Rock mass quality rapid evaluation method, device, equipment and readable storage medium

Abstract

The application relates to a rock mass quality rapid evaluation method, device and equipment and a readable storage medium, which comprises the following steps: obtaining target drilling parameters after a drilling machine drills into a rock mass to be measured; inputting the target drilling parameters into a preset rock hardness prediction model, a preset rock weathering prediction model and a preset rock mass integrity prediction model to obtain a target rock hardness comprehensive index, a target rock weathering comprehensive index and a target rock mass integrity comprehensive index; determining a target rock strength grade based on a mapping relationship between the target rock hardness comprehensive index, the target rock weathering comprehensive index and rock strength grades; determining a target rock mass integrity grade based on a mapping relationship between the target rock mass integrity comprehensive index and rock mass integrity grades; and determining a target rock mass quality grade of the rock mass to be measured based on a mapping relationship between the target rock strength grade, the target rock mass integrity grade and rock mass quality grades, so that drilling, rapid and accurate evaluation of engineering rock mass quality is realized.

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 rapid evaluation of rock mass quality. Background Technology

[0002] In engineering construction, accurate and timely evaluation of rock mass quality is fundamental for economically and rationally designing rock mass excavation and reinforcement support, as well as for rapid and safe construction. Therefore, how to quickly and accurately obtain rock mass mechanical parameters and structural characteristics has become a research hotspot. Currently, laboratory testing and in-situ testing methods are commonly used to obtain these parameters. However, laboratory testing requires sending rock cores to a laboratory, resulting in drawbacks such as long processing time and high costs; while conventional in-situ testing methods suffer from cumbersome procedures and significant variation in test results. Thus, both laboratory testing and in-situ testing methods are insufficient to meet the requirements of rapid and accurate rock mass quality evaluation in practical engineering projects.

[0003] In addition, in actual engineering projects, the qualitative classification of rock mass quality is usually carried out by technicians on site to identify and judge many factors affecting rock mass quality or to evaluate and score certain indicators. This method relies heavily on the engineering practice experience of technicians, and the number of tests in actual work is very limited. The testing process is slow and it is difficult to guide construction in a timely manner. In other words, it has problems such as strong human subjectivity, limited test data, and low testing efficiency. Summary of the Invention

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

[0005] Firstly, a rapid evaluation method for rock mass quality is provided, including the following steps:

[0006] The target drilling parameters are obtained after the drilling rig enters the rock mass to be tested. The target drilling parameters include the corresponding acoustic parameters, vibration parameters, electro-hydraulic parameters, rock characteristic parameters, mineral characteristic parameters, geometric characteristic parameters of structural surfaces, and structural surface property characteristic parameters during the drilling process.

[0007] The target drilling parameters are respectively input into the preset rock hardness prediction model, the preset rock weathering degree prediction model and the preset rock mass integrity prediction model to obtain the target rock hardness comprehensive index, the target rock weathering comprehensive index and the target rock mass integrity comprehensive index.

[0008] The target rock strength grade is determined based on the mapping relationship between the target rock hardness index, the target rock weathering index and the rock strength grade.

[0009] Based on the mapping relationship between the target rock mass integrity comprehensive index and the rock mass integrity grade, the target rock mass integrity grade is determined;

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

[0011] In some embodiments, before the steps of inputting the target drilling parameters into the preset rock hardness prediction model, the preset rock weathering degree prediction model, and the preset rock mass integrity prediction model, the method further includes:

[0012] The experimental main frequency data and experimental sound pressure amplitude data at the rock breaking location during drilling, as well as the experimental vibration acceleration during drilling near the drill bit, were obtained through digital drilling tests.

[0013] A drilling acoustic sub-model is constructed based on the experimental master frequency data and the experimental sound pressure amplitude data.

[0014] A drilling vibration sub-model was constructed based on the experimental drilling vibration acceleration.

[0015] A preset rock hardness prediction model is generated based on the drilling acoustic sub-model and the drilling vibration sub-model.

[0016] In some embodiments, the drilling acoustic sub-model is:

[0017]

[0018] The drilling vibration sub-model is as follows:

[0019]

[0020] The rock hardness prediction model is as follows:

[0021] RH = 0.5RH1 + 0.5RH2

[0022] In the formula, RH1 represents the first rock hardness index, F(i) represents the frequency data of the i-th experimental principal component, and SP i Represents the experimental sound pressure amplitude data corresponding to the frequency of the i-th principal component in the experiment, RH2 represents the second rock hardness index, and RMS represents the second rock hardness index. i denoted as the root mean square value of the experimental vibration acceleration in the i-th direction during drilling, where a, b, c, and d are fitting coefficients, and RH represents the rock hardness index.

[0023] In some embodiments, before the steps of inputting the target drilling parameters into the preset rock hardness prediction model, the preset rock weathering degree prediction model, and the preset rock mass integrity prediction model, the method further includes:

[0024] Digital drilling tests were used to obtain experimental characteristic element information and experimental structural information of the drilled rocks, as well as experimental component characteristic information and experimental spectral data of the drilled minerals.

[0025] A rock structure sub-model is constructed based on the experimental feature element information and the experimental structural construction information;

[0026] A mineral alteration model is constructed based on the experimental component characteristic information and the experimental spectral data information;

[0027] A preset rock weathering degree prediction model is generated based on the rock structure sub-model and the mineral alteration sub-model.

[0028] In some embodiments, the preset rock weathering degree prediction model is:

[0029] RW = 0.5δ SC +0.5λ CA

[0030] In the formula, RW represents the comprehensive rock weathering index, δ SC λ represents the amount of structural variation in rocks. CA It indicates the degree of variation in the composition and color of a mineral.

[0031] In some embodiments, before the steps of inputting the target drilling parameters into the preset rock hardness prediction model, the preset rock weathering degree prediction model, and the preset rock mass integrity prediction model, the method further includes:

[0032] The number of experimental structural face groups, the average experimental spacing, experimental rotational pressure, experimental drilling speed, and experimental drill bit torque were obtained through digital drilling tests during the drilling process.

[0033] A developmental sub-model was constructed based on the number of experimental structural plane groups and the average experimental spacing.

[0034] A sub-model of the degree of integration is constructed based on the experimental rotary pressure, the experimental drilling speed, and the experimental drill bit torque.

[0035] Based on the development degree sub-model and the combination degree sub-model, a preset rock mass integrity prediction model is generated.

[0036] In some embodiments, the preset rock mass integrity prediction model is as follows:

[0037]

[0038] In the formula, RI represents the comprehensive index of rock mass integrity. η represents the degree of development of structural surfaces. APIndicates the degree of bonding between structural surfaces;

[0039] The structural surface bonding degree value η AP The calculation formula is:

[0040]

[0041] In the formula: X1 represents the slewing pressure value, X2 represents the drilling speed value, X3 represents the drill bit torque value, W1 represents the weight value of the slewing pressure, W2 represents the weight value of the drilling speed, W3 represents the weight value of the drill bit torque, ΠX represents the product of variables X, and e and f are fitting coefficients.

[0042] Secondly, a rapid rock mass quality evaluation device is provided, comprising:

[0043] The parameter acquisition unit is used to acquire the target drilling parameters after the drilling rig drills into the rock mass to be tested. The target drilling parameters include the corresponding acoustic parameters, vibration parameters, electro-hydraulic parameters, rock characteristic parameters, mineral characteristic parameters, structural surface geometric characteristic parameters, and structural surface morphology characteristic parameters during the drilling process.

[0044] The index prediction unit is used to input the target drilling parameters into the preset rock hardness prediction model, the preset rock weathering degree prediction model and the preset rock mass integrity prediction model respectively, to obtain the target rock hardness comprehensive index, the target rock weathering comprehensive index and the target rock mass integrity comprehensive index.

[0045] The quality evaluation unit is used to determine the target rock strength grade based on the mapping relationship between the target rock hardness comprehensive index, the target rock weathering comprehensive index and the rock strength grade; to determine the target rock mass integrity grade based on the mapping relationship between the target rock mass integrity comprehensive index and the rock mass integrity grade; and to determine the target rock mass quality grade of the rock mass to be tested based on the mapping relationship between the target rock strength grade, the target rock mass integrity grade and the rock mass quality grade.

[0046] Thirdly, a rapid 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 realize the aforementioned rapid rock mass quality evaluation method.

[0047] Fourthly, a computer-readable storage medium is provided, which stores a computer program that, when executed by a processor, implements the aforementioned rapid rock mass quality evaluation method.

[0048] This application provides a method, apparatus, equipment, and readable storage medium for rapid evaluation of rock mass quality. The method includes acquiring target drilling parameters after a drilling rig has drilled into the rock mass to be tested. These target drilling parameters include corresponding acoustic parameters, vibration parameters, electro-hydraulic parameters, rock characteristic parameters, mineral characteristic parameters, geometric characteristic parameters of structural surfaces, and structural surface morphology characteristic parameters during drilling. The target drilling parameters are then input into a preset rock hardness prediction model, a preset rock weathering degree prediction model, and a preset rock mass integrity prediction model to obtain a target rock hardness comprehensive index, a target rock weathering comprehensive index, and a target rock mass integrity comprehensive index. Based on the mapping relationship between the target rock hardness comprehensive index, the target rock weathering comprehensive index, and the rock strength grade, the target rock strength grade is determined. Based on the mapping relationship between the target rock mass integrity comprehensive index and the rock mass integrity grade, the target rock mass integrity grade is determined. Based on the mapping relationship between the target rock strength grade, the target rock mass integrity grade, and the rock mass quality grade, the target rock mass quality grade of the rock mass to be tested is determined. This application comprehensively analyzes the basic influencing factors of rock mass quality and divides them into three categories: rock hardness, rock weathering degree, and rock mass integrity. Corresponding drilling analysis models are established for the characteristic factors in the classification process of these three categories, and corresponding comprehensive indices are obtained for classification. This allows the rock mass quality of the drilled strata to be obtained in real time during drilling operations, and the test results are objective and accurate, realizing the drilling-while-drilling, rapid, and accurate evaluation of engineering rock mass quality. Attached Figure Description

[0049] 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.

[0050] Figure 1 A flowchart illustrating a rapid rock mass quality evaluation method provided in this application embodiment;

[0051] Figure 2 A schematic flowchart illustrating the rapid rock mass quality evaluation method provided in this application embodiment;

[0052] Figure 3 This is a schematic diagram of the structure of a rapid rock mass quality evaluation device provided in an embodiment of this application;

[0053] Figure 4 This is a structural schematic diagram of a rapid rock mass quality evaluation device provided in an embodiment of this application. Detailed Implementation

[0054] 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.

[0055] Figure 1 This application provides a method for rapid evaluation of rock mass quality, comprising the following steps:

[0056] Step S10: Obtain the target drilling parameters after the drilling rig enters the rock mass to be tested. The target drilling parameters include the corresponding acoustic parameters, vibration parameters, electro-hydraulic parameters, rock characteristic parameters, mineral characteristic parameters, geometric characteristic parameters of structural surfaces, and structural surface property characteristic parameters during the drilling process.

[0057] As an example, with the rapid development of digital drilling testing technology, digital drilling equipment can be used to monitor and analyze drilling parameters such as electro-hydraulic parameters, acoustic signals, vibration signals, and lithological parameters during the drilling process. This establishes the correlation between rock mass mechanical parameters and structural characteristics and the drilling parameters, enabling rapid and accurate evaluation of rock mass quality during drilling. Therefore, in this embodiment, a digital drilling test will be conducted on a specific underground engineering rock mass to collect and analyze the target drilling parameters in real time during drilling operations such as anchor holes, blast holes, advance exploratory holes, and geological exploration holes. The target drilling parameters include acoustic parameters, vibration parameters, electro-hydraulic parameters, rock characteristic parameters, mineral characteristic parameters, structural plane geometric characteristic parameters, and structural plane morphological characteristic parameters. Among these, various electronic sensors can collect drilling parameters such as acoustic parameters, vibration parameters, and electro-hydraulic parameters during the drilling process, while lithological analysis instruments can obtain drilling parameters such as rock characteristic parameters, mineral characteristic parameters, structural plane geometric characteristic parameters, and structural plane morphological characteristic parameters during the drilling process.

[0058] It is understood that the above-mentioned instruments and equipment are only examples of embodiments, and specific ones can be selected according to actual needs. However, they should meet the technical parameter requirements of this embodiment, including but not limited to sensitivity, resolution, accuracy, sampling frequency, measurement range, and installation size.

[0059] Step S20: Input the target drilling parameters into the preset rock hardness prediction model, the preset rock weathering degree prediction model, and the preset rock mass integrity prediction model respectively to obtain the target rock hardness comprehensive index, the target rock weathering comprehensive index, and the target rock mass integrity comprehensive index;

[0060] As an example, in this embodiment, after the target drilling parameters are obtained, the target drilling parameters are input into the preset rock hardness prediction model, the preset rock weathering degree prediction model and the preset rock mass integrity prediction model respectively. After the relevant processing of each model, the target rock hardness comprehensive index, the target rock weathering comprehensive index and the target rock mass integrity comprehensive index can be derived respectively.

[0061] Furthermore, before the steps of inputting the target drilling parameters into the preset rock hardness prediction model, the preset rock weathering degree prediction model, and the preset rock mass integrity prediction model, respectively, the method further includes:

[0062] The experimental main frequency data and experimental sound pressure amplitude data at the rock breaking location during drilling, as well as the experimental vibration acceleration during drilling near the drill bit, were obtained through digital drilling tests.

[0063] A drilling acoustic sub-model is constructed based on the experimental master frequency data and the experimental sound pressure amplitude data.

[0064] A drilling vibration sub-model was constructed based on the experimental drilling vibration acceleration.

[0065] A preset rock hardness prediction model is generated based on the drilling acoustic sub-model and the drilling vibration sub-model.

[0066] The drilling acoustic sub-model is as follows:

[0067]

[0068] The drilling vibration sub-model described in section 5 is as follows:

[0069]

[0070] The rock hardness prediction model is as follows:

[0071] RH = 0.5RH1 + 0.5RH2

[0072] In the formula, RH1 represents the first rock hardness index, F(i) represents the frequency data of the i-th experimental principal component, and SP i This represents the experimental sound pressure amplitude data corresponding to the frequency of the i-th principal component in the experiment, and RH2 represents the second rock hardness index. denoted as the root mean square value of the experimental vibration acceleration in the i-th direction during drilling, where a, b, c, and d are fitting coefficients, and RH represents the rock hardness index.

[0073] As an example, it is understandable that when qualitatively classifying engineering rock masses, rock hardness is mainly determined by technicians using hammering to judge the crispness and rebound of the sound. However, this method suffers from strong subjectivity and coarse classification results in practical engineering. Therefore, to address this issue, this embodiment will acquire the acoustic and vibration information of the drilled rock through a drilling acoustic sub-model and a drilling vibration sub-model, respectively. Then, a rock hardness prediction model will be used to obtain a comprehensive rock hardness index for rapid evaluation of rock hardness. Therefore, this embodiment will construct the drilling acoustic and drilling vibration sub-models based on the results of digital drilling test experiments, thereby generating a rock hardness prediction model.

[0074] Specifically, it can be understood that since audio signals are closely related to formation lithology, different rocks have corresponding inherent frequencies, and the amplitude of sound waves propagating at these frequencies is the largest. By analyzing the two factors of frequency and amplitude, the degree of crispness in rock hardness can be classified. Therefore, this embodiment will obtain the experimental audio frequency time-domain signal at the rock-breaking location of the drill bit through digital drilling test experiments. After performing spectral analysis on this signal, the experimental principal component frequency data set and its corresponding experimental sound pressure amplitude data set will be obtained. Based on the experimental principal component frequency data set and its corresponding experimental sound pressure amplitude data set, a drilling audio frequency sub-model will be constructed to identify and classify the degree of crispness in rock hardness. The calculation formula of the drilling audio frequency sub-model is as follows:

[0075]

[0076] In the formula, RH1 represents the first rock hardness index, F(i) represents the frequency data of the i-th experimental principal component, and SP i This represents the experimental sound pressure amplitude data corresponding to the i-th principal component frequency, where n is the number of preset principal component frequencies, and a and b are fitting coefficients.

[0077] It should be noted that the experimental principal component frequency data set is a data set composed of multiple principal component characteristic frequencies related to the rock hardness. The preset number of principal component frequencies n is related to the accuracy of the rock property description. The more frequencies there are, the more refined the description of the lithology. In this embodiment, it is preferable to use 5 principal component frequency data, and the range of the principal component frequency data is 5000 to 9000 Hz.

[0078] It should be understood that during the drilling process, the rock drill will experience impact and rebound on the rock surface, causing drill vibration. During drilling, the drill bit's vibration manifests in three forms: axial vibration, lateral vibration, and torsional vibration. These vibration frequency changes can be monitored using a three-component accelerometer. Since the amplitude of acceleration changes reflects the energy of rock breaking, the drill's vibration response level can be calculated using the root mean square value, allowing for time-domain evaluation of the vibration signal using the effective value of the vibration acceleration. For example, this embodiment will construct a drilling vibration sub-model based on the characteristic data of the experimental orthogonal triaxial acceleration near the drill bit position obtained from the experimental vibration time-domain signal acquired through digital drilling tests. The calculation formula for the drilling vibration sub-model is as follows:

[0079]

[0080] In the formula, RH2 represents the second rock hardness index, RMS. i Let represent the root mean square value of the experimental vibration acceleration in the i-th direction during drilling, and c and d are fitting coefficients.

[0081] It should be noted that the root mean square value of the drilling vibration acceleration... This represents the root mean square value of the vibration acceleration after preprocessing. Since drilling rig vibration is mainly determined by the drill string itself and the rock type encountered, the vibration signal generated by the drill string itself is stable. Therefore, preprocessing can filter out the vibration influence generated by the drill string itself. The preprocessing method can be as follows: extract the vibration signal when the drill string is idling (in unbroken rock strata) through data analysis, and then drill into rock-breaking strata.

[0082] The vibration signal during drilling is subtracted from the vibration signal during idling to obtain a vibration signal only related to rock properties 5. Preferably, the x-axis of the triaxial vibration acceleration corresponds to the radial direction of the drill pipe cross-section, the y-axis corresponds to the tangential direction of the drill pipe cross-section, and the z-axis corresponds to the axial direction of the drill pipe.

[0083] Then, a preset rock hardness prediction model can be constructed and generated using the drilling acoustic sub-model and the drilling vibration sub-model, which is the first rock hardness index corresponding to the drilling acoustic sub-model.

[0084] Substituting RH1 and the second rock hardness index RH2 corresponding to the drilling vibratory sub-model into the following calculation formula, the comprehensive rock hardness index RH can be obtained:

[0085] RH = 0.5RH1 + 0.5RH2

[0086] Furthermore, it should be noted that the aforementioned fitting coefficients a, b, c, and d can be determined through digital drilling tests and rock mechanics tests corresponding to the first preset working condition. Specific steps include...

[0087] The process includes drilling tests, data processing while drilling, rock strength testing, and model analysis while drilling. The first preset working condition (5) refers to different lithological types (sedimentary rocks, igneous rocks, metamorphic rocks) and different hardness levels (uniaxial compressive strength of rock < 5 MPa). c Complete unweathered rock with a pressure of <300MPa.

[0088] The following will illustrate the process of determining the fitting coefficients a and b as an example: First, select several representative intact and unweathered sedimentary rocks and tectonic rocks of different lithological categories.

[0089] Igneous rocks and metamorphic rocks, depending on the rock's hardness, are represented by R. c =10MPa intervals were used to select intact unweathered rocks of different strengths, and then digital drilling tests were carried out corresponding to the first preset working condition. The acoustic time-domain signals during the drilling process were collected, and the principal component frequency data group F(i) and its corresponding sound pressure amplitude data group SP were obtained. i Secondly, rock strength tests were conducted on the rock samples from the drilling tests to obtain their uniaxial compressive strength R. c Finally, the principal components were established using fitting algorithms such as the least squares method.

[0090] Component frequency data set F(i) and its corresponding sound pressure amplitude data set SP i The experimental rock's uniaxial compressive strength R c By establishing the correlation between the parameters, a drilling acoustic sub-model is obtained, i.e., the fitting coefficients a and b are determined. Therefore, this embodiment, through implementing digital drilling tests on representative unweathered rocks of different lithological types and hardness, acquires drilling acoustic and vibration data, thereby predicting rock hardness and evaluating the brittleness and resilience of the encountered rock. Compared to manual hammering identification, this method offers advantages such as speed, real-time performance, objectivity, and accuracy.

[0091] Furthermore, before the steps of inputting the target drilling parameters into the preset rock hardness prediction model, the preset rock weathering degree prediction model, and the preset rock mass integrity prediction model, respectively, the method further includes:

[0092] Digital drilling tests were used to obtain experimental characteristic element information and experimental structural information of the drilled rocks, as well as experimental component characteristic information and experimental spectral data of the drilled minerals.

[0093] A rock structure sub-model is constructed based on the experimental feature element information and the experimental structural construction information;

[0094] A mineral alteration model is constructed based on the experimental component characteristic information and the experimental spectral data information;

[0095] A preset rock weathering degree prediction model is generated based on the rock structure sub-model and the mineral alteration sub-model.

[0096] The preset rock weathering degree prediction model is as follows:

[0097] RW = 0.5δ SC +0.5λ CA

[0098] In the formula, RW represents the comprehensive rock weathering index, δ SC λ represents the amount of structural variation in rocks. CA It indicates the degree of variation in the composition and color of a mineral.

[0099] As an example, it is understandable that when qualitatively classifying engineering rock masses, the degree of rock weathering mainly considers the destruction of rock structure, mineral alteration, and color change. Therefore, in this embodiment, the changes in the structure of the drilled rock and the changes in the composition and color of the drilled minerals will be obtained through a rock structure sub-model and a mineral alteration sub-model, respectively. Then, a preset rock weathering degree prediction model will be used to obtain the comprehensive weathering index of the target rock to quickly evaluate the degree of rock weathering.

[0100] In this embodiment, a rock structure sub-model is constructed using experimental characteristic element information and experimental structural information of the drilled rock obtained from the rock cuttings during the drilling process. It should be noted that characteristic elements mainly refer to elements contained in the rock composition, such as silicon, magnesium, and calcium. Specifically, the rock structure variation δ corresponding to the rock structure sub-model... SC The calculation method is as follows: First, the lithology of the drilled rock is determined based on the characteristic elements in the experimental characteristic element information. Then, the structural features in the experimental structural information of the drilled rock with the determined lithology are compared with the structural features of the corresponding rocks in the preset database to determine the change in the structural features of the drilled rock. The standards for determining the value of the change in rock structural features are shown in Table 1.

[0101] Table 1. Changes in rock structure and texture

[0102]

[0103] It is understandable that every rock has its own structure and texture, which are determined by the rock's formation environment or conditions. Rock weathering causes changes in its structure and texture. Therefore, this embodiment will determine the degree of rock weathering by measuring the changes in rock structure and texture. The specific steps are as follows: First, a database of the structure and texture of various types of fresh rocks is established. Then, the characteristic elements of the drilled rock are matched with the characteristic elements of all rocks in the database to determine the category of the drilled rock. Finally, the structure and texture of the drilled rock are compared with the structure and texture of the corresponding rocks in the database to determine the amount of change in the structure and texture of the drilled rock. For example, when the structure and texture of the drilled rock are the same as those of the corresponding rocks in the database, i.e., both are fresh rocks, the comparison result is "completely unchanged," therefore, the amount of change in rock structure and texture is greater than 80. However, when the structure and texture of the drilled rock are different from those of the corresponding rocks in the database, and the drilled rock appears to have disintegrated and decomposed into loose soil or sand, the comparison result is "completely destroyed," therefore, the amount of change in rock structure and texture is less than 20.

[0104] It should be noted that the variation δ in rock structure and texture SC The upper and lower limits of the interval can be determined according to the actual situation and are not limited here. Furthermore, the variation δ of the rock structure and texture of the drilled rock was determined based on the comparison results. SC After determining the range, a specific value can be selected from the corresponding range as the rock structure variation δ according to actual needs. SC This is not a limitation. For example, the variation in rock structure and texture δ SC The value is between 20 and 40, and the average value of 30 within this range can be taken as the variation in rock structure and texture δ. SC The value of .

[0105] Furthermore, this embodiment will construct a mineral alteration sub-model using experimental component characteristic information and experimental spectral data of the drilled minerals obtained from rock powder during the drilling process; specifically, the mineral alteration sub-model corresponds to the change in mineral composition and color λ. CA The calculation method is as follows: First, the component category of the drilled mineral is determined based on the component content in the experimental component characteristic information of the drilled mineral. Then, the spectral data in the experimental spectral data information of the drilled mineral is compared with the spectral data of the corresponding mineral in the database to determine the component color change of the drilled mineral. The standard for the value of the mineral component color change is shown in Table 2.

[0106] Table 2. Changes in color of mineral components

[0107]

[0108] It is understandable that rock weathering not only destroys the original rock structure but also alters the composition and color of the original rock minerals and produces altered minerals. Therefore, this embodiment will determine the degree of rock weathering by measuring the change in mineral color. The specific steps are as follows: First, a database of the composition and color of various types of fresh minerals is established. Then, the component content of the drilled mineral is matched with the component content of all minerals in the database to determine the category of the drilled mineral. Finally, the spectral data of the drilled mineral is compared with the spectral data of the corresponding minerals in the database to determine the change in the composition and color of the drilled mineral, λ. CA .

[0109] Specifically, when the encountered mineral is compared with the corresponding mineral in the database, and the mineral shows a complete change in color and loss of luster, with most of the minerals except quartz grains altered into secondary minerals, the comparison result is "complete change," and the change in mineral composition and color is less than 20. When there is a significant change in composition and color, with feldspar, mica, and iron-magnesium minerals weathered and altered, the comparison result is "significant change," and the change in mineral composition and color is 20–40. When there is a relatively significant change in composition and color, with iron-manganese weathering and alteration, the comparison result is "relatively significant change," and the change in mineral composition and color is 40–60. When there is basically no change in composition and color, with iron-manganese parts showing bleaching or slight discoloration, the comparison result is "basically no change," and the change in mineral composition and color is 60–80. If there is no change in composition and color, the comparison result is "completely no change," and the change in mineral composition and color is greater than 80.

[0110] It should be noted that the variation in color of mineral components λ CA The upper and lower limits of the range can be determined according to the actual situation and are not limited here. Furthermore, the variation λ of the mineral composition and color of the drilled rock was determined based on the comparison results. CA After determining the range, a specific value can be selected from the corresponding range as the mineral composition color change λ according to actual needs. CA This is not a limitation. For example, the variation in color of mineral components, λ CA The value is 60-80, and the average value of 70 within this range can be taken as the variation λ of mineral composition color. CA The value of .

[0111] Furthermore, before the steps of inputting the target drilling parameters into the preset rock hardness prediction model, the preset rock weathering degree prediction model, and the preset rock mass integrity prediction model, respectively, the method further includes:

[0112] The number of experimental structural face groups, the average experimental spacing, experimental rotational pressure, experimental drilling speed, and experimental drill bit torque were obtained through digital drilling tests during the drilling process.

[0113] A developmental sub-model was constructed based on the number of experimental structural plane groups and the average experimental spacing.

[0114] A sub-model of the degree of integration is constructed based on the experimental rotary pressure, the experimental drilling speed, and the experimental drill bit torque.

[0115] Based on the development degree sub-model and the combination degree sub-model, a preset rock mass integrity prediction model is generated.

[0116] The preset rock mass integrity prediction model is as follows:

[0117]

[0118] In the formula, RI represents the comprehensive index of rock mass integrity. η represents the degree of development of structural surfaces. AP Indicates the degree of bonding between structural surfaces;

[0119] The structural surface bonding degree value η AP The calculation formula is:

[0120]

[0121] In the formula: X1 represents the slewing pressure value, X2 represents the drilling speed value, X3 represents the drill bit torque value, W1 represents the weight value of the slewing pressure, W2 represents the weight value of the drilling speed, W3 represents the weight value of the drill bit torque, and e and f are fitting coefficients.

[0122] As an example, it is understandable that when qualitatively classifying engineering rock masses, the integrity of the rock mass mainly considers the degree of development and the degree of bonding of structural surfaces. Therefore, in this embodiment, the degree of development and the degree of bonding of the structural surfaces of the drilled rock mass are obtained through the development degree sub-model and the bonding degree sub-model, respectively. Then, the comprehensive index of the integrity of the target rock mass is obtained through the preset rock mass integrity prediction model to quickly evaluate the integrity of the rock mass.

[0123] It should be understood that the geometric features of the structural surface can be comprehensively described as the degree of structural surface development, which includes the number of structural surface groups and the average spacing. Therefore, this embodiment will construct a sub-model of the degree of development based on the number of experimental structural surface groups and the experimental average spacing obtained from the panoramic borehole images during the drilling process. Specifically, the degree of development value corresponding to the sub-model of the degree of development is... The calculation method is as follows: First, the panoramic three-dimensional image of the borehole is unfolded into a two-dimensional planar image. Then, the number of structural surface groups and the average spacing are obtained through image preprocessing, region localization, edge detection, edge extraction, and sine function fitting, thereby determining the degree of development of the structural surface.

[0124] The criteria for determining the degree of development of structural surfaces are shown in Table 3.

[0125] Table 3. Development Degree Values ​​of Structural Surfaces

[0126]

[0127] It should be noted that the degree of development of structural surfaces is... The upper and lower limits of the interval can be determined according to the actual situation and are not limited here. Furthermore, the development degree value of the structural surfaces was determined based on the number of structural surface groups and the average spacing. After determining the range, a specific value can be selected from the corresponding range as the degree of structural surface development based on actual needs. No specific limitations are set here. For example, the degree of development of structural planes. The value is between 60 and 80, and the average value of 70 within this range can be taken as the degree of structural surface development. The value of .

[0128] Furthermore, this embodiment will construct a sub-model of the bonding degree based on the experimental electro-hydraulic parameters obtained during drilling (i.e., experimental rotary pressure, experimental drilling speed, and experimental drill bit torque), thereby obtaining the bonding degree of the structural surface; specifically, the bonding degree value η of the structural surface AP The calculation formula is:

[0129]

[0130] In the formula: X1 represents the experimental slewing pressure value, X2 represents the experimental drilling speed value, X3 represents the experimental drill bit torque value, W1 represents the weight value of the experimental slewing pressure, W2 represents the weight value of the experimental drilling speed, W3 represents the weight value of the experimental drill bit torque, ΠX represents the product of variables X, and e and f are fitting coefficients.

[0131] It should be noted that the fitting coefficients e and f can be determined through digital drilling tests corresponding to the second preset working condition. The specific steps include digital drilling tests, data processing while drilling, and model analysis while drilling. The second preset working condition refers to rock masses with different opening degrees, roughness conditions, and infill material properties and characteristics. The following explains the process of determining the fitting coefficients e and f: First, digital drilling tests corresponding to the second preset working condition are conducted on rock masses with known opening degrees, roughness conditions, and infill materials. Second, while drilling parameters such as rotational pressure X1, drilling speed X2, and drill bit torque X3 are collected during the drilling process. Then, the instability index analysis method is used to determine the weight values ​​W of these while drilling parameters. i Finally, the "drilling parameters X" were established using least squares fitting algorithms. i and its corresponding weight value W i "The degree of bonding between the structural surfaces of the test rock mass and η" APThe correlation between them is used to determine the fitting coefficients e and f, and then to generate a sub-model of the degree of integration.

[0132] The criteria for determining the degree of bonding between structural surfaces are shown in Table 4.

[0133] Table 4. Values ​​of Structural Surface Bonding

[0134]

[0135]

[0136] Understandably, since technicians control the drilling process by adjusting drilling pressure and rotation speed, and parameters such as rotational pressure, drilling speed, and drill bit torque are passively adjustable parameters related to the encountered lithology, this embodiment collects corresponding adaptive parameters X by conducting digital drilling tests on structural rock masses with different degrees of bonding. i That is, determine the corresponding A in Table 4. i ~D i Thus, the "value η of the structural surface bonding degree of the test rock mass" was established. AP "and the corresponding adaptive drilling parameter X" i and its weight value W i The correlation between these elements is used to determine the degree of integration of the sub-model and then evaluate the geometric characteristics of the rock mass structural plane.

[0137] It should be noted that the structural surface bonding degree value η AP The upper and lower limits of the range can be determined according to the actual situation and are not limited here. Furthermore, the structural surface bonding degree value η is determined based on the rotational pressure, drilling speed, and drill bit torque. AP After determining the interval, a specific value can be selected from the corresponding interval as the structural surface bonding degree value η according to actual needs. AP This is not a limitation. For example, the degree of bonding of structural surfaces η AP The value is between 25 and 50, and the average value of 37.5 within this range can be taken as the structural surface bonding degree value η. AP The value of .

[0138] Step S30: Determine the target rock strength grade based on the mapping relationship between the target rock hardness index, the target rock weathering index, and the rock strength grade;

[0139] As an example, it is understandable that rocks undergo long-term physical and chemical weathering, causing them to become porous and even loose, resulting in deterioration of their physical and mechanical properties. Therefore, the degree of weathering must be considered when determining rock strength. Thus, in this embodiment, the target rock's hardness index and weathering index are processed using a rock strength mapping relationship to obtain the target rock strength grade corresponding to the rock mass being tested. This target rock strength grade reflects the degree of hardness of the weathered rock. Specifically, the rock strength mapping relationship is shown in Table 5.

[0140] Table 5 Rock Strength Mapping Relationship

[0141]

[0142] For specific classifications of rock hardness and rock weathering degree, please refer to Tables 6 and 7:

[0143] Table 6 Classification of Rock Hardness

[0144]

[0145] Table 7 Classification of Rock Weathering Degree

[0146]

[0147] It should be noted that the upper and lower limits of the target rock hardness index RH and the target rock weathering index RW can be determined according to the actual situation, and are not limited here.

[0148] Step S40: Determine the target rock mass integrity level based on the mapping relationship between the target rock mass integrity comprehensive index and the rock mass integrity level;

[0149] As an example, it is understandable that the integrity of the rock mass is another important factor determining its quality. Factors affecting rock mass integrity can be categorized into two types: the degree of development of structural planes and the degree of bonding between structural planes. The target rock mass integrity comprehensive index in this embodiment considers both types of factors. Based on this index, the integrity of the rock mass can be classified and named. Specifically, the mapping relationship of rock mass integrity is shown in Table 8:

[0150] Table 8 Complete Mapping Relationships of Rock Mass

[0151]

[0152] It should be noted that the upper and lower limits of the target rock mass integrity comprehensive index RI can be determined according to the actual situation, and are not limited here.

[0153] Step S50: Based on the mapping relationship between the target rock strength grade, the target rock mass integrity grade, and the rock mass quality grade, determine the target rock mass quality grade of the rock mass to be tested.

[0154] Exemplary and understandable, rock mass quality is a combination of two grading factors: rock strength and rock mass integrity. Qualitative grading of rock mass quality can be performed based on this combination. In this embodiment, after obtaining the target rock strength grade and target rock mass integrity grade corresponding to the rock mass to be tested, the target rock mass quality grade can be determined through the mapping relationship between the target rock strength grade, the target rock mass integrity grade, and the rock mass quality grade, thereby achieving rapid evaluation of rock mass quality. Specifically, the rock mass quality mapping relationship is shown in Table 9:

[0155] Table 9. Mapping Relationship of Rock Mass Quality

[0156]

[0157] Therefore, see Figure 2 This embodiment addresses rock strength and rock mass integrity information in rock mass quality evaluation. First, digital drilling tests and rock mechanics experiments are conducted to determine six sub-models: a drilling acoustic sub-model and a drilling vibration sub-model to classify rock hardness; a rock structure sub-model and a mineral alteration sub-model to classify rock weathering; and a development degree sub-model and a bonding degree sub-model to classify rock mass integrity. Second, after implementing digital drilling in a specific project, the collected target drilling parameters are substituted into the above sub-models to obtain the target rock hardness composite index RH, the target rock weathering composite index RW, and the target rock mass integrity composite index RI. Then, the target rock hardness composite index RH and the target rock weathering composite index RW are substituted into the mapping relationship corresponding to the rock strength level to determine the target rock strength level, and the target rock mass integrity composite index RI is substituted into the mapping relationship corresponding to the rock mass integrity level to determine the target rock mass integrity level. Finally, the target rock strength level and the target rock mass integrity level are substituted into the mapping relationship corresponding to the rock mass quality level to determine the target rock mass quality level, thus achieving rapid evaluation of rock mass quality.

[0158] In summary, this embodiment achieves rapid evaluation of engineering rock mass quality by real-time monitoring and analysis of drilling parameters, including acoustic parameters, vibration parameters, electro-hydraulic parameters, rock characteristic parameters, mineral characteristic parameters, geometric characteristic parameters of structural surfaces, and morphological characteristic parameters of structural surfaces. This allows for the acquisition of rock strength parameters and rock mass integrity information. Specifically, this embodiment comprehensively considers the basic influencing factors of rock mass quality grading. Rock hardness integrates the brittleness and resilience of the rock; rock weathering integrates changes in rock structure and mineral composition and color; rock strength parameters integrate rock hardness and weathering; and rock mass integrity integrates the degree of bonding and development of structural surfaces. This allows for the acquisition of rock mass quality of the drilled strata during drilling operations, achieving rapid and accurate evaluation of engineering rock mass quality during drilling. The evaluation results can be used in technical fields such as excavation design, support optimization, and deformation control in underground engineering.

[0159] See Figure 3 As shown in the embodiment of this application, a rapid rock mass quality evaluation device is also provided, comprising:

[0160] The parameter acquisition unit is used to acquire the target drilling parameters after the drilling rig drills into the rock mass to be tested. The target drilling parameters include the corresponding acoustic parameters, vibration parameters, electro-hydraulic parameters, rock characteristic parameters, mineral characteristic parameters, structural surface geometric characteristic parameters, and structural surface morphology characteristic parameters during the drilling process.

[0161] The index prediction unit is used to input the target drilling parameters into the preset rock hardness prediction model, the preset rock weathering degree prediction model and the preset rock mass integrity prediction model respectively, to obtain the target rock hardness comprehensive index, the target rock weathering comprehensive index and the target rock mass integrity comprehensive index.

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

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

[0164] The experimental main frequency data and experimental sound pressure amplitude data at the rock breaking location during drilling, as well as the experimental vibration acceleration during drilling near the drill bit, were obtained through digital drilling tests.

[0165] A drilling acoustic sub-model is constructed based on the experimental master frequency data and the experimental sound pressure amplitude data.

[0166] A drilling vibration sub-model was constructed based on the experimental drilling vibration acceleration.

[0167] A preset rock hardness prediction model is generated based on the drilling acoustic sub-model and the drilling vibration sub-model.

[0168] Furthermore, the drilling acoustic sub-model is as follows:

[0169]

[0170] The drilling vibration sub-model is as follows:

[0171]

[0172] The rock hardness prediction model is as follows:

[0173] RH = 0.5RH1 + 0.5RH2

[0174] In the formula, RH1 represents the first rock hardness index, F(i) represents the frequency data of the i-th experimental principal component, and SP i This represents the experimental sound pressure amplitude data corresponding to the frequency of the i-th principal component in the experiment, and RH2 represents the second rock hardness index. denoted as the root mean square value of the experimental vibration acceleration in the i-th direction during drilling, where a, b, c, and d are fitting coefficients, and RH represents the rock hardness index.

[0175] Furthermore, the model building unit is also used for:

[0176] Digital drilling tests were used to obtain experimental characteristic element information and experimental structural information of the drilled rocks, as well as experimental component characteristic information and experimental spectral data of the drilled minerals.

[0177] A rock structure sub-model is constructed based on the experimental feature element information and the experimental structural construction information;

[0178] A mineral alteration model is constructed based on the experimental component characteristic information and the experimental spectral data information;

[0179] A preset rock weathering degree prediction model is generated based on the rock structure sub-model and the mineral alteration sub-model.

[0180] Furthermore, the preset rock weathering degree prediction model is as follows:

[0181] RW = 0.5δ SC +0.5λ CA

[0182] In the formula, RW represents the comprehensive rock weathering index, δSC λ represents the amount of structural variation in rocks. CA It indicates the degree of variation in the composition and color of a mineral.

[0183] Furthermore, the model building unit is also used for:

[0184] The number of experimental structural face groups, the average experimental spacing, experimental rotational pressure, experimental drilling speed, and experimental drill bit torque were obtained through digital drilling tests during the drilling process.

[0185] A developmental sub-model was constructed based on the number of experimental structural plane groups and the average experimental spacing.

[0186] A sub-model of the degree of integration is constructed based on the experimental rotary pressure, the experimental drilling speed, and the experimental drill bit torque.

[0187] Based on the development degree sub-model and the combination degree sub-model, a preset rock mass integrity prediction model is generated.

[0188] Furthermore, the preset rock mass integrity prediction model is as follows:

[0189]

[0190] In the formula, RI represents the comprehensive index of rock mass integrity. η represents the degree of development of structural surfaces. AP Indicates the degree of bonding between structural surfaces;

[0191] The structural surface bonding degree value η AP The calculation formula is:

[0192]

[0193] In the formula: X1 represents the slewing pressure value, X2 represents the drilling speed value, X3 represents the drill bit torque value, W1 represents the weight value of the slewing pressure, W2 represents the weight value of the drilling speed, W3 represents the weight value of the drill bit torque, ΠX represents the product of variables X, and e and f are fitting coefficients.

[0194] 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 rapid rock mass quality evaluation method, and will not be repeated here.

[0195] The apparatus provided in the above embodiments can be implemented as a computer program, which can be used in, for example... Figure 4 The rock mass quality rapid evaluation equipment shown is running.

[0196] This application also provides a rapid 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 rapid rock mass quality evaluation method.

[0197] The network interface is used for network communication, such as sending assigned tasks. Those skilled in the art will understand that... Figure 4 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.

[0198] 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.

[0199] 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.

[0200] 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 rapid rock mass quality evaluation method.

[0201] 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.

[0202] 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.

[0203] 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.

[0204] 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.

[0205] 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 rapid rock mass quality evaluation, characterized in that, The method comprises the following steps: obtaining target drilling parameters after a drilling rig drills into a rock mass to be measured, the target drilling parameters including corresponding acoustic parameters, vibration parameters, electro-hydraulic parameters, rock characteristic parameters, mineral characteristic parameters, structural plane geometric characteristic parameters and structural plane property characteristic parameters in the drilling process; inputting the target drilling parameters into preset rock hardness degree prediction models, preset rock weathering degree prediction models and preset rock mass integrity degree prediction models respectively to obtain target rock hardness comprehensive indexes, target rock weathering comprehensive indexes and target rock mass integrity comprehensive indexes; determining a target rock strength grade based on a mapping relationship between the target rock hardness comprehensive indexes, the target rock weathering comprehensive indexes and rock strength grades; determining a target rock mass integrity grade based on a mapping relationship between the target rock mass integrity comprehensive indexes and rock mass integrity grades; determining a target rock mass quality grade of the rock mass to be measured based on a mapping relationship between the target rock strength grade, the target rock mass integrity grade and rock mass quality grades; wherein, before the step of inputting the target drilling parameters into the preset rock hardness degree prediction models, the preset rock weathering degree prediction models and the preset rock mass integrity degree prediction models respectively, the method further comprises: obtaining experimental main frequency data and experimental sound pressure amplitude data at a rock breaking position during drilling and experimental drilling vibration acceleration at a position close to the drill bit through digital drilling tests; constructing a drilling acoustic sub-model based on the experimental main frequency data and the experimental sound pressure amplitude data; constructing a drilling vibration sub-model based on the experimental drilling vibration acceleration; constructing the preset rock hardness degree prediction model according to the drilling acoustic sub-model and the drilling vibration sub-model; the drilling acoustic sub-model is: the drilling vibration sub-model is: the rock hardness degree prediction model is: In the formula, represents the first rock hardness index, represents the i-th experimental principal component frequency data, represents the i-th experimental principal component frequency corresponding to the experimental sound pressure amplitude data, represents the second rock hardness index, represents the i-th direction of the experimental while-drilling vibration acceleration root mean square value, a, b, c, d are all fitting coefficients, represents the rock hardness comprehensive index.

2. The QIA method of claim 1, wherein, before the step of inputting the target drilling parameters into the preset rock hardness degree prediction models, the preset rock weathering degree prediction models and the preset rock mass integrity degree prediction models respectively, the method further comprises: obtaining experimental characteristic element information and experimental structural information of drilled rocks and experimental component characteristic information and experimental spectral data information of drilled minerals through digital drilling tests; constructing a rock structure sub-model based on the experimental characteristic element information and the experimental structural information; constructing a mineral alteration sub-model based on the experimental component characteristic information and the experimental spectral data information; constructing the preset rock weathering degree prediction model according to the rock structure sub-model and the mineral alteration sub-model.

3. The QIA method of claim 2, wherein, the preset rock weathering degree prediction model is: In the formula, represents a comprehensive index of rock weathering, represents a structural change amount of the rock, represents a color change amount of the mineral composition.

4. The QIA method of claim 1, wherein, before the step of inputting the target drilling parameters into the preset rock hardness degree prediction models, the preset rock weathering degree prediction models and the preset rock mass integrity degree prediction models respectively, the method further comprises: obtaining experimental structural plane group numbers and experimental average spacings and experimental rotary pressures, experimental drilling speeds and experimental drill bit torques in the drilling process through digital drilling tests; constructing a development degree sub-model based on the experimental structural plane group numbers and the experimental average spacings; construct a bonding degree sub-model based on the experimental rotary pressure, the experimental drilling speed and the experimental drill bit torque; construct a preset rock mass integrity degree prediction model according to the development degree sub-model and the bonding degree sub-model.

5. The QIA method of claim 4, wherein, The preset rock mass integrity degree prediction model is: In the formula, represents the rock mass integrity comprehensive index, represents the structural plane development degree value, represents the structural plane combination degree value; The structural plane combination degree value The calculation formula is: wherein: represents a rotary pressure value, represents a penetration rate value, represents a bit torque value, represents a weight value for the rotary pressure, represents a weight value for the penetration rate, represents a weight value for the bit torque, represents a multiplication of the variable X, e and f being fitting coefficients.

6. A rock mass quality rapid evaluation device, characterized in that, comprises: a parameter acquisition unit configured to acquire target drilling parameters of a drilling rig after the drilling rig drills into a rock mass to be measured, the target drilling parameters including corresponding acoustic parameters, vibration parameters, electro-hydraulic parameters, rock characteristic parameters, mineral characteristic parameters, structural plane geometric characteristic parameters and structural plane property characteristic parameters in a drilling process; an index prediction unit configured to input the target drilling parameters into a preset rock hardness degree prediction model, a preset rock weathering degree prediction model and a preset rock mass integrity degree prediction model respectively to obtain a target rock hardness comprehensive index, a target rock weathering comprehensive index and a target rock mass integrity comprehensive index; a quality evaluation unit configured to determine a target rock strength grade based on a mapping relationship between the target rock hardness comprehensive index, the target rock weathering comprehensive index and rock strength grades, and determine a target rock mass integrity grade based on a mapping relationship between the target rock mass integrity comprehensive index and rock mass integrity grades; determine a target rock mass quality grade of the rock mass to be measured based on a mapping relationship between the target rock strength grade, the target rock mass integrity grade and rock mass quality grades; a model construction unit configured to acquire experimental main frequency data and experimental sound pressure amplitude data at a drilling rock breaking position and experimental drilling vibration acceleration at a position close to a drill bit by digital drilling test, construct a drilling acoustic sub-model based on the experimental main frequency data and the experimental sound pressure amplitude data, construct a drilling vibration sub-model based on the experimental drilling vibration acceleration, and construct a preset rock hardness degree prediction model according to the drilling acoustic sub-model and the drilling vibration sub-model; the drilling acoustic sub-model is: the drilling vibration sub-model is: the rock hardness degree prediction model is: In the formula, represents the first rock hardness index, represents the i-th experimental principal component frequency data, represents the i-th experimental principal component frequency corresponding to the experimental sound pressure amplitude data, represents the second rock hardness index, represents the i-th direction of the experimental while-drilling vibration acceleration root mean square value, a, b, c, d are all fitting coefficients, represents the rock hardness comprehensive index.

7. A rock mass quality rapid evaluation device, characterized by, comprises: a memory and a processor, at least one instruction is stored in the memory, and the at least one instruction is loaded and executed by the processor to implement the rock mass quality rapid evaluation method in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The computer readable storage medium stores a computer program, and when the computer program is executed by the processor, the rock mass quality rapid evaluation method in any one of claims 1 to 5 is implemented.

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