Rock mass explosibility three-dimensional classification and engineering correction method and system

Abstract

The application discloses a rock mass explosibility three-dimensional grading and engineering correction method and system, and the method comprises the following steps: screening rock mass explosibility evaluation indexes, dividing each index into five grades, and establishing a corresponding relationship between the grades and basic scores of the explosibility; taking the explosive unit consumption as a benchmark to carry out orthogonal test to determine the weight of each index, distributing the grade scores according to the percentage system, and constructing an index-explosibility standardized scoring mapping; constructing a voxel grid according to the blasting return times and geologically zoning, spatially interpolating the grid after mapping the multi-source index data, and realizing complete parameter assignment of the whole grid; calling the index matching mapping to obtain the sub-item scores and accumulate them grid by grid, and outputting the global three-dimensional explosibility original grading; analyzing the influence of the relationship between the occurrence of the blasting free surface and the occurrence of the dominant structural surface, establishing a standardized explosibility score correction rule; collecting the occurrence of the free surface and the dominant structural surface on site, and outputting the corrected three-dimensional explosibility grading results; and providing accurate three-dimensional geological basis for intelligent explosive unit consumption selection and blasting parameter dynamic optimization.

Description

Technical Field

[0001] This invention belongs to the field of geotechnical engineering technology, and more specifically, relates to a method and system for three-dimensional classification and engineering correction of rock mass blastability. Background Technology

[0002] Rock mass blastability characterizes the ease with which rock mass fractures under explosive loading. It is a comprehensive engineering attribute formed by the coupling of multiple factors, including rock mass physical and mechanical parameters, geological structure, and hydrological conditions. In rock and soil blasting engineering in mining, water conservancy, and infrastructure, rock mass blastability is the core basis for selecting explosive consumption, intelligent design of blasting parameters, and prediction of blasting effects. Due to the influence of stratigraphic spatial differentiation and differences in tectonic development, the blastability of rock mass within the same blasting area exhibits significant spatial heterogeneity. Accurately quantifying the three-dimensional distribution of rock mass blastability and correcting the classification results based on on-site blasting excavation layout conditions is a key prerequisite for the implementation of intelligent blasting design.

[0003] Currently, rock mass blastability classification technology is mainly divided into three generations of technology systems: The first generation is the single-index grading method, with the Protodyakonov robustness coefficient grading as a typical example. It uses only the uniaxial compressive strength of rock as a single index for evaluation, and the calculation process is simple and quick to be used in the field. The second generation is the multi-index comprehensive evaluation method. In order to make up for the shortcomings of the single index, the industry has gradually developed multi-factor evaluation models such as fuzzy comprehensive evaluation, rock mass quality grading coupled evaluation, entropy weighting method, and combined weighting-cloud model. These models can simultaneously incorporate multiple geological parameters such as rock, structure, and hydrology, and the evaluation dimensions are more comprehensive.

[0004] The third generation is a machine learning-based intelligent classification method that relies on massive samples to train the model and automatically determine explosiveness, which is a cutting-edge research direction.

[0005] However, the single-index grading method only considers rock strength, completely ignoring key geological elements such as rock mass integrity, joint filling state, and groundwater. In fractured, water-bearing, and complex strata with multiple structures, the grading results are highly biased, often failing to effectively guide the selection of explosive consumption. Existing multi-index comprehensive evaluation systems have five core defects: First, the algorithm and weights rely on specific engineering samples, the model parameters lack universality, and are difficult to reuse across mines and geotechnical engineering projects, resulting in poor universality; Second, all geological indicators are uniformly calculated using regional average values, failing to consider the spatial variability of geological bodies, and thus failing to output continuously distributed blastability grading results in three-dimensional space, resulting in a disconnect from real strata spatial characteristics; Third, there are multiple correlations among the selected evaluation indicators, with similar geological influencing factors being repeatedly weighted, distorting the grading values; Fourth, some evaluation indicators are difficult to obtain in the field, leading to high evaluation costs and weak practicality; Fifth, grading is based solely on static geological conditions, completely ignoring blasting engineering layout elements, and failing to establish a spatial orientation coupling correction mechanism for blasting free faces and dominant structural faces, making it unable to match actual excavation conditions and resulting in insufficient grading accuracy.

[0006] Therefore, existing classification methods cannot simultaneously achieve objective weighting of multiple independent indicators, three-dimensional voxel-based spatial classification, and integrated evaluation of spatial occurrence correction for excavation conditions. The industry lacks a unified, easily implemented, universally applicable, and balanced method for quantitative classification and correction of rock mass blastability that takes into account both three-dimensional spatial characteristics and blasting layout conditions, which restricts the large-scale application of intelligent blasting design. Summary of the Invention

[0007] To address the aforementioned problems in existing technologies, this invention provides a three-dimensional classification and engineering correction method and system for rock mass blastability. First, five independent evaluation indicators—rock strength, rock density, rock mass integrity coefficient, joint state, and groundwater conditions—are selected and divided into five levels. A correspondence between each indicator level and the basic blastability score is established. Then, using explosive consumption as a quantitative benchmark, orthogonal experiments with data sources including field measurements and numerical simulations determine the objective weights of each indicator. A standardized mapping relationship between indicator values ​​and blastability scores is generated based on a percentage conversion. Subsequently, a voxel grid model is constructed for each blasting cycle, combined with geological interface partitioning. Multi-source discrete indicator data from manual assignment, exploration statistics, and 3D mapping are integrated and spatially interpolated to achieve full grid parameter coverage. This is performed grid-by-grid. The original three-dimensional explosiveness classification result is obtained by accumulating the component scores. Then, the standardized correction rules corresponding to the dip and dip angle of the free surface and the dominant structural surface are calibrated by experiments. Combined with the field occurrence parameters, the original classification is corrected to obtain the final three-dimensional classification result that fits the construction conditions. This invention selects mutually independent index systems to adapt to various complex geological engineering projects, relies on orthogonal experiments to achieve objective weighting and eliminate human bias, and uses voxel interpolation to completely restore the three-dimensional spatial distribution characteristics of rock mass explosiveness. It is the first to create a spatial coupling correction mechanism between structural surface and free surface to make up for the shortcomings of static classification and field conditions. It has the beneficial effects of simple operation, strong engineering universality, and high classification accuracy. It can provide accurate three-dimensional geological basis for intelligent blasting explosive consumption and dynamic optimization of blasting parameters.

[0008] To achieve the above objectives, one aspect of the present invention provides a method for three-dimensional classification and engineering correction of rock mass blastability, comprising the following steps: S1: Screen independent rock mass blastability evaluation indicators, divide each evaluation indicator into five levels according to the parameter value range, establish the correspondence between each indicator level and the basic score of blastability, and output the standardized grading rules and the original score comparison table; the evaluation indicators include rock strength, rock density, rock mass integrity, joint state and groundwater conditions. S2: Using explosive consumption per unit as the quantitative benchmark for rock mass explosiveness, an orthogonal test sample set is constructed, and the influence weights of five evaluation indicators on explosiveness are solved through orthogonal tests; based on the weight ratio, the total score and the score of each indicator are allocated on a percentage basis, and a mapping relationship between standardized indicator values ​​and explosiveness scores is generated. S3: Construct a voxel grid model for a single blasting cycle, delineate the spatial range, and partition the voxel model based on the geological interface; collect multi-source discrete index data and map them to voxel grid cells, and use spatial interpolation to ensure that all grid cells in the model carry the values ​​of five evaluation indices. S4: Traverse all grid cells within the voxel grid model, calculate and sum the scores of each index of a single grid cell according to the mapping relationship, obtain the basic score of blastability of a single grid cell, integrate the basic scores of blastability of all grid cells, and generate the original three-dimensional blastability classification result of the rock mass. S5: Analyze the influence of the spatial angle between the free face and the dominant structural face on the blastability of rock mass through blasting tests, and establish a standardized correction rule for blastability based on the two dimensions of the dip angle and the dip angle between the free face and the dominant structural face. S6: Obtain the free surface direction and dip angle of the current blasting cycle, as well as the dip and dip angle of the regional dominant structural surface, match the standardized correction rules to obtain the correction score, correct the basic score of the corresponding unit in the original three-dimensional blastability classification result of the rock mass, and output the corrected three-dimensional blastability classification result of the rock mass.

[0009] Furthermore, the five-level classification criteria for each indicator in step S1 are as follows: Rock strength is classified into five levels: <80MPa, 80-120MPa, 120-160MPa, 160-180MPa, and >180MPa. Rock density is classified into five levels: <2.0 g / cm³, 2.0–2.3 g / cm³, 2.3–2.6 g / cm³, 2.6–3.0 g / cm³, and >3.0 g / cm³. The rock mass integrity coefficient is divided into five levels: ≤0.15, 0.15~0.35, 0.35~0.55, 0.55~0.75, and >0.75. Joint conditions are classified into five levels based on joint filling material, degree of opening, and undulation shape. Groundwater conditions are classified into five levels: dry, humid, moist, dripping, and gushing.

[0010] Furthermore, the data sources for the orthogonal test sample set in step S2 include field blasting measurement data or numerical simulation equivalent data; when numerical simulation equivalent data is used, the volume joint number is used to replace the rock mass integrity coefficient, the fissure water pressure is used to replace the groundwater conditions, and the joint mechanical parameters are used to replace the joint state.

[0011] Further, step S2 includes: inputting all samples from the orthogonal experimental sample set into the orthogonal analysis model, using explosive unit consumption... To calculate the range of individual indicators based on the experimental results: in, : No. The range of the evaluation index represents the sensitivity of the index to the unit consumption of explosives. : No. The first indicator is taken. At the gear position, the average explosive consumption per unit of all test samples; ; ; Calculate the objective weights of each indicator based on the normalized range of individual indicators: ,in, : No. Normalized weights for each evaluation indicator ,and ; The sum of the range values ​​of the five evaluation indicators.

[0012] Furthermore, step S2 also includes: Using total score The 100-point system allocates maximum scores for each of the five indicators based on their calculated weights; the expression is: in, The total score for the comprehensive evaluation of explosiveness is fixed at 100. For the first The maximum score that can be obtained from the allocation of each indicator; The normalized weights for each evaluation indicator; Based on the original scores in step S1, convert them into standardized single-item scores: in, In the standardized mapping relationship, the first Item No. Standardized scores for each gear level; : for the first step in S1 Item No. Original experience score; This represents the raw total score for each individual indicator. The maximum score is 100 for each individual indicator.

[0013] Furthermore, the multi-source discrete index data mentioned in step S3 includes at least three categories: manually assigned data, exploration borehole statistics data, and three-dimensional mapping structural surface identification data; among them, rock strength and rock density are assigned manually in batches according to geological zones, based primarily on the results of indoor rock mechanics tests. Rock mass integrity and joint status: Three-dimensional rock mass mapping models are preferred for automatic identification and statistical analysis of structural surface data. If no mapping model is available, statistical data from previous exploration boreholes are used. Groundwater conditions: Priority should be given to using data from exploration borehole water levels and water inflow monitoring. If monitoring data is missing, on-site manual judgment and assignment are required.

[0014] Furthermore, the formula for calculating the basic explosiveness score of a single grid in step S4 is as follows: in, A basic score for the explosiveness of a single grid cell; For the first The evaluation indicator is at the first Standardized sub-scores corresponding to each gear position; These correspond to rock strength, rock density, rock mass integrity, joint state, and groundwater conditions, respectively. These correspond to gears I, II, III, IV, and V, respectively.

[0015] Furthermore, step S5 also includes calculating the total correction score; the total correction score is mainly controlled by the angle between the dominant structural surface and the free surface, and when it is close to the slope dip, it is further corrected according to the angle between the dips.

[0016] Furthermore, the revised explosiveness score calculation formula in step S6 is as follows: In the formula: The overall explosiveness score for a single grid cell after correction; The total correction score for the coupling of the attitude of the free surface and the dominant structural surface; This is the basic score for explosiveness.

[0017] A second aspect of the present invention provides a three-dimensional classification and engineering correction system for rock mass blastability, used to implement the aforementioned three-dimensional classification and engineering correction method for rock mass blastability, comprising: The indicator screening and grade division module is used to screen independent rock mass blastability evaluation indicators, divide each evaluation indicator into five grade levels according to the parameter value range, establish a preliminary correspondence between each indicator grade and the basic blastability score, and output standardized grading rules and original score comparison table. The orthogonal test weighting modeling module is used to construct an orthogonal test sample set with explosive consumption as the quantitative benchmark for rock mass blastability. The module solves the influence weights of five evaluation indicators on rock mass blastability through orthogonal tests. Based on the weight ratio, the module allocates the total score and subdivided scores of each indicator on a percentage system, and generates a standardized index value and blastability score mapping relationship library. The 3D voxel modeling and multi-source data interpolation module is used to construct a 3D voxel mesh model for a single blasting cycle, defining the spatial range; importing geological interface data to perform geological zoning on the voxel model; integrating three types of discrete index data: manually assigned, exploration borehole statistics, and 3D mapping identification, and mapping the discrete index data to the neighboring grid cells of the voxel model; performing 3D spatial interpolation processing on the index data within the grid, so that all grid cells in the model can completely store the values ​​of the five evaluation indices, and outputting a 3D voxel model with full domain assignment; The three-dimensional explosiveness original classification calculation module is used to traverse all grid cells in the voxel grid model and retrieve the values ​​of five indicators within the cell; retrieve the standardized indicator-score mapping relationship to convert the scores of each indicator in a single grid; accumulate the scores of the five indicators to obtain the basic explosiveness score of a single grid cell; integrate the spatial coordinates, indicator parameters, and basic scores of all grid cells to generate the three-dimensional explosiveness original classification numerical field of the rock mass and output the original classification results; The attitude correction rule library module is used to analyze the influence of the dip angle and dip angle of the attitude of the blasted free surface and the dominant structural surface on the blastability of the rock mass through field blasting tests and numerical simulation tests; it divides the angle intervals and matches the corresponding correction scores to establish a two-dimensional standardized blastability correction rule; it stores the corresponding lookup table relationship between the angle intervals and the correction scores, outputs the sub-item correction scores according to the input dip angle and dip angle, and sums them to obtain the total correction score; The classification result correction output module is used to collect the direction and dip angle of the free surface of the current blasting cycle, as well as the dip and dip angle of the dominant structural surface in the region; calculate the dip angle and dip angle between the dominant structural surface and the blasting free surface; call the attitude correction rule library to obtain the total correction score; traverse all grid cells and correct the basic score of the unit in the original three-dimensional blastability classification result in combination with the total correction score; bind the grid spatial coordinates, original index, basic score, and corrected score, and output the corrected three-dimensional rock mass blastability classification result; The visualization output auxiliary module is used to load and render 3D voxel mesh models, 3D explosiveness original classification cloud maps, and corrected explosiveness classification cloud maps; query the original values, basic scores, corrected scores, and final classification scores of five indicators for any grid cell; and export detailed explosiveness classification reports to intuitively display the spatial distribution differences of rock mass explosiveness in the blasting area.

[0018] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects: (1) This invention selects five physically independent evaluation indicators: rock strength, rock density, rock mass integrity coefficient, joint state, and groundwater conditions. These indicators cover three dimensions: rock block mechanical and physical properties, rock mass structural development characteristics, and hydrological weakening effect. This avoids the defects of traditional multi-indicator evaluation methods, such as multiple correlations of indicators and repeated weighting, which cause grading distortion. For quantitative indicators, numerical intervals are divided, and for qualitative indicators, state gradients are divided. Five-level quantitative scoring standards are uniformly set. The indicator parameters can be conveniently obtained through multiple channels, such as indoor tests, exploration boreholes, and three-dimensional rock mass mapping. This invention is suitable for complex geological scenarios of various rock and soil blasting projects, such as mining, water conservancy, and infrastructure. It can solve the problems of existing grading model parameters depending on specific projects, poor universality, and difficulty in field collection of some indicators. This invention greatly improves the engineering universality and field operability of the rock mass blastability grading method.

[0019] (2) This invention uses the explosive consumption per unit of explosive as the core indicator of on-site blasting as the orthogonal test response benchmark. The objective influence weight of five evaluation indicators on rock mass blastability is quantitatively solved through orthogonal tests, abandoning the traditional subjective weighting mode of expert experience. At the same time, two orthogonal sample acquisition methods are set up: on-site measurement and numerical simulation equivalent conversion. When there is no measured data, the qualitative indicators can be replaced by volume joint number, fracture water pressure, and joint mechanical parameters to generate test samples in batches. Based on the normalized weight, the standardized scores of each indicator and each level are uniformly allocated on a percentage system. A quantitative and reproducible index-blastability scoring mapping relationship is established, so that the whole set of graded scoring standards has real blasting data support, which significantly improves the objectivity, scientificity and credibility of the quantitative evaluation results of rock mass blastability.

[0020] (3) This invention constructs a three-dimensional voxel grid model with a single blasting cycle as the boundary, and completes geological zoning based on geological interfaces such as strata and faults. It is compatible with three types of discrete index data sources: manual assignment, exploration borehole statistics, and three-dimensional structural surface mapping and identification, and sets differentiated data acquisition priorities. The spatial interpolation algorithm fills the whole-domain grid index parameters, overcoming the shortcomings of traditional grading which simplifies regional geological parameters to a single fixed value and cannot reflect the spatial variability of geology. The basic score of explosiveness is calculated independently for each grid unit, and a continuous three-dimensional explosiveness numerical field and a visualized grading cloud map are output. The non-uniform spatial distribution characteristics of rock mass explosiveness in the blasting area are fully restored, and the three-dimensional fine grading of rock mass explosiveness under complex strata conditions is realized, providing complete three-dimensional geological data for intelligent dynamic design of blasting zones.

[0021] (4) Existing rock mass blastability classification relies solely on static geological parameters for evaluation, completely ignoring the influence of blasting excavation layout on the difficulty of rock mass fragmentation. The classification results deviate significantly from the actual blasting effect on site. This invention calibrates a two-dimensional standardized correction rule for the dip angle and inclination angle of the blasting free surface and dominant structural surface through blasting control tests. Based on the on-site measured excavation attitude and the regional structural surface attitude, the score is corrected. The three-dimensional static blastability classification results are uniformly corrected across the entire domain. Coupled with the inherent geological conditions of the rock mass and the blasting spatial layout conditions, the classification error caused by the spatial combination of structural surfaces and free surfaces is corrected from the mechanism. This significantly improves the matching degree between the rock mass blastability classification results and the on-site blasting conditions, effectively optimizes the selection of explosive consumption and the accuracy of blasting parameter design, and improves blasting quality and construction economy. Attached Figure Description

[0022] Figure 1 This is a flowchart illustrating a method for three-dimensional classification and engineering correction of rock mass blastability according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the process for obtaining three-dimensional explosiveness classification results based on a voxel model in a three-dimensional explosiveness classification and engineering correction method for rock mass explosiveness according to an embodiment of the present invention. Figure 3 This is a schematic diagram of a three-dimensional classification and engineering correction system for rock mass blastability according to an embodiment of the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0024] like Figure 1 As shown, one aspect of the present invention provides a method for three-dimensional classification and engineering correction of rock mass blastability, comprising the following steps: S1: Screen independent rock mass blastability evaluation indicators, divide each evaluation indicator into five levels according to the parameter value range, establish the correspondence between each indicator level and the basic score of blastability, and output the standardized grading rules and the original score comparison table; the evaluation indicators include rock strength, rock density, rock mass integrity, joint state and groundwater conditions. S2: Using explosive consumption per unit as the quantitative benchmark for rock mass explosiveness, an orthogonal test sample set is constructed, and the influence weights of five evaluation indicators on explosiveness are solved through orthogonal tests; based on the weight ratio, the total score and the score of each indicator are allocated on a percentage basis, and a mapping relationship between standardized indicator values ​​and explosiveness scores is generated. S3: Construct a voxel grid model for a single blasting cycle, delineate the spatial range, and partition the voxel model based on the geological interface; collect multi-source discrete index data and map them to voxel grid cells, and use spatial interpolation to ensure that all grid cells in the model carry the values ​​of five evaluation indices. S4: Traverse all grid cells within the voxel grid model, calculate and sum the scores of each index of a single grid cell according to the mapping relationship, obtain the basic score of blastability of a single grid cell, integrate the basic scores of blastability of all grid cells, and generate the original three-dimensional blastability classification result of the rock mass. S5: Analyze the influence of the spatial angle between the free face and the dominant structural face on the blastability of rock mass through blasting tests, and establish a standardized correction rule for blastability based on the two dimensions of the dip angle and the dip angle between the free face and the dominant structural face. S6: Obtain the free surface direction and dip angle of the current blasting cycle, as well as the dip and dip angle of the regional dominant structural surface, match the standardized correction rules to obtain the correction score, correct the basic score of the corresponding unit in the original three-dimensional blastability classification result of the rock mass, and output the corrected three-dimensional blastability classification result of the rock mass.

[0025] The steps of the method of the present invention will be described in detail below.

[0026] (1) Screening independent evaluation indicators and dividing them into levels, and establishing a preliminary correspondence between levels and base scores. The blastability of rock mass is controlled by multiple factors coupled together, including rock mechanics, rock mass structure, and hydrological environment. In order to avoid the defects of correlation and weight overlap in traditional multi-index evaluation system, this step selects five core evaluation indicators that are physically independent, have no information overlap, and are easy to obtain on the engineering site: rock strength, rock density, rock mass integrity, joint state, and groundwater conditions.

[0027] Rock strength (mechanical properties of rock): Characterizes the ability of a rock to resist failure, usually expressed as uniaxial compressive strength (UCS); Rock density (physical compactness property of rock): characterizes the degree of compactness of rock and directly affects the propagation and attenuation of explosive stress waves in rock mass; Rock mass integrity (overall fracture development): characterizes the degree to which the rock mass is cut by structural planes, using the volumetric joint number (Volume Joint Number). ) or integrity coefficient ( )express; Joint state (structural plane filling, opening, and surface morphology details): Characterizes the roughness of the structural plane, the filling material, and other characteristics, and is a key factor affecting the control failure of rock mass structural planes; Groundwater conditions: influence the ease of fracturing rocks by softening them and altering their energy dissipation patterns; Rock strength and rock density characterize the inherent mechanical and physical properties of intact rock blocks; rock mass integrity and joint state characterize the degree of fragmentation and structural surface development characteristics of the internal structure of the rock mass; groundwater conditions characterize rock softening and water wedge effect; the five categories of indicators correspond to the three dimensions of rock block, rock mass structure and hydrology, respectively, covering all core influencing factors, and there is no strong correlation between the indicators, avoiding the distortion of the classification caused by repeated weight calculation. After determining the above indicator system, to facilitate quantitative scoring, for each indicator, combined with indoor rock tests and field exploration measurement data, five levels of rock mass were distinguished from extremely easy to blast to extremely difficult to blast. Quantitative indicators were given numerical ranges, and qualitative indicators were classified into state categories. The complete grading standards are shown in Tables 1-5: Table 1 - Rock Strength Grading Table Table 2 - Rock Density Grading Table Table 3 - Rock Mass Integrity Classification Table Table 4 - Joint Status Classification Table Table 5 - Classification of Groundwater Conditions Rock strength (unit MPa): divided into five levels: <80, 80-120, 120-160, 160-180, and >180; the higher the rock strength, the greater the difficulty of rock mass fracturing, and the higher the corresponding basic score. Rock density (unit: g / cm³): divided into five levels: <2.0, 2.0-2.3, 2.3-2.6, 2.6-3.0, and >3.0; the higher the density, the denser the rock mass, and the higher the energy consumption for blasting. Rock mass integrity coefficient: divided into five levels: ≤0.15, 0.15~0.35, 0.35~0.55, 0.55~0.75, and >0.75; the higher the integrity coefficient, the more intact the rock mass, the fewer the cracks, and the worse the blastability. Joint condition: Based on the type of joint filling material, opening width, and the smoothness of the joint surface, it is divided into 5 grades: Grade 1: Widely open, clayey / unfilled joints (No. 1, 2, 3); Grade 2: Clayey-filled, slightly open joints of various types (No. 4, 5, 6); Grade 3: Rock debris-filled, slightly open joints of various types (No. 7, 8, 9); Grade 4: Unfilled, slightly open joints of various types (No. 10, 11, 12); Grade 5: Completely closed, unfilled joints (No. 13, 14). Unfilled and closed joints indicate stronger rock mass integrity and receive higher scores; open and clayey-filled joints weaken the rock mass and receive lower scores. Groundwater conditions are categorized into five levels: dry, wet, moist, dripping, and gushing. Under gushing conditions, rock strength decreases, structural surfaces are weakened, and the rock mass tends to be more easily blasted, corresponding to the lowest score. Dry rock mass has the worst blastability. Based on on-site blasting experience, preliminary base scores were assigned to the five levels of each indicator in advance. This forms a simple mapping table with a one-to-one correspondence between "indicator level - basic score", which serves as the original benchmark for subsequent orthogonal experiment weight calibration and standardized score model establishment; Rock strength rating: <80MPa (5 points), 80-120MPa (10 points), 120-160MPa (15 points), 160-180MPa (20 points), >180MPa (30 points); Rock mass integrity coefficient score range: ≤0.15 (5 points), 0.15~0.35 (10 points), 0.35~0.55 (15 points), 0.55~0.75 (20 points), >0.75 (30 points); Rock density grade scores: <2.0 (3 points), 2.0~2.3 (6 points), 2.3~2.6 (9 points), 2.6~3.0 (12 points), >3.0 (15 points); The basic scores for joint management are as follows: Level 1: 0 points, Level 2: 5 points, Level 3: 10 points, Level 4: 15 points, Level 5: 20 points. Groundwater level scores: gushing water 1 point, dripping water 2 points, moist 3 points, damp 4 points, dry 5 points; This preliminary scoring table serves as the original benchmark for the objective weighting and standardized percentage scoring model construction of the S2 orthogonal experiment; Define the formula for calculating the raw total score of a single indicator: in, For the first The sum of all five levels of original experience scores for the evaluation indicators; Number the evaluation indicators. Represents rock strength, Represents rock density, Represents rock mass integrity, Represents jointing state, Represents groundwater conditions; For indicator level numbers, 1, 2, 3, 4, and 5 correspond to gears I through V; For the first Item No. The base experience score for each gear level; Step S1 avoids the defects of index correlation in traditional multi-index evaluation systems from the source; unifies the quantitative grading standards to achieve standardized grading of qualitative and quantitative geological indicators; and establishes an index-score basic mapping framework to provide a unified calculation basis for subsequent orthogonal experiment weighting and automatic scoring of three-dimensional grid units.

[0028] (2) Orthogonal experiment weighting to construct a standardized index value-explosiveness score mapping relationship. Step S2 specifically includes: A. Determine the quantitative benchmark index for rock mass blastability Explosive consumption per unit volume was selected as an objective quantitative benchmark. Explosive consumption per unit volume is the mass of explosive consumed per unit rock mass under the same blasting block size standard (unit: kg / m³). 3 The higher the explosive consumption, the greater the difficulty in breaking the rock mass and the worse the blastability. Using explosive consumption as the response output variable of the orthogonal experiment ensures that the weight calculation is fully consistent with the actual blasting project on site and avoids human bias caused by expert subjective weighting. B. Construct an orthogonal experimental sample set and distinguish between the two types of sample sources. Using the five independent indicators (rock strength, rock density, rock mass integrity, joint state, and groundwater conditions) selected in step S1 as influencing factors for orthogonal experiments, and taking the five levels defined in S1 for each factor, a multi-factor orthogonal experimental sample set was constructed. The samples were obtained through two methods, with priority given to field-measured samples: On-site blasting test samples (preferred) Measured explosive consumption per blast was collected for different geological zones and joint water-bearing conditions. Five indicators were measured to construct a sample of real working conditions; Numerical simulation equivalent sample (used as a substitute when no field measurement data is available) Experimental samples are generated in batches through numerical simulation, and qualitative indicators are replaced with equivalent parameters. The equivalent replacement rules are as follows: Rock mass integrity index: using volume joint number Equivalent substitution; Groundwater condition indicators: fissure water pressure Equivalent substitution; Joint state index: using joint mechanical parameters (friction coefficient) Cohesion Opening degree Equivalent substitution; C. Calculate the objective influence weights of each index using orthogonal experiments. Input all samples from the orthogonal experimental sample set into the orthogonal analysis model, using the explosive unit consumption... To calculate the range of individual indicators based on the experimental results: ,in, : No. The range value of the evaluation index represents the sensitivity of the index to the unit consumption of explosive. The larger the value, the stronger the influence of this index on the blastability of the rock mass; : No. The first indicator is taken. At the gear position, the average explosive consumption per unit of all test samples; ; ; Calculate the objective weights of each indicator based on the normalized range of individual indicators: ,in, : No. Normalized weights for each evaluation indicator ,and ; The sum of the range values ​​of the five evaluation indicators; This weighting is derived entirely from blasting test data, which differs from the subjective weighting of traditional expert scoring, significantly improving the scientific rigor and objectivity of the grading and scoring standards; D. Generate a standardized indicator-score mapping relationship based on the weighted percentage scores. Using total score The 100-point system allocates maximum scores for each of the five indicators based on their calculated weights; the expression is: in, The total score for the comprehensive evaluation of explosiveness is fixed at 100. For the first The maximum score obtained from the allocation of each indicator (the sum of the five standardized scores of the indicator); The normalized weights for each evaluation indicator; Based on the raw scores in step S1, calculate the standardized single-item scores (core mapping formula): in, In the standardized mapping relationship, the first Item No. Standardized scores for each gear level; In step S1, the first Item No. Original experience score; This represents the raw total score for each individual indicator. For each individual indicator, the maximum score is 100. The preliminary grade score comparison table established solely based on engineering experience in step S1 was corrected. A standardized mapping relationship between measured values ​​of indicators and explosiveness sub-item scores was uniformly generated, and the corresponding Tables 1-5 were stored as quantitative tables that can be called by the program. Standardized mapping relationship implementation: Any set of measured index values ​​can be quickly matched with the corresponding sub-item scores. This provides a unified calculation standard for subsequent batch automatic scoring of three-dimensional voxel mesh elements; Step S2 uses the on-site explosive consumption as a benchmark and objectively quantifies the influence weight of each indicator through orthogonal experiments to solve the defects of traditional grading methods, such as strong subjectivity and inconsistent standards in manual weighting. It provides two sample acquisition paths: on-site measurement and numerical simulation, to adapt to engineering scenarios without on-site exploration data and improve the universality of the method. It establishes a unified percentage-based standardized scoring mapping rule to open up the quantitative calculation channel for qualitative and quantitative geological indicators, providing a mathematical basis for three-dimensional full-domain automated grading calculation.

[0029] (3) Construct a voxel grid model for the blasting cycle, and perform spatial interpolation and assignment of multi-source index data (such as...). Figure 2 (As shown) A. Define the blasting space and construct a three-dimensional voxel mesh model. Using a single complete blasting cycle as the spatial boundary, the three-dimensional spatial area corresponding to this blasting operation is delineated; this spatial area is discretized into uniform and regular three-dimensional voxel grid units to establish a digital voxel model, thereby realizing the three-dimensional digital representation of the geological space of the blasting area; the grid size can be customized according to the engineering accuracy requirements, and the grid unit is the smallest calculation unit for subsequent index assignment and explosiveness score calculation; B. Import geological interface data and complete the geological zoning of the voxel model. Import spatial data of geological interfaces such as stratigraphic boundaries, faults, and tectonic interfaces obtained from exploration and mapping; use geological interfaces to segment the overall voxel grid model to divide it into multiple independent geological zones; within the same geological zone, lithology, structure, and hydrological background are continuous and stable, while geological parameters between different zones can change abruptly, providing a boundary basis for differentiated assignment of zone values. C. Collect discrete data of hierarchical indicators through multiple channels and transmit them to neighboring grid cells. There are three channels for obtaining indicator data: manual assignment, exploration borehole statistics, and 3D mapping model recognition. The optimal data collection method is matched for different indicators. Rock strength and rock density: values ​​are assigned manually in batches according to geological zones, primarily based on the results of indoor rock mechanics tests. Rock mass integrity and joint status: Three-dimensional rock mass mapping models are preferred for automatic identification and statistical analysis of structural surface data. If no mapping model is available, statistical data from previous exploration boreholes are used. Groundwater conditions: Priority should be given to using data from exploration borehole water levels and water inflow monitoring. If monitoring data is missing, on-site manual judgment and assignment are required. The discrete index data obtained from borehole measurement points, partition assignment, and mapping identification are matched and mapped to the grid cell closest to the data point in the voxel model to complete the transfer of the original discrete data. D. Conduct three-dimensional spatial interpolation processing to achieve full coverage of all grid indicators. To address the issue of measured index data existing only in local grids and a large number of blank grids lacking parameters, a three-dimensional spatial interpolation algorithm is used to interpolate the five index data of the discrete grids. After interpolation, all grid cells within the voxel model completely store the values ​​of the five indexes: rock strength, rock density, rock mass integrity, joint state, and groundwater conditions. This eliminates the shortcomings of traditional classification methods that only use single-point values ​​to represent the entire area, restores the spatial continuous variation characteristics of geological parameters, and provides a complete data foundation for full-domain three-dimensional explosiveness calculation. Step S3 achieves 3D digitization of the blasting area based on voxel grids, and distinguishes abrupt stratigraphic boundaries by combining geological interface zoning, which conforms to the actual geological spatial distribution characteristics; it is compatible with multi-source geological data such as manual, borehole, and 3D mapping data, and adapts to the data acquisition conditions of different projects such as mines and infrastructure, thereby improving the method's field versatility; by filling the global grid index through spatial interpolation, it solves the pain point that traditional static value evaluation cannot reflect the differences in geological space, and provides data support for outputting 3D continuous blastability classification results.

[0030] (4) Calculate the basic score grid by grid to generate the original three-dimensional explosiveness classification results. Step S4 specifically includes: A. Traverse all 3D mesh cells and retrieve the values ​​of the five indicators within each cell. Using the voxel grid model constructed and spatially interpolated in step S3 as the computational carrier, each independent three-dimensional grid cell within the model is traversed sequentially; the complete set of index parameters stored in the current grid cell is read: rock strength value, rock density value, rock mass integrity coefficient, joint state type, and groundwater condition state; a single grid cell is used as the smallest independent computational unit to ensure that explosiveness scoring calculations are carried out independently at each spatial location, reflecting the differences in geological space; B. Matching the mapping relationship and scoring each item separately, then summing them up to obtain the basic score for unit explosiveness. Retrieve the mapping relationship between standardized index values ​​and explosiveness scores established by S2 (Tables 1-5 Quantitative Comparison Tables), and for each index in the current grid unit, match its corresponding level and query the corresponding standardized sub-item score. ; The basic explosiveness score of the grid cell without engineering condition correction is obtained by linearly summing the scores of the five indicators. The calculation formula is as follows: in, A basic score for the explosiveness of a single grid cell; For the first The evaluation indicator is at the first Standardized sub-scores corresponding to each gear position; These correspond to rock strength, rock density, rock mass integrity, joint state, and groundwater conditions, respectively. These correspond to gears I, II, III, IV, and V, respectively. The higher the base score, the greater the difficulty of blasting under the inherent geological conditions of the rock mass at the corresponding grid location; the lower the score, the easier the rock mass is to break. C. Integrate the full-grid scoring data and output the original three-dimensional explosiveness classification results. The spatial coordinates of all grid cells in the voxel model, the five original index parameters, and the basic explosiveness score are bound and stored to form a continuous three-dimensional explosiveness numerical field across the entire domain. Outputs the original three-dimensional explosiveness classification results of the rock mass, and can generate a visualized three-dimensional cloud map (such as...). Figure 3 As shown in the figure, it visually demonstrates the spatial distribution differences in the blastability of the rock mass within the range of a blasting cycle; The original classification result was calculated based solely on static geological parameters and did not take into account the engineering effects of the spatial orientation of the free face and dominant structural face during blasting excavation. Further steps are needed to correct the working conditions. Step S4 relies on voxel grids to perform independent calculations cell by cell, which solves the shortcomings of traditional classification that uses regional average values ​​and cannot characterize the spatially uneven distribution of rock mass blastability. It reuses the standardized mapping relationship obtained from the orthogonal test in step S2 to achieve full-process quantitative automatic scoring and avoid the subjectivity of manual classification. It outputs three-dimensional continuous raw blastability classification data, providing a complete three-dimensional data foundation for subsequent corrections and intelligent blasting parameter design in conjunction with blasting engineering layout. (5) Establish a two-dimensional standardized explosiveness correction rule for free surface-dominant structural surface. Step S5 includes: A. Determine the two types of core spatial geometric parameters and design a control experiment system. Two sets of control variables are defined: the attitude of the blasting free face (excavation slope) and the attitude of the regional dominant structural surface; these are decomposed into two sets of evaluation dimensions based on the included angle. ① The angle between the dominant structural plane and the free surface of the blasting; ② The angle between the dominant structural plane and the blasting free plane.

[0031] Multiple sets of comparative tests were conducted, including field blasting tests and numerical simulation tests. The geological conditions of the rock mass were kept constant, and only the spatial angle combination of the free surface and the dominant structural surface was changed. The actual blasting effect and measured explosive consumption were collected under each working condition to quantify the impact of the angle change on the difficulty of rock mass fragmentation. Mechanism explanation: The two types of included angles jointly determine the propagation path of the explosive stress wave and the ease of slippage and cracking of the structural surface, directly changing the actual difficulty of rock mass fracturing; the existing static classification only considers geological parameters and does not take into account the coupling effect of the project layout, which is an important source of classification error; B. Divide the included angle interval and match the corresponding correction score. Based on statistical analysis of experimental data, intervals were divided according to the angle of inclination and the angle of dip, and explosiveness score correction values ​​were matched to form a standardized correction rule base; see Table 6; Table 6 - Correspondence between the Correction Scores for the Direction of the Dominant Structural Surface and the Free Surface The correction score is the cumulative amount: a positive value indicates that the working conditions are favorable for blasting, which effectively reduces the blasting difficulty and increases the blastability score after correction; a negative value indicates that the working conditions are unfavorable for rock mass fracturing, which decreases the blastability score after correction. The correction score can be added to the base score. The greater the angle between the rock mass and the structural plane, the higher the correction score, which effectively reduces the difficulty of blasting the rock mass. Conversely, the score is deducted to reflect unfavorable excavation conditions. C. Solidify the dual-dimensional standardized correction rule base By binding the angle interval, the inclination angle interval, and the corresponding correction score one by one, a standardized correction rule can be directly called by the program and used for on-site table lookup. The rules cover both dip and tilt angle spatial constraints, enabling quantitative correction logic that combines geological static classification results with blasting excavation layout conditions. The rule base is stored independently and can be directly read and called in the S6 step to build a correlation correction system between static geological classification and dynamic engineering layout; This invention, through step S5, overcomes the shortcomings of traditional rock mass blastability classification, which completely ignores the spatial coupling relationship between the blasting free surface and the dominant structural surface, thus solving the problem of the disconnect between static geological classification and actual on-site blasting conditions. By quantifying the influence of the two-dimensional angle through experiments, a quantitative correction standard is established, and the correction score is automatically superimposed based on the total correction score superposition formula, avoiding subjective errors caused by manual experience correction. Standardized and reusable correction rules are formed, providing a unified calculation basis for the batch automated correction of full-domain three-dimensional blastability classification, and significantly improving the engineering fit of the classification results.

[0032] (6) Match the attitude parameters to correct the score and output the corrected three-dimensional explosiveness classification results. A. Acquisition of operating parameters Collect measured engineering parameters of the excavation face during this blasting cycle, including: azimuth (dip) of the blasting free face and slope angle of the free face; Extract the attitude parameters of the dominant structural planes obtained from geological surveys and three-dimensional rock mass mapping of the blasting area, including: the overall dip of the dominant structural planes and the dip angle of the dominant structural planes; B. Calculate the angle between the two-dimensional spaces, match it with the standardized correction rules, and obtain the total correction score. Calculate the dip angle and the angle between the free surface and the dominant structural surface during blasting. Retrieve the standardized correction rules established in S5 and look up the correction scores corresponding to the dip angle and the angle between the dip angles respectively. Add the two correction scores together to obtain the total correction score corresponding to this blasting condition. Explanation of score correction: The total correction score is positive: the spatial combination of free surfaces and dominant structural surfaces is conducive to rock mass cracking and fragmentation, which effectively reduces the difficulty of blasting; The total correction score is negative: the spatial combination is not conducive to rock mass fragmentation, which effectively increases the difficulty of blasting; C. Correcting the basic score of explosiveness of three-dimensional mesh elements Traverse all mesh elements of the voxel model and read the basic explosiveness score calculated by S4 for each mesh element. ; The corrected explosiveness score was calculated using a linear correction formula: In the formula: The overall explosiveness score for a single grid cell after correction; The total correction score for the coupling of the attitude of the free surface and the dominant structural surface; This is the basic score for explosiveness. Complete the unified correction of the scores of all grid units in the entire domain, and realize the quantitative classification of the coupling of inherent geological properties and on-site blasting layout conditions; D. Output the corrected three-dimensional explosiveness classification results Bind all grid cell spatial coordinates, five original geological indicators, basic score, and corrected score to generate a complete three-dimensional explosiveness correction data field; Output a visualized 3D hierarchical cloud map to intuitively show the spatial distribution of rock mass blastability after considering excavation conditions; The revised three-dimensional classification results are directly used for intelligent blasting design, dynamically matching blasting parameters such as explosive consumption, borehole layout, and charge structure in different zones to guide precise blasting operations on site. This invention establishes a connection between static geological classification and blasting engineering layout conditions through step S6. It utilizes the corrected single-grid unit comprehensive explosiveness score calculation formula to complete automatic full-grid correction, overcoming the shortcomings of traditional classification which only considers geology and ignores the coupling effect of excavation space orientation. This significantly improves the matching degree between classification results and actual blasting difficulty on site. Based on the standardized rules solidified by the S5 test, it automatically batch corrects the three-dimensional grid scores, performing quantitative calculations throughout the process to eliminate subjective errors caused by manual experience corrections. It outputs three-dimensional explosiveness data that closely matches real construction conditions, providing high-precision basic data for intelligent dynamic optimization of blasting parameters, thereby improving the economy and quality of blasting construction.

[0033] This invention selects five independent rock mass blastability evaluation indicators without multiple correlations and provides a standardized five-level quantitative scoring system. These indicators can be collected through multiple channels, including laboratory tests, exploration boreholes, and 3D mapping, making them convenient for field implementation and adaptable to various complex geological conditions in rock and soil blasting projects. Using orthogonal experiments with explosive consumption as the benchmark, the influence weights of each indicator are objectively determined, abandoning traditional subjective weighting methods and significantly improving the scientific rigor and reproducibility of the indicator score classification standards. A 3D voxel mesh model is used for each blasting cycle to complete geological zoning and multi-source discrete index calculations. Spatial interpolation is used to assign values ​​across the entire domain, and the explosiveness score is calculated by accumulating the scores of each grid cell. This outputs a complete three-dimensional spatial distribution field of rock mass explosiveness, accurately restoring the spatial variability of geological parameters. Innovatively, a standardized correction rule is established by introducing the dip and inclination angles of the dominant structural plane and the blasting free plane in two dimensions. Combined with the on-site blasting and excavation conditions, the static three-dimensional classification results are quantitatively corrected. This effectively makes up for the shortcomings of existing technologies that rely solely on geological parameters for evaluation and ignore the influence of engineering layout, significantly improving the matching accuracy between the rock mass explosiveness classification results and the actual on-site blasting effects.

[0034] like Figure 3 As shown, a second aspect of the present invention provides a three-dimensional classification and engineering correction system for rock mass blastability, used to implement the above-mentioned method, comprising: The indicator screening and grade division module is used to screen independent rock mass blastability evaluation indicators, divide each evaluation indicator into five grade levels according to the parameter value range, establish a preliminary correspondence between each indicator grade and the basic score of blastability, and output standardized grading rules and original score comparison table; the evaluation indicators include rock strength, rock density, rock mass integrity coefficient, joint state, and groundwater conditions. The orthogonal test weighted modeling module is used to construct an orthogonal test sample set with explosive consumption as the quantitative benchmark for rock mass blastability. The sample supports two methods: on-site blasting measurement and numerical simulation equivalent generation. In numerical simulation, volume joint number, fracture water pressure, and joint mechanical parameters are used to equivalently replace the rock mass integrity, groundwater, and joint state indices, respectively. The influence weights of the five evaluation indices on rock mass blastability are solved through orthogonal tests. Based on the weight ratio, the total score of each index and the subdivided scores of each level are allocated on a percentage system to generate a standardized index value and blastability score mapping relationship library. The 3D voxel modeling and multi-source data interpolation module is used to construct a 3D voxel mesh model for a single blasting cycle, defining the spatial range; importing geological interface data to perform geological zoning on the voxel model; integrating three types of discrete index data: manually assigned, exploration borehole statistics, and 3D mapping identification, and mapping the discrete index data to the neighboring grid cells of the voxel model; performing 3D spatial interpolation processing on the index data within the grid, so that all grid cells in the model can completely store the values ​​of the five evaluation indices, and outputting a 3D voxel model with full domain assignment; The three-dimensional explosiveness original classification calculation module is used to traverse all grid cells in the voxel grid model and retrieve the values ​​of five indicators within the cell; retrieve the standardized indicator-score mapping relationship to convert the scores of each indicator in a single grid; accumulate the scores of the five indicators to obtain the basic explosiveness score of a single grid cell; integrate the spatial coordinates, indicator parameters, and basic scores of all grid cells to generate the three-dimensional explosiveness original classification numerical field of the rock mass and output the original classification results; The attitude correction rule library module is used to analyze the influence of the dip angle and dip angle of the attitude of the blasted free surface and the dominant structural surface on the blastability of the rock mass through field blasting tests and numerical simulation tests; it divides the angle intervals and matches the corresponding correction scores to establish a two-dimensional standardized blastability correction rule; it stores the corresponding lookup table relationship between the angle intervals and the correction scores, outputs the sub-item correction scores according to the input dip angle and dip angle, and sums them to obtain the total correction score; The classification result correction output module is used to collect the direction and dip angle of the free surface of the current blasting cycle, as well as the dip and dip angle of the dominant structural surface in the region; calculate the dip angle and dip angle between the dominant structural surface and the blasting free surface; call the attitude correction rule library to obtain the total correction score; traverse all grid cells and correct the basic score of the unit in the original three-dimensional blastability classification result in combination with the total correction score; bind the grid spatial coordinates, original index, basic score, and corrected score, and output the corrected three-dimensional rock mass blastability classification result; The visualization output auxiliary module is used to load and render 3D voxel mesh models, 3D explosiveness original classification cloud maps, and corrected explosiveness classification cloud maps; query the original values, basic scores, corrected scores, and final classification scores of five indicators for any grid cell; and export detailed explosiveness classification reports to intuitively display the spatial distribution differences of rock mass explosiveness in the blasting area.

[0035] It should be noted that the rock mass blastability three-dimensional classification and engineering correction system provided in this embodiment can be a computer program (including program code) running on a computer device. For example, the rock mass blastability three-dimensional classification and engineering correction system is an application software; the rock mass blastability three-dimensional classification and engineering correction system can be used to execute the corresponding steps in the above-mentioned methods provided in the embodiments of this application.

[0036] This application also provides a computer-readable storage medium storing a computer program that is executed by a processor to perform... Figure 1 The methods provided in each step are detailed in the implementation methods provided in the above steps, and will not be repeated here.

[0037] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for three-dimensional classification and engineering correction of rock mass blastability, characterized in that, Includes the following steps: S1: Screen independent rock mass blastability evaluation indicators, divide each evaluation indicator into five levels according to the parameter value range, establish the correspondence between each indicator level and the basic score of blastability, and output the standardized grading rules and the original score comparison table; the evaluation indicators include rock strength, rock density, rock mass integrity, joint state and groundwater conditions. S2: Using explosive consumption per unit as the quantitative benchmark for rock mass explosiveness, an orthogonal test sample set is constructed, and the influence weights of five evaluation indicators on explosiveness are solved through orthogonal tests; based on the weight ratio, the total score and the score of each indicator are allocated on a percentage basis, and a mapping relationship between standardized indicator values ​​and explosiveness scores is generated. S3: Construct a voxel grid model for a single blasting cycle, delineate the spatial range, and partition the voxel model based on the geological interface; collect multi-source discrete index data and map them to voxel grid cells, and use spatial interpolation to ensure that all grid cells in the model carry the values ​​of five evaluation indices. S4: Traverse all grid cells within the voxel grid model, calculate and sum the scores of each index of a single grid cell according to the mapping relationship, obtain the basic score of blastability of a single grid cell, integrate the basic scores of blastability of all grid cells, and generate the original three-dimensional blastability classification result of the rock mass. S5: Analyze the influence of the spatial angle between the free face and the dominant structural face on the blastability of rock mass through blasting tests, and establish a standardized correction rule for blastability based on the two dimensions of the dip angle and the dip angle between the free face and the dominant structural face. S6: Obtain the free surface direction and dip angle of the current blasting cycle, as well as the dip and dip angle of the regional dominant structural surface, match the standardized correction rules to obtain the correction score, correct the basic score of the corresponding unit in the original three-dimensional blastability classification result of the rock mass, and output the corrected three-dimensional blastability classification result of the rock mass.

2. The method for three-dimensional classification and engineering correction of rock mass blastability according to claim 1, characterized in that: The five-level classification criteria for each indicator in step S1 are as follows: Rock strength is classified into five levels: <80MPa, 80-120MPa, 120-160MPa, 160-180MPa, and >180MPa. Rock density is classified into five levels: <2.0 g / cm³, 2.0–2.3 g / cm³, 2.3–2.6 g / cm³, 2.6–3.0 g / cm³, and >3.0 g / cm³. The rock mass integrity coefficient is divided into five levels: ≤0.15, 0.15~0.35, 0.35~0.55, 0.55~0.75, and >0.

75. Joint conditions are classified into five levels based on joint filling material, degree of opening, and undulation shape. Groundwater conditions are classified into five levels: dry, humid, moist, dripping, and gushing.

3. The method for three-dimensional classification and engineering correction of rock mass blastability according to claim 2, characterized in that: The data sources for the orthogonal test sample set in step S2 include field blasting measured data or numerical simulation equivalent data. When numerical simulation equivalent data is used, the volume joint number is used to replace the rock mass integrity coefficient, the fissure water pressure is used to replace the groundwater conditions, and the joint mechanical parameters are used to replace the joint state.

4. The method for three-dimensional classification and engineering correction of rock mass blastability according to claim 3, characterized in that, Step S2 includes: inputting all samples from the orthogonal experimental sample set into the orthogonal analysis model, with explosive unit consumption... To calculate the range of individual indicators based on the experimental results: in, : No. The range of the evaluation index represents the sensitivity of the index to the unit consumption of explosives. : No. The first indicator is taken. At the gear position, the average explosive consumption per unit of all test samples; ; ; Calculate the objective weights of each indicator based on the normalized range of individual indicators: ,in, : No. Normalized weights for each evaluation indicator ,and ; The sum of the range values ​​of the five evaluation indicators.

5. The method for three-dimensional classification and engineering correction of rock mass blastability according to claim 4, characterized in that, Step S2 also includes: Using total score The 100-point system allocates maximum scores for each of the five indicators based on their calculated weights; the expression is: in, The total score for the comprehensive evaluation of explosiveness is fixed at 100. For the first The maximum score that can be obtained from the allocation of each indicator; The normalized weights for each evaluation indicator; Based on the original scores in step S1, convert them into standardized single-item scores: in, In the standardized mapping relationship, the first Item No. Standardized scores for each gear level; : for the first step in S1 Item No. Original experience score; This represents the raw total score for each individual indicator. The maximum score is 100 for each individual indicator.

6. A method for three-dimensional classification and engineering correction of rock mass blastability according to any one of claims 1-5, characterized in that: The multi-source discrete index data mentioned in step S3 includes at least three categories: manually assigned data, exploration borehole statistics data, and three-dimensional mapping structural surface identification data; among them, rock strength and rock density are assigned manually in batches according to geological zones, based primarily on the results of indoor rock mechanics tests. Rock mass integrity and joint status: Three-dimensional rock mass mapping models are preferred for automatic identification and statistical analysis of structural surface data. If no mapping model is available, statistical data from previous exploration boreholes are used. Groundwater conditions: Priority should be given to using data from exploration borehole water levels and water inflow monitoring. If monitoring data is missing, on-site manual judgment and assignment are required.

7. A method for three-dimensional classification and engineering correction of rock mass blastability according to any one of claims 1-5, characterized in that: The formula for calculating the basic explosiveness score of a single grid in step S4 is as follows: in, A basic score for the explosiveness of a single grid cell; For the first The evaluation indicator is at the first Standardized sub-scores corresponding to each gear position; These correspond to rock strength, rock density, rock mass integrity, joint state, and groundwater conditions, respectively. These correspond to gears I, II, III, IV, and V, respectively.

8. A method for three-dimensional classification and engineering correction of rock mass blastability according to any one of claims 1-5, characterized in that: Step S5 also includes calculating the total correction score; the total correction score is mainly controlled by the angle between the dominant structural surface and the free surface, and when it is close to the slope dip, it is further corrected according to the angle between the dips.

9. The method for three-dimensional classification and engineering correction of rock mass blastability according to claim 8, characterized in that: The revised explosiveness score calculation formula in step S6 is as follows: In the formula: The overall explosiveness score for a single grid cell after correction; The total correction score for the coupling of the attitude of the free surface and the dominant structural surface; This is the basic score for explosiveness.

10. A three-dimensional classification and engineering correction system for rock mass blastability, characterized in that, The method for implementing the three-dimensional classification and engineering correction of rock mass blastability as described in any one of claims 1-9 includes: The indicator screening and grade division module is used to screen independent rock mass blastability evaluation indicators, divide each evaluation indicator into five grade levels according to the parameter value range, establish a preliminary correspondence between each indicator grade and the basic blastability score, and output standardized grading rules and original score comparison table. The orthogonal test weighting modeling module is used to construct an orthogonal test sample set with explosive consumption as the quantitative benchmark for rock mass blastability. The module solves the influence weights of five evaluation indicators on rock mass blastability through orthogonal tests. Based on the weight ratio, the module allocates the total score and subdivided scores of each indicator on a percentage system, and generates a standardized index value and blastability score mapping relationship library. The 3D voxel modeling and multi-source data interpolation module is used to construct a 3D voxel mesh model for a single blasting cycle, defining the spatial range; importing geological interface data to perform geological zoning on the voxel model; integrating three types of discrete index data: manually assigned, exploration borehole statistics, and 3D mapping identification, and mapping the discrete index data to the neighboring grid cells of the voxel model; performing 3D spatial interpolation processing on the index data within the grid, so that all grid cells in the model can completely store the values ​​of the five evaluation indices, and outputting a 3D voxel model with full domain assignment; The three-dimensional explosiveness original classification calculation module is used to traverse all grid cells in the voxel grid model and retrieve the values ​​of five indicators within the cell; retrieve the standardized indicator-score mapping relationship to convert the scores of each indicator in a single grid; accumulate the scores of the five indicators to obtain the basic explosiveness score of a single grid cell; integrate the spatial coordinates, indicator parameters, and basic scores of all grid cells to generate the three-dimensional explosiveness original classification numerical field of the rock mass and output the original classification results; The attitude correction rule library module is used to analyze the influence of the dip angle and dip angle of the attitude of the blasted free surface and the dominant structural surface on the blastability of the rock mass through field blasting tests and numerical simulation tests; it divides the angle intervals and matches the corresponding correction scores to establish a two-dimensional standardized blastability correction rule; it stores the corresponding lookup table relationship between the angle intervals and the correction scores, outputs the sub-item correction scores according to the input dip angle and dip angle, and sums them to obtain the total correction score; The classification result correction output module is used to collect the direction and dip angle of the free surface of the current blasting cycle, as well as the dip and dip angle of the dominant structural surface in the region; calculate the dip angle and dip angle between the dominant structural surface and the blasting free surface; call the attitude correction rule library to obtain the total correction score; traverse all grid cells and correct the basic score of the unit in the original three-dimensional blastability classification result in combination with the total correction score; bind the grid spatial coordinates, original index, basic score, and corrected score, and output the corrected three-dimensional rock mass blastability classification result; The visualization output auxiliary module is used to load and render 3D voxel mesh models, 3D explosiveness original classification cloud maps, and corrected explosiveness classification cloud maps; query the original values, basic scores, corrected scores, and final classification scores of five indicators for any grid cell; and export detailed explosiveness classification reports to intuitively display the spatial distribution differences of rock mass explosiveness in the blasting area.

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