A mine area level three-dimensional rock mass quality evaluation method, device, equipment and medium

Abstract

The application relates to the technical field of mine engineering, and discloses a mine area level three-dimensional rock mass quality evaluation method, device, equipment and medium. The method comprises the following steps: obtaining a plurality of drill holes and rock cores thereof through geological drilling, and counting rock mass quality data of the rock cores of each cycle in each drill hole; obtaining a plurality of groups of structure surface data of structure surfaces along the depth direction of the drill holes, and constructing a drill hole database according to the positioning data, the rock mass quality data and the structure surface data of the drill holes; establishing a block model covering all the drill holes based on the drill hole database, creating an ellipsoid model for each block in the block model according to the structure surface data, and obtaining a vector ellipsoid model group; determining a three-dimensional space block evaluation algorithm according to the vector ellipsoid model group, and calculating a three-dimensional rock mass quality distribution map of the block model by using the three-dimensional space block evaluation algorithm. The application can realize mine area level three-dimensional rock mass quality evaluation with strong anisotropy characteristics, and effectively solves the problem of fine rock mass quality evaluation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing, and in particular to a mine area level three-dimensional rock mass quality evaluation method, device, equipment and medium. BACKGROUND

[0002] The various lithological characteristics of the mine area level rock mass distribution are inconsistent, and different rock mass structure surface characteristics are developed in different regions, especially the occurrence characteristics and development density of the rock mass structure surface, which significantly control and make the rock mass exhibit strong anisotropy characteristics.

[0003] The three-dimensional estimation evaluation of the previous geological grade mainly performs attribute estimation on the global ore body through a single search ellipsoid, but when it is applied to the three-dimensional estimation of rock mass quality evaluation, the single search ellipsoid is difficult to characterize the strong anisotropy characteristics of the global rock mass, and cannot accurately reflect the influence degree of the rock mass structure surface occurrence. SUMMARY

[0004] Therefore, the purpose of the present application is to overcome the deficiencies in the prior art and provide a mine area level three-dimensional rock mass quality evaluation method, device, equipment and medium.

[0005] The present application provides the following technical solutions:

[0006] In a first aspect, the present application provides a mine area level three-dimensional rock mass quality evaluation method, which comprises:

[0007] Obtaining a plurality of drill holes and their cores through geological drilling, and counting the rock mass quality data of the cores of each cycle in each drill hole;

[0008] Obtaining a plurality of sets of structure surface data of the structure surfaces tested along the depth direction of the drill holes, and constructing a drill hole database according to the positioning data, rock mass quality data and structure surface data of each drill hole;

[0009] Establishing a block model covering all the drill holes based on the drill hole database, and creating an independent ellipsoid model for each block in the block model according to the structure surface data, to obtain a vector ellipsoid model group;

[0010] Determining a three-dimensional space block estimation algorithm according to the vector ellipsoid model group, and calculating a three-dimensional rock mass quality distribution map of the block model by using the three-dimensional space block estimation algorithm.

[0011] Further, the counting of the rock mass quality of each cycle of cores in each drill hole comprises:

[0012] Collecting the rock mass mechanical property data of each cycle in each drill hole;

[0013] The rock mass quality of each round of core is calculated by using a rock mass quality evaluation method and according to the rock mass mechanical property data, wherein the rock mass quality evaluation method comprises MRMR method, Q system method and Q' / GSI method.

[0014] Further, a block model covering all the boreholes is established based on the borehole database, and an independent ellipsoid model is created for each block in the block model according to the structural plane data, comprising:

[0015] A three-dimensional geometric model covering all the boreholes is established based on the borehole database, and a block model under the constraint condition is established by setting the constraint condition and the size of the block according to actual needs;

[0016] According to the structural plane data, the mean vector and the covariance matrix of each group of structural planes are calculated, the ellipsoid model corresponding to each group of structural planes is established, and the range of the ellipsoid model is adjusted by using the confidence interval;

[0017] Based on the radial basis method, the parameter estimation anisotropy of the ellipsoid model is calculated into each block in the block model, and an independent ellipsoid model is created for each block in the block model.

[0018] Further, according to the structural plane data, the mean vector and the covariance matrix of each group of structural planes are calculated, and the ellipsoid model corresponding to each group of structural planes is established, comprising:

[0019] According to the structural plane data, the mean vector and the covariance matrix of each group of structural planes are calculated, and the probability density function of the ellipsoid model is constructed according to the mean vector and the covariance matrix of each group of structural planes;

[0020] The probability density of any given structural plane parameter value is calculated by using the probability density function of the ellipsoid model, the ellipsoid model of each group of structural planes is constructed, and the dominant surface of each ellipsoid model is determined according to the covariance matrix.

[0021] Further, the parameter estimation anisotropy of the ellipsoid model is calculated into each block in the block model based on the radial basis method, comprising:

[0022] The ellipsoid model of any group of structural planes is taken as a starting point based on the radial basis function, and the gradient or sub-gradient of the objective function at the starting point is calculated;

[0023] updating the starting point by a preset step length rule based on the basis function of the radial basis and the gradient or sub-gradient of the target function, and repeating the calculation of the gradient or sub-gradient of the target function at the updated starting point and the updating of the starting point until a preset step length stopping rule is met, and estimating the parameters of the ellipsoid model into each block in the block model.

[0024] Further, the calculation of the three-dimensional rock mass quality distribution map of the block model by the three-dimensional block estimation algorithm comprises:

[0025] selecting rock mass quality data of known blocks from the borehole database according to the direction of the advantage surface;

[0026] estimating the rock mass quality data of the known blocks into each block in the block model by the three-dimensional block estimation algorithm to predict the rock mass quality of each unknown block and obtain the three-dimensional rock mass quality distribution map of the block model, wherein the three-dimensional block estimation algorithm comprises a distance power inverse ratio method and a Kriging method.

[0027] Further, after the calculation of the three-dimensional rock mass quality distribution map of the block model by the three-dimensional block estimation algorithm, the method further comprises:

[0028] selecting any block in the estimated block model and reviewing the anisotropy characteristics of the any block to obtain a review result;

[0029] adjusting and optimizing the three-dimensional block estimation algorithm and the parameters of the ellipsoid model according to the review result.

[0030] In a second aspect, the disclosure provides a device for evaluating the quality of a three-dimensional rock mass at a mine site, the device comprising:

[0031] a statistical module configured to obtain a plurality of boreholes and their cores by geological drilling, and to statistically record the rock mass quality data of the cores of each cycle in the boreholes;

[0032] a construction module configured to obtain a plurality of sets of structural plane data of structural planes tested along the depth direction of the boreholes, and to construct a borehole database according to the positioning data, rock mass quality data and structural plane data of the boreholes;

[0033] a creation module configured to establish a block model covering all the boreholes based on the borehole database, and to create an independent ellipsoid model for each block in the block model according to the structural plane data, thereby obtaining a group of vector ellipsoid models;

[0034] A calculation module is configured to determine a three-dimensional spatial block estimation algorithm according to the group of vector ellipsoidal models, and calculate a three-dimensional rock mass quality distribution map of the block model by using the three-dimensional spatial block estimation algorithm.

[0035] In a third aspect, the embodiments of the present disclosure provide a computer device, which comprises a memory and a processor, the memory stores a computer program, and the processor implements the steps of the mine-level three-dimensional rock mass quality evaluation method in the first aspect when executing the computer program.

[0036] In a fourth aspect, the embodiments of the present disclosure provide a computer readable storage medium, which stores a computer program, and the computer program implements the steps of the mine-level three-dimensional rock mass quality evaluation method in the first aspect when executed by a processor.

[0037] The present application has the following beneficial effects:

[0038] The mine-level three-dimensional rock mass quality evaluation method provided by the embodiments of the present application comprises the following steps: obtaining a plurality of drill holes and their cores through geological drilling, and counting the rock mass quality data of the cores of each cycle in each drill hole; obtaining a plurality of groups of structural plane data of structural planes tested along the depth direction of the drill holes, and constructing a drill hole database according to the positioning data, rock mass quality data and structural plane data of each drill hole; establishing a block model covering all the drill holes based on the drill hole database, and creating an independent ellipsoidal model for each block in the block model according to the structural plane data to obtain a group of vector ellipsoidal models; determining a three-dimensional spatial block estimation algorithm according to the group of vector ellipsoidal models, and calculating a three-dimensional rock mass quality distribution map of the block model by using the three-dimensional spatial block estimation algorithm. The present application can realize mine-level three-dimensional rock mass quality evaluation of strong anisotropy characteristics under complex geological conditions, and effectively solve the problem of fine evaluation of large-scale rock mass quality in a mine area.

[0039] In order to make the above objectives, features and advantages of the present application more apparent and easy to understand, the following preferred embodiments are described in detail below, and the accompanying drawings are described as follows. BRIEF DESCRIPTION OF DRAWINGS

[0040] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can also be obtained without creative labor. In each drawing, similar components are denoted by similar reference numerals.

[0041] Figure 1A flow chart of a mine area level three-dimensional rock mass quality evaluation method provided by an embodiment of the application is shown;

[0042] Figure 2 A flow chart of another mine area level three-dimensional rock mass quality evaluation method provided by an embodiment of the application is shown;

[0043] Figure 3 A structural schematic diagram of a mine area level three-dimensional rock mass quality evaluation device provided by an embodiment of the application is shown;

[0044] Figure 4 A structural schematic diagram of a computer device provided by an embodiment of the application is shown. DETAILED DESCRIPTION

[0045] Embodiments of the application are described in detail below with reference to the accompanying drawings, in which the same or similar elements or elements having the same or similar functions are denoted by the same or similar reference numerals throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the application and cannot be understood as limiting the application.

[0046] It should be noted that when an element is referred to as being "fixed" to another element, it can be directly on the other element or there can be an intervening element. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or there can be an intervening element. In contrast, when an element is referred to as being "directly on" another element, there is no intervening element. The terms "vertical", "horizontal", "left", "right", and similar expressions used herein are for illustrative purposes only.

[0047] In the present application, unless specifically and particularly defined otherwise, the terms "mount", "connect", "connect", "fix", and other terms should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or it can be integrated; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the internal communication of two elements or the interaction relationship between two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0048] In addition, the terms "first", "second" are only for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more of the features. In the description of the present application, the meaning of "multiple" is two or more, unless otherwise specifically and specifically limited.

[0049] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the template description is for the purpose of describing particular embodiments only and is not intended to limit the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0050] Example 1

[0051] like Figure 1 The diagram shown is a flowchart of a three-dimensional rock mass quality evaluation method for mining areas according to an embodiment of this application. The three-dimensional rock mass quality evaluation method for mining areas provided in this embodiment includes the following steps:

[0052] Step S110: Obtain multiple boreholes and their cores through geological drilling, and statistically analyze the rock mass quality data of the cores from each run in each borehole.

[0053] In this embodiment, rock mass mechanical property data are collected for each run in each borehole through a large number of geological exploration boreholes and their cores, as well as a limited number of supplementary exploration boreholes and their cores. The rock mass mechanical property data may include rock strength, deformation modulus, shear strength, etc.

[0054] Rock mass quality evaluation methods are employed to calculate the rock mass quality of each core sample based on the collected rock mass mechanical property data. These methods comprehensively consider the physical and mechanical properties of the rock and geological structural conditions, and can accurately reflect the actual quality of the rock mass. In this embodiment, the rock mass quality evaluation methods include, but are not limited to, the MRMR method, the Q-system method, and the Q' / GSI method; this application embodiment does not limit these methods.

[0055] The methods described above for obtaining boreholes and their cores directly yield physical and mechanical property data of the rock mass, which forms the basis for subsequent rock mass quality assessment. Statistical analysis of rock mass quality data from cores of each borehole run ensures the comprehensiveness and accuracy of the data, providing reliable data support for subsequent 3D modeling and valuation.

[0056] Step S120: Obtain structural surface data of multiple sets of structural surfaces obtained by testing along the depth direction of the borehole, and construct a borehole database based on the positioning data, rock mass quality data and structural surface data of each borehole.

[0057] Specifically, the attitude of structural planes obtained from tests along the borehole depth direction is statistically obtained through a limited number of supplementary exploratory boreholes. Structural planes are discontinuities such as fractures and fissures in the rock mass, which have a significant impact on the mechanical properties and stability of the rock mass.

[0058] According to the method, the occurrence distribution of each group of structural planes in a fixed distance is counted every other fixed distance, including the most dominant structural plane inclination, inclination angle and quantity in each group, and the number of structural planes in the other two directions which are 90° to the dominant direction in space, which helps to understand the spatial distribution law and dominant direction of structural planes in the rock mass.

[0059] Further, all the positioning data of the drill holes (such as longitude, latitude, elevation, etc.), inclinometer data (such as drill hole inclination angle, direction, etc.), rock mass quality data and structural plane data are integrated together to form a complete drill hole database, which provides a basis for subsequent three-dimensional modeling and valuation.

[0060] The above method obtains the structural plane data obtained by testing along the depth direction of the drill hole, which helps to understand the spatial distribution law and dominant direction of structural planes in the rock mass, which is crucial for evaluating the stability and quality of the rock mass. The drill hole database is constructed, and the positioning data of the drill hole, the rock mass quality data and the structural plane data are integrated together to provide a complete data basis for subsequent three-dimensional modeling and valuation.

[0061] Step S130, based on the drill hole database, a block model covering all the drill holes is established, and an independent ellipsoid model is created for each block in the block model according to the structural plane data, obtaining a group of vector ellipsoid models.

[0062] In an optional embodiment, as shown in Figure 2 Step S130 includes:

[0063] Step S131, based on the drill hole database, a three-dimensional geometric model covering all the drill holes is established, and constraint conditions and block size are set according to actual needs to establish a block model under the constraint conditions.

[0064] Understandably, based on the drill hole database, a three-dimensional geometric model covering the range of geological exploration and supplementary exploration drill holes is established, which can reflect the spatial form and distribution of the rock mass. Then, constraint conditions (such as terrain, geological structure, etc.) are set according to actual needs, and the size of the block is determined to establish a block model under the constraint conditions, which helps to more accurately reflect the actual structure and properties of the rock mass.

[0065] Step S132, according to the structural plane data, the mean vector and the covariance matrix of each group of structural planes are calculated, the ellipsoid model corresponding to each group of structural planes is established, and the range of the ellipsoid model is adjusted by using the confidence interval.

[0066] Understandably, according to the structural plane data, the mean vector and the covariance matrix of each group of structural planes are calculated. The calculation formula of the mean vector is:

[0067]

[0068] where μ represents the mean vector, the sample set X = {x1, x2, …, xN}, each x N represents a parameter vector of a structural plane, and N is the number of structural planes. i

[0069] The formula for calculating the covariance matrix is:

[0070]

[0071] where ∑ represents the covariance matrix.

[0072] Next, the probability density function of the ellipsoid model is constructed according to the mean vector and the covariance matrix of each group of structural planes:

[0073]

[0074] where f(x; μ, ∑) represents the probability density function of the ellipsoid model, and |∑| represents the determinant of the covariance matrix.

[0075] The range of the ellipsoid model is adjusted using the confidence interval to ensure the accuracy of the model at a certain confidence level. The formula for calculating the confidence interval is:

[0076]

[0077] where μ represents the sample mean, and S represents

[0078] Further, the probability density of any given structural plane parameter value is calculated using the probability density function of the ellipsoid model, thereby constructing the ellipsoid model of each group of structural planes. The dominant plane of each ellipsoid model is determined according to the covariance matrix. Understandably, the eigenvectors of the covariance matrix correspond to the main variation directions of the data in each direction, where the largest eigenvalue corresponds to the long axis direction and the smallest eigenvalue corresponds to the short axis direction. The short axis and the long axis form the dominant plane.

[0079] Step S133, based on the radial basis method, anisotropically estimates the parameters of the ellipsoid model into each block in the block model, and creates an independent ellipsoid model for each block in the block model.

[0080] ​​Understandably, the starting point is the beginning of the iteration process, usually choose any set of structural plane ellipsoid model as the starting point, each ellipsoid model represents the main distribution characteristics of the structural plane, including the mean vector and covariance matrix. Based on the radial basis function, the gradient or sub-gradient of the objective function at the starting point is calculated, and the objective function may be a function representing the matching degree of the ellipsoid model and the actual structural plane in the block model. The gradient or sub-gradient is used to determine the direction of the next iteration, that is, how to adjust the parameters of the ellipsoid model to better match the actual data.

[0081] Then, based on the radial basis function and according to the gradient or sub-gradient of the objective function, the starting point is updated using a preset step length rule (such as fixed step length, adaptive step length, etc.). The step length rule determines the distance moved in the gradient direction to ensure that the iteration process can converge to the optimal solution, and the updated starting point represents the new ellipsoid model parameters. The gradient or sub-gradient of the objective function at the updated starting point and the step of updating the starting point are repeated until the preset step length stopping rule is met. The stopping rule may be that the number of iterations reaches a preset upper limit, or the value of the objective function converges below a certain threshold. In each iteration, the ellipsoid model gradually adjusts its parameters to better reflect the actual structural plane distribution in the block model.

[0082] In this embodiment, the radial basis function includes but is not limited to Gaussian function, multi-quadratic function, inverse multi-quadratic function and template spline function, which can be determined according to actual conditions, and the present embodiment does not limit this.

[0083] Further, after the iteration process is completed, the final ellipsoid model parameter estimates are anisotropic to each block in the block model, obtaining a group of vector ellipsoid models. This means that each block will have an ellipsoid model parameter set corresponding to its position, and these parameter sets reflect the structural plane distribution characteristics at the block position.

[0084] The above method can reflect the spatial form and distribution of the rock mass based on the borehole database to establish the block model. Creating an independent ellipsoid model for each block can more accurately describe the spatial distribution and characteristics of the structural plane, and provide a more accurate mathematical model for subsequent calculation of the three-dimensional rock mass quality distribution map.

[0085] Step S140, determining a three-dimensional spatial block estimation algorithm according to the group of vector ellipsoid models, and calculating the three-dimensional rock mass quality distribution map of the block model using the three-dimensional spatial block estimation algorithm.

[0086] Understandably, a search radius is determined, and a suitable three-dimensional block estimation algorithm is determined according to the vector ellipsoid model group. Then, according to the direction of the advantage surface, rock mass quality data of a known block are selected from the borehole database, the three-dimensional block estimation algorithm is used to estimate the rock mass quality data of the known block to each block in the block model, the quality of each unknown block is predicted, and a three-dimensional rock mass quality distribution map of the block model is obtained.

[0087] In an optional embodiment, the three-dimensional block estimation algorithm can be a distance power inverse ratio method. For each unknown point P, the distance power inverse ratio method calculates the distance between the unknown point P and all known points; according to a distance calculation formula, the influence weight of each known point on the unknown point is calculated; and according to the value and the weight of the known point, the predicted value of the unknown point is calculated. For the unknown point P, the predicted value Z P The predicted value Z

[0088]

[0089] In the formula, Z P represents the value of the unknown point P, Z i represents the value of the known point i, d i represents the distance between the unknown point P and the known point i, t represents a power parameter, which is usually a real number greater than 0, and n represents the number of known points.

[0090] In another optional embodiment, the three-dimensional block estimation algorithm can be a Kriging method. For each unknown point P, the Kriging method calculates the distance between the unknown point P and all known points; based on the distance and the spatial autocorrelation between the known points, the weight of each known point is determined; and according to the weight and the value of the known point, the predicted value of the unknown point is calculated. For the unknown point P, the predicted value Z P The predicted value Z

[0091]

[0092] In the formula, Z P represents the value of the unknown point P, Z i represents the value of the known point i, λ i represents the weight related to the known point i, and n represents the number of known points.

[0093] It should be noted that, in the present embodiment, the three-dimensional block estimation algorithm includes but is not limited to the distance power inverse ratio method and the Kriging method, and the present embodiment is not limited thereto.

[0094] The above method, by selecting a suitable three-dimensional spatial block estimation algorithm, can ensure the accuracy and reliability of the calculation results. By using a suitable algorithm to estimate the rock mass quality data of known blocks onto each block in the block model, a three-dimensional rock mass quality distribution map of the block model can be predicted, providing intuitive visualization results for the stability and quality assessment of the rock mass.

[0095] Preferably, after calculating the three-dimensional rock mass mass distribution map of the block model, any block in the estimated block model can be selected, and the anisotropic characteristics of any block can be verified to obtain the verification result. Based on the verification result, the anisotropic characteristics of the verified estimated block are checked to see if they are significant and reasonable. Then, the parameters of the three-dimensional block estimation algorithm and the ellipsoid model are adjusted and optimized to ensure the reliability of the evaluation result.

[0096] The method for evaluating the quality of three-dimensional rock mass at the mining area level provided in this application involves obtaining multiple boreholes and their cores through geological drilling, and statistically analyzing the rock mass quality data of the cores from each run within each borehole. It also involves acquiring structural surface data from multiple sets of structural planes obtained along the depth direction of the boreholes, and constructing a borehole database based on the location data, rock mass quality data, and structural surface data of each borehole. A block model covering all boreholes is established based on the borehole database, and an independent ellipsoidal model is created for each block in the block model based on the structural surface data, resulting in a vector ellipsoidal model group. A three-dimensional spatial block estimation algorithm is determined based on the vector ellipsoidal model group, and the three-dimensional rock mass quality distribution map of the block model is calculated using this algorithm. This application can achieve three-dimensional rock mass quality estimation at the mining area level under complex geological conditions with strong anisotropy, effectively solving the problem of refined evaluation of large-scale rock mass quality at the mining area level.

[0097] Example 2

[0098] like Figure 3 The diagram shown is a structural schematic of a three-dimensional rock mass quality evaluation device 300 for mining areas, as described in an embodiment of this application. The device includes:

[0099] The statistics module 310 is used to obtain multiple boreholes and their cores through geological drilling, and to collect rock mass quality data of the cores from each run in each borehole.

[0100] The construction module 320 is used to acquire structural surface data of multiple sets of structural surfaces obtained by testing along the depth direction of the borehole, and to construct a borehole database based on the positioning data, rock mass quality data and structural surface data of each borehole.

[0101] The creating module 330 is configured to establish a block model covering all the drill holes based on the drill hole database, and create an independent ellipsoid model for each block in the block model according to the structural plane data, to obtain a group of vector ellipsoid models.

[0102] The calculating module 340 is configured to determine a three-dimensional space block evaluation algorithm according to the group of vector ellipsoid models, and calculate a three-dimensional rock mass quality distribution map of the block model by using the three-dimensional space block evaluation algorithm.

[0103] The mine area level three-dimensional rock mass quality evaluation device provided by the embodiment can realize mine area level three-dimensional rock mass quality evaluation of strong anisotropy characteristics under complex geological conditions, and effectively solves the problem of fine evaluation of large-scale rock mass quality in a mine area.

[0104] Embodiment 3

[0105] The embodiment of the present application also provides a computer device. For details, please refer to Figure 4 , Figure 4 The basic structure block diagram of the computer device of the embodiment is shown in the figure.

[0106] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 which are connected to each other through a system bus. It should be noted that only the computer device 4 with the memory 41, the processor 42, and the network interface 43 is shown in the figure, but it should be understood that it is not required to implement all the shown components, and more or fewer components can be alternatively implemented. Among them, those skilled in the art can understand that the computer device herein is a device capable of automatically performing numerical calculation and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to a microprocessor, an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital signal processor (DSP), an embedded device, etc.

[0107] The computer device can be a desktop computer, a notebook computer, a palm computer, a cloud server, and the like. The computer device can interact with a user through a keyboard, a mouse, a remote controller, a touchpad, a voice control device, and the like.

[0108] The memory 41 includes at least one type of readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., an SD or D slot compatible memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the memory 41 can be an internal storage unit of the computer device 4, such as a hard disk or a memory of the computer device 4. In other embodiments, the memory 41 can also be an external storage device of the computer device 4, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device 4. Of course, the memory 41 can also include both the internal storage unit and the external storage device of the computer device 4. In this embodiment, the memory 41 is generally used to store an operating system and various application software installed on the computer device 4, such as computer readable instructions of the slot compatibility test method, etc. In addition, the memory 41 can also be used to temporarily store various data that have been output or will be output.

[0109] The processor 42 can be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other mining area level three-dimensional rock mass quality evaluation chip in some embodiments. The processor 42 is generally used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to run computer readable instructions or process data stored in the memory 41, such as computer readable instructions of the slot compatibility test method.

[0110] The network interface 43 can include a wireless network interface or a wired network interface, and the network interface 43 is generally used to establish a communication connection between the computer device 4 and other electronic devices.

[0111] The computer device provided in this embodiment can perform the mining area level three-dimensional rock mass quality evaluation method described above. Here, the mining area level three-dimensional rock mass quality evaluation method can be the mining area level three-dimensional rock mass quality evaluation method of each of the above embodiments.

[0112] Embodiment 4

[0113] This embodiment also provides a computer readable storage medium having a computer program stored thereon, and the computer program is executed by a processor to implement the steps of the mining area level three-dimensional rock mass quality evaluation method in the embodiments.

[0114] In this embodiment, the computer readable storage medium includes a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the computer readable storage medium can be an internal storage unit of the computer device, such as a hard disk or a memory of the computer device. In other embodiments, the computer readable storage medium can also be an external storage device of the computer device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device. Of course, the computer readable storage medium can also include both the internal storage unit and the external storage device of the computer device. In this embodiment, the computer readable storage medium is usually used to store an operating system and various application software installed on the computer device. In addition, the computer readable storage medium can also be used to temporarily store various data that have been output or will be output.

[0115] In several embodiments provided in the present application, it should be understood that the disclosed apparatus and method can also be implemented by other means. The apparatus embodiments described above are only illustrative, for example, the flowcharts and structural diagrams in the drawings show the possible implementation architecture, functions and operations of the apparatus, method and computer program product according to the embodiments of the present application. In this regard, each block in the flowchart or block diagram can represent a module, a program segment or a part of code, which contains one or more executable instructions for implementing the specified logical function. It should also be noted that in alternative implementation, the functions noted in the block can also occur in different order from that noted in the drawings. For example, two consecutive blocks can actually be executed substantially in parallel, and sometimes they can be executed in reverse order, depending on the functions involved. It should also be noted that each block in the structural diagram and / or flowchart, and the combination of blocks in the structural diagram and / or flowchart, can be implemented by a dedicated hardware-based system for executing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0116] In addition, each functional module or unit in the embodiments of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0117] If the functions are implemented in the form of software function modules and sold or used as independent products, the functions can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the parts of the technical solutions that essentially contribute to the prior art can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a smart phone, a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium can be a non-volatile storage medium or a volatile storage medium, for example, the storage medium can be a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0118] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. A method for evaluating the quality of three-dimensional rock masses at the mining area level, characterized in that, The method includes: Multiple boreholes and their cores were obtained through geological drilling, and the rock mass quality data of the cores from each run in each borehole were statistically analyzed. Obtain structural surface data of multiple sets of structural surfaces obtained by testing along the depth direction of the borehole, and construct a borehole database based on the positioning data, rock mass quality data and structural surface data of each borehole; the structural surface data includes the dip direction, dip angle and number of the most dominant structural surface in each group, as well as the number of structural surfaces in two other directions that are 90° to the most dominant structural surface in each group in space. Based on the borehole database, a block model covering all the boreholes is established, and an independent ellipsoidal model is created for each block in the block model according to the structural surface data, resulting in a vector ellipsoidal model group. A three-dimensional spatial block estimation algorithm is determined based on the vector ellipsoid model group, and a three-dimensional rock mass mass distribution map of the block model is calculated using the three-dimensional spatial block estimation algorithm. The step of establishing a block model covering all the boreholes based on the borehole database, and creating an independent ellipsoidal model for each block in the block model according to the structural surface data, includes: Based on the borehole database, a three-dimensional geometric model covering all the boreholes is established, and constraints and block sizes are set according to actual needs to establish a block model under constraints. Based on the structural surface data, calculate the mean vector and covariance matrix of each set of structural surfaces, and establish the ellipsoid model corresponding to each set of structural surfaces. The radial basis method is used to anisotropically distribute the parameter estimates of the ellipsoidal model to each block in the block model, thereby creating an independent ellipsoidal model for each block in the block model.

2. The method for evaluating the quality of three-dimensional rock mass at the mining area level according to claim 1, characterized in that, The statistical analysis of rock mass quality from core samples obtained in each of the aforementioned boreholes for each run includes: Collect rock mass mechanical property data for each run in each of the aforementioned boreholes; The rock mass quality of each core sample is calculated using rock mass quality evaluation methods and based on the rock mass mechanical property data. The rock mass quality evaluation methods include the MRMR method, the Q system method, and the Q' / GSI method.

3. The method for evaluating the quality of three-dimensional rock mass at the mining area level according to claim 1, characterized in that, The step of calculating the mean vector and covariance matrix of each set of structural surfaces based on the structural surface data, and establishing an ellipsoidal model corresponding to each set of structural surfaces, includes: Based on the structural surface data, calculate the mean vector and covariance matrix of each set of structural surfaces, and construct the probability density function of the ellipsoid model based on the mean vector and covariance matrix of each set of structural surfaces. Using the probability density function of the ellipsoidal model, the probability density of any given structural surface parameter value is calculated, an ellipsoidal model for each set of structural surfaces is constructed, and the dominant surface of each ellipsoidal model is determined according to the covariance matrix.

4. The method for evaluating the quality of three-dimensional rock mass at the mining area level according to claim 1, characterized in that, The method of anisotropically approximating the parameter estimates of the ellipsoidal model to each block in the block model based on the radial basis method includes: Using an ellipsoidal model of any set of structural surfaces as the starting point, the gradient or sub-gradient of the objective function is calculated at the starting point based on radial basis functions. Based on the basis functions of the radial basis and according to the gradient or sub-gradient of the objective function, the starting point is updated using a preset step size rule. The gradient or sub-gradient of the objective function at the updated starting point is repeatedly calculated and the starting point is repeatedly updated until the preset step size stopping rule is met. The parameters of the ellipsoid model are estimated into each block of the block model. The basis functions of the radial basis include Gaussian functions, multiple quadratic functions, inverse multiple quadratic functions, and spline functions.

5. The method for evaluating the quality of three-dimensional rock mass at the mining area level according to claim 3, characterized in that, The calculation of the three-dimensional rock mass mass distribution map of the block model using the three-dimensional spatial block estimation algorithm includes: Rock mass quality data of known blocks are selected from the borehole database according to the direction of the dominant surface; The three-dimensional spatial block estimation algorithm is used to estimate the rock mass quality data of the known blocks onto each block in the block model, predict the rock mass quality of each unknown block, and obtain a three-dimensional rock mass quality distribution map of the block model. The three-dimensional spatial block estimation algorithm includes the distance power inverse ratio method and the kriging method.

6. The method for evaluating the quality of three-dimensional rock mass at the mining area level according to claim 1, characterized in that, After calculating the three-dimensional rock mass mass distribution map of the block model using the three-dimensional spatial block estimation algorithm, the method further includes: Select any block in the estimated block model and verify the anisotropic features of the arbitrary block to obtain the verification results; Based on the verification results, the parameters of the three-dimensional spatial block estimation algorithm and the ellipsoid model are adjusted and optimized.

7. A three-dimensional rock mass quality evaluation device for mining areas, characterized in that, The apparatus is used to implement the mining area-level three-dimensional rock mass quality evaluation method as described in any one of claims 1-6, and the apparatus includes: The statistics module is used to obtain multiple boreholes and their cores through geological drilling, and to statistically analyze the rock mass quality data of the cores from each run in each borehole. The construction module is used to acquire structural surface data of multiple sets of structural surfaces obtained by testing along the depth direction of the borehole, and to construct a borehole database based on the positioning data, rock mass quality data and structural surface data of each borehole. A module is created to build a block model covering all the boreholes based on the borehole database, and to create an independent ellipsoidal model for each block in the block model according to the structural surface data, thereby obtaining a group of vector ellipsoidal models. The calculation module is used to determine a three-dimensional spatial block estimation algorithm based on the vector ellipsoid model group, and to calculate a three-dimensional rock mass mass distribution map of the block model using the three-dimensional spatial block estimation algorithm.

8. A computer device, characterized in that, It includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the mining area-level three-dimensional rock mass quality evaluation method according to any one of claims 1-6.

9. 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 steps of the mining area-level three-dimensional rock mass quality evaluation method according to any one of claims 1-6.

Images