Hole site parameter optimization analysis method based on open-air deep hole blasting

Abstract

The invention belongs to the technical field of deep hole blasting parameter optimization, and discloses a hole site parameter optimization analysis method based on open-air deep hole blasting. According to the method, the rock type is judged through multi-index cooperation, and a dynamic threshold adjustment mechanism is combined, so that the rock classification accuracy is improved, and accurate matching of hole site parameters and geological conditions is ensured. According to the method, through geological parameter-rock type-mapping relation three-level correlation determination, limitation of an empirical formula is avoided, and the parameter range better fits actual geological features. And meanwhile, a historical blasting data set is introduced for similar case matching, a potential risk parameter set is removed through experience screening, the deviation between theoretical simulation and actual engineering is reduced, and the parameter reliability is improved. According to the method, the multi-objective optimization model is adopted, the crushing quality, the safety control and the economical efficiency are synchronously considered, the parameter set for balancing all the objectives is output through the Pareto optimal algorithm, and high-quality, low-risk and low-cost collaborative optimization is achieved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of deep hole blasting parameter optimization, and relates to a hole position parameter optimization analysis method based on open deep hole blasting. BACKGROUND

[0002] In the fields of open pit mining, water conservancy engineering, and transportation construction, open deep hole blasting is a commonly used rock breaking technology. The core of open deep hole blasting is to achieve efficient, safe, and economic blasting effect by reasonably setting hole position parameters. The rationality of hole position parameters directly affects the rock breaking quality after blasting, blasting vibration intensity, fly rock distance, and engineering cost. Therefore, it is of great engineering significance to optimize and analyze the hole position parameters.

[0003] With the expansion of engineering construction scale and the increase of complex geological conditions, the traditional hole position parameter setting method based on empirical formula has been difficult to meet the needs of high-precision blasting. The diversity of geological conditions can significantly affect the blasting effect. If these differences are ignored, it may lead to poor blasting effect, increased safety risks, or cost waste. Therefore, a method is needed that can combine specific geological parameters and achieve accurate optimization of hole position parameters through scientific analysis.

[0004] The traditional technical solution relies on empirical formula when setting hole position parameters, and does not fully consider the differences in specific geological parameters of the blasting area, such as rock uniaxial compressive strength and joint fissure density. It is not suitable for different types of rocks such as soft rock, medium-hard rock, and hard rock.

[0005] The traditional technical solution focuses on a single target and ignores the coordinated optimization of safety control and economy, making it difficult to maximize comprehensive benefits. In addition, it does not effectively utilize the experience in historical blasting data, but determines the parameters through theoretical simulation or a single calculation model, which may have the risk of being disconnected from the actual engineering scene. SUMMARY

[0006] In view of the above problems in the background art, a hole position parameter optimization analysis method based on open deep hole blasting is proposed.

[0007] The purpose of the application can be achieved by the following technical solution: a hole position parameter optimization analysis method based on open deep hole blasting, comprising: basic geological parameter acquisition, using a geological parameter detection device to obtain the geological parameters of the blasting area, including basic physical property parameters, integrity parameters, and step characteristic parameters, and constructing a geological parameter dataset.

[0008] Initial hole position parameter setting, according to the geological parameter dataset, the rock type of the blasting area is determined, including soft rock, medium-hard rock, and hard rock, and based on the basic empirical formula, the initial hole position parameter range is determined in combination with the rock type.

[0009] Parameter optimization model construction, based on the initial hole site parameter range and geological parameter data set, the numerical software simulation blasting situation outputs the blasting effect data, input pre-built blasting parameter coupling model for multi-objective optimization calculation, output multiple hole site parameter set and corresponding comprehensive score.

[0010] Final hole site parameter determination, based on the blasting effect data and corresponding comprehensive score for simulation screening, based on the historical blasting data set selects the corresponding historical blasting data of similar geological parameters, and selects the final hole site parameter set after the simulation screening.

[0011] Compared with the prior art, the beneficial effects of the present application are as follows:

[0012] (1) The present application determines the rock type by multi-index coordination, and improves the rock classification accuracy by combining the dynamic threshold adjustment mechanism, and ensures the accurate matching of hole site parameters and geological conditions.

[0013] (2) The present application determines through three-level association of geological parameter-rock type-mapping relationship, avoids the limitation of empirical formula, makes the parameter range more suitable for actual geological characteristics. At the same time, the historical blasting data set is introduced for similar case matching, and the potential risk parameter set is removed through experience screening, which reduces the deviation between theoretical simulation and actual engineering, and improves the parameter reliability.

[0014] (3) The present application adopts multi-objective optimization model, simultaneously considers the breaking quality, safety control and economy, outputs the parameter set balancing each target through Pareto optimal algorithm, realizes the collaborative optimization of high quality, low risk and low cost. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical scheme of the embodiments of the present application, the following will briefly introduce the drawings needed to be used for the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0016] Figure 1 The method steps of the present application are illustrated.

[0017] Figure 2 The implementation schematic diagram of the boundary threshold setting step corresponding to one embodiment provided by the present application is illustrated.

[0018] Figure 3 The multi-objective optimization calculation step schematic diagram corresponding to one embodiment provided by the present application is illustrated. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of protection of the present application.

[0020] Please refer to Figure 1 As shown in the drawings, the present application provides a hole position parameter optimization analysis method based on open deep hole blasting, comprising: basic geological parameter acquisition, acquiring geological parameters of a blasting area by using a geological parameter detection device, including basic physical property parameters, integrity parameters and step characteristic parameters, and constructing a geological parameter dataset.

[0021] It should be noted that the basic physical property parameters mainly reflect the physical and mechanical properties of the rock itself, and the core indexes include but are not limited to the uniaxial compressive strength, density and elastic modulus of the rock, etc. These parameters directly affect the resistance and breaking difficulty of the rock to the blasting effect.

[0022] The integrity parameters focus on the structural integrity of the rock, and the core index is the joint fissure density, which can also include the crack opening degree and the filling property. Such parameters determine the distribution of weak links in the rock, and affect the transmission of blasting energy and the uniformity of the breaking effect.

[0023] The step characteristic parameters are aimed at the engineering scene of open blasting, mainly including the step height and the step slope angle, etc. These parameters are directly related to the drilling arrangement and the determination of the blasting range, and are important constraint conditions for the hole position parameter setting.

[0024] Initial hole position parameter setting, according to the geological parameter dataset, the rock type of the blasting area is determined, including soft rock, medium-hard rock and hard rock, and the initial hole position parameter range is determined based on the basic empirical formula combined with the rock type.

[0025] In a preferred embodiment of the present application, the specific analysis method for determining the rock type of the blasting area is as follows: based on the uniaxial compressive strength and the joint fissure density of the rock in the geological parameter dataset, the rock type of the blasting area is identified.

[0026] It should be explained that the reason for selecting the uniaxial compressive strength and the joint fissure density of the rock as the basis for rock type classification is that the uniaxial compressive strength of the rock reflects the ability of the rock to resist axial pressure damage, and is a key physical property parameter for measuring the hardness of the rock. Generally speaking, the higher the strength, the harder the rock. The joint fissure density reflects the development degree of the internal cracks and joints of the rock, and is a core parameter for measuring the integrity of the rock. Generally speaking, the higher the density, the more broken the rock structure, and the worse the integrity.

[0027] The first rock type tendency is identified based on a pre-constructed soft-medium hard rock uniaxial compressive strength threshold and a medium hard-hard rock uniaxial compressive strength threshold.

[0028] Preferably, if the rock uniaxial compressive strength is less than or equal to the soft-medium hard rock uniaxial compressive strength threshold, the first rock type tendency is soft rock.

[0029] If the rock uniaxial compressive strength is greater than the soft-medium hard rock uniaxial compressive strength threshold and less than or equal to the medium hard-hard rock uniaxial compressive strength threshold, the first rock type tendency is medium hard rock.

[0030] If the rock uniaxial compressive strength is greater than the medium hard-hard rock uniaxial compressive strength threshold, the first rock type tendency is hard rock.

[0031] The second rock type tendency is identified based on a pre-constructed soft-medium hard rock joint fissure density threshold and a medium hard-hard rock joint fissure density threshold.

[0032] Similarly, if the rock joint fissure density is greater than or equal to the soft-medium hard rock joint fissure density threshold, the second rock type tendency is soft rock.

[0033] If the rock joint fissure density is less than the soft-medium hard rock joint fissure density threshold and greater than or equal to the medium hard-hard rock joint fissure density threshold, the second rock type tendency is medium hard rock.

[0034] If the rock joint fissure density is less than the medium hard-hard rock joint fissure density threshold, the second rock type tendency is hard rock.

[0035] When the first rock type and the second rock type are consistent, the rock type is taken as the rock type of the blasting area.

[0036] When the first rock type and the second rock type are inconsistent, the rock uniaxial compressive strength and the joint fissure density are respectively analyzed in terms of relative deviation degree with respect to the corresponding thresholds, and the rock type corresponding to the minimum relative deviation degree is taken as the rock type of the blasting area.

[0037] A specific rock type determination method when the first rock type and the second rock type corresponding to an embodiment are inconsistent:

[0038] D1, if the first type tendency is A and the second type tendency is B (A≠B), the threshold between A and B is extracted. For example, if the first type tendency is soft rock and the second type tendency is medium hard rock, the soft-medium hard rock uniaxial compressive strength threshold and the soft-medium hard rock joint fissure density threshold need to be concerned.

[0039] D2, calculate the relative deviation degree of the uniaxial compressive strength of the rock and the corresponding threshold value and the relative deviation degree of the joint fissure density.

[0040] D3, compare the relative deviation degrees of the two indexes: if the relative deviation degree of the uniaxial compressive strength is smaller, it indicates that the matching degree of the index and the corresponding threshold value is higher, and the first rock type is taken as the final result; if the relative deviation degree of the joint fissure density is smaller, the second rock type is taken as the final result.

[0041] In a preferred embodiment of the present application, please refer to Figure 2 As shown in the figure, the specific construction method of the soft-medium hard rock uniaxial compressive strength threshold value, the medium hard-hard rock uniaxial compressive strength threshold value, the soft-medium hard joint fissure density threshold value and the medium hard-hard joint fissure density threshold value is as follows: A1, collect historical experimental data, cover rock samples in different geological regions, extract the uniaxial compressive strength, joint fissure density of each sample and the corresponding blasting effect data.

[0042] A2, group the data, divide several combined intervals according to the numerical range of the uniaxial compressive strength and the joint fissure density, and calculate the average value of the blasting effect in each interval.

[0043] A3, take the blasting effect standard as the core screening standard, and mark the sample proportion of the effect in each combined interval.

[0044] A4, for the uniaxial compressive strength, gradually increase the critical value from low to high, calculate the cumulative proportion of the samples that meet the standard under different critical values, and determine the soft-medium hard rock uniaxial compressive strength threshold value and the medium hard-hard rock uniaxial compressive strength threshold value.

[0045] For example, gradually increase the critical value from low to high, such as starting from 10MPa, increase by 5MPa each time, calculate the cumulative proportion of the blasting effect that meets the standard in all samples under each critical value; when the critical value increases to a certain value, the cumulative proportion of the standard appears a significant inflection point, such as from 60% to 80%, the critical value corresponding to the inflection point is taken as the soft-medium hard rock uniaxial compressive strength threshold value and the medium hard-hard rock uniaxial compressive strength threshold value, such as the low inflection point corresponds to the soft-medium hard threshold value, and the high inflection point corresponds to the medium hard-hard rock threshold value.

[0046] A5, for the joint fissure density, set the critical value from high to low, calculate the proportion of the samples that meet the standard in the corresponding uniaxial compressive strength interval under different critical values, and determine the soft-medium hard joint fissure density threshold value and the medium hard-hard joint fissure density threshold value.

[0047] A6. Verify the matching of rock type and blasting parameters using historical engineering cases. If the rock type determination of the vast majority of cases matches the actual blasting effect under a certain threshold, then confirm that threshold. If the deviation is large, readjust the threshold and repeat the above steps until the proportion of qualified samples corresponding to the threshold stabilizes at a high level, and finally determine the specific value of each threshold.

[0048] In a preferred embodiment of the present invention, the specific analysis method for determining the initial pore location parameter range is as follows: based on the determined rock type, extract the uniaxial compressive strength, joint and fracture density, step height and selected pore diameter value from the basic geological parameters.

[0049] Based on the pre-constructed rock type-related parameter mapping relationship, the uniaxial compressive strength, joint and fracture density, step height and selected pore diameter values ​​in the basic geological parameters are matched with the related parameter mapping relationship corresponding to each rock type to obtain the initial pore location parameter range of the blasting area.

[0050] In one specific embodiment, the relevant borehole position parameter range is determined as follows: 1. Determine the borehole depth range: Based on the step height, the over-depth ratio is set according to the rock type. For soft rock, the ratio is 10%-12% of the step height; for medium-hard rock, the ratio is 12%-14%; and for hard rock, the ratio is 14%-16%. The borehole depth range is the sum of the step height and the corresponding over-depth range.

[0051] 2. Determine the range of the chassis resistance line: Calculate the initial value according to the borehole diameter using the empirical coefficient method. For soft rock, take 25-30 times the borehole diameter; for medium-hard rock, take 30-35 times; and for hard rock, take 35-40 times. Then, combine this with the uniaxial compressive strength correction. The higher the strength, the higher the upper limit of the resistance line range will be increased by 5%-10%.

[0052] 3. Determine the range of hole spacing: Based on the range of the chassis resistance line, calculate according to the hole spacing coefficient. For soft rock, take 1.0-1.2 times the resistance line; for medium-hard rock, take 1.2-1.4 times; for hard rock, take 1.4-1.5 times. When the joint and fissure density is high, appropriately reduce the lower limit of the coefficient.

[0053] 4. Determine the spacing range: According to the hole layout method, take 0.8-1.0 times the hole spacing range when the layout is rectangular, and take 0.85-0.95 times the hole spacing range when the layout is quincunx. The lower limit of the soft rock deviation range and the upper limit of the hard rock deviation range.

[0054] It should be noted that the advantage of determining the initial hole position parameter range is that it is based on the determined rock type, accurately extracts key geological parameters such as uniaxial compressive strength and joint fracture density, and matches in combination with the pre-constructed rock type-related parameter mapping relationship. This process not only incorporates the engineering wisdom of the basic empirical formula, but also realizes precise adjustment through the dynamic association of geological parameters and mapping relationships, avoiding the limitations of traditional empirical formulas, making the initial hole position parameter range highly adaptable to actual geological conditions, providing scientific and reasonable input boundaries for subsequent parameter optimization models, and improving the pertinence and reliability of hole position parameter setting.

[0055] In a preferred embodiment of the present application, the specific construction method of the rock type-related parameter mapping relationship combination is as follows: collect historical blasting data, and select complete data corresponding to different rock types, including uniaxial compressive strength, joint fracture density, bench height, selected hole diameter value, and actual application hole position parameters.

[0056] The data of soft rock, medium-hard rock and hard rock are grouped respectively, and the association of basic geological parameters and hole position parameters in each group is sorted according to rock type.

[0057] For each rock type, the response law of hole position parameters when the basic geological parameters change is analyzed, and the mapping mode between the parameters is refined.

[0058] It should be noted that for each rock type, the response law of hole position parameters when the basic geological parameters change is analyzed. Through statistical analysis, data fitting and other methods, the mapping mode between the basic geological parameters and the hole position parameters is refined. For example, it is found that in hard rock, the higher the uniaxial compressive strength, the smaller the hole spacing and row spacing; when the bench height increases, the hole depth increases accordingly, and the bottom resistance line also adjusts.

[0059] The mapping mode of basic geological parameters and hole position parameters under each rock type is integrated to form the related parameter mapping relationship corresponding to soft rock, medium-hard rock and hard rock, respectively, and the rock type-related parameter mapping relationship combination is constructed.

[0060] It should be noted that the advantage of constructing the rock type-related parameter mapping relationship combination is that it is based on a large amount of historical blasting data, and the association of geological parameters and hole position parameters is sorted according to soft rock, medium-hard rock and hard rock, and a targeted mapping mode is refined. This combination integrates the parameter response law under different rock types, can accurately match specific geological conditions, provides a scientific basis for determining the initial hole position parameter range, avoids the limitations of single empirical formula, improves the rationality and adaptability of parameter setting, and lays a reliable foundation for subsequent optimization.

[0061] The parameter optimization model is constructed, the blasting effect data is output by simulating the blasting condition based on the initial hole position parameter range and the geological parameter data set, the pre-constructed blasting parameter coupling model is input for multi-objective optimization calculation, and multiple hole position parameter sets and corresponding comprehensive scores are output.

[0062] In a preferred embodiment of the present application, please refer to Figure 3 The specific way of performing multi-objective optimization calculation is as follows: an optimization model with fragmentation quality, safety control and economy as objective functions is constructed.

[0063] In the present application, the specific indexes corresponding to fragmentation quality, safety control and economy are large block rate, blasting vibration intensity and drilling explosive cost. The large block rate directly reflects the fragmentation effect and affects the subsequent operation efficiency; the blasting vibration intensity is a safety core index and is related to the safety of surrounding facilities; and the drilling explosive cost is a key component of economy and directly affects the engineering cost. The three cover the core objectives of blasting, are easy to quantify and the data is easy to obtain, meet the needs of multi-objective optimization, and ensure that the optimization direction is consistent with the actual engineering.

[0064] The hole spacing, row spacing and bottom plate resistance line are selected as optimization variables, and the value interval of each variable is set based on the initial hole position parameter range.

[0065] The multi-objective optimization algorithm is adopted, the objective function and variable value interval are input into the calculation model, and the Pareto optimal solution set is found by algorithm iteration.

[0066] Multiple hole position parameter sets are extracted from the Pareto optimal solution set and output.

[0067] It should be noted that the reason for performing multi-objective optimization calculation is that open pit deep hole blasting needs to consider multi-dimensional targets such as fragmentation quality, safety control and economy, and single target optimization is easy to compromise. Through multi-objective optimization, taking hole spacing as a variable, combining the initial parameter range, and using algorithm to find the Pareto optimal solution set, the hole position parameter set balancing each target can be output. This avoids the limitations of single-dimensional optimization, ensures that the parameters improve the fragmentation effect while controlling safety risks and reducing costs, realizes the maximization of comprehensive benefits, and meets the actual engineering requirements.

[0068] In a preferred embodiment of the present application, the specific calculation method of the corresponding comprehensive score is as follows: the fragmentation quality, safety control and economy parameters corresponding to each hole position parameter set are standardized to eliminate the dimensional differences.

[0069] It should be noted that the parameters corresponding to each hole site parameter set, such as the bulk rate, blasting vibration intensity and drilling explosive cost, are standardized, and the core purpose is to eliminate the dimensional differences of different parameters, so that each parameter is in the same order of magnitude, and the subsequent weighted sum calculation of the comprehensive score is facilitated. The specific processing method of the present application is: using the formula (maximum value-measured value) / (maximum value-minimum value) for normalization, ensuring the uniformity of the evaluation scale of different dimensional parameters, and avoiding the improper amplification or reduction of the weight of a parameter in the comprehensive score due to the dimensional difference.

[0070] The parameters after the standardization are weighted and summed according to the preset weight to obtain the corresponding comprehensive score.

[0071] It should be noted that the preset weight is set according to the priority of each target of the project

[0072] The final hole site parameter is determined, and the corresponding comprehensive score is simulated and screened based on the blasting effect data, and the historical blasting data corresponding to the similar geological parameters is selected based on the historical blasting data set, and the experience is selected after the simulation screening of the hole site parameter set, and the final hole site parameter set is selected.

[0073] In a preferred embodiment of the present application, the specific analysis method for simulating screening is as follows: the comprehensive score corresponding to each hole site parameter set is compared with the pre-set comprehensive score threshold to determine whether it meets the engineering requirements.

[0074] If the comprehensive score corresponding to a certain hole site parameter set is greater than or equal to the comprehensive score threshold, it is determined to meet the engineering requirements, otherwise, it is determined not to meet the engineering requirements.

[0075] It should be noted that the setting of the comprehensive score threshold mainly comes from two aspects: one is the comprehensive score distribution of the standard cases in the historical blasting data, and the comprehensive score of the hole site parameter set that meets the past effect is statistically analyzed, and the minimum value or the lower limit of the confidence interval is taken as the basic threshold; The second is the actual demand of the project, combined with the minimum standard of the project for the crushing quality, safety control and economy, the standards are converted into the corresponding comprehensive score critical value. At the same time, the threshold is verified by trial calculation to ensure that it can not only screen out the parameter set that meets the engineering requirements, but also not excessively narrow the optimization range, and finally form a comprehensive score threshold that takes into account the historical experience and actual demand.

[0076] It should be noted that the reason for simulation screening is that the candidate parameter set after experience screening still needs to verify the actual application effect. By simulating the blasting scene, the performance of the crushing quality and safety control corresponding to the parameter set can be tested in a virtual environment, and potential problems can be found in advance. This can avoid the risk of direct application to the project, further eliminate parameters that are theoretically feasible but have poor actual adaptability, and ensure that the final parameter set meets the multi-objective requirements while fitting the complex geological conditions on site, thereby improving the reliability of the blasting scheme.

[0077] In a preferred embodiment of the present application, the specific analysis process of selecting historical blasting data corresponding to similar geological parameters is as follows: extract the historical blasting data set, and obtain the geological parameter and rock type data corresponding to each historical blasting data.

[0078] Compare the geological parameter and rock type data with the geological parameter and rock type data of the current blasting area. If all the following conditions are met, it is determined that the historical blasting data is similar to the actual geological conditions of the current blasting area:

[0079] Condition 1: The rock type of the historical blasting data is consistent with the rock type of the current blasting area.

[0080] Condition 2: The relative deviation degree of each geological parameter corresponding to the historical blasting data and each geological parameter of the current blasting area is less than a preset threshold.

[0081] It should be noted that the rock type of the historical data is completely consistent with the rock type of the current area, ensuring that both belong to the same category in terms of overall hardness and structural characteristics. The geological parameter deviation threshold: the numerical deviation of each key geological parameter is within the preset threshold range, ensuring that the quantitative difference of the specific parameter is within the acceptable similarity range of the project. By simultaneously satisfying the type consistency and parameter deviation control, it can be ensured that the geological conditions reflected by the historical blasting data have high similarity with the current area, and the corresponding hole position parameters and blasting effect have reference value for the current project, providing a reliable basis for subsequent experience screening of hole position parameters.

[0082] In a preferred embodiment of the present application, the specific process of experience screening is as follows: selecting historical blasting data with abnormal blasting effect from historical blasting data corresponding to similar geological parameters.

[0083] Perform similarity analysis on each hole position parameter set after simulation screening and the hole position parameter set corresponding to the historical blasting data with abnormal blasting effect.

[0084] It should be noted that the process is to compare the hole site parameter set reserved after simulation screening with the hole site parameter set with abnormal effect in historical blasting, such as oversize rate exceeding the standard, vibration exceeding the limit, and analyze the similarity of the two. Specifically, the numerical deviation of key indicators in the parameter set, such as hole depth, hole diameter, hole spacing, charge weight, etc. is calculated, combined with the matching degree of geological parameters, to determine the similarity of the parameter set. If the parameter set after simulation screening is highly similar to the abnormal historical parameter set, it means that there is a potential risk, which needs to be further evaluated or eliminated, so as to avoid repeating historical mistakes and improve the safety and reliability of the final hole site parameter set.

[0085] If the similarity analysis result is greater than the preset threshold, the hole site parameter set is eliminated, and the hole site parameter set that meets the similarity analysis result comparison condition is reserved.

[0086] The hole site parameter set that meets the similarity analysis result comparison condition is sorted according to the comprehensive score, and the hole site parameter set corresponding to the maximum comprehensive score is selected as the final hole site parameter set.

[0087] It should be noted that the reason for experience screening is that multi-objective optimization calculation can provide a theoretical optimal solution, but there may be a situation of insufficient adaptability to actual engineering scenarios. The hole site parameters similar to the current regional geological conditions in the historical blasting data are more suitable for the field conditions after actual verification. By screening high-score experience parameter sets and combining with the optimization solution set, the historical engineering practice experience and algorithm optimization results can be combined to make up for the limitations of pure theoretical optimization, further improve the reliability and applicability of the candidate parameter set, and ensure that the final hole site parameters meet the actual needs of open deep hole blasting.

[0088] The above content is only an example and description of the concept of the present application. Those skilled in the art can make various modifications or supplements to the described specific embodiments or use similar ways to replace them, as long as they do not deviate from the concept of the present application or exceed the scope defined by the present application. They should belong to the protection scope of the present application.

Claims

1. A hole site parameter optimization analysis method based on open deep hole blasting, characterized in that, The method comprises the following steps: Basic geological parameter acquisition, using a geological parameter detection device to obtain the geological parameters of the blasting area, including basic physical property parameters, integrity parameters and step characteristic parameters, to construct a geological parameter dataset; Initial hole position parameter setting, according to the geological parameter dataset, the rock type of the blasting area is calibrated, including soft rock, medium-hard rock and hard rock, and the initial hole position parameter range is determined based on the basic empirical formula combined with the rock type; Parameter optimization model construction, based on the initial hole position parameter range and the geological parameter dataset, the blasting situation is simulated by using numerical software to output blasting effect data, and the pre-constructed blasting parameter coupling model is input for multi-objective optimization calculation, and a plurality of hole position parameter sets and corresponding comprehensive scores are output; Final hole position parameter determination, based on the blasting effect data and the corresponding comprehensive score, the simulation screening is carried out, the historical blasting data corresponding to the similar geological parameters are selected based on the historical blasting data set, and the experience screening is carried out on the hole position parameter set after the simulation screening, and the final hole position parameter set is selected.

2. The hole site parameter optimization analysis method based on open deep hole blasting according to claim 1, characterized in that: The specific analysis method for calibrating the rock type of the blasting area is as follows: Based on the uniaxial compressive strength and joint fracture density of the rock in the geological parameter dataset, the rock type of the blasting area is identified; Based on the pre-constructed soft-medium-hard rock uniaxial compressive strength threshold and medium-hard-hard rock uniaxial compressive strength threshold, the first rock type tendency identification is carried out; Based on the pre-constructed soft-medium-hard joint fracture density threshold and medium-hard-hard joint fracture density threshold, the second rock type tendency identification is carried out; When the first rock type and the second rock type are consistent, the rock type is taken as the rock type of the blasting area; When the first rock type and the second rock type are inconsistent, the relative deviation degree analysis is carried out on the uniaxial compressive strength and joint fracture density respectively and the corresponding threshold value, and the rock type corresponding to the minimum relative deviation degree is taken as the rock type of the blasting area.

3. The hole site parameter optimization analysis method based on open deep hole blasting according to claim 2, characterized in that: The specific construction method of the soft-medium-hard rock uniaxial compressive strength threshold, the medium-hard-hard rock uniaxial compressive strength threshold, the soft-medium-hard joint fracture density threshold and the medium-hard-hard joint fracture density threshold is as follows: A1, collect historical experimental data, cover rock samples in different geological areas, extract the uniaxial compressive strength, joint fracture density and corresponding blasting effect data of each sample; A2, group the data, divide several combined intervals according to the numerical range of the uniaxial compressive strength and the joint fracture density, and calculate the average value of the blasting effect in each interval; A3, taking the blasting effect reaching the standard as the core screening standard, mark the proportion of the samples reaching the standard in each combined interval; A4, for the uniaxial compressive strength, gradually increase the critical value from low to high, calculate the cumulative proportion of the samples reaching the standard under different critical values, and determine the soft-medium-hard rock uniaxial compressive strength threshold and the medium-hard-hard rock uniaxial compressive strength threshold; A5, for the joint fracture density, set the critical value from high to low, calculate the proportion of the samples reaching the standard in the corresponding uniaxial compressive strength interval under different critical values, and determine the soft-medium-hard joint fracture density threshold and the medium-hard-hard joint fracture density threshold. A6. Verify the matching cases of rock type and blasting parameters in historical projects. If the rock type determination of the vast majority of cases matches the actual blasting effect under a certain threshold, then confirm the boundary threshold. If the deviation is large, readjust the boundary threshold and repeat the above steps until the proportion of qualified samples corresponding to the boundary threshold stabilizes at a high level, and finally determine the specific value of each boundary threshold.

4. The hole site parameter optimization analysis method based on open deep hole blasting according to claim 1, characterized in that: The specific analysis method for determining the initial borehole position parameter range is as follows: Based on the identified rock type, extract the uniaxial compressive strength, joint and fracture density, step height, and selected pore size from the basic geological parameters; Based on the pre-constructed rock type-related parameter mapping relationship, the uniaxial compressive strength, joint and fracture density, step height and selected pore diameter values ​​in the basic geological parameters are matched with the related parameter mapping relationship corresponding to each rock type to obtain the initial pore location parameter range of the blasting area.

5. The hole site parameter optimization analysis method based on open deep hole blasting according to claim 4, characterized in that: The specific construction method of the rock type-related parameter mapping relationship combination: Collect historical blasting data, filter out complete data corresponding to different rock types, including uniaxial compressive strength, joint and fracture density, step height, selected hole diameter value, and hole position parameters for actual application; The data for soft rock, medium-hard rock, and hard rock were grouped separately, and the relationship between basic geological parameters and pore location parameters in each group was analyzed based on rock type. For each rock type, the response law of pore location parameters to changes in basic geological parameters is analyzed, and the mapping pattern between parameters is extracted. The mapping patterns of basic geological parameters and pore location parameters under each rock type are integrated to form the relevant parameter mapping relationships for soft rock, medium-hard rock, and hard rock, respectively, thus constructing a combination of rock type-related parameter mapping relationships.

6. The hole site parameter optimization analysis method based on open deep hole blasting according to claim 1, characterized in that: The specific method for performing multi-objective optimization calculations is as follows: An optimization model is constructed with crushing quality, safety control, and economy as objective functions; Hole spacing, row spacing, and chassis resistance line are selected as optimization variables, and the value range of each variable is set based on the initial hole position parameter range. A multi-objective optimization algorithm is adopted, in which the objective function and the range of variable values ​​are input into the computational model, and the Pareto optimal solution set is found through algorithm iteration; Multiple sets of pore location parameters are extracted and output from the Pareto optimal solution set.

7. The hole site parameter optimization analysis method based on open deep hole blasting according to claim 6, characterized in that: The specific calculation method for the corresponding comprehensive score is as follows: The parameters corresponding to each orifice parameter set, such as crushing quality, safety control, and economy, are standardized to eliminate dimensional differences. The standardized parameters are weighted and summed according to preset weights to obtain the corresponding comprehensive score.

8. The hole site parameter optimization analysis method based on open deep hole blasting according to claim 7, characterized in that: The specific analysis method for conducting simulated screening is as follows: The comprehensive score corresponding to each hole position parameter set is compared with the pre-set comprehensive score threshold to determine whether it meets the engineering requirements. If the comprehensive score corresponding to a certain set of parameters for a hole position is greater than or equal to the comprehensive score threshold, it is determined to meet the engineering requirements; otherwise, it is determined not to meet the engineering requirements.

9. The hole site parameter optimization analysis method based on open deep hole blasting according to claim 1, characterized in that: The specific analysis process for selecting historical blasting data corresponding to similar geological parameters is as follows: Extract historical blasting datasets to obtain the geological parameters and rock type data for each historical blasting data; The geological parameter and rock type data are compared with the geological parameter and rock type data of the current blasting area, and if all the following conditions are met, it is determined that the historical blasting data is similar to the actual geological conditions of the current blasting area: Condition 1: The rock type of the historical blasting data is consistent with the rock type of the current blasting area; Condition 2: The relative deviation degree of each geological parameter corresponding to the historical blasting data and each geological parameter of the current blasting area is less than a preset threshold.

10. The hole site parameter optimization analysis method based on open deep hole blasting according to claim 9, characterized in that: The specific process of the experience screening is as follows: From the historical blasting data corresponding to the similar geological parameters, the historical blasting data with abnormal blasting effect is screened out; The similarity analysis is performed on the hole position parameter set after the simulation screening and the hole position parameter set corresponding to the historical blasting data with abnormal blasting effect; If the similarity analysis result is greater than a preset threshold, the hole position parameter set is excluded, and the hole position parameter set that meets the similarity analysis result comparison condition is retained; The hole position parameter set that meets the similarity analysis result comparison condition is sorted according to the comprehensive score, and the hole position parameter set corresponding to the maximum comprehensive score is selected as the final hole position parameter set.

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