresponding to the rock in tunnel excavation; wherein, the second data includes rock physical and mechanical parameter data and rock fragmentation degree data;

[0010] Generate third data corresponding to tunnel excavation in real time according to the second data; wherein, the third data is prediction data of the fragmentation degree of the face surrounding rock corresponding to tunnel excavation.

[0011] Furthermore, the real-time acquisition of the first data corresponding to tunnel excavation further includes:

[0012] Generate and acquire the first data, and filter the first data to generate fourth data corresponding to the first data; wherein, the fourth data is the data after the first data is filtered.

[0013] Acquire the fourth data, and perform real-time calibration processing on the fourth data to generate fifth data corresponding to the fourth data; wherein, the fifth data is the data after the fourth data is calibrated.

[0014] Furthermore, the creation of the single-tooth thrust theoretical model, according to the single-tooth thrust theoretical model, and based on the first data, generating the second data corresponding to the rock in tunnel excavation further includes:

[0015] Establish a single-tooth thrust theoretical model according to the cavity expansion theory, and based on the single-tooth thrust theoretical model, establish a first correspondence between the penetration force and the second data during the process of a single tooth penetrating the rock.

[0016] Generate and acquire sixth data corresponding to the rock in tunnel excavation, and based on the sixth data, construct a second correspondence between the penetration pressure and the penetration depth under penetration; wherein, the sixth data is geological strength index data.

[0017] Generate and acquire seventh data corresponding to the rock in tunnel excavation, and based on the seventh data, establish a third correspondence between the seventh data, the penetration depth, the penetration force, and the dimensionless plastic zone radius; wherein, the seventh data includes: rock strength parameter data, tool shape parameter data, and constraint condition parameter data.

[0018] Furthermore, the establishment of a single-tooth thrust theoretical model according to the cavity expansion theory, and based on the single-tooth thrust theoretical model, establishing a first correspondence between the penetration force and the second data during the process of a single tooth penetrating the rock further includes:

[0019] According to the first correspondence, and in combination with the single-tooth thrust theoretical model, generate eighth data corresponding to the process of a single tooth penetrating the rock; wherein, the eighth data includes stress field data and displacement field data.

[0020] Generate the ninth data corresponding to the eighth data based on the equilibrium equation, the Hoek-Brown failure criterion, and the non-associated flow rule; wherein, the ninth data includes radial stress data, tangential stress data, and displacement expression data.

[0021] Further, creating a single-tooth thrust theoretical model according to the cavity expansion theory, and based on the single-tooth thrust theoretical model, establishing a first correspondence relationship between the penetration force and the second data during the process of a single tooth penetrating into the rock, further includes:

[0022] In the elastic region, combining the boundary conditions, calculate and generate the radial stress and tangential stress corresponding to the stress field respectively; wherein, the boundary conditions are: σ r *| r＝R = P y *; σ r *| r＝∞ = P0*;

[0023]

[0024] In the formula: k is a parameter related to the shape of the cavity; R is the outer boundary radius of the plastic region; r is the distance from the center of the cavity to the point under consideration; is the normalized yield pressure applied on the cavity wall; is the normalized pressure on the cavity at infinity.

[0025] In the plastic region, combining the boundary conditions, calculate and generate the plastic zone radius corresponding to the displacement field; wherein, the calculation formula is:

[0026]

[0027] In the formula: R is the plastic zone radius; a CE is the inner diameter of the cavity; C1 is a coefficient; β is a coefficient, where β = a / (1 - a); k is a parameter related to the shape of the cavity.

[0028] Further, generating and obtaining the seventh data corresponding to the rock during tunnel excavation, and based on the seventh data, establishing a third correspondence relationship between the seventh data, the penetration depth, the penetration force, and the dimensionless plastic zone radius, further includes:

[0029] Generate and obtain the tenth data corresponding to the seventh data and with different values; wherein, the tenth data is parameter data with different parameter values;

[0030] Based on the tenth data, calculate and generate the corresponding penetration depth and penetration pressure relationship data; wherein, the calculation formula is:

[0031]

[0032] In the formula: F is the penetration force; d is the penetration depth; α is the cutter inclination angle.

[0033] The second object of the present invention is achieved as follows: The system is applied to the method for predicting the degree of fragmentation of the surrounding rock of the tunnel face suitable for tunnel excavation, and the system includes:

[0034] A data acquisition unit for real-time acquiring first data corresponding to tunnel excavation and preprocessing the first data; wherein, the first data includes: drilling depth data and thrust data;

[0035] A model creation unit for creating a single-tooth thrust theoretical model, and generating second data corresponding to the rock in tunnel excavation based on the single-tooth thrust theoretical model and the first data; wherein, the second data includes rock physical and mechanical parameter data and rock fragmentation degree data;

[0036] A data generation unit for generating third data corresponding to tunnel excavation in real time according to the second data; wherein, the third data is prediction data of the degree of fragmentation of the surrounding rock of the tunnel face corresponding to tunnel excavation.

[0037] Furthermore, the data acquisition unit further includes:

[0038] A first generation module for generating and acquiring the first data, filtering the first data, and generating fourth data corresponding to the first data; wherein, the fourth data is the data after the first data is filtered;

[0039] A second generation module for acquiring the fourth data and performing real-time calibration processing on the fourth data to generate fifth data corresponding to the fourth data; wherein, the fifth data is the data after the fourth data is calibrated;

[0040] And / or, the model creation unit further includes:

[0041] A first creation module for creating a single-tooth thrust theoretical model according to the small hole expansion theory, and establishing a first correspondence between the penetration force and the second data during the process of a single tooth penetrating the rock based on the single-tooth thrust theoretical model;

[0042] A second creation module for generating and acquiring sixth data corresponding to the rock in tunnel excavation, and constructing a second correspondence between the penetration pressure and the penetration depth under penetration based on the sixth data; wherein, the sixth data is geological strength index data;

[0043] A third creation module, configured to generate and obtain seventh data corresponding to the rock in tunnel excavation, and based on the seventh data, establish a third corresponding relationship between the seventh data, the penetration depth, the penetration force, and the dimensionless plastic zone radius; wherein, the seventh data includes: rock strength parameter data, tool shape parameter data, and constraint condition parameter data.

[0044] Further, the first creation module further includes:

[0045] A third generation module, configured to generate eighth data corresponding to the process of a single tooth penetrating the rock according to the first corresponding relationship and in combination with the single-tooth thrust theoretical model; wherein, the eighth data includes stress field data and displacement field data;

[0046] A fourth generation module, configured to generate ninth data corresponding to the eighth data based on the equilibrium equation, the Hoek-Brown failure criterion, and the non-associated flow rule; wherein, the ninth data includes radial stress data, tangential stress data, and displacement expression data;

[0047] A first calculation module, configured to calculate and generate the radial stress and the tangential stress corresponding to the stress field respectively in the elastic region in combination with the boundary conditions; wherein, the boundary conditions are: σ r *| r＝R =P y *; σ r *| r＝∞ =P0*;

[0048]

[0049] In the formula: k is a parameter related to the shape of the small hole; R is the outer boundary radius of the plastic region; r is the distance from the center of the small hole to the point under consideration; is the normalized yield pressure applied on the small hole wall; is the normalized pressure received by the small hole at infinity.

[0050] A second calculation module, configured to calculate and generate the plastic zone radius corresponding to the displacement field in the plastic region in combination with the boundary conditions; wherein, the calculation formula is:

[0051]

[0052] In the formula: R is the plastic zone radius; a CE is the inner diameter of the small hole; C1 is a coefficient; β is a coefficient, where β = a / (1 - a); k is a parameter related to the shape of the small hole.

[0053] And / or, the third creation module further includes:

[0054] A fifth generation module, configured to generate and obtain a tenth data corresponding to the seventh data and having different values; wherein, the tenth data is parameter data with different parameter values;

[0055] A third calculation module, configured to calculate and generate corresponding penetration depth and penetration pressure relationship data based on the tenth data; wherein, the calculation formula is:

[0056]

[0057] In the formula: F is the penetration force; d is the penetration depth; α is the cutter inclination angle.

[0058] The third object of the present invention is achieved as follows: including a processor, a memory, and a prediction platform control program for the degree of fragmentation of the face rock suitable for tunnel excavation; wherein, in the processor, the prediction platform control program for the degree of fragmentation of the face rock suitable for tunnel excavation is executed, and the prediction platform control program for the degree of fragmentation of the face rock suitable for tunnel excavation is stored in the memory, and the prediction platform control program for the degree of fragmentation of the face rock suitable for tunnel excavation realizes the prediction method for the degree of fragmentation of the face rock suitable for tunnel excavation.

[0059] The present invention obtains first data corresponding to tunnel excavation in real time through a method, and preprocesses the first data; wherein, the first data includes: drilling depth data and thrust data;

[0060] Create a single-tooth thrust theoretical model, and based on the single-tooth thrust theoretical model and the first data, generate second data corresponding to the rock in tunnel excavation; wherein, the second data includes rock physical and mechanical parameter data and rock fragmentation degree data;

[0061] According to the second data, third data corresponding to tunnel excavation is generated in real time; wherein, the third data is prediction data for the degree of fragmentation of the face rock corresponding to tunnel excavation, and a system corresponding to the method can predict the degree of fragmentation of the face rock through data such as drilling depth and thrust, providing an accurate prediction of the degree of fragmentation of the face rock for tunnel engineering construction.

[0062] That is to say, when predicting the degree of fragmentation of the face rock in actual engineering, it is more inclined to be safe, and it can more timely detect the bad geological bodies on the face, providing better guarantee for construction safety. In addition, at present. There is little research considering confining pressure in the rock-breaking theoretical model. Especially in the case of considering rock fragmentation, considering the influence of confining pressure on thrust helps to more comprehensively understand the rock-breaking process, improve the accuracy of digital advanced drilling, and obtain the relationship between penetration depth and penetration force under different rock strength parameters, penetration tool shapes, confining pressures, etc. Description of the Drawings

[0063] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0064] Figure 1 It is a schematic flow chart of the steps of a method for predicting the fragmentation degree of the face surrounding rock suitable for tunnel excavation according to the present invention;

[0065] Figure 2 It is a schematic implementation flow chart of an embodiment of a method for predicting the fragmentation degree of the face surrounding rock suitable for tunnel excavation according to the present invention;

[0066] Figure 3 It is a schematic geometric structure diagram of the small hole expansion theory model of a method for predicting the fragmentation degree of the face surrounding rock suitable for tunnel excavation according to the present invention;

[0067] Figure 4 It is a schematic shape structure diagram of the wedge-shaped cutter of a method for predicting the fragmentation degree of the face surrounding rock suitable for tunnel excavation according to the present invention;

[0068] Figure 5 It is a schematic system architecture diagram of a system for predicting the fragmentation degree of the face surrounding rock suitable for tunnel excavation according to the present invention;

[0069] Figure 6 It is a schematic platform architecture diagram of a platform for predicting the fragmentation degree of the face surrounding rock suitable for tunnel excavation according to the present invention. Detailed implementation manners

[0070] To better understand the purpose, technical solutions and advantages of the present invention more clearly, the following further explains the present invention in conjunction with the accompanying drawings and specific implementation manners. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification.

[0071] The present invention can also be implemented or applied through other different specific examples, and various details in this specification can also be modified and changed based on different viewpoints and applications without departing from the spirit of the present invention.

[0072] It should be noted that if there are directional indications (such as up, down, left, right, front, back...) involved in the embodiments of the present invention, then such directional indications are only used to explain the relative positional relationship and movement conditions between components in a specific posture (as shown in the accompanying drawings). If this specific posture changes, then such directional indications will also change accordingly.

[0073] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, such descriptions of "first", "second", etc. are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include at least one such feature. Secondly, the technical solutions between various embodiments may be combined with each other, but it must be based on the fact that those of ordinary skill in the art can implement them. When the combination of technical solutions results in contradictions or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0074] Preferably, a method for predicting the degree of surrounding rock fragmentation of a tunnel face suitable for tunnel excavation according to the present invention is applied to one or more terminals or servers. The terminal is a device capable of automatically performing numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to a microprocessor, an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital signal processor (DSP), an embedded device, etc.

[0075] The terminal may be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The terminal can interact with the customer through a keyboard, a mouse, a remote control, a touchpad, a voice control device, etc.

[0076] The present invention aims to implement a method, a system, and a platform for predicting the degree of surrounding rock fragmentation of a tunnel face suitable for tunnel excavation.

[0077] As Figure 1 shown, it is a flowchart of the method for predicting the degree of surrounding rock fragmentation of a tunnel face suitable for tunnel excavation provided by the embodiments of the present invention.

[0078] In this embodiment, the method for predicting the degree of surrounding rock fragmentation of a tunnel face suitable for tunnel excavation can be applied to a terminal with a display function or a fixed terminal, and the terminal is not limited to a personal computer, a smart phone, a tablet computer, a desktop computer or an all-in-one computer equipped with a camera, etc.

[0079] The method for predicting the degree of surrounding rock fragmentation of the tunnel face suitable for tunnel excavation can also be applied to a hardware environment composed of a terminal and a server connected to the terminal through a network. The network includes but is not limited to: wide area network, metropolitan area network or local area network. The method for predicting the degree of surrounding rock fragmentation of the tunnel face suitable for tunnel excavation according to the embodiments of the present invention can be executed by the server, can also be executed by the terminal, or can be jointly executed by the server and the terminal.

[0080] For example, for a terminal that needs to predict the degree of surrounding rock fragmentation of the tunnel face suitable for tunnel excavation, the function of predicting the degree of surrounding rock fragmentation of the tunnel face provided by the method of the present invention can be directly integrated on the terminal, or a client for implementing the method of the present invention can be installed. Again, the method provided by the present invention can also run on devices such as servers in the form of a Software Development Kit (SDK), and provide an interface for the function of predicting the degree of surrounding rock fragmentation of the tunnel face in the form of an SDK. The terminal or other devices can implement the function of predicting the degree of surrounding rock fragmentation of the tunnel face through the provided interface. The present invention will be further described below with reference to the accompanying drawings.

[0081] As Figures 1-4 shown, the present invention provides a method for predicting the degree of surrounding rock fragmentation of the tunnel face suitable for tunnel excavation, and the method includes the following steps:

[0082] S1. Real-time obtain first data corresponding to tunnel excavation, and preprocess the first data; wherein, the first data includes: drilling depth data and thrust data;

[0083] S2. Create a single-tooth thrust theoretical model, and generate second data corresponding to the rock in tunnel excavation based on the single-tooth thrust theoretical model and the first data; wherein, the second data includes rock physical and mechanical parameter data and rock fragmentation degree data;

[0084] S3. Generate third data corresponding to tunnel excavation in real time according to the second data; wherein, the third data is the predicted data of the degree of surrounding rock fragmentation of the tunnel face corresponding to tunnel excavation.

[0085] The real-time obtaining of the first data corresponding to tunnel excavation and the preprocessing of the first data further includes:

[0086] S11. Generate and obtain the first data, and filter the first data to generate fourth data corresponding to the first data; wherein, the fourth data is the data after the first data is filtered.

[0087] S12. Obtain the fourth data and perform real-time calibration processing on the four data to generate fifth data corresponding to the fourth data; wherein, the fifth data is the data after the fourth data is calibrated.

[0088] The creation of the single-tooth thrust theoretical model, based on the single-tooth thrust theoretical model, and based on the first data, generating second data corresponding to the rock in tunnel excavation, further includes:

[0089] S21. Create a single-tooth thrust theoretical model according to the small hole expansion theory, and based on the single-tooth thrust theoretical model, establish a first corresponding relationship between the penetration force and the second data during the process of a single tooth penetrating the rock;

[0090] S22. Generate and obtain sixth data corresponding to the rock in tunnel excavation, and based on the sixth data, construct a second corresponding relationship between the penetration pressure and the penetration depth under penetration; wherein, the sixth data is geological strength index data;

[0091] S23. Generate and obtain seventh data corresponding to the rock in tunnel excavation, and based on the seventh data, establish a third corresponding relationship between the seventh data, the penetration depth, the penetration force, and the dimensionless plastic zone radius; wherein, the seventh data includes: rock strength parameter data, tool shape parameter data, and constraint condition parameter data.

[0092] The creation of the single-tooth thrust theoretical model according to the small hole expansion theory, and based on the single-tooth thrust theoretical model, establishing a first corresponding relationship between the penetration force and the second data during the process of a single tooth penetrating the rock, further includes:

[0093] S211. According to the first corresponding relationship, and in combination with the single-tooth thrust theoretical model, generate eighth data corresponding to the process of a single tooth penetrating the rock; wherein, the eighth data includes stress field data and displacement field data;

[0094] S212. Based on the equilibrium equation, the Hoek-Brown failure criterion, and the non-associated flow rule, generate ninth data corresponding to the eighth data; wherein, the ninth data includes radial stress data, tangential stress data, and displacement expression data.

[0095] The creation of the single-tooth thrust theoretical model according to the small hole expansion theory, and based on the single-tooth thrust theoretical model, establishing a first corresponding relationship between the penetration force and the second data during the process of a single tooth penetrating the rock, further includes:

[0096] S213. In the elastic region, in combination with the boundary conditions, calculate and generate the radial stress and the tangential stress corresponding to the stress field respectively; wherein, the boundary condition is: σ r *| r＝R= P y *; σ r *| r＝∞ = P0*;

[0097]

[0098] where: k is a parameter related to the shape of the small hole; R is the outer boundary radius of the plastic region; r is the distance from the center of the small hole to the point under consideration; is the normalized yield pressure applied on the small hole wall; is the normalized pressure on the small hole at infinity.

[0099] S214. In the plastic region, combining the boundary conditions, calculate and generate the plastic zone radius corresponding to the displacement field; where the calculation formula is:

[0100]

[0101] where: R is the plastic zone radius; a CE is the inner diameter of the small hole; C1 is a coefficient; β is a coefficient, where β = a / (1 - a); k is a parameter related to the shape of the small hole.

[0102] The step of generating and obtaining the seventh data corresponding to the rock in the tunnel excavation, and based on the seventh data, establishing the third correspondence relationship between the seventh data, the penetration depth, the penetration force, and the dimensionless plastic zone radius, further includes:

[0103] S231. Generate and obtain the tenth data corresponding to the seventh data and with different values; where the tenth data is the parameter data with different parameter values;

[0104] S232. Based on the tenth data, calculate and generate the corresponding penetration depth and penetration pressure relationship data; where the calculation formula is:

[0105]

[0106] where: F is the penetration force; d is the penetration depth; α is the tool inclination angle.

[0107] Specifically, in the embodiments of the present invention, the present solution proposes a prediction method for the degree of surrounding rock fragmentation of a tunnel excavation face under the influence of multiple factors, including: establishing a single-tooth thrust theoretical model based on the small hole expansion theory, considering the influence of rock fragmentation degree, non-associated flow rule, and confining pressure, and establishing the relationship between the penetration force and the rock fragmentation degree and physical and mechanical parameters during the process of a single tooth penetrating the rock; conducting a wedge-shaped cutter penetration test on the rock according to the single-tooth thrust theoretical model, obtaining the relationship between the penetration pressure and the penetration depth of rock specimens with different geological strength indexes under penetration, and comparing and verifying it with the single-tooth thrust theoretical model; conducting parameter analysis on the single-tooth thrust theoretical model, exploring the influence of rock strength parameters, cutter shape, and constraint conditions on the penetration test results, and determining the relationship between each parameter and the penetration depth, penetration force, and dimensionless plastic zone radius; according to the distribution of single teeth in the drill bit in actual engineering, applying the single-tooth thrust theoretical model to the study of the relationship between actual engineering thrust parameters and surrounding rock parameters, and predicting the degree of surrounding rock fragmentation of the excavation face by obtaining data such as drilling depth and thrust.

[0108] The single-tooth thrust theoretical model uses the Hoek-Brown failure criterion to describe the integrity and strength characteristics of the rock. The steps of the single-tooth thrust theoretical model for describing rock characteristics include: establishing the small hole expansion theory according to the Hoek-Brown failure criterion; according to the non-associated flow rule and the action of confining pressure; according to the stress field and displacement field of the small hole expansion model, applying the single-tooth thrust theoretical model to the rock penetration test.

[0109] In the solution of the present invention, the problems of cylindrical and spherical small hole expansion in an infinitely large ideal elastoplastic Hoek-Brown material are considered. As the internal pressure increases, a plastic region (radius R) and an elastic region (r≥R) are formed around the cavity.

[0110] The analysis steps of the stress field and displacement field in the elastic-plastic region include: in the elastic region, the stress is the classical elastic solution, combined with the boundary conditions σ r *| r＝R =P y * and σ r *| r＝∞ =P0* to obtain that the radial stress and tangential stress are respectively:

[0111]

[0112] and

[0113] where k is a parameter related to the small hole shape, where k = 1 for a cylindrical hole and k = 2 for a spherical hole.

[0114] In the plastic region, the stress satisfies the equilibrium equation and the Hoek-Brown failure criterion formula, and combined with the boundary conditions, it is obtained that:

[0115]

[0116] and

[0117] Where: a is the rock strength parameter; W0 is the 0th branch of the Lambert W function.

[0118] The dimensionless plastic zone radius is defined as:

[0119]

[0120] In the elastic region, strain and displacement satisfy Hooke's law and small deformation theory, combined with boundary conditions and Get:

[0121]

[0122] and

[0123] in, Elastic-plastic boundary displacement:

[0124]

[0125] In the plastic region, the non-associative flow criterion with a constant dilatancy angle and the large strain theory are considered;

[0126] Strain meets:

[0127]

[0128] Among them, K d =(1+sinψ) / (1-sinψ), ψ is the shear expansion angle.

[0129] The wedge tool penetration test considers wedge and spherical tools, establishes a quantitative relationship between the penetration depth and the dimensionless plastic zone radius during the single-tooth penetration of the rock, obtains a quantitative relationship between the penetration depth and the penetration force, and the derivation steps of the penetration pressure include:

[0130] For wedge-shaped tools, the formula:

[0131]

[0132] Where α is the inclination angle of the wedge tool, and the relevant formulas are combined to obtain

[0133]

[0134] Where: γ is the coefficient, where γ=k / K d +1; δ is the coefficient, δ=uEPB / R.

[0135] The penetration depth t is defined as the ratio of the penetration depth d to the inter-cone width 2a0, where t = d / 2a0.

[0136] For spherical tools, the related formulas can be obtained:

[0137]

[0138] Through the dimensionless plastic zone radius ε R And the combined formula:

[0139]

[0140] and

[0141] in m b , s, a are rock strength parameters, and the penetration pressure P is obtained i .

[0142] The test conditions of the wedge cutter rock penetration test include using a specific loading system and rock sample, and setting a specific cutter shape and loading rate. The parameter analysis method, taking the wedge cutter as an example, selects parameters such as rock strength parameters, cutter shape and constraint conditions, explores the influence of each parameter on the penetration test results, and obtains the relationship between each parameter and the penetration depth, penetration force and dimensionless plastic zone radius.

[0143] That is to say, the prediction method of the degree of surrounding rock crushing at the tunnel excavation face under the influence of multiple factors includes: conducting a wedge-shaped tool penetration test in rock according to the single-tooth thrust theoretical model, obtaining the relationship between the penetration pressure and penetration depth of rock samples with different geological strength indicators under penetration, and comparing and verifying with the theoretical model. The model is analyzed by parameters to explore the influence of rock strength parameters, tool shape and constraint conditions on the results of the penetration test, and the relationship between each parameter and the penetration depth, penetration force and dimensionless plastic zone radius is determined. According to the distribution of single teeth in the drill bit in actual engineering, the model is applied to the study of the relationship between thrust parameters and surrounding rock parameters in actual engineering, and the degree of crushing of the surrounding rock at the face is predicted by obtaining data such as drilling depth and thrust. The single-tooth thrust theoretical model considers the expansion problem of cylindrical and spherical small holes in infinite ideal elastic-plastic Hoek-Brown materials. As the internal pressure increases, a plastic area (radius R) and an elastic area (r≥R) surrounding the hole will be formed.

[0144] Set the parameter range and select different rock strength parameters (uniaxial compressive strength, dilation angle, geological strength index, etc.), cutter shape parameters (cutter head inclination angle), and constraint condition parameters (confining pressure) to analyze their influence on the penetration pressure.

[0145] Conduct experiments or simulations, perform wedge cutter penetration tests on rocks or conduct numerical simulations. During the experiments or simulations, change the value of one parameter while keeping other parameters unchanged, and record the results of the penetration tests.

[0146] Observe the changes in the results such as penetration pressure and penetration depth under different parameter values.

[0147] Derive the relationship between the penetration depth and the penetration pressure according to the formula:

[0148]

[0149] where F is the penetration force; d is the penetration depth; and α is the cutter inclination angle.

[0150] Analyze the relationships between parameters such as rock strength parameters, cutter shape, and constraint conditions and the results of the penetration tests. The parameter analysis methods include: comparing and analyzing the test results under different parameter combinations to find out the influence of the interaction between parameters on the results of the penetration tests.

[0151] Compare the test results with the model calculation results and verify them by comparing with the test data in existing literature.

[0152] Conduct parameter analysis on the small hole expansion theoretical model based on the Hoek - Brown failure criterion. Taking the wedge cutter as an example, select rock strength parameters (uniaxial compressive strength, dilation angle, shear modulus, geological strength index, disturbance factor, intact friction strength parameter), cutter shape (cutter head inclination angle), constraint conditions (confining pressure), etc. to explore the influence of each parameter on the results of the penetration tests.

[0153] Using the small hole expansion theoretical model based on the Hoek - Brown failure criterion, the relationship between the penetration depth and the penetration force under different rock strength parameters, penetration cutter shapes, confining pressures, etc. can be obtained. At the same time, important data such as rock strength parameters can be inversely deduced when the penetration test data are known.

[0154] Obtain the relationships between different rock strength parameters, penetration cutter shapes, confining pressures and the penetration depth, penetration force, and dimensionless plastic zone radius.

[0155] The beneficial effects of the embodiments of the present application compared with the prior art are as follows: In existing research, single-tooth rock-breaking models considering the degree of rock fragmentation are extremely rare. According to the Hoek-Brown failure criterion, it can more accurately reflect the strength and fragmentation characteristics of rocks, establish the relationship between the penetration force and the degree of rock fragmentation and physical and mechanical parameters, and improve the accuracy and reliability of the model. Through the wedge probe penetration rock test and the comparison with the test data in the literature, it provides a more reliable theoretical basis for predicting the characteristics of surrounding rock using drilling parameters while drilling. When predicting the degree of fragmentation of the surrounding rock of the tunnel face in actual engineering, it is safer, can more timely detect the bad geological bodies on the tunnel face, and provide better guarantee for construction safety. In addition, few studies consider confining pressure in the rock-breaking theoretical model. Especially when considering rock fragmentation, considering the influence of confining pressure on the thrust helps to more comprehensively understand the rock-breaking process, improve the accuracy of digital advanced drilling, and obtain the relationship between the penetration depth and the penetration force under different rock strength parameters, penetration tool shapes, confining pressures, etc.

[0156] In other words, the present invention proposes a method for predicting the degree of fragmentation of the surrounding rock of the tunnel face under the influence of multiple factors: establish a single-tooth thrust theoretical model according to the small hole expansion theory, consider factors such as the degree of rock fragmentation and non-associated flow rule, and establish the relationship between the penetration force and the degree of rock fragmentation and physical and mechanical parameters during the process of a single tooth penetrating into the rock. Obtain the physical and mechanical parameters of the rock, including: determining parameters such as the uniaxial compressive strength, shear modulus, and geological strength index of the rock. This can be done through laboratory tests, geological exploration reports, and on-site sampling analysis, etc. Considering the degree of rock fragmentation includes: evaluating the degree of rock fragmentation according to the joint fissure distribution, geological structure, etc. of the rock. Applying the non-associated flow rule can combine parameters such as the dilatancy angle of the rock to determine the strain relationship in the plastic region. Determine the value of the dilatancy angle through experiments or empirical formulas.

[0157] Considering the influence of confining pressure, the magnitude and direction of the in-situ stress near the tunnel face can be measured to determine the influence of confining pressure on the mechanical behavior of the rock, or in-situ stress measuring instruments can be used for on-site measurement, or the confining pressure can be estimated through numerical simulation methods.

[0158] Obtain the relationship between the penetration force and the degree of rock fragmentation and physical and mechanical parameters through the single-tooth thrust theoretical model, and deduce the stress field and displacement field during the process of a single tooth penetrating into the rock. Through the equilibrium equation, Hoek-Brown failure criterion, and non-associated flow rule, etc., solve the expressions of radial stress, tangential stress, and displacement. Finally, establish the quantitative relationship between the penetration force and the degree of rock fragmentation and physical and mechanical parameters.

[0159] The single-tooth thrust theoretical model considers the problems of cylindrical and spherical small hole expansion in an infinite ideal elastoplastic Hoek-Brown material. As the internal pressure increases, a plastic region and an elastic region will be formed.

[0160] Solve the stress field in the elastic-plastic zone. In the elastic region, the stress is the classical elastic solution; in the plastic region, the stress satisfies the equilibrium equation and the Hoek-Brown failure criterion.

[0161] Solve the displacement field in the elastic-plastic zone. In the elastic region, the strain and displacement satisfy Hooke's law and the small deformation theory; in the plastic region, consider the non-associated flow criterion with a constant dilation angle and the large strain theory.

[0162] Solve the stress field in the elastic-plastic zone. In the elastic region, the stress is the classical elastic solution of the infinite medium small hole expansion theory, obtained from the boundary conditions σ r *| r＝R =P y * and σ r *| r＝∞ =P0*. The radial stress and tangential stress are respectively:

[0163]

[0164] and

[0165] In the plastic region, combining the equilibrium equation, the Hoek-Brown failure criterion and the boundary conditions, we can obtain:

[0166]

[0167] Define the dimensionless radius of the plastic zone,

[0168]

[0169] Solve the displacement field in the elastic-plastic zone. In the elastic region, the strain and displacement satisfy Hooke's law and the small deformation theory. Combining the boundary conditions and we get:

[0170]

[0171] and

[0172] where The displacement at the elastic-plastic boundary:

[0173]

[0174] In the plastic region, considering the non-associated flow criterion with a constant dilation angle, its strain satisfies:

[0175]

[0176] where K d=(1+sinψ) / (1-sinψ), ψ is the shear expansion angle.

[0177] According to the single-tooth thrust theory model, a wedge-shaped tool is used to penetrate the rock to obtain the relationship between the penetration pressure and penetration depth of rock samples with different geological strength indicators, and then compared with the theoretical model for verification. Rock samples are collected from the tunnel construction site or areas with similar geological conditions and processed into rectangular rock samples of specified sizes. The geological strength index is determined according to the distribution of rock cracks. Rocks with no more than two obvious penetrating cracks are given a value of GSI=100, and rocks with three to five obvious penetrating cracks are given a value of GSI=90. Wedge-shaped tools are made according to specific inclination angles (such as 30°) and inter-cone widths (such as 0.5mm). Ensure that the dimensional accuracy and hardness of the tool meet the test requirements.

[0178] Place the rock sample on the testing machine, install the wedge-shaped cutter, and adjust the sample position so that the cutter penetrates into the center of the sample. Use MTS-E45.305 electronic universal testing machine.

[0179] Set the loading rate (e.g. 0.5 mm / min) and start the test until the specimen is completely penetrated. During the test, data such as penetration force and tool displacement are recorded in real time.

[0180] The wedge tool penetration rock test considers wedge and spherical tools, establishes a quantitative relationship between the penetration depth and the dimensionless plastic zone radius during the single-tooth penetration of the rock, and obtains a quantitative relationship between the penetration depth and the penetration force.

[0181] For wedge-shaped tools, the formula:

[0182]

[0183] Among them, α is the inclination angle of the wedge tool. Combining the relevant formulas, we get:

[0184]

[0185] Where: γ is the coefficient, where γ=k / K d +1; δ is the coefficient, δ=u EPB / R.

[0186] The penetration depth t is defined as the ratio of the penetration depth d to the inter-cone width 2a0, where t = d / 2a0.

[0187] For spherical tools, the related formulas can be obtained:

[0188]

[0189] By using the dimensionless plastic zone radius and combining the formula:

[0190]

[0191] and

[0192] wherein m b , s, and a are rock strength parameters, and the penetration pressure P is obtained i .

[0193] The test conditions for the penetration test of the wedge-shaped cutter into the rock include using a specific loading system and rock specimens, and setting a specific cutter shape and loading rate. Parameter analysis is carried out on the single-tooth thrust theoretical model to explore the influence of rock strength parameters, cutter shape, and constraint conditions on the penetration test results, and to determine the relationships between various parameters and the penetration depth, penetration force, and dimensionless plastic zone radius.

[0194] Different rock strength parameters (uniaxial compressive strength, dilation angle, geological strength index, etc.), cutter shape parameters (cutter head inclination angle), and constraint condition parameters (confining pressure) are selected for analysis. The value ranges of the parameters are determined according to the actual situation.

[0195] Calculations are carried out by changing the parameters. For different parameter combinations, the established single-tooth thrust theoretical model is used to calculate results such as the penetration depth, penetration force, and dimensionless plastic zone radius.

[0196] The derivation of the relationship between the penetration depth and the penetration pressure is based on the formula:[[]]

[0197]

[0198] where F is the penetration force; d is the penetration depth; and α is the cutter inclination angle.

[0199] Observe the influence of different parameter changes on the penetration test results. Analyze the relationships between parameters such as rock strength indexes, cutter shape, and confining pressure and the penetration depth, penetration force, and dimensionless plastic zone radius. According to the distribution of single teeth in the drill bit in actual engineering, the model is applied to the study of the relationship between the thrust parameters and surrounding rock parameters in actual engineering. By obtaining data such as the drilling depth and thrust, predict the fragmentation degree of the surrounding rock of the tunnel face.

[0200] According to the type of drill bit actually used, determine the distribution position and angle of single teeth on the drill bit, understand the working principle of the drill bit and the force conditions of each single tooth during the drilling process. During tunnel construction, real-time data such as drilling depth and thrust are obtained through sensors on the drilling rig. To ensure the accuracy and reliability of the data, methods such as data filtering and calibration can be used to process the collected data. Substitute the obtained data such as drilling depth and thrust into the established theoretical model of single-tooth thrust to inversely deduce the physical and mechanical parameters and fragmentation degree of the rock. According to the output results of the model, predict the fragmentation degree of the surrounding rock of the tunnel face, such as determining indicators such as the depth of the fragmentation zone and the fragmentation degree level. According to the predicted fragmentation degree of the surrounding rock, formulate corresponding construction measures. If a high fragmentation degree of the surrounding rock is predicted, measures such as strengthening the support and adjusting the excavation method may be required to ensure construction safety and project quality.

[0201] To achieve the above object, the present invention also provides a prediction system for the fragmentation degree of the surrounding rock of the tunnel face suitable for tunnel excavation. The system is applied to the prediction method for the fragmentation degree of the surrounding rock of the tunnel face suitable for tunnel excavation, as Figure 5 shown, the system specifically includes:

[0202] A data acquisition unit for real-time acquiring first data corresponding to tunnel excavation and preprocessing the first data; wherein, the first data includes: drilling depth data and thrust data;

[0203] A model creation unit for creating a theoretical model of single-tooth thrust, and generating second data corresponding to the rock in tunnel excavation based on the first data according to the theoretical model of single-tooth thrust; wherein, the second data includes rock physical and mechanical parameter data and rock fragmentation degree data;

[0204] A data generation unit for generating third data corresponding to tunnel excavation in real time according to the second data; wherein, the third data is prediction data for the fragmentation degree of the surrounding rock of the tunnel face corresponding to tunnel excavation.

[0205] The data acquisition unit further includes:

[0206] A first generation module for generating and acquiring the first data, filtering and processing the first data, and generating fourth data corresponding to the first data; wherein, the fourth data is the data after the first data is filtered;

[0207] A second generation module for acquiring the fourth data and performing real-time calibration processing on the fourth data to generate fifth data corresponding to the fourth data; wherein, the fifth data is the data after the fourth data is calibrated;

[0208] And / or, the model creation unit further includes:

[0209] The first creation module is used to create a single-tooth thrust theoretical model according to the small hole expansion theory, and based on the single-tooth thrust theoretical model, establish a first correspondence relationship between the penetration force and the second data during the process of a single tooth penetrating into the rock;

[0210] The second creation module is used to generate and obtain the sixth data corresponding to the rock in tunnel excavation, and based on the sixth data, construct a second correspondence relationship between the penetration pressure and the penetration depth under penetration; wherein, the sixth data is geological strength index data;

[0211] The third creation module is used to generate and obtain the seventh data corresponding to the rock in tunnel excavation, and based on the seventh data, establish a third correspondence relationship between the seventh data, the penetration depth, the penetration force and the dimensionless plastic zone radius; wherein, the seventh data includes: rock strength parameter data, tool shape parameter data and constraint condition parameter data.

[0212] The first creation module further includes:

[0213] The third generation module is used to generate the eighth data corresponding to the process of a single tooth penetrating into the rock according to the first correspondence relationship and in combination with the single-tooth thrust theoretical model; wherein, the eighth data includes stress field data and displacement field data;

[0214] The fourth generation module is used to generate the ninth data corresponding to the eighth data based on the equilibrium equation, the Hoek-Brown failure criterion and the non-associated flow rule; wherein, the ninth data includes radial stress data, tangential stress data and displacement expression data;

[0215] The first calculation module is used to calculate and generate the radial stress and tangential stress corresponding to the stress field respectively in the elastic region in combination with the boundary conditions; wherein, the boundary conditions are: σ r *| r＝R =P y *;σ r *| r＝∞ =P0*;

[0216]

[0217] In the formula, k is a parameter related to the small hole shape; R is the outer boundary radius of the plastic region; r is the distance from the center of the small hole to the considered point; is the normalized yield pressure applied on the small hole wall; is the normalized pressure received by the small hole at infinity.

[0218] A second calculation module, used in the plastic region, calculates and generates the radius of the plastic zone corresponding to the displacement field in combination with the boundary conditions; the calculation formula is as follows:

[0219]

[0220] In the formula: R is the radius of the plastic zone; a CE is the inner diameter of the small hole; C1 is a coefficient; β is a coefficient, where β = a / (1 - a), and k is a parameter related to the shape of the small hole.

[0221] And / or, the third modeling further includes:

[0222] A fifth generation module, used to generate and obtain tenth data corresponding to the seventh data and having different values; the tenth data is parameter data with different parameter values;

[0223] A third calculation module, used to calculate and generate corresponding penetration depth and penetration pressure relationship data based on the tenth data; the calculation formula is as follows:

[0224]

[0225] In the formula: F is the penetration force; d is the penetration depth; α is the tool inclination angle.

[0226] In the embodiment of the system solution of the present invention, the method steps involved in predicting the fragmentation degree of the face rock mass suitable for tunnel excavation have been described in detail above. That is to say, the functional modules in the system are used to implement the steps or sub-steps in the above method embodiment, which will not be elaborated here.

[0227] To achieve the above object, the present invention also provides a prediction platform for the fragmentation degree of the face rock mass suitable for tunnel excavation, as Figure 6 shown, including a processor, a memory, and a prediction platform control program for the fragmentation degree of the face rock mass suitable for tunnel excavation; wherein, when the processor executes the prediction platform control program for the fragmentation degree of the face rock mass suitable for tunnel excavation, the prediction platform control program for the fragmentation degree of the face rock mass suitable for tunnel excavation is stored in the memory, and the prediction platform control program for the fragmentation degree of the face rock mass suitable for tunnel excavation realizes the method steps for predicting the fragmentation degree of the face rock mass suitable for tunnel excavation. For example:

[0228] S1. Real-time obtain first data corresponding to tunnel excavation and preprocess the first data; the first data includes: drilling depth data and thrust data;

[0229] S2. Create a single-tooth thrust theoretical model. According to the single-tooth thrust theoretical model and based on the first data, generate second data corresponding to the rock in tunnel excavation; wherein, the second data includes rock physical and mechanical parameter data and rock fragmentation degree data.

[0230] S3. According to the second data, generate third data corresponding to tunnel excavation in real time; wherein, the third data is the predicted data of the fragmentation degree of the face surrounding rock corresponding to tunnel excavation.

[0231] The specific details of the steps have been described above and will not be elaborated here.

[0232] In the embodiment of the present invention, the processor built in the prediction platform for the fragmentation degree of the face surrounding rock suitable for tunnel excavation can be composed of integrated circuits. For example, it can be composed of a single packaged integrated circuit, or can be composed of multiple integrated circuits with the same or different functions packaged, including the combination of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips, etc. The processor uses various interfaces and circuits to connect to each component, and by running or executing the programs or units stored in the memory, as well as calling the data stored in the memory, to execute various functions for predicting the fragmentation degree of the face surrounding rock suitable for tunnel excavation and process data.

[0233] The memory is used to store program codes and various data, is installed in the prediction platform for the fragmentation degree of the face surrounding rock suitable for tunnel excavation, and realizes the high-speed and automatic access of programs or data during operation.

[0234] The memory includes a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electrically-erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM), or other optical disc memories, magnetic disc memories, magnetic tape memories, or any other computer-readable medium that can be used to carry or store data.

[0235] The present invention obtains first data corresponding to tunnel excavation in real time through a method and preprocesses the first data; wherein, the first data includes: drilling depth data and thrust data; a single-tooth thrust theoretical model is created, and according to the single-tooth thrust theoretical model and based on the first data, second data corresponding to the rock in tunnel excavation is generated; wherein, the second data includes rock physical and mechanical parameter data and rock fragmentation degree data; according to the second data, third data corresponding to tunnel excavation is generated in real time; wherein, the third data is the prediction data of the fragmentation degree of the face rock corresponding to tunnel excavation, and the system corresponding to the method can predict the fragmentation degree of the face rock through data such as drilling depth and thrust, providing an accurate prediction of the fragmentation degree of the surrounding rock for tunnel engineering construction.

[0236] That is to say, when predicting the fragmentation degree of the face rock in actual engineering, it is more inclined to be safe, and it can more timely detect the bad geological bodies on the face, giving better guarantee for construction safety. In addition, currently, few studies consider confining pressure in the rock-breaking theoretical model. Especially when considering rock fragmentation, considering the influence of confining pressure on thrust helps to more comprehensively understand the rock-breaking process, improve the accuracy of digital advanced drilling, and obtain the relationship between penetration depth and penetration force under different rock strength parameters, penetration tool shapes, confining pressures, etc.

[0237] In other words, in the solution of the present invention, a prediction method for the degree of surrounding rock fragmentation of a tunnel excavation face under the influence of multiple factors is provided, including: establishing a single-tooth thrust theoretical model according to the cavity expansion theory, considering factors such as the degree of rock fragmentation, non-associated flow rule, and confining pressure, and establishing the relationship between the penetration force and the degree of rock fragmentation and physical and mechanical parameters during the process of a single tooth penetrating the rock; conducting a wedge-shaped cutter penetration rock test according to the single-tooth thrust theoretical model, obtaining the relationship between the penetration pressure and the penetration depth of rock specimens with different geological strength indexes, and comparing and verifying with the theoretical model; conducting parameter analysis on the model, studying the influence of rock strength parameters, cutter shape, and constraint conditions on the results of the penetration test, and determining the relationship between each parameter and the penetration depth, penetration force, and dimensionless plastic zone radius; combining the single-tooth distribution of the drill bit in the actual project, applying the single-tooth thrust theoretical model to the study of the relationship between the thrust parameters and the surrounding rock parameters in the actual project, predicting the degree of surrounding rock fragmentation of the excavation face through data such as the drilling depth and thrust, providing an accurate prediction of the degree of surrounding rock fragmentation for tunnel engineering construction, and ensuring the construction safety and quality.

[0238] The above embodiments only represent several implementation manners of the present invention. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the scope of the present invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention patent shall be subject to the appended claims.

Claims

1. A prediction method for the fragmentation degree of surrounding rock at the tunnel face suitable for tunnel excavation, characterized in that The method includes the steps of: Obtaining first data corresponding to tunnel excavation in real time and preprocessing the first data; wherein, the first data includes: drilling depth data and thrust data; Creating a single-tooth thrust theoretical model, and generating second data corresponding to the rock in tunnel excavation based on the single-tooth thrust theoretical model and the first data; wherein, the second data includes rock physical and mechanical parameter data and rock fragmentation degree data; Generating third data corresponding to tunnel excavation in real time according to the second data; wherein, the third data is the prediction data of the fragmentation degree of the face rock corresponding to tunnel excavation.

2. The prediction method for the fragmentation degree of the face surrounding rock suitable for tunnel excavation according to claim 1, characterized in that, The step of obtaining first data corresponding to tunnel excavation in real time and preprocessing the first data further includes: Generating and obtaining the first data, filtering the first data, and generating fourth data corresponding to the first data; wherein, the fourth data is the data after the first data is filtered; Obtaining the fourth data and performing real-time calibration processing on the fourth data to generate fifth data corresponding to the fourth data; wherein, the fifth data is the data after the fourth data is calibrated.

3. The method for predicting the fragmentation degree of the face surrounding rock suitable for tunnel excavation according to claim 1, characterized in that, The step of creating a single-tooth thrust theoretical model, and generating second data corresponding to the rock in tunnel excavation based on the single-tooth thrust theoretical model and the first data further includes: Creating a single-tooth thrust theoretical model according to the small hole expansion theory, and establishing a first correspondence relationship between the penetration force and the second data during the process of a single tooth penetrating the rock based on the single-tooth thrust theoretical model; Generating and obtaining sixth data corresponding to the rock in tunnel excavation, and constructing a second correspondence relationship between the penetration pressure and the penetration depth under penetration based on the sixth data; wherein, the sixth data is geological strength index data; Generating and obtaining seventh data corresponding to the rock in tunnel excavation, and establishing a third correspondence relationship between the seventh data, the penetration depth, the penetration force, and the dimensionless plastic zone radius based on the seventh data; wherein, the seventh data includes: rock strength parameter data, tool shape parameter data, and constraint condition parameter data.

4. The prediction method for the fragmentation degree of the face surrounding rock suitable for tunnel excavation according to claim 3, characterized in that, The step of creating a single-tooth thrust theoretical model according to the small hole expansion theory, and establishing a first correspondence relationship between the penetration force and the second data during the process of a single tooth penetrating the rock based on the single-tooth thrust theoretical model further includes: Generating eighth data corresponding to the process of a single tooth penetrating the rock according to the first correspondence relationship and combining the single-tooth thrust theoretical model; wherein, the eighth data includes stress field data and displacement field data; Generating ninth data corresponding to the eighth data based on the equilibrium equation, the Hoek-Brown failure criterion, and the non-associated flow rule; wherein, the ninth data includes radial stress data, tangential stress data, and displacement expression data.

5. The method for predicting the fragmentation degree of the face surrounding rock suitable for tunnel excavation according to claim 3 or 4, characterized in that, The step of creating a single-tooth thrust theoretical model according to the small hole expansion theory, and establishing a first correspondence relationship between the penetration force and the second data during the process of a single tooth penetrating the rock based on the single-tooth thrust theoretical model further includes: In the elastic region, combining the boundary conditions, the radial stress and tangential stress corresponding to the stress field are calculated respectively; wherein, the boundary conditions are: σ r *| r＝R = P y *; σ r *| r＝∞ = P0*; Where: k is a parameter related to the shape of the small hole; R is the outer boundary radius of the plastic region; r is the distance from the center of the small hole to the point under consideration; is the normalized yield pressure applied on the wall of the small hole; P0 * is the normalized pressure on the small hole at infinity; In the plastic region, combining the boundary conditions, calculate and generate the radius of the plastic zone corresponding to the displacement field; the calculation formula is as follows: Where: R is the radius of the plastic zone; a CE is the inner diameter of the small hole; C1 is a coefficient; β is a coefficient, where β = a / (1 - a); k is a parameter related to the shape of the small hole.

6. The prediction method for the fragmentation degree of the face surrounding rock suitable for tunnel excavation according to claim 3, wherein The method of generating and obtaining the seventh data corresponding to the rock in tunnel excavation, and based on the seventh data, establishing the third correspondence relationship between the seventh data, the penetration depth, the penetration force, and the dimensionless plastic zone radius, further includes: Generating and obtaining the tenth data corresponding to the seventh data and having different values; wherein, the tenth data is parameter data with different parameter values; Based on the tenth data, calculate and generate the corresponding penetration depth and penetration pressure relationship data; the calculation formula is as follows: In the formula: F is the penetration force; d is the penetration depth; α is the tool inclination angle.

7. A prediction system for the degree of fragmentation of the surrounding rock of the tunnel face suitable for tunnel excavation, characterized in that, The system is applied to the prediction method for the fragmentation degree of the surrounding rock of the tunnel face suitable for tunnel excavation according to any one of claims 1 to 6, and the system includes: A data acquisition unit, configured to acquire in real time the first data corresponding to tunnel excavation and preprocess the first data; wherein, the first data includes: drilling depth data and thrust data; A model creation unit, configured to create a single-tooth thrust theoretical model, and based on the single-tooth thrust theoretical model and the first data, generate the second data corresponding to the rock in tunnel excavation; wherein, the second data includes rock physical and mechanical parameter data and rock fragmentation degree data; A data generation unit, configured to generate in real time the third data corresponding to tunnel excavation according to the second data; wherein, the third data is the prediction data for the fragmentation degree of the surrounding rock of the tunnel face corresponding to tunnel excavation.

8. The prediction system for the fragmentation degree of the face surrounding rock suitable for tunnel excavation according to claim 7, wherein, The data acquisition unit further includes: A first generation module, configured to generate and acquire the first data, filter the first data, and generate the fourth data corresponding to the first data; wherein, the fourth data is the data after the first data is filtered; A second generation module, configured to acquire the fourth data and perform real-time calibration processing on the fourth data to generate the fifth data corresponding to the fourth data; wherein, the fifth data is the data after the fourth data is calibrated; And / or, the model creation unit further includes: A first creation module, configured to create a single-tooth thrust theoretical model according to the cavity expansion theory, and based on the single-tooth thrust theoretical model, establish the first correspondence relationship between the penetration force and the second data during the process of a single tooth penetrating the rock; A second creation module, configured to generate and acquire the sixth data corresponding to the rock in tunnel excavation, and based on the sixth data, construct the second correspondence relationship between the penetration pressure and the penetration depth under penetration; wherein, the sixth data is geological strength index data; A third creation module, configured to generate and acquire the seventh data corresponding to the rock in tunnel excavation, and based on the seventh data, establish the third correspondence relationship between the seventh data, the penetration depth, the penetration force, and the dimensionless plastic zone radius; wherein, the seventh data includes: rock strength parameter data, tool shape parameter data, and constraint condition parameter data.

9. The prediction system for the fragmentation degree of the face rock mass suitable for tunnel excavation according to claim 8, characterized in that, The first creation module further includes: A third generation module, configured to generate eighth data corresponding to the process of a single tooth penetrating into rock according to the first correspondence and in combination with the single-tooth thrust theoretical model; wherein, the eighth data includes stress field data and displacement field data; A fourth generation module, configured to generate ninth data corresponding to the eighth data based on the equilibrium equation, the Hoek-Brown failure criterion, and the non-associated flow rule; wherein, the ninth data includes radial stress data, tangential stress data, and displacement expression data; The first calculation module is used to calculate and generate the radial stress and tangential stress corresponding to the stress field respectively in the elastic region in combination with the boundary conditions; wherein, the boundary conditions are: σ r *| r＝R = P y *; σ r *| r＝∞ = P0*; where: k is a parameter related to the shape of the small hole; R is the outer boundary radius of the plastic region; r is the distance from the center of the small hole to the point under consideration; is the normalized yield pressure applied on the wall of the small hole; is the normalized pressure received by the small hole at infinity; A second calculation module, configured to calculate and generate a plastic zone radius corresponding to the displacement field in the plastic region in combination with the boundary conditions; wherein, the calculation formula is: Where: R is the radius of the plastic zone; a CE is the inner diameter of the small hole; C1 is a coefficient; β is a coefficient, where β = a / (1 - a); k is a parameter related to the shape of the small hole; And / or, the third creation model further includes: A fifth generation module, configured to generate and obtain tenth data corresponding to the seventh data and having different values; wherein, the tenth data is parameter data with different parameter values; A third calculation module, configured to calculate and generate corresponding penetration depth and penetration pressure relationship data based on the tenth data; wherein, the calculation formula is: In the formula: F is the penetration force; d is the penetration depth; α is the tool inclination angle.

10. A prediction platform for the fragmentation degree of surrounding rock at the tunnel face suitable for tunnel excavation, characterized in that, It includes a processor, a memory, and a prediction platform control program for the fragmentation degree of the face surrounding rock suitable for tunnel excavation; wherein, when the processor executes the prediction platform control program for the fragmentation degree of the face surrounding rock suitable for tunnel excavation, the prediction platform control program for the fragmentation degree of the face surrounding rock suitable for tunnel excavation is stored in the memory, and the prediction platform control program for the fragmentation degree of the face surrounding rock suitable for tunnel excavation implements the prediction method for the fragmentation degree of the face surrounding rock suitable for tunnel excavation according to any one of claims 1 to 6.

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