Rock mass quality real-time evaluation method, device, equipment and readable storage medium

Abstract

This application relates to a method, apparatus, equipment, and readable storage medium for real-time evaluation of rock mass quality, belonging to the fields of underground engineering and geotechnical engineering technology. The method includes inputting a first target drilling parameter corresponding to the drill rod end after drilling into the rock mass to be tested into a preset drilling parameter prediction model, and inverting to obtain a second target drilling parameter corresponding to the drill bit position; inputting the second target drilling parameter into a preset rock breaking energy model to obtain a target rock breaking energy; inputting the target rock breaking energy into a preset rock strength inversion model and a preset rock mass integrity inversion model respectively, and inverting to obtain a target rock strength comprehensive index and a target rock mass integrity comprehensive index; and determining the rock mass quality of the rock mass to be tested based on the mapping relationship between the target rock strength comprehensive index, the target rock mass integrity comprehensive index, and the rock mass quality grade. This application improves the accuracy and reliability of drilling data and realizes real-time evaluation of rock mass quality during drilling operations, applicable to various drilling conditions.

Description

Technical Field

[0001] This application relates to the fields of underground engineering and geotechnical engineering technology, and in particular to a method, apparatus, equipment and readable storage medium for real-time evaluation of rock mass quality. Background Technology

[0002] With the continuous expansion of underground engineering construction in my country, higher demands are being placed on the real-time and accurate evaluation of rock mass quality. Rock mass quality evaluation requires acquiring a large amount of rock mass mechanical parameters and structural characteristic information. Traditional indoor testing methods and in-situ testing methods suffer from drawbacks such as long processing times, cumbersome operations, and high costs, making it difficult to meet the rapid and real-time evaluation needs of long, large tunnels in deep-earth engineering projects. Drilling-while-drilling lithology identification technology is a technique that uses drilling parameters such as thrust, torque, rotational speed, and drilling rate during the drilling process to inversely analyze rock mass mechanical parameters. Research by scholars both domestically and internationally has shown that drilling-while-drilling parameters have a good correlation with rock strength parameters and rock mass structural parameters. This technology provides a new approach to solving the aforementioned problems.

[0003] Since the concept of Mechanical Specific Energy (MSE) was proposed in 1965, many scholars have carried out specific energy model research in order to accurately obtain drilling efficiency, such as the Pessier model, Dupriest model, Cherif model, Armenta model, Fan Honghai model, Meng Yingfeng model, etc., which have greatly promoted the development of mechanical specific energy research theory. However, there are still some technical problems that have not been effectively solved. Specifically, the following are the problems: (1) The drilling parameters of the existing specific energy model are generally measured at the end of the drill rod or the operating table of the drilling rig. Since the distance from the drill bit is far, it is impossible to obtain the real working conditions and actual parameters of the drill bit, making it difficult to directly use the test results for rock and soil identification; (2) The existing specific energy model has not fully considered the impact rotary drilling working conditions. Since the rock breaking mechanism of impact cutting and the rock breaking mechanism of rotary cutting are completely different, the existing model is difficult to characterize the drilling efficiency of rock drills, down-the-hole hammers and other impact drills; (3) The existing specific energy model is mainly used for mechanical drilling speed prediction, drilling efficiency evaluation, drilling working condition identification, drill bit wear monitoring, etc., but it is difficult to apply it to the engineering rock mass quality evaluation research. It is evident that existing technologies for evaluating the quality of engineering rock masses suffer from several drawbacks, including the difficulty and high cost of obtaining drill bit position parameters during drilling, the failure of the energy specificity model to consider impact drilling conditions, and the relatively coarse results of traditional rock mass quality evaluation. Summary of the Invention

[0004] This application provides a method, apparatus, equipment, and readable storage medium for real-time evaluation of rock mass quality, in order to solve the problems existing in related technologies.

[0005] Firstly, a method for real-time evaluation of rock mass quality is provided, including the following steps:

[0006] Obtain the first target drilling parameters at the end of the drill rod after the drilling rig has drilled into the rock mass to be tested;

[0007] The first target drilling parameters are input into a preset drilling parameter prediction model, and the second target drilling parameters corresponding to the drill bit position are obtained by inversion.

[0008] The second target drilling parameters are input into the preset rock breaking energy model to obtain the target rock breaking energy.

[0009] The target rock breaking energy is input into the preset rock strength inversion model and the preset rock mass integrity inversion model, respectively, and the target rock strength comprehensive index and the target rock mass integrity comprehensive index are obtained respectively.

[0010] The rock mass quality of the rock mass to be tested is determined based on the mapping relationship between the comprehensive index of target rock strength, the comprehensive index of target rock mass integrity, and the rock mass quality grade.

[0011] In some embodiments, before the step of inputting the first target drilling parameter into a preset drilling parameter prediction model, the method further includes:

[0012] Obtain the first experimental drilling parameters at the drill rod end and the second experimental drilling parameters at the drill bit position under different working conditions. The working conditions include lithology, stratum combination, drill rod diameter, drill bit type, drilling mode, and borehole angle.

[0013] The preset neural network model is trained based on the first and second experimental drilling parameters to obtain a preset drilling parameter prediction model, which is as follows:

[0014] DP2′=f1(DP1′)

[0015] In the formula, DP2′ represents the target drilling parameters at the drill bit position, f1 represents the training function, and DP1′ represents the target drilling parameters at the drill pipe end.

[0016] In some embodiments, before the step of inputting the second target drilling parameters into the preset rock breaking energy model, the method further includes:

[0017] Based on the drilling parameters of the second experiment, impact energy quantum model, drill pressure energy quantum model, rotation energy quantum model, hydraulic energy quantum model and rock fragmentation volume quantum model were constructed respectively.

[0018] A preset rock-breaking specific energy model is generated based on the impact energy model, the drilling pressure energy model, the rotation energy model, the hydraulic energy model, and the rock fragmentation volumetric model. The preset rock-breaking specific energy model is as follows:

[0019]

[0020] In the formula, BSE represents the rock-breaking energy, and W s W represents impact energy. f W represents drilling pressure energy. r W represents gyration energy. w V represents water conservancy energy. r Let P represent the rock fragmentation volume, η be the impact transmission efficiency, f be the impact frequency, and P be the impact frequency. s Let P be the impact pressure, Δσ be the difference in area between the front and rear of the impact piston, δ be the pulse duration, m be the piston mass, d be the drill bit diameter, v be the drilling speed, a be the cross-sectional area of ​​the advance piston, and P be the impact pressure. f For propulsion pressure, N is rotational speed, M is torque, and P is... b This refers to the water power of the drill bit.

[0021] In some embodiments, before the step of inputting the target rock breaking energy into the preset rock strength inversion model and the preset rock mass integrity inversion model, the method further includes:

[0022] The comprehensive strength index of the experimental rock was calculated based on the uniaxial compressive strength and point load strength of the experimental rock.

[0023] The comprehensive index of experimental rock mass integrity is calculated based on the volume joint number and integrity coefficient of the experimental rock mass.

[0024] The mechanical efficiency coefficient is determined based on the experimental rock strength comprehensive index and the preset rock breaking energy model.

[0025] A preset rock strength inversion model is created based on the mechanical efficiency coefficient and the preset rock breaking energy model.

[0026] The regression function is determined based on the experimental rock mass integrity comprehensive index and the preset rock breaking energy model.

[0027] A preset rock mass integrity inversion model is created based on the regression function and the preset rock breaking energy model.

[0028] In some embodiments, the formula for calculating the comprehensive strength index of the experimental rock is as follows:

[0029] R D =a·R C +b·(22.82I S 0.75 )

[0030] The formula for calculating the comprehensive index of rock mass integrity in the experiment is as follows:

[0031]

[0032] In the formula, R D R represents the comprehensive strength index of the experimental rock. C I represents the uniaxial compressive strength of rock. S I represents the rock point load strength. D J represents the comprehensive index of experimental rock mass integrity. V K represents the volumetric joint number of the rock mass. V The value represents the rock mass integrity coefficient, where a, b, c, and d are all weighting coefficients.

[0033] In some embodiments, the regression function is:

[0034] f2=b0+b1R BSE +b2IQR BSE +b3σ BSE +b4MD BSE +b5CV BSE

[0035] In the formula, f2 represents the regression function, b0, b1, b2, b3, b4, and b5 all represent partial regression coefficients, and R0... BSE IQR represents the range of rock-breaking specific energy. BSE σ represents the interquartile range of rock-breaking specific energy. BSE The standard deviation of rock-breaking energy, MD BSE CV represents the average difference in rock-breaking specific energy. BSE This represents the coefficient of variation of rock breaking energy.

[0036] In some embodiments, the preset rock strength inversion model is:

[0037] R′ D =mBSE

[0038] The preset rock mass integrity inversion model is as follows:

[0039] I' D =f2(R BSE IQR BSE ,σ BSE ,MD BSE ,CV BSE )

[0040] In the formula, R′ D The target rock strength index is represented by m, the mechanical efficiency coefficient is represented by BSE, and the rock breaking energy is represented by I′. D This represents the comprehensive index of the integrity of the target rock mass.

[0041] Secondly, a real-time rock mass quality evaluation device is provided, including:

[0042] The parameter acquisition unit is used to acquire the first target drilling parameters at the end of the drill rod after the drilling rig has drilled into the rock mass to be tested.

[0043] The first inversion unit is used to input the first target drilling parameters into a preset drilling parameter prediction model and invert to obtain the second target drilling parameters corresponding to the drill bit position.

[0044] The data calculation unit is used to input the second target drilling parameters into a preset rock breaking energy model to obtain the target rock breaking energy.

[0045] The second inversion unit is used to input the target rock breaking energy into the preset rock strength inversion model and the preset rock mass integrity inversion model respectively, and invert to obtain the target rock strength comprehensive index and the target rock mass integrity comprehensive index respectively.

[0046] The quality evaluation unit is used to determine the rock mass quality of the rock mass to be tested based on the mapping relationship between the comprehensive strength index of the target rock, the comprehensive integrity index of the target rock mass, and the rock mass quality grade.

[0047] Thirdly, a real-time rock mass quality evaluation device is provided, comprising: a memory and a processor, wherein the memory stores at least one instruction, and the at least one instruction is loaded and executed by the processor to implement the previous real-time rock mass quality evaluation method.

[0048] Fourthly, a computer-readable storage medium is provided, which stores a computer program that, when executed by a processor, implements the aforementioned real-time rock mass quality evaluation method.

[0049] This application provides a method, apparatus, equipment, and readable storage medium for real-time evaluation of rock mass quality. The method includes: acquiring a first target drilling parameter at the end of the drill rod corresponding to the rock mass to be tested after the drilling rig has drilled into it; inputting the first target drilling parameter into a preset drilling parameter prediction model to invert and obtain a second target drilling parameter corresponding to the drill bit position; inputting the second target drilling parameter into a preset rock breaking energy model to obtain a target rock breaking energy; inputting the target rock breaking energy into a preset rock strength inversion model and a preset rock mass integrity inversion model to obtain a target rock strength comprehensive index and a target rock mass integrity comprehensive index, respectively; and determining the rock mass quality of the rock mass to be tested based on the mapping relationship between the target rock strength comprehensive index, the target rock mass integrity comprehensive index, and the rock mass quality grade. This application obtains the drilling parameters of the drill bit position by inverting the drilling parameters at the drill pipe end, which improves the accuracy and reliability of the drilling data and solves the problems of high difficulty and high cost in measuring the drilling parameters of the drill bit position in actual engineering. At the same time, it can quickly and accurately obtain the rock breaking energy during the drilling process by using the drilling parameters during drilling operations, and obtain the comprehensive rock strength index and the comprehensive rock mass integrity index through the rock breaking energy, thereby realizing the real-time evaluation of rock mass quality during drilling operations. It can be applied to various drilling conditions such as percussion and rotary drilling. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0051] Figure 1 A flowchart illustrating a real-time rock mass quality evaluation method provided in this application embodiment;

[0052] Figure 2 A schematic diagram illustrating the specific process of the real-time rock mass quality evaluation method provided in the embodiments of this application;

[0053] Figure 3 A schematic diagram illustrating the specific process of the target drilling parameters for the drill bit position provided in this embodiment of the application;

[0054] Figure 4 This is a schematic diagram of the structure of a real-time rock mass quality evaluation device provided in an embodiment of this application;

[0055] Figure 5 This is a structural schematic diagram of a real-time rock mass quality evaluation device provided in an embodiment of this application. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0057] See Figure 1 and Figure 2 As shown in the figure, this application provides a method for real-time evaluation of rock mass quality, including the following steps:

[0058] Step S10: Obtain the first target drilling parameters at the end of the drill rod after the drilling rig has drilled into the rock mass to be tested;

[0059] As an example, it is understandable that in actual engineering drilling operations, due to technical, time, and cost issues, it is not possible to equip every digital drilling rig with near-bit measurement-while-drilling (WWWD) equipment; only WWWD parameters at the drill rod end or control panel position can be obtained. Therefore, this embodiment will monitor WWWD parameters in real time during drilling operations such as anchor holes, blast holes, advance exploratory holes, and geological exploration holes corresponding to specific engineering digital drilling tests. This involves collecting WWWD parameters such as impact pressure, rotational pressure, feed pressure, flow rate, displacement, rotational speed, drilling speed, and torque through various electronic sensors to obtain the first target WWWD parameters at the drill rod end after the drilling rig has penetrated the rock mass under test. These first target WWWD parameters include impact pressure, feed pressure, rotational pressure, displacement, rotational speed, drilling speed, torque, and flushing fluid flow rate at the drill rod end.

[0060] Step S20: Input the first target drilling parameters into the preset drilling parameter prediction model to invert and obtain the second target drilling parameters corresponding to the drill bit position;

[0061] As an example, in this embodiment, after obtaining the drilling parameters corresponding to the drill pipe end, the drilling parameters corresponding to the drill pipe end are input into a preset drilling parameter prediction model. After the preset drilling parameter prediction model is processed accordingly, the second target drilling parameters corresponding to the drill bit position after the drilling rig enters the rock mass to be tested can be derived by inversion. The second target drilling parameters include the impact pressure, propulsion pressure, rotation pressure, displacement, rotation speed, drilling speed, torque, flushing fluid flow rate, etc. corresponding to the drill bit position.

[0062] Furthermore, before the step of inputting the first target drilling parameters into the preset drilling parameter prediction model, the method further includes:

[0063] Obtain the first experimental drilling parameters at the drill rod end and the second experimental drilling parameters at the drill bit position under different working conditions. The working conditions include lithology, stratum combination, drill rod diameter, drill bit type, drilling mode, and borehole angle.

[0064] The preset neural network model is trained based on the first and second experimental drilling parameters to obtain a preset drilling parameter prediction model, which is as follows:

[0065] DP2′=f1(DP1′)

[0066] In the formula, DP2′ represents the target drilling parameters at the drill bit position, f1 represents the training function, and DP1′ represents the target drilling parameters at the drill pipe end.

[0067] As an example, it is understandable that measuring the drilling parameters at the drill bit position in actual engineering projects is difficult and costly. Therefore, in order to solve this problem, this embodiment will establish a preset drilling parameter prediction model through deep learning methods, so that the preset drilling parameter prediction model can obtain the drilling parameters at the drill bit position by inverting the drilling parameters at the drill pipe end.

[0068] See Figure 3 As shown, indoor and in-situ digital drilling tests were conducted under different working conditions. A deep learning model M1 (preset drilling parameter prediction model) was established based on the experimental drilling parameters DP1 at the drill pipe end and DP2 at the drill bit position. The working conditions included different lithological types, strata combinations, drill pipe diameter, drill bit type, drilling mode, and borehole angle.

[0069] Specifically, the following neural network model is trained using the experimental drilling parameters DP1 at the end of the drill pipe and DP2 at the drill bit position: DP2 = f1(DP1). After training, the training function f1 can be obtained. It should be noted that the training function f1 can be determined by deep learning networks such as convolutional neural networks, fully connected neural networks, and recurrent neural networks. The specific method can be determined according to actual needs and is not limited here.

[0070] For example, taking a convolutional neural network as an example, the calculation steps are as follows: The experimental drilling parameters DP1 at the drill pipe end are used as the input to the neural network, and the experimental drilling parameters DP2 at the drill bit position are used as the label of the neural network. First, the weights of the convolutional neural network are initialized, and the experimental drilling parameters DP1 at the drill pipe end are input. High-dimensional features of the data are extracted through five convolutional layers. Next, downsampling is performed through a max pooling layer, using the local maximum value of the data to represent the data features of that region. Then, the learned features are mapped to the output of the neural network through a fully connected layer, i.e., the predicted value of the experimental drilling parameters DP2 at the drill bit position. Then, the mean squared error between the neural network output and the label is calculated. Based on the mean squared error, the Adam optimizer is used to update the parameters in the neural network. The above steps are iterated until the neural network error converges, resulting in a series of convolutional neural network parameters used to predict the experimental drilling parameters DP2 at the drill bit position, thus completing the training of the neural network.

[0071] Once the training function f1 is obtained, the preset drilling parameter prediction model M1 can be generated:

[0072] DP2′=f1(DP1′)

[0073] In the formula, DP2′ represents the target drilling parameters at the drill bit position, and DP1′ represents the target drilling parameters at the drill pipe end.

[0074] Therefore, this embodiment establishes a drilling parameter prediction model for the drill bit position by comparing drilling parameters based on the drill pipe end and drill bit position through deep learning methods. For actual engineering drilling operations, the drilling parameters for the drill bit position can be inverted by collecting the drilling parameters at the drill pipe end. Without changing the drilling process and drilling equipment, it solves the problems of high difficulty and cost in measuring drilling parameters at the drill bit position in actual engineering, eliminates the measurement error when using the drilling parameters at the drill pipe end to calculate the rock breaking energy, and improves the authenticity and accuracy of the drilling data. It is suitable for drilling measurements under various complex geological conditions.

[0075] Step S30: Input the second target drilling parameters into the preset rock breaking energy model to obtain the target rock breaking energy;

[0076] As an example, in this embodiment, the drilling parameters at the drill bit location are processed by a preset rock breaking energy model to obtain the rock breaking energy corresponding to the rock mass to be tested. The rock breaking energy can accurately reflect the mechanical energy consumed in breaking a unit volume of rock.

[0077] Furthermore, before the step of inputting the second target drilling parameters into the preset rock breaking energy model, the method further includes:

[0078] Based on the drilling parameters of the second experiment, impact energy quantum model, drill pressure energy quantum model, rotation energy quantum model, hydraulic energy quantum model and rock fragmentation volume quantum model were constructed respectively.

[0079] A preset rock-breaking specific energy model is generated based on the impact energy model, the drilling pressure energy model, the rotation energy model, the hydraulic energy model, and the rock fragmentation volumetric model. The preset rock-breaking specific energy model is as follows:

[0080]

[0081] In the formula, BSE represents the rock-breaking energy, and W s W represents impact energy. f W represents drilling pressure energy. r W represents gyration energy. w V represents water conservancy energy. r Let P represent the rock fragmentation volume, η be the impact transmission efficiency, f be the impact frequency, and P be the impact frequency. s Let P be the impact pressure, Δσ be the difference in area between the front and rear of the impact piston, δ be the pulse duration, m be the piston mass, d be the drill bit diameter, v be the drilling speed, a be the cross-sectional area of ​​the advance piston, and P be the impact pressure. f For propulsion pressure, N is rotational speed, M is torque, and P is... b This refers to the water power of the drill bit.

[0082] Exemplary and understandable, the experimental drilling parameters DP2 obtained at the drill bit location through digital drilling testing include drilling electro-hydraulic parameters and drilling site engineering parameters. The drilling electro-hydraulic parameters are the aforementioned drilling parameters such as impact pressure, rotational pressure, feed pressure, flow rate, displacement, rotational speed, and torque. The drilling site engineering parameters are the aforementioned working conditions such as lithology, strata combination, drill pipe diameter, drill bit type, drilling mode, and borehole angle. Based on the second experimental drilling parameters DP2, the impact energy, drilling pressure energy, rotational energy, hydraulic energy, and rock breaking volume during the drill bit's drilling process can be calculated, thereby obtaining the preset rock breaking energy model M2.

[0083] Specifically, the impact energy W corresponding to the impact energy sub-model s The calculation formula is:

[0084]

[0085] In the formula, W s P represents the impact energy, measured in J; η represents the impact transmission efficiency, preferably 0.4–0.7; s The impact pressure is expressed in MPa; Δσ is the difference in area between the front and rear of the impact piston, expressed in mm. 2 δ is the pulse duration; f is the impact frequency, in times / min; t is the drilling time, in min; m is the piston mass, in kg.

[0086] Drilling pressure energy W corresponding to the drilling pressure energy sub-model f The calculation formula is:

[0087] W f =P f al

[0088] In the formula, W f Drilling pressure energy, measured in J; P f The thrust is expressed in MPa; 'a' represents the cross-sectional area of ​​the thrust piston, expressed in mm. 2 ; l represents the drilling distance, in meters;

[0089] The rotational energy W corresponding to the rotational energy quantum model r The calculation formula is:

[0090] W r =2πNtM

[0091] In the formula, W r The unit is rotational energy (J); N is rotational speed (rev / min); t is drilling time (min); M is torque (N·m).

[0092] The hydraulic energy W corresponding to the hydraulic energy sub-model w The calculation formula is:

[0093] W w =-λ·P b ·t

[0094] In the formula, W w λ represents hydraulic energy, measured in J; λ is the hydraulic correlation coefficient, λ = 1.1164 × d -1.9126 ;P b t represents the drill bit water power, in kW; t represents the drilling time, in min.

[0095] Wherein, the drill bit water power P b The calculation formula is:

[0096]

[0097] In the formula, P b Δp represents the drill bit's water power, measured in kW. b The drill bit pressure drop is expressed in MPa; Q is the flushing fluid flow rate in L / s; and ρ is the flushing fluid density in g / cm³. 3 c is the nozzle flow coefficient, taken as 0.950~0.985; d i Where i is the nozzle diameter (i = 1, 2, ..., z), in cm; z is the number of nozzles;

[0098] Rock fragmentation volume V corresponding to the rock fragmentation volume sub-model r The calculation formula is:

[0099]

[0100] In the formula, V r The volume of broken rock is expressed in meters. 3 ; d is the drill bit diameter, in meters; l is the drilling distance, in meters;

[0101] Then the rock breaking energy model M2 is:

[0102]

[0103] In the formula, BSE is the rock breaking energy in Pa; v is the drilling speed in m / min.

[0104] Therefore, this embodiment obtains the rock-breaking energy model by comprehensively considering impact energy, drilling pressure energy, rotational energy, and hydraulic energy. Various electronic sensors can collect parameters such as impact pressure, rotational pressure, propulsion pressure, flow rate, displacement, rotational speed, drilling speed, and torque during drilling, thereby quickly and accurately obtaining the rock-breaking energy during the drilling process. It is applicable to various drilling conditions such as impact drilling and rotary drilling.

[0105] Step S40: Input the target rock breaking energy into the preset rock strength inversion model and the preset rock mass integrity inversion model respectively, and obtain the target rock strength comprehensive index and the target rock mass integrity comprehensive index respectively;

[0106] As an example, in this embodiment, the target rock breaking energy is processed by a preset rock strength inversion model and a preset rock mass integrity inversion model, respectively, so as to obtain the target rock strength comprehensive index and the target rock mass integrity comprehensive index corresponding to the rock mass to be tested. The magnitude of the target rock strength comprehensive index and the target rock mass integrity comprehensive index can characterize the quality of the rock mass to be tested.

[0107] Furthermore, before the step of inputting the target rock breaking energy into the preset rock strength inversion model and the preset rock mass integrity inversion model respectively, the method further includes:

[0108] The comprehensive strength index of the experimental rock is calculated based on its uniaxial compressive strength and point load strength. The formula for calculating the comprehensive strength index of the experimental rock is as follows:

[0109] R D =a·R C +b·(22.82I S 0.75 )

[0110] In the formula, RD R represents the comprehensive strength index of the experimental rock. C I represents the uniaxial compressive strength of rock. S This represents the rock point load strength, where a and b are both weighting coefficients;

[0111] The comprehensive integrity index of the experimental rock mass is calculated based on the volumetric joint number and the integrity coefficient of the experimental rock mass; wherein, the formula for calculating the comprehensive integrity index of the experimental rock mass is:

[0112]

[0113] In the formula, I D J represents the comprehensive index of experimental rock mass integrity. V K represents the volumetric joint number of the rock mass. V This represents the rock mass integrity coefficient, where c and d are both weighting coefficients;

[0114] The mechanical efficiency coefficient is determined based on the experimental rock strength comprehensive index and the preset rock breaking energy model.

[0115] A preset rock strength inversion model is created based on the mechanical efficiency coefficient and the preset rock breaking energy model; wherein, the preset rock strength inversion model is:

[0116] R′ D =mBSE

[0117] In the formula, R′ D The target rock strength index is represented by m, the mechanical efficiency coefficient is represented by BSE, and the rock breaking energy is represented by BSE.

[0118] A regression function is determined based on the experimental rock mass integrity comprehensive index and the preset rock breaking energy model; wherein, the regression function is:

[0119] f2=b0+b1R BSE +b2IQR BSE +b3σ BSE +b4MD BSE +b5CV BSE

[0120] In the formula, f2 represents the regression function, b0, b1, b2, b3, b4, and b5 all represent partial regression coefficients, and R0... BSE IQR represents the range of rock-breaking specific energy. BSE σ represents the interquartile range of rock-breaking specific energy. BSE The standard deviation of rock-breaking energy, MD BSE CV represents the average difference in rock-breaking specific energy. BSE The coefficient of variation represents the rock-breaking energy.

[0121] A preset rock mass integrity inversion model is created based on the regression function and the preset rock breaking energy model, wherein the preset rock mass integrity inversion model is as follows:

[0122] I' D =f2(R BSE IQR BSE ,σ BSE ,MD BSE ,CV BSE )

[0123] In the formula, I′ D This represents the comprehensive index of the integrity of the target rock mass.

[0124] As an example, this embodiment will obtain the experimental rock strength composite index R by performing rock strength tests and rock mass integrity tests. D and the comprehensive index of rock mass integrity I D Among them, rock strength testing includes uniaxial compressive strength testing and point load testing to obtain strength parameters including uniaxial compressive strength and point load strength; while rock mass integrity testing includes geological survey testing and elastic wave velocity testing to obtain structural parameters including rock mass volume joint number and rock mass integrity coefficient.

[0125] Specifically, the comprehensive strength index R of the experimental rock D It will be obtained through the following calculation formula:

[0126] R D =a·R C +b·(22.82I S 0.75 )

[0127] In the formula, R C I represents the uniaxial compressive strength of rock, expressed in MPa. S Let be the rock point load strength, in MPa; a and b are weighting coefficients, and a+b=1;

[0128] Rock Mass Integrity Composite Index I D It will be obtained through the following calculation formula:

[0129]

[0130] In the formula, J V This represents the volumetric joint number of the rock mass, expressed in units of joints / m². 3 ;K V is the rock mass integrity coefficient; c and d are weighting coefficients, and c+d=1;

[0131] The weighting coefficients a, b, c, and d are determined using the instability index analysis method. The specific steps include data standardization, variability analysis of each indicator, and determination of the weights for each indicator. The determination process of weighting coefficients a and b will be illustrated below as an example: First, the uniaxial compressive strength R of the rock is calculated. C Rock point load strength I S The corresponding average value σ i (i = 1, 2) and standard deviation μ i (i = 1, 2), then through formula V i =σ i / μ i Determine the coefficient of variation V for each factor. i (i=1,2), and finally, based on the coefficient of variation of each factor, use the formula W i =V i Calculate its weighting coefficient W using / (V1+V2). i (i = 1, 2), that is, determining the weighting coefficients a and b. Therefore, this embodiment proposes a comprehensive rock strength index R by comprehensively considering commonly used testing methods for rock strength and rock mass integrity. D Comprehensive index of rock mass integrity I D The instability index analysis method is used to objectively determine the weight of the indicators, which can more effectively reflect the rock strength and rock mass integrity information compared with single indicator factors.

[0132] It is understandable that the physical meaning of rock-breaking specific energy is the mechanical energy consumed in breaking a unit volume of rock. That is, when all input mechanical energy is used to break the rock and there is no energy loss, the mechanical efficiency of the drilling rig reaches its maximum. At this point, the rock-breaking specific energy can be considered equal to the uniaxial compressive strength of the rock. Therefore, this embodiment establishes a rock strength inversion model M3 based on the above idea. Specifically, this embodiment will be based on the experimental rock strength comprehensive index R... D The rock strength inversion model M3 is constructed using the rock breaking energy model M2, which is the comprehensive index of experimental rock strength R. D Substituting the rock breaking energy model BSE into R D =In mBSE, the mechanical efficiency coefficient m is determined; then, the rock strength inversion model M3 can be constructed using the mechanical efficiency coefficient m and the rock breaking energy model M2.

[0133] R′ D =mBSE

[0134] In the formula, R′ D This represents the comprehensive strength index of the target rock.

[0135] Therefore, in actual engineering drilling operations, the comprehensive index R′ of the target rock strength can be obtained through the rock breaking energy and rock strength inversion model M3. D .

[0136] It should be understood that since rock breaking energy reflects the mechanical energy consumed in breaking a unit volume of rock, and there is a good correlation between drilling parameters and rock mass structural parameters, the dispersion of rock breaking energy can reflect rock mass integrity information. When the rock mass is relatively fragmented, the drilling parameters produce a corresponding response, specifically manifested as a larger dispersion of rock breaking energy; conversely, when the rock mass is relatively intact, the dispersion of rock breaking energy obtained based on drilling parameters is smaller. Therefore, based on the above idea, this embodiment will use the stepwise regression method to sequentially introduce commonly used dispersion indicators into the regression equation to obtain the optimal regression equation reflecting rock mass integrity, that is, the regression function f2 is determined by the stepwise regression method.

[0137] Specifically, the calculation steps of the stepwise regression method are as follows: First, calculate the dispersion evaluation index X for each rock breaking energy. i The partial regression sum of squares of the comprehensive rock mass integrity index is used to introduce each variable into the regression equation in descending order of partial regression sum of squares. Next, the introduced variables are subjected to hypothesis testing. If the hypothesis is passed, the variable is introduced into the regression equation. The variables in the equation are then subjected to hypothesis testing, and the indicators that contribute the least and degenerate into insignificance are removed. Finally, the above steps are repeated until there are no independent variables that can be introduced into the regression equation and no independent variables that can be removed from the regression equation. The final result is the optimal regression equation.

[0138] It is understandable that this embodiment will first calculate the regression function based on the comprehensive index of experimental rock mass integrity and the preset rock breaking energy model, that is, the comprehensive index of experimental rock mass integrity I D The range R of rock-breaking energy BSE Interquartile range (IQR) of rock breaking energy BSE Standard deviation of rock breaking energy σ BSE The average difference in rock breaking energy MD BSE Coefficient of variation (CV) of rock breaking energy BSE Substituting the values ​​into the following formula, the regression function f2 can be calculated:

[0139] I D =f2(R BSE IQR BSE ,σ BSE ,MD BSE ,CV BSE )

[0140] Specifically, the partial regression coefficients are calculated by substituting the regression function values ​​and the dispersion evaluation index corresponding to the rock breaking energy into the following formula:

[0141] f2=b0+b1X1+b2X2+b3X3+b4X4+b5X5

[0142] In the formula, X i X1 is the dispersion index of rock-breaking energy, where i = {0, 1, ..., 5}, and X1 is the range R of rock-breaking energy. BSE X2 is the interquartile range (IQR) of rock-breaking specific energy. BSE X3 is the standard deviation σ of the rock-breaking specific energy. BSE X4 represents the average difference in rock-breaking specific energy, MD. BSE X5 is the coefficient of variation (CV) of rock-breaking specific energy. BSE b i These are the biased regression coefficients, i = {0, 1, ..., 5};

[0143] Then, substitute the calculated partial regression coefficients b0 to b5 into the following formula to obtain the regression function f2:

[0144] f2=b0+b1R BSE +b2IQR BSE +b3σ BSE +b4MD BSE +b5CV BSE

[0145] Finally, based on the regression function f2 and the preset rock breaking energy model, the preset rock mass integrity inversion model M4 can be constructed:

[0146] I' D =f2(R BSE IQR BSE ,σ BSE ,MD BSE ,CV BSE )

[0147] In the formula, I′ D This represents the comprehensive index of target rock mass integrity. It should be noted that before substituting the target rock breaking energy (BSE) into the preset rock mass integrity inversion model M4 for calculation, preprocessing such as data cleaning, standardization, normalization, and correlation analysis is required.

[0148] Step S50: Determine the rock mass quality of the rock mass to be tested based on the mapping relationship between the comprehensive strength index of the target rock, the comprehensive integrity index of the target rock mass, and the rock mass quality grade.

[0149] As an example, in this embodiment, after obtaining the comprehensive index R′ of the target rock strength corresponding to the rock mass to be tested... D and the comprehensive index of target rock mass integrity I′ D Then, the comprehensive strength index R′ of the target rock can be used. D Comprehensive index of target rock mass integrity I′ DThe mapping relationship between rock mass quality grade and rock mass quality grade is used to determine the rock mass quality of the rock mass to be tested, thereby realizing real-time evaluation of rock mass quality.

[0150] Specifically, the rock mass quality index (BQ) is first calculated using the following formula. Then, the BQ value is substituted into the mapping relationship to obtain the rock mass quality level. The specific mapping relationship is shown in Table 1.

[0151] BQ = 90 + 3R' D +250I' D

[0152] Where, when R' D >90I' D At +30, it should be R' D =90I' D +30 and I′ D Substitute into the calculation of BQ value; when I' D >0.04R' D When +0.4, it should be I' D =0.04R' D +0.4 and R′ D Substitute the values ​​into the formula to calculate the BQ value.

[0153] Table 1 Classification of Rock Mass Quality Grades

[0154] Rock mass quality index BQ >550 550～451 450～351 350～251 <250 Rock mass quality grade Ⅰ Ⅱ Ⅲ Ⅳ Ⅴ

[0155] Therefore, this embodiment, for rock strength parameters and rock integrity information in rock mass quality evaluation, first conducts digital drilling tests and rock mechanics experiments to obtain four models: A preset drilling parameter prediction model M1 is obtained based on the first experimental drilling parameters corresponding to the drill rod end and the second experimental drilling parameters corresponding to the drill bit position, used to invert the drilling parameters at the drill bit position after the drilling rig enters the rock mass to be tested; a preset rock breaking energy model M2 is obtained by calculating the impact energy, drilling pressure energy, rotational energy, hydraulic energy, and rock fragmentation volume during the drilling process based on the experimental drilling parameters at the drill bit position; and a preset rock strength inversion model M2 is obtained based on the preset rock breaking energy model M2. The process involves several steps: First, the drilling parameters collected at the drill rod end are substituted into the preset drilling parameter prediction model M1 to obtain the drilling parameters at the drill bit position. Then, the drilling parameters at the drill bit position are substituted into the preset rock breaking energy model M2 to obtain the target rock breaking energy. Finally, the target rock strength comprehensive index and target rock integrity comprehensive index are obtained through the preset rock strength inversion model M3 and the preset rock integrity inversion model M4. Based on these target rock strength comprehensive index and target rock integrity comprehensive index, the real-time evaluation of rock mass quality can be achieved.

[0156] In summary, this embodiment controls, monitors, and analyzes drilling parameters such as impact pressure, propulsion pressure, rotational pressure, displacement, rotational speed, drilling speed, torque, and flushing fluid flow rate during the drilling process to obtain rock strength parameters and rock mass integrity information, thereby enabling real-time evaluation of the engineering rock mass quality. Specifically, model M1 in this embodiment can obtain drilling parameters at the drill bit position based on the drilling parameters at the drill pipe end, improving the accuracy and reliability of the drilling data. In actual engineering construction, due to limitations in exploration methods and the influence of natural geological conditions, the actual classification of surrounding rock grades is relatively coarse, failing to achieve a refined evaluation of rock mass quality at all mileage markers. Therefore, this embodiment monitors and analyzes drilling parameters in real time during drilling operations such as anchor holes, blast holes, advance exploratory holes, and geological exploration holes, and obtains the comprehensive rock strength index and comprehensive rock mass integrity index through rock breaking energy. This achieves a refined and real-time evaluation of the rock mass quality encountered during drilling operations. The evaluation results can be used in technical fields such as tunnel excavation design, support optimization, and deformation control.

[0157] See Figure 4 As shown in the figure, this application embodiment also provides a real-time rock mass quality evaluation device, including:

[0158] The parameter acquisition unit is used to acquire the first target drilling parameters at the end of the drill rod after the drilling rig has drilled into the rock mass to be tested.

[0159] The first inversion unit is used to input the first target drilling parameters into a preset drilling parameter prediction model and invert to obtain the second target drilling parameters corresponding to the drill bit position.

[0160] The data calculation unit is used to input the second target drilling parameters into a preset rock breaking energy model to obtain the target rock breaking energy.

[0161] The second inversion unit is used to input the target rock breaking energy into the preset rock strength inversion model and the preset rock mass integrity inversion model respectively, and invert to obtain the target rock strength comprehensive index and the target rock mass integrity comprehensive index respectively.

[0162] The quality evaluation unit is used to determine the rock mass quality of the rock mass to be tested based on the mapping relationship between the comprehensive strength index of the target rock, the comprehensive integrity index of the target rock mass, and the rock mass quality grade.

[0163] Furthermore, the device also includes a model building unit, which is used for:

[0164] Obtain the first experimental drilling parameters at the drill rod end and the second experimental drilling parameters at the drill bit position under different working conditions. The working conditions include lithology, stratum combination, drill rod diameter, drill bit type, drilling mode, and borehole angle.

[0165] The preset neural network model is trained based on the first and second experimental drilling parameters to obtain a preset drilling parameter prediction model, which is as follows:

[0166] DP2′=f1(DP1′)

[0167] In the formula, DP2′ represents the target drilling parameters at the drill bit position, f1 represents the training function, and DP1′ represents the target drilling parameters at the drill pipe end.

[0168] Furthermore, the model building unit is also used for:

[0169] Based on the drilling parameters of the second experiment, impact energy quantum model, drill pressure energy quantum model, rotation energy quantum model, hydraulic energy quantum model and rock fragmentation volume quantum model were constructed respectively.

[0170] A preset rock-breaking specific energy model is generated based on the impact energy model, the drilling pressure energy model, the rotation energy model, the hydraulic energy model, and the rock fragmentation volumetric model. The preset rock-breaking specific energy model is as follows:

[0171]

[0172] In the formula, BSE represents the rock-breaking energy, and W s W represents impact energy. f W represents drilling pressure energy. r W represents gyration energy. w V represents water conservancy energy. r Let P represent the rock fragmentation volume, η be the impact transmission efficiency, f be the impact frequency, and P be the impact frequency. s Let P be the impact pressure, Δσ be the difference in area between the front and rear of the impact piston, δ be the pulse duration, m be the piston mass, d be the drill bit diameter, v be the drilling speed, a be the cross-sectional area of ​​the advance piston, and P be the impact pressure. f For propulsion pressure, N is rotational speed, M is torque, and P is... b This refers to the water power of the drill bit.

[0173] Furthermore, the model building unit is also used for:

[0174] The comprehensive strength index of the experimental rock was calculated based on the uniaxial compressive strength and point load strength of the experimental rock.

[0175] The comprehensive index of experimental rock mass integrity is calculated based on the volume joint number and integrity coefficient of the experimental rock mass.

[0176] The mechanical efficiency coefficient is determined based on the experimental rock strength comprehensive index and the preset rock breaking energy model.

[0177] A preset rock strength inversion model is created based on the mechanical efficiency coefficient and the preset rock breaking energy model.

[0178] The regression function is determined based on the experimental rock mass integrity comprehensive index and the preset rock breaking energy model.

[0179] A preset rock mass integrity inversion model is created based on the regression function and the preset rock breaking energy model.

[0180] Furthermore, the formula for calculating the comprehensive strength index of the experimental rock is as follows:

[0181] R D =a·R C +b·(22.82I S 0.75 )

[0182] The formula for calculating the comprehensive index of rock mass integrity in the experiment is as follows:

[0183]

[0184] In the formula, R D R represents the comprehensive strength index of the experimental rock. C I represents the uniaxial compressive strength of rock. S I represents the rock point load strength. D J represents the comprehensive index of experimental rock mass integrity. V K represents the volumetric joint number of the rock mass. V The value represents the rock mass integrity coefficient, where a, b, c, and d are all weighting coefficients.

[0185] Furthermore, the regression function is:

[0186] f2=b0+b1R BSE +b2IQR BSE +b3σ BSE +b4MD BSE +b5CV BSE

[0187] In the formula, f2 represents the regression function, b0, b1, b2, b3, b4, and b5 all represent partial regression coefficients, and R0... BSE IQR represents the range of rock-breaking specific energy. BSE σ represents the interquartile range of rock-breaking specific energy. BSE The standard deviation of rock-breaking energy, MD BSE CV represents the average difference in rock-breaking specific energy. BSE This represents the coefficient of variation of rock breaking energy.

[0188] Furthermore, the preset rock strength inversion model is as follows:

[0189] R′ D =mBSE

[0190] The preset rock mass integrity inversion model is as follows:

[0191] I' D =f2(R BSE IQR BSE ,σ BSE ,MD BSE ,CV BSE )

[0192] In the formula, R′ D The target rock strength index is represented by m, the mechanical efficiency coefficient is represented by BSE, and the rock breaking energy is represented by I′. D This represents the comprehensive index of the integrity of the target rock mass.

[0193] It should be noted that those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the device and each unit described above can be referred to the corresponding process in the aforementioned embodiments of the real-time rock mass quality evaluation method, and will not be repeated here.

[0194] The apparatus provided in the above embodiments can be implemented as a computer program, which can be used in, for example... Figure 5 The real-time rock mass quality evaluation equipment shown is running.

[0195] This application also provides a real-time rock mass quality evaluation device, including: a memory, a processor, and a network interface connected via a system bus. The memory stores at least one instruction, which is loaded and executed by the processor to implement all or part of the steps of the aforementioned real-time rock mass quality evaluation method.

[0196] The network interface is used for network communication, such as sending assigned tasks. Those skilled in the art will understand that... Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0197] A processor can be a CPU, or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor can be a microprocessor, or any conventional processor. The processor is the control center of a computer device, connecting all parts of the computer device through various interfaces and lines.

[0198] Memory can be used to store computer programs and / or modules. The processor performs various functions of the computer device by running or executing the computer programs and / or modules stored in the memory, and by accessing data stored in the memory. Memory can primarily include a program storage area and a data storage area. The program storage area can store the operating system, application programs required for at least one function (such as video playback, image playback, etc.), etc.; the data storage area can store data created based on the use of the mobile phone (such as video data, image data, etc.). Furthermore, memory can include high-speed random access memory (RAM), and can also include non-volatile memory, such as hard disks, RAM, plug-in hard disks, SmartMedia Cards (SMC), Secure Digital Cards (SD cards), Flash Cards, at least one disk storage device, flash memory devices, or other volatile solid-state storage devices.

[0199] This application also provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements all or part of the steps of the aforementioned real-time rock mass quality evaluation method.

[0200] The embodiments of this application can implement all or part of the aforementioned processes, or they can be accomplished by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various methods described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added to or subtracted according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0201] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, servers, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0202] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0203] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0204] The above description is merely a specific embodiment of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for real-time evaluation of rock mass quality, characterized in that, Includes the following steps: Obtain the first target drilling parameters at the end of the drill rod after the drilling rig has drilled into the rock mass to be tested; The first target drilling parameters are input into a preset drilling parameter prediction model, and the second target drilling parameters corresponding to the drill bit position are obtained by inversion. The second target drilling parameters are input into the preset rock breaking energy model to obtain the target rock breaking energy. The target rock breaking energy is input into the preset rock strength inversion model and the preset rock mass integrity inversion model, respectively, and the target rock strength comprehensive index and the target rock mass integrity comprehensive index are obtained respectively. The rock mass quality of the rock mass to be tested is determined based on the mapping relationship between the target rock strength comprehensive index, the target rock mass integrity comprehensive index and the rock mass quality grade. The step of inputting the second target drilling parameters into the preset rock breaking energy model includes, prior to the step of inputting the second target drilling parameters into the preset rock breaking energy model. Based on the second experimental drilling parameters corresponding to the drill bit position under different working conditions, impact energy quantum model, drill pressure energy quantum model, rotation energy quantum model, hydraulic energy quantum model and rock fragmentation volume quantum model were constructed respectively. A preset rock-breaking specific energy model is generated based on the impact energy model, the drilling pressure energy model, the rotation energy model, the hydraulic energy model, and the rock fragmentation volumetric model. The preset rock-breaking specific energy model is as follows: In the formula, BSE represents the rock-breaking energy, and W s W represents impact energy. f W represents drilling pressure energy. r W represents gyration energy. w V represents water conservancy energy. r Indicates the volume of rock fragmentation. For impact transmission efficiency, f is the impact frequency, and P is the impact frequency. s Let P be the impact pressure, Δσ be the difference in area between the front and rear of the impact piston, δ be the pulse duration, m be the piston mass, d be the drill bit diameter, v be the drilling speed, a be the cross-sectional area of ​​the advance piston, and P be the impact pressure. f For propulsion pressure, N is rotational speed, M is torque, and P is... b The water power of the drill bit; Before the step of inputting the target rock breaking energy into the preset rock strength inversion model and the preset rock mass integrity inversion model respectively, the method further includes: The comprehensive strength index of the experimental rock was calculated based on the uniaxial compressive strength and point load strength of the experimental rock. The comprehensive index of experimental rock mass integrity is calculated based on the volume joint number and integrity coefficient of the experimental rock mass. The mechanical efficiency coefficient is determined based on the experimental rock strength comprehensive index and the preset rock breaking energy model. A preset rock strength inversion model is created based on the mechanical efficiency coefficient and the preset rock breaking energy model. The regression function is determined based on the experimental rock mass integrity comprehensive index and the preset rock breaking energy model. A preset rock mass integrity inversion model is created based on the regression function and the preset rock breaking energy model. The formula for calculating the comprehensive strength index of the experimental rock is as follows: The formula for calculating the comprehensive index of rock mass integrity in the experiment is as follows: In the formula, R D R represents the comprehensive strength index of the experimental rock. C I represents the uniaxial compressive strength of rock. S I represents the rock point load strength. D J represents the comprehensive index of experimental rock mass integrity. V K represents the volumetric joint number of the rock mass. V The value represents the rock mass integrity coefficient, where a, b, c, and d are all weighting coefficients.

2. The real-time rock mass quality evaluation method as described in claim 1, characterized in that, Before the step of inputting the first target drilling parameter into the preset drilling parameter prediction model, the method further includes: Obtain the first experimental drilling parameters at the drill rod end and the second experimental drilling parameters at the drill bit position under different working conditions. The working conditions include lithology, stratum combination, drill rod diameter, drill bit type, drilling mode, and borehole angle. The preset neural network model is trained based on the first and second experimental drilling parameters to obtain a preset drilling parameter prediction model, which is as follows: In the formula, Let f1 represent the target drilling parameters at the drill bit position, and f1 represent the training function. This indicates the target drilling parameters at the end of the drill pipe.

3. The real-time rock mass quality evaluation method as described in claim 1, characterized in that, The regression function is: In the formula, f2 represents the regression function, b0, b1, b2, b3, b4, and b5 all represent partial regression coefficients, and R0... BSE IQR represents the range of rock-breaking specific energy. BSE σ represents the interquartile range of rock-breaking specific energy. BSE The standard deviation of rock-breaking energy, MD BSE CV represents the average difference in rock-breaking specific energy. BSE This represents the coefficient of variation of rock breaking energy.

4. The real-time rock mass quality evaluation method as described in claim 3, characterized in that: The preset rock strength inversion model is as follows: The preset rock mass integrity inversion model is as follows: In the formula, The target rock strength index is represented by m, the mechanical efficiency coefficient is represented by BSE, and the rock breaking energy is represented by BSE. This represents the comprehensive index of the integrity of the target rock mass.

5. A real-time rock mass quality evaluation device, characterized in that, include: The parameter acquisition unit is used to acquire the first target drilling parameters at the end of the drill rod after the drilling rig has drilled into the rock mass to be tested. The first inversion unit is used to input the first target drilling parameters into a preset drilling parameter prediction model and invert to obtain the second target drilling parameters corresponding to the drill bit position. The data calculation unit is used to input the second target drilling parameters into a preset rock breaking energy model to obtain the target rock breaking energy. The second inversion unit is used to input the target rock breaking energy into the preset rock strength inversion model and the preset rock mass integrity inversion model respectively, and invert to obtain the target rock strength comprehensive index and the target rock mass integrity comprehensive index respectively. The quality evaluation unit is used to determine the rock mass quality of the rock mass to be tested based on the mapping relationship between the comprehensive strength index of the target rock, the comprehensive integrity index of the target rock mass, and the rock mass quality grade. The model building unit is used to construct impact energy sub-models, drill pressure energy sub-models, rotational energy sub-models, hydraulic energy sub-models, and rock breaking volume sub-models based on the second experimental drilling parameters corresponding to the drill bit position under different working conditions; and to generate a preset rock breaking specific energy model based on the impact energy sub-model, the drill pressure energy sub-model, the rotational energy sub-model, the hydraulic energy sub-model, and the rock breaking volume sub-model. The preset rock breaking specific energy model is as follows: In the formula, BSE represents the rock-breaking energy, and W s W represents impact energy. f W represents drilling pressure energy. r W represents gyration energy. w V represents water conservancy energy. r Indicates the volume of rock fragmentation. For impact transmission efficiency, f is the impact frequency, and P is the impact frequency. s Let P be the impact pressure, Δσ be the difference in area between the front and rear of the impact piston, δ be the pulse duration, m be the piston mass, d be the drill bit diameter, v be the drilling speed, a be the cross-sectional area of ​​the advance piston, and P be the impact pressure. f For propulsion pressure, N is rotational speed, M is torque, and P is... b The water power of the drill bit; The comprehensive strength index of the experimental rock was calculated based on the uniaxial compressive strength and point load strength of the experimental rock. The comprehensive index of experimental rock mass integrity is calculated based on the volume joint number and integrity coefficient of the experimental rock mass. The mechanical efficiency coefficient is determined based on the experimental rock strength comprehensive index and the preset rock breaking energy model. A preset rock strength inversion model is created based on the mechanical efficiency coefficient and the preset rock breaking energy model. The regression function is determined based on the experimental rock mass integrity comprehensive index and the preset rock breaking energy model. A preset rock mass integrity inversion model is created based on the regression function and the preset rock breaking energy model. The formula for calculating the comprehensive strength index of the experimental rock is as follows: The formula for calculating the comprehensive index of rock mass integrity in the experiment is as follows: In the formula, R D R represents the comprehensive strength index of the experimental rock. C I represents the uniaxial compressive strength of rock. S I represents the rock point load strength. D J represents the comprehensive index of experimental rock mass integrity. V K represents the volumetric joint number of the rock mass. V The value represents the rock mass integrity coefficient, where a, b, c, and d are all weighting coefficients.

6. A real-time rock mass quality evaluation device, characterized in that, include: A memory and a processor, wherein the memory stores at least one instruction, which is loaded and executed by the processor to implement the real-time rock mass quality evaluation method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program that, when executed by a processor, implements the real-time rock mass quality evaluation method according to any one of claims 1 to 4.

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