BIM-based open bench blasting hole fine charging design optimization method

Abstract

The invention provides a BIM-based open bench blasting blast hole fine charging design optimization method, and relates to the technical field of electric digital data processing, and the method comprises the following steps: collecting related characteristic parameters of a blasting project; establishing a blasting wave and range mathematical model, and outputting a blasting wave and coefficient corresponding to the current initial explosive charge; acquiring the upper limit of the shock resistance margin of the explosive, collecting the average distance between adjacent blasting holes, and calculating the blasting coherence index by combining the blasting sweep efficiency; and setting a coherence threshold value, and comparing the blasting coherence index with the set coherence threshold value. According to the method, the blasting interference risk between the adjacent blast holes is quantitatively evaluated by introducing the blasting coherence index, and the problem of explosive load design deviation caused by the fact that a conventional scheme only depends on an empirical formula or static parameters is solved; and a closed-loop feedback optimization algorithm is adopted to automatically adjust the explosive load until a coherence threshold value is met, collaborative operation guarantee of the blasting sequence is realized, and the blasting safety and the resource utilization efficiency are remarkably improved.

Description

BIM-based optimization method for fine charge design of open-pit bench blasting boreholes Technical Field

[0001] This invention relates to the field of electronic digital data processing technology, specifically to a BIM-based method for optimizing the design of fine-scale explosive charges for open-pit bench blasting boreholes. Background Technology

[0002] In open-pit bench blasting, the sequential blasting of multiple blast holes after being charged in one go, based on Building Information Modeling (BIM) technology, can significantly improve operational efficiency and fragmentation effect. It avoids the time cost of repeated hole layout and segmented detonation, and optimizes the uniformity of rock fragmentation through the stress wave superposition effect. However, if the influence of the first blast hole on adjacent holes is ignored, the blast shock wave may prematurely detonate the undetonated charge, resulting in the risk of sympathetic detonation, or damage the charge structure of adjacent holes, leading to failure accidents such as misfires and blasting deviation. At the same time, excessive impact energy can cause safety hazards such as flyrock and excessive vibration. Therefore, accurate prediction and suppression of blasting interference is the core prerequisite for ensuring the safe, efficient and coordinated operation of the entire blasting sequence.

[0003] In the prior art, CN120297751A discloses a method and system for early warning of safety risks of explosive charging in open-pit goaf areas based on BIM. This technology includes: acquiring geological data, borehole parameter data, and historical blasting data of the open-pit goaf area, and constructing a three-dimensional BIM geological model containing rock hardness data, joint density, and fracture distribution data through UAV scanning and core sampling; determining the minimum effective charge amount that meets the preset average fragmentation size in the three-dimensional BIM geological model; obtaining simulation results through dynamic simulation of the three-dimensional BIM geological model; and outputting the final charge amount when the simulation results meet the preset safety constraints; generating charge parameters based on the final charge amount and binding them to the spatial coordinates of the three-dimensional BIM geological model. The above-mentioned existing solution effectively reduces the safety risks of explosive charging while ensuring the blasting effect by determining the optimal charge amount and optimizing the layout of blasting holes and the detonation sequence.

[0004] However, the aforementioned existing technologies rely on static empirical formulas or preset historical data to determine the charge amount, which cannot dynamically integrate complex parameters such as rock porosity, hardness, and humidity to accurately predict the blast wave range. This results in large calculation deviations and an inability to quantify the interference risk of adjacent blast holes, which can easily cause safety accidents such as flyrock and vibration or blasting sequence failure. At the same time, the charge amount design is too conservative or excessive, which wastes explosive resources and makes it difficult to balance safety and efficiency. Furthermore, due to the lack of a closed-loop iterative optimization process, the fixed charge amount cannot adapt to complex working conditions, resulting in low overall safety and resource utilization efficiency.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide a BIM-based optimization method for the precise charge design of open-pit bench blasting boreholes, addressing the problems mentioned in the background section. This invention introduces a blasting continuity index to quantitatively assess the risk of blasting interference between adjacent boreholes, solving the problem of charge quantity design deviations caused by conventional methods relying solely on empirical formulas or static parameters. Furthermore, it employs a closed-loop feedback optimization algorithm to automatically adjust the charge quantity until a continuity threshold is met, achieving coordinated operation assurance for the blasting sequence. This system-level optimization effect is unattainable in conventional precise charge design for independent boreholes, significantly improving blasting safety and resource utilization efficiency.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] The BIM-based method for optimizing the design of fine-charge charges for open-pit bench blasting boreholes includes the following steps:

[0009] S1: Collect relevant characteristic parameters of the blasting project, including: the initial charge amount to be set in the blasting borehole, rock hardness coefficient, rock porosity ratio, and ambient air humidity in the blasting environment;

[0010] S2: Establish a mathematical model of the blast wave range. The mathematical model of the blast wave range adopts a neural network convolutional structure and includes an input layer, a processing layer and an output layer. The relevant feature parameters are input into the input layer of the mathematical model of the blast wave range. After the processing layer calculates, the blast wave coefficient corresponding to the current initial charge is output through the output layer.

[0011] S3: Collect the peak range of impact energy in the planned blasting operation environment of the explosive to be used, adjust the basic impact detonation threshold according to the correction coefficient corresponding to the operation environment, perform up and down fluctuation calibration based on the impact tolerance extreme value of the explosive to be used, obtain the maximum external impact energy value that the explosive to be used can withstand in the current operation scenario, and set it as the upper limit of the explosive's impact resistance margin, and at the same time collect the average distance between adjacent blasting holes, and calculate the blasting continuity index by combining it with the blasting sweep coefficient output in S2;

[0012] S4: Set a continuity threshold, compare the blasting continuity index with the set continuity threshold. If the continuity index is less than the continuity threshold, reduce the initial charge in each blasting hole by a fixed gradient. Repeat S2~S4 and perform the comparison process between the blasting continuity index and the continuity threshold until the blasting continuity index is not less than the continuity threshold.

[0013] Furthermore, the initial charge amount to be set in the blasting borehole in S1 is preset based on historical blasting data and adjusted according to the on-site blasting requirements; the rock hardness coefficient is obtained based on the rock mechanics test results in the geological exploration report.

[0014] The porosity ratio of the rock mass is calculated by collecting geological structure model data and then calculating the volume ratio of voids inside the rock based on the geological structure model data; the air humidity of the blasting environment is extracted from a meteorological database established in the field area, and each of the relevant characteristic parameters is verified through a standardized data acquisition process.

[0015] Furthermore, the initial charge quantity is preset based on historical blasting data through the following process: calling up complete database records of the same historical blasting projects, including drilling depth, hole diameter, rock type, and blasting effect indicators; establishing a statistical correlation model based on historical parameters to identify the optimal charge quantity range under the current rock hardness and porosity conditions; predicting the suitable initial value for the current scenario through machine learning algorithms; and simultaneously verifying the rationality of the preset value and calibrating the data trend based on engineering experience.

[0016] Furthermore, the blast sweep efficiency corresponding to the initial charge amount is calculated using the following formula:

[0017]

[0018] in:

[0019] This refers to the blast wave sweep coefficient;

[0020] This is the initial charge amount;

[0021] This represents the proportion of rock mass porosity.

[0022] This refers to the rock mass hardness coefficient.

[0023] Humidity of the air in the blasting environment;

[0024] The influence of humidity is weighted; It is a proportionality constant;

[0025] Explosion wave coefficient Used to reflect the relative blast radius, and the blast radius coefficient. The larger the value, the wider the range; the proportion of rock mass porosity The range of values ​​is The proportionality constant The proportionality constant is obtained by fitting data from field blasting tests or historical data. The typical initial value is set to 1.0.

[0026] Furthermore, the proportionality constant The acquisition process is achieved through the following data-driven workflow: Based on measured data from historical blasting projects or small-scale on-site test blasts, the system collects the actual blast wave range and relevant characteristic parameters under corresponding working conditions, and uses the following inverse formula to calculate the temporary proportional constant. The value:

[0027]

[0028] Statistical fitting of multiple sets of back-calculated values ​​was performed using the least squares method. After removing outliers, the mean was calculated as the initial value. Constraint verification was then performed using the maximum permissible impact range boundary conditions required by engineering safety specifications. Finally, a proportional constant that balances accuracy and safety was determined through iterative optimization. And the proportionality constant The values ​​are continuously updated and maintained as new blasting case data is added.

[0029] Furthermore, in S3, during the process of collecting the peak impact energy range of the blasting operation environment in which the explosives are planned to be used, historical blasting vibration monitoring data and current geological structural characteristics are integrated. The geological structural characteristics include rock layer dip angle, joint density and groundwater conditions. A dynamic peak distribution model is constructed by establishing the energy propagation attenuation law.

[0030] The basic impact detonation threshold is determined based on the standard laboratory test values ​​in the explosive technical parameter library and is weighted and adjusted in combination with the operation environment correction coefficient, which includes the terrain undulation index, rock mass wave impedance difference and overburden thickness spatial variable.

[0031] Based on the extreme impact tolerance of the explosive used, a material sensitivity factor and a confidence interval fluctuation range are introduced, with the confidence interval fluctuation range set at ±10%~15%. Finally, the maximum external impact energy value that the explosive can withstand under the current scenario is output. This value is officially set as the upper limit of the explosive's impact resistance margin after safety redundancy verification.

[0032] Furthermore, the formula for calculating the blasting continuity index is as follows:

[0033]

[0034] in:

[0035] This is the blasting continuity index, and its value ranges from positive. Explosion continuity index The larger the value, the higher the anti-interference capability of adjacent blast holes;

[0036] This represents the upper limit of the explosive's impact resistance margin, indicating the maximum external impact energy that the explosive can withstand in the current operating scenario;

[0037] The average spacing between adjacent blasting holes;

[0038] The average spacing between adjacent blasting holes This represents the average distance between adjacent blast holes in a blasting sequence.

[0039] Furthermore, the average spacing between adjacent blasting holes The acquisition process is achieved through the following data integration process: Based on the drilling construction records and three-dimensional spatial coordinate dataset of the blasting area, the measured values ​​of the center point spacing of all adjacent borehole pairs are extracted, and cross-validation is performed in combination with the theoretical borehole grid layout data in the blasting design drawings to eliminate abnormal points caused by positioning errors or construction offsets.

[0040] Subsequently, local mean values ​​were calculated for all effective spacing values ​​in groups. Then, a weighted average method was used to integrate the actual influence coefficients of topographic relief and rock mass structure continuity on the spacing, and finally, a uniform average spacing of blasting boreholes across the entire region was output. .

[0041] Furthermore, a coherence threshold is set as follows: When the calculated blasting continuity index is obtained Then according to:

[0042]

[0043] Reduce the initial charge amount of all blasting holes. ,in, This serves as the baseline for the first iteration of the charge amount. The dosage is gradient, and the current iteration number n is recorded, limiting the maximum number of iterations. This is used to prevent over-optimization.

[0044] Re-enter the dosage each time it is updated. The updated blast wave sweep coefficient is simultaneously obtained from the mathematical model of the blast wave range of S2. .

[0045] Furthermore, based on the updated charge quantity... Combined with the upper limit of the explosive shock resistance margin of S3 and the average spacing between adjacent blasting holes Calculate the new coherence index The cycle continues until End at time;

[0046] The newly obtained coherence index Set as final charge amount Output the final charge amount and the corresponding final charge amount .

[0047] Compared with the prior art, the beneficial effects of the present invention are:

[0048] This invention introduces a blasting coherence index to quantitatively assess the risk of blasting interference between adjacent boreholes. It utilizes a neural network model to accurately fuse multi-dimensional parameters such as rock porosity, hardness, and moisture content to predict the blasting wave range in real time, solving the problem of charge design deviations caused by conventional schemes relying solely on empirical formulas or static parameters. Secondly, through a dynamic calibration mechanism of the upper limit of explosive shock resistance margin, the charge amount is precisely controlled to a safe critical point, avoiding both the flyrock, vibration hazards, and explosive waste caused by traditional overcharging, and overcoming the insufficient blasting effect caused by conservative design in conventional schemes. Finally, a closed-loop feedback optimization algorithm is used to automatically adjust the charge amount until the coherence threshold is met, achieving collaborative operation assurance for the blasting sequence. This is a system-level optimization effect that conventional independent borehole design cannot achieve, significantly improving blasting safety and resource utilization efficiency. Attached Figure Description

[0049] Figure 1 is a flowchart illustrating the optimization method for fine charge design of open-pit bench blasting boreholes based on BIM according to the present invention. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0051] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0052] Example:

[0053] Please refer to Figure 1. The present invention provides the following technical solution:

[0054] The BIM-based method for optimizing the design of fine-charge charges for open-pit bench blasting boreholes includes the following steps:

[0055] S1: Collect relevant characteristic parameters of the blasting project, including: the initial charge amount to be set in the blasting borehole, rock hardness coefficient, rock porosity ratio, and ambient air humidity in the blasting environment;

[0056] The initial charge quantity to be set in the blasting borehole is primarily preset using historical blasting data. This historical data comes from complete records of similar previous blasting projects, including information on borehole depth, borehole diameter, rock type, and actual blasting effects. During the preset process, the system establishes a statistical analysis model based on historical data and dynamically adjusts it according to the specific blasting requirements on site. The rock hardness coefficient is obtained based on a detailed geological exploration report, which includes test results of rock mechanical properties such as compressive strength and elastic modulus. This data, after professional analysis, can be directly used to calculate the hardness coefficient.

[0057] The calculation of rock mass porosity ratio requires the acquisition of high-precision geological structure model data. This model clearly reflects the internal structure of the rock strata, and the ratio of internal void volume to total volume is calculated based on the model data, thus providing important rock mass physical parameters for blasting design. Air humidity data for the blasting environment is extracted from a dedicated meteorological database established for the site area. This database continuously monitors and records various meteorological indicators such as temperature, humidity, and wind speed in the blasting operation area, providing real-time or near-real-time environmental parameters. Each of the above-mentioned relevant characteristic parameters undergoes a standardized data verification process after acquisition, including data integrity checks, outlier screening, and calibration against actual conditions to ensure the reliability and validity of all input data.

[0058] The initial charge quantity is preset using historical blasting data. The system retrieves complete database records from previous similar blasting projects. This database is typically accumulated and structured over a long period to ensure data integrity and comparability. Each record in the database contains multiple key parameters, including, in this implementation, the specific depth and diameter of the borehole, the rock type classification of the work area, and various indicators for evaluating the post-blasting effect, such as rock fragmentation, throwing distance, and vibration intensity.

[0059] Based on these historical parameters, a statistical correlation model is further established to analyze the influence of different geological and charge conditions on blasting effectiveness. The model identifies the optimal charge range that balances blasting efficiency and safety under specific rock hardness and porosity conditions. Based on this, regression analysis or machine learning algorithms can be used to predict the current blasting scenario and generate a suitable initial charge value. These algorithms can handle nonlinear relationships between multiple variables, thereby improving the accuracy and adaptability of the prediction.

[0060] After the prediction is completed, the rationality of the preset charge quantity is verified by combining long-term engineering practice experience in the field. Engineers comprehensively evaluate and adjust the predicted values ​​based on successful blasting cases under similar geological conditions, intuitive judgment of the on-site rock mass structure, and safety regulations. Finally, by comparing the changing trends of recent blasting data, the preset values ​​are dynamically calibrated to ensure that they conform to the theoretical model while also reflecting the continuous changes in the actual engineering environment, thus providing an initial benchmark for subsequent optimization of the refined charge design.

[0061] S2: When establishing the mathematical model of the blast wave and its range, a neural network convolutional structure with strong feature extraction and nonlinear fitting capabilities was adopted. The model consists of three main parts: an input layer, a processing layer, and an output layer, forming an end-to-end computational framework. In the input layer, the system normalizes and vectorizes the relevant feature parameters collected in the preceding steps—such as initial charge amount, rock hardness coefficient, porosity ratio, and ambient humidity—converting them into standardized input data that the model can recognize.

[0062] The processing layer consists of multiple convolutional layers, activation functions, and possible pooling layers. It progressively uncovers the intrinsic correlations and spatial dependencies between input features and simulates the propagation and attenuation of blast energy within the rock mass through weight adjustments. This layer ultimately transmits the processed information to the output layer, which typically comprises one or more fully connected layers. The output layer maps high-level features to a specific numerical value: the blast sweep efficiency corresponding to the current initial charge. This efficiency quantifies the expected impact range of the explosion on the surrounding rock mass under given geological and charge conditions. During the training phase, the entire model utilizes supervised learning based on historical blasting case data, iteratively optimizing network parameters to ensure its output more closely reflects the blast sweep efficiency phenomena observed in actual engineering projects.

[0063] The blast wave effect coefficient corresponding to the initial charge amount is calculated using the following formula:

[0064]

[0065] in:

[0066] This refers to the blast wave sweep coefficient;

[0067] The initial charge amount and the blast sweep efficiency. Proportional. Increasing the explosive charge directly increases the explosion energy and expands the shock wave propagation radius;

[0068] The ratio of rock mass porosity to blast sweep efficiency. It is directly proportional. High-porosity rocks are more easily broken, reducing energy absorption and promoting shock wave diffusion. Increased porosity makes rocks looser and expands their range.

[0069] The rock mass hardness coefficient is related to the blast sweep efficiency. Inversely proportional. The higher the hardness, the greater the compressive strength of the rock, which hinders the propagation of shock waves. For example, the blast radius of hard granite is significantly smaller than that of soft sandstone.

[0070] The ambient air humidity during blasting is used as an adjustment factor to influence the BPC (Blast Cube). Increased humidity slightly increases air density, reducing energy loss. A humid environment can enhance shock wave transmission, but the effect is limited; therefore, the weighting is determined by influencing humidity. Weakening effect when When the value is close to zero, the effect is negligible;

[0071] The influence of humidity is weighted; It is a proportionality constant;

[0072] Explosion wave coefficient Used to reflect the relative blast radius, and the blast radius coefficient. The larger the value, the wider the range; the proportion of rock mass porosity The range of values ​​is The proportionality constant The values ​​are obtained from on-site blasting tests or historical data fitting, with a typical initial value set to 1.0.

[0073] The process of obtaining the proportionality constant k involves utilizing existing blasting practice data, including complete records of historical blasting projects or measured data collected from small-scale test blasts conducted specifically at the current site. The system systematically collects the observed blast wave range from these cases and simultaneously extracts all corresponding operational characteristic parameters, such as the charge quantity used in the blast, rock mass characteristics, and environmental conditions, ensuring the matching and completeness of the data pairs.

[0074] Based on this, a provisional proportionality constant k is numerically calculated for each valid data case using a reverse calculation formula. This step essentially uses actual results to calibrate key parameters in the model. To improve the reliability and representativeness of the obtained k value, multiple sets of measured data under different working conditions are collected and processed, and the distribution pattern of the k value is analyzed to provide sufficient statistical basis for its final determination. This allows the proportionality constant k to more accurately reflect the localized characteristics of explosion energy propagation under specific mining area or rock strata conditions.

[0075]

[0076] After obtaining multiple sets of temporary proportionality constant k values ​​derived from the back-calculation, the data are first statistically fitted using the least squares method. This method aims to find an optimal benchmark k value that minimizes the overall deviation between the benchmark and the data points, thereby statistically reducing the impact of random errors. During the fitting process, the system performs preliminary screening of all back-calculated values, using standard deviation analysis or clustering methods to identify and remove outlier data points that significantly deviate from the main distribution. These outliers originate from measurement errors, recording mistakes, or extreme operating conditions.

[0077] After cleaning, the arithmetic mean of the remaining valid data is used as the initial value of the proportionality constant k. This initial value also needs to be verified by engineering safety specifications, that is, by substituting it into the model to check whether the calculated theoretical range always meets the safety limit requirements under the preset maximum allowable blast wave range boundary conditions.

[0078] In the iterative optimization phase, the k value is adjusted multiple times, and the model's predictions are compared with actual observation data. This parameter is gradually fine-tuned until it achieves the optimal balance between prediction accuracy and engineering safety. The final determined k value is not fixed but is continuously updated with newly added blasting case data as subsequent blasting projects are carried out, and is periodically or triggered for refitting and updating. This dynamic maintenance mechanism allows the proportionality constant k to continuously adapt to changes in geological conditions, explosive properties, and construction techniques, maintaining the model's accuracy and applicability in the long term.

[0079] S3: Collect the peak impact energy range of the planned blasting operation environment for the explosives used. This range is determined by analyzing historical blasting vibration monitoring data and combining it with the specific characteristics of the current geological structure. When obtaining the basic impact initiation threshold, it is necessary to dynamically adjust the data based on the technical parameters of the explosives themselves and the corresponding correction coefficients for the operation environment. These correction coefficients cover actual spatial variables such as terrain undulations, differences in rock mass wave impedance, and overburden thickness.

[0080] Furthermore, based on the extreme impact tolerance value of the explosive used, a material sensitivity factor and a certain confidence interval fluctuation range are introduced to calibrate this extreme value both upwards and downwards, thereby obtaining a tolerance range that is closer to the actual working conditions. Finally, the maximum external impact energy value that the explosive can safely withstand under the current operating scenario is determined from this value. This value needs to be set as the upper limit of the explosive's impact resistance margin after passing a safety redundancy check.

[0081] The average spacing between adjacent blasting holes was collected. This spacing data was derived from the drilling records and precise three-dimensional coordinate information of the blasting area. The upper limit of the explosive impact resistance margin and the average spacing between adjacent blasting holes obtained above were combined with the blast sweep efficiency output in the second stage, and a specific calculation model was used to solve for the blasting coherence index. This index is used to quantitatively assess whether harmful interference will occur between successively detonated explosive charges under the current charge and layout scheme, thus providing a key criterion for subsequent charge optimization.

[0082] During the process of collecting the peak impact energy range of the blasting operation environment for the explosives to be used, historical blasting vibration monitoring data and current geological structural characteristics are integrated, including rock layer dip angle, joint density and groundwater conditions. A dynamic peak distribution model is constructed by establishing the energy propagation and attenuation law.

[0083] The basic impact detonation threshold is determined based on the standard laboratory test values ​​in the explosive technical parameter library and is weighted and adjusted in combination with the operation environment correction coefficient, which includes spatial variables such as terrain undulation index, rock mass wave impedance difference and overburden thickness.

[0084] Based on the extreme impact tolerance of the explosive used, a material sensitivity factor and a confidence interval fluctuation range are introduced, with the confidence interval fluctuation range set at ±10%~15%. Finally, the maximum external impact energy value that the explosive can withstand under the current scenario is output. This value is officially set as the upper limit of the explosive's impact resistance margin after safety redundancy verification.

[0085] The formula for calculating the blasting continuity index is as follows:

[0086]

[0087] in:

[0088] This is the blasting continuity index, and its value ranges from positive. Explosion continuity index The larger the value, the higher the anti-interference capability of adjacent blast holes;

[0089] The upper limit of the impact margin of an explosive is used to represent the maximum external impact energy that an explosive can withstand in the current operating scenario. With Explosion Continuity Index Proportional to the upper limit of the explosive's impact resistance margin The larger the explosive charge, the stronger its ability to resist external impacts (such as the energy generated by explosions in adjacent holes), reducing the risk of accidental premature detonation and thus increasing the probability of continuous detonation. For example, within the same blast radius, high explosive charges have a higher upper limit of impact resistance margin. Provides a greater safety buffer;

[0090] The average spacing between adjacent blasting holes, and the blasting continuity index. It is directly proportional. As the spacing increases, the explosive impact energy decreases with distance, significantly reducing interference to adjacent holes. For example, when the average spacing between adjacent blasting holes increases... When the energy is doubled, the impact energy drops to about 1 / 4, significantly reducing the probability of accidental detonation;

[0091] The average spacing between adjacent blasting holes This represents the average distance between adjacent blast holes in a blasting sequence.

[0092] Average spacing between adjacent blast holes The data acquisition process is achieved through the following data integration workflow: Based on the drilling construction records and three-dimensional spatial coordinate dataset of the blasting area, the construction records contain the actual borehole opening and bottom position information of each borehole, while the three-dimensional coordinate dataset provides the precise spatial positioning of the borehole center point. Based on this data, the system automatically extracts all adjacent borehole pairs in the blasting sequence and calculates the straight-line distance between their center points, thereby obtaining a series of measured spacing values. The measured spacing values ​​of the center points of all adjacent borehole pairs are extracted, and these measured data are cross-validated and compared with the theoretical borehole grid layout in the blasting design drawings. The system identifies and evaluates the deviation between the actual and designed borehole positions caused by positioning errors of construction machinery, local changes in rock strata, or operational deviations. Through comparative analysis, abnormal spacing points with excessive deviations and obvious non-compliance with design logic are screened and eliminated.

[0093] After obtaining the set of effective spacing values ​​after cleaning, the entire area is divided into several sub-blocks, and the local mean of the effective spacing values ​​within each sub-block is calculated. Then, a weighted average method is used to synthesize these local means. Two key factors are considered during weighting: first, the degree of terrain undulation, for example, in areas with steep slopes, the borehole spacing may undergo systematic changes due to construction difficulty; second, the continuity of the rock mass structure, in areas with well-developed joints and fractures or broken rock strata, the spacing design may need special adjustments to control the blasting effect. Appropriate weight coefficients are assigned to these factors, and finally, an average borehole spacing D that represents the overall situation of the entire area and incorporates actual engineering constraints is calculated and output. This spacing value is an important geometric input parameter for subsequent blasting continuity assessment and charge optimization.

[0094] S4: Set a continuity threshold, compare the blasting continuity index with the set continuity threshold. If the continuity index is less than the continuity threshold, reduce the initial charge in each blasting hole by a fixed gradient. Repeat S2~S4 and perform the comparison process between the blasting continuity index and the continuity threshold until the blasting continuity index is not less than the continuity threshold.

[0095] Set the coherence threshold to When the calculated blasting continuity index is obtained Then according to:

[0096]

[0097] Reduce the initial charge amount of all blasting holes. ,in, The initial charge quantity serves as the baseline for the first iteration, while simultaneously recording the current iteration number n, limiting the maximum number of iterations. This is used to prevent over-optimization.

[0098] Each time the charge quantity is updated, the system will recalculate the charge quantity value, which is the new charge quantity. New drug quantity Subtract the preset gradient dosage from the current dosage. Re-enter The updated blast wave sweep coefficient is simultaneously obtained from the mathematical model of the blast wave range of S2. This coefficient reflects the expected range of impact of the explosion energy on the surrounding rock mass under the current reduced charge conditions.

[0099] Based on the updated charge quantity Combined with the upper limit of the explosive shock resistance margin of S3 and the average spacing between adjacent blasting holes Following the established calculation formula, a new round of coherence index calculation is performed to obtain the new coherence index. The cycle continues until The calculation process essentially involves reassessing the risk level of interference between sequentially detonated explosive charges after reducing the energy of a single-hole explosion.

[0100] When the iteration terminates, the system will perform a final calculation of the new coherence index. Set as final charge amount Output two key results corresponding to this final state: first, the final charge quantity corresponding to the final charge scheme determined after multiple rounds of optimization. Secondly, the final blast sweep efficiency calculated under this charge amount. ;

[0101] These two output parameters together constitute the optimized solution for fine charge design, ensuring that harmful interference between successive blasting holes is effectively eliminated while meeting the requirements for blasting effect.

[0102] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0103] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0104] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0105] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A BIM-based method for optimizing the design of fine-charge charges for open-pit bench blasting boreholes, characterized in that, Includes the following steps: S1: Collect relevant characteristic parameters of the blasting project, including: the initial charge amount to be set in the blasting borehole, rock hardness coefficient, rock porosity ratio, and ambient air humidity in the blasting environment; S2: Establish a mathematical model of the blasting sweep range. The mathematical model of the blasting sweep range adopts a neural network convolutional structure and includes an input layer, a processing layer, and an output layer. The relevant characteristic parameters are input into the input layer of the mathematical model of the blasting sweep range. After calculation by the processing layer, the blasting sweep coefficient corresponding to the current initial charge amount is output through the output layer; S3: Collect the peak impact energy range of the planned blasting operation environment for the explosives used, and adjust the basic impact initiation threshold according to the corresponding operation environment. The positive coefficient is adjusted, and the maximum external impact energy that the explosive can withstand in the current operation scenario is obtained and set as the upper limit of the explosive's impact resistance margin. At the same time, the average distance between adjacent blasting holes is collected, and the blasting continuity index is calculated by combining the blasting sweep efficiency output in S2. S4: Set the continuity threshold, compare the blasting continuity index with the set continuity threshold. If the continuity index is less than the continuity threshold, reduce the initial charge in each blasting hole by a fixed gradient. Repeat S2~S4 and compare the blasting continuity index with the continuity threshold until the blasting continuity index is not less than the continuity threshold.

2. The method for optimizing the design of fine-charge explosive charges for open-pit bench blasting boreholes based on BIM as described in claim 1, characterized in that: The initial charge amount to be set in the blasting borehole in S1 is preset based on historical blasting data and adjusted according to the on-site blasting requirements; the rock hardness coefficient is obtained based on the rock mechanics test results in the geological exploration report; the rock porosity ratio is calculated by collecting geological structure model data and calculating the proportion of void volume inside the rock based on the geological structure model data; the air humidity of the blasting environment is extracted from the meteorological database established in the field area, and each of the relevant characteristic parameters is verified through a standardized data acquisition process.

3. The method for optimizing the design of fine-charge explosive charges for open-pit bench blasting boreholes based on BIM according to claim 2, characterized in that, The initial charge quantity is preset based on historical blasting data through the following process: calling up complete database records of the same historical blasting projects, including drilling depth, hole diameter, rock type, and blasting effect indicators; establishing a statistical correlation model based on historical parameters to identify the optimal charge quantity range under the current rock hardness and porosity conditions; predicting the appropriate initial value for the current scenario using machine learning algorithms; and verifying the rationality of the preset value and calibrating the data trend based on engineering experience.

4. The method for optimizing the design of fine-charge explosive charges for open-pit bench blasting boreholes based on BIM according to claim 1, characterized in that, The blast wave effect coefficient corresponding to the initial charge amount is calculated using the following formula: ;in: This refers to the blast wave sweep coefficient; This is the initial charge amount; This represents the proportion of rock mass porosity. This refers to the rock mass hardness coefficient. The humidity of the air in the blasting environment; The influence of humidity is weighted; is a proportionality constant; blast wave sweep coefficient Used to reflect the relative blast radius, and the blast radius coefficient. The larger the value, the wider the range; the proportion of rock mass porosity The range of values ​​is The proportionality constant The proportionality constant is obtained by fitting data from field blasting tests or historical data. The typical initial value is set to 1.

0.

5. The method for optimizing the design of fine-charge explosive charges for open-pit bench blasting boreholes based on BIM according to claim 4, characterized in that, The proportionality constant The acquisition process is achieved through the following data-driven workflow: Based on measured data from historical blasting projects or small-scale on-site test blasts, the system collects the actual blast wave range and relevant characteristic parameters under corresponding working conditions, and uses the following inverse formula to calculate the temporary proportional constant. The value: The least squares method was used to statistically fit multiple sets of back-calculated values. After removing outliers, the mean was calculated as the initial value. The results were then verified by considering the boundary conditions of the maximum permissible impact range required by engineering safety specifications. Finally, a proportional constant that balances accuracy and safety was determined through iterative optimization. And the proportionality constant The values ​​are continuously updated and maintained as new blasting case data is added.

6. The method for optimizing the design of fine-charge explosive charges for open-pit bench blasting boreholes based on BIM according to claim 4, characterized in that: In step S3, during the process of collecting the peak impact energy range of the planned blasting operation environment for the explosives, historical blasting vibration monitoring data and current geological structural characteristics are integrated. These geological structural characteristics include rock stratum dip angle, joint density, and groundwater conditions. A dynamic peak distribution model is constructed by establishing the energy propagation attenuation law. The basic impact detonation threshold is determined based on standard laboratory test values ​​in the explosives technical parameter library and is weighted and adjusted in conjunction with operation environment correction coefficients. These operation environment correction coefficients include topographic relief index, rock mass wave impedance difference, and spatial variables of overburden thickness. Based on the extreme impact tolerance value of the explosives used, a material sensitivity factor and a confidence interval fluctuation range are introduced, with the confidence interval fluctuation range set at ±10%~15%. Finally, the maximum external impact energy value that the explosives can withstand in the current scenario is output. This value is officially set as the upper limit of the explosives' impact resistance margin after safety redundancy verification.

7. The method for optimizing the design of fine-charge explosive charges for open-pit bench blasting boreholes based on BIM according to claim 4, characterized in that, The formula for calculating the blasting continuity index is as follows: ;in: This is the blasting continuity index, and its value ranges from positive. Explosion continuity index The larger the value, the higher the anti-interference capability of adjacent blast holes; This represents the upper limit of the explosive's impact resistance margin, indicating the maximum external impact energy that the explosive can withstand in the current operating scenario; The average spacing between adjacent blasting holes; This represents the average distance between adjacent blast holes in a blasting sequence.

8. The method for optimizing the design of fine-charge explosive charges for open-pit bench blasting boreholes based on BIM according to claim 7, characterized in that: The average spacing between adjacent blasting holes The acquisition process is achieved through the following data integration workflow: Based on the drilling construction records and three-dimensional spatial coordinate dataset of the blasting area, the measured values ​​of the center point spacing of all adjacent borehole pairs are extracted. These values ​​are then cross-validated with the theoretical borehole grid layout data in the blasting design drawings to eliminate outliers caused by positioning errors or construction offsets. Subsequently, the local mean values ​​of all valid spacing values ​​are calculated in groups. The weighted average method is then used to comprehensively consider the actual influence coefficients of terrain undulation and rock mass structure continuity on the spacing, ultimately outputting a uniform average spacing of blasting boreholes for the entire area. 。 9. The method for optimizing the design of fine-charge explosive charges for open-pit bench blasting boreholes based on BIM according to claim 7, characterized in that: Set the coherence threshold to When the calculated blasting continuity index is obtained Then according to: Reduce the initial charge amount in all blasting holes. ,in, This serves as the baseline for the first iteration of the charge amount. The dosage is gradient, and the current iteration number n is recorded, limiting the maximum number of iterations. This is used to prevent over-optimization; the charge quantity needs to be re-entered after each update. The updated blast wave sweep coefficient is simultaneously obtained from the mathematical model of the blast wave range of S2. 。 10. The method for optimizing the design of fine-charge explosive charges for open-pit bench blasting boreholes based on BIM according to claim 9, characterized in that: Based on the updated charge quantity Combined with the upper limit of the explosive shock resistance margin of S3 and the average spacing between adjacent blasting holes Calculate the new coherence index The cycle continues until The process will terminate at that time; and the newly obtained coherence index will be used as the final index. Set as final charge amount Output the final charge amount and the corresponding final charge amount 。

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