A method and system for optimizing a scheme based on automated blasting

Abstract

The present invention discloses a method and system for optimizing a scheme based on automated blasting, belonging to the technical field of data strategy optimization, including: obtaining an automated blasting scheme uploaded by a lower computer and the three-dimensional geological structure of a blasting object; performing energy analysis on blasting parameters in the automated blasting scheme according to the three-dimensional geological structure; predicting a blasting target through the energy analysis to obtain the expected completion situation of the blasting target under the current scheme; using the blasting target to optimize the blasting parameters to obtain an optimal scheme for automated blasting; and sending the obtained expected completion situation and the optimal scheme to the lower computer respectively for guiding the scheme of automated blasting. It realizes closed-loop control from blasting design, optimization to execution, significantly improves the automation degree, construction safety and resource utilization efficiency of blasting operations, and is applicable to refined and intelligent blasting scenarios under complex geological conditions.

Description

Technical Field

[0001] The present invention relates to the technical field of data strategy optimization, and particularly relates to a method and system for optimizing a plan based on automated blasting. Background Art

[0002] As an important means for rock and soil fragmentation and structure demolition, blasting technology is widely used in engineering scenarios such as mine exploitation, tunnel excavation, building demolition, and water conservancy projects. Traditional blasting design usually relies on empirical formulas, test data, and the engineering experience of on-site personnel to determine the charge structure, hole pattern parameters, and initiation sequence. Although there is already a certain standardized design process, there are still problems such as inaccurate parameter selection, unstable blasting effects, and difficult prediction of interference to the surrounding environment in complex geological environments.

[0003] In recent years, with the development of sensing technology, geological exploration technology, and numerical simulation methods, blasting design has gradually evolved towards digitalization and intelligence. Three-dimensional geological modeling, energy analysis simulation, and initiation process simulation have become key supporting means for improving the scientificity and controllability of blasting design. At the same time, the blasting system has gradually realized automated operation, and the lower-level devices can achieve precise control of multiple initiation points, providing an implementation basis for blasting parameter optimization and feedback control.

[0004] However, most current optimization methods are still limited to single-objective or simple rule-driven, and it is difficult to achieve multi-objective collaborative optimization and intelligent decision-making in complex environments. In addition, the lack of quantitative evaluation and dynamic analysis methods for the process of blasting energy action limits the adaptability of the automated blasting system under higher precision and higher safety standards. Therefore, how to integrate multi-source geological information, finely model the blasting process, and achieve a higher level of optimization control has become an important development direction in the industry. Summary of the Invention

[0005] To solve the above technical problems, a method for optimizing a plan based on automated blasting is proposed, including obtaining the automated blasting plan uploaded by the lower-level device and the three-dimensional geological structure of the blasting object;

[0006] Performing energy analysis on the blasting parameters in the automated blasting plan according to the three-dimensional geological structure;

[0007] Predicting the blasting target through the energy analysis to obtain the expected completion situation of the blasting target under the current plan;

[0008] Using the blasting target to perform parameter optimization on the blasting parameters to obtain the optimal plan for automated blasting;

[0009] Sending the obtained expected completion situation and the optimal plan to the lower-level device respectively for guiding the plan of automated blasting;

[0010] The energy analysis includes analyzing whether the blasting target can be completed by constructing the concept of blasting entropy and analyzing the propagation and accumulation of the blasting entropy.

[0011] As a preferred embodiment of the method for optimizing an automated blasting scheme according to the present invention, wherein: the automated blasting scheme includes a blasting target, a blasting location, the positions of each blasting hole in the three-dimensional geological structure, and the blasting parameters of each blasting hole;

[0012] The blasting target includes the area that needs to be damaged or removed in the blasting task;

[0013] The three-dimensional geological structure includes a spatial data model formed by digitizing the spatial distribution, physical properties, and structural characteristics of underground rock and soil masses through geological structure survey techniques.

[0014] As a preferred embodiment of the method for optimizing an automated blasting scheme according to the present invention, wherein: the blasting parameters include explosive type, initiation time, and charge amount.

[0015] As a preferred embodiment of the method for optimizing an automated blasting scheme according to the present invention, wherein: the blasting entropy includes obtaining the functional relationship between the energy released during explosive explosion and the charge amount by fitting the charge amount and the energy released during explosive explosion for each explosive type, as the type-A functional relationship;

[0016] For each of the blasting parameters, after matching the explosive type to the functional relationship a in the type-A functional relationship, input the charge amount into the functional relationship a, and output the energy released during explosive explosion as the blasting entropy of the blasting parameter;

[0017] Analyzing the propagation and accumulation of the blasting entropy includes detonating the explosives in each blasting hole on the time axis through the initiation time; assuming that when the explosives in each blasting hole explode, the blasting entropy starts from the bottom of the blasting hole and propagates radially;

[0018] By fitting the functional relationship between the attenuation of the blasting entropy at the same coordinate position in different media and the magnitude of the blasting entropy, a type-B functional relationship is obtained;

[0019] By fitting the functional relationship between the attenuation of the blasting entropy when the blasting entropy propagates from the current coordinate position to the next coordinate position during the propagation process and the magnitude of the blasting entropy at the current coordinate position, a type-C functional relationship is obtained;

[0020] Using the C-type function relationship, on the time axis, according to the energy propagation speed, the blasting entropy is propagated at each coordinate position of the three-dimensional geological structure; during the propagation process, the blasting entropy at each coordinate position is accumulated, and using the B-type function relationship, the accumulated blasting entropy at each coordinate position is attenuated; the blasting entropy of each coordinate on the time axis is obtained.

[0021] As a preferred solution of a method for optimizing a blasting scheme based on automation according to the present invention, wherein: the predicted completion situation includes comprehensively analyzing the blasting entropy of each coordinate, presetting a stability threshold for each medium, and in the coordinate position (x, y, z), if the blasting entropy is greater than the corresponding stability threshold, it is determined that the position (x, y, z) is unstable; otherwise, it is determined to be stable;

[0022] Statistically analyze all unstable coordinate positions. If in area T, the density of unstable coordinates is greater than the preset value 1, it is predicted that area T is damaged; if in any plane R, the density of unstable coordinates is greater than the preset value 2, it is predicted that the part outside plane R is removed;

[0023] On the time axis, when any area or plane achieves the damage or removal of the blasting target, synchronization is performed in the three-dimensional geological structure, and continuous analysis is carried out according to the synchronized three-dimensional geological structure until the blasting ends, realizing the accumulation of the damaged or removed part in the three-dimensional geological structure;

[0024] After the blasting ends, if the blasting target does not exist in the synchronized three-dimensional geological structure, it is determined that the blasting target is completed; otherwise, it is determined that the blasting fails;

[0025] The stability threshold includes a threshold for judging whether the blasting entropy can affect the structural stability for each measurement part represented by the coordinates in different media.

[0026] As a preferred solution of a method for optimizing a blasting scheme based on automation according to the present invention, wherein: the parameter optimization includes presetting the step size during adjustment for each blasting parameter respectively; calculating the feasible values of each blasting parameter; the feasible values of the explosive type in each blast hole: ;

[0027] The feasible values of the initiation time in each blast hole: ;

[0028] The feasible values of the charge amount in each blast hole: ;

[0029] Wherein, represents the kth explosive type, and k represents the number of optional explosive types; It represents the q-th optional moment on the time axis for the initiation time; q represents the number of optional moments for the initiation time in the blast hole. It represents the e-th optional charge amount in the blast hole; e represents the optional values of the charge amount in the blast hole.

[0030] Select one parameter from KL, KQ, and KZ respectively for combination to obtain a set of blasting parameters as the parameter combination to be evaluated; for the said parameter combination to be evaluated, predict the completion situation of the blasting target, and obtain all the parameter combinations to be evaluated that meet the constraint conditions and the predicted blasting target is completed, as the parameter combinations to be optimized.

[0031] For each parameter combination to be optimized, sum the charge amounts of each explosive type to obtain the total charge amount of all explosive types used under each parameter combination to be optimized and each explosive type.

[0032] The said constraint condition is: the cumulative volume of the damaged or removed part - the volume of the blasting target ≤ the preset value θ.

[0033] As a preferred scheme of a method for optimizing a scheme based on automated blasting according to the present invention, wherein: the optimal scheme includes selecting the optimal scheme according to the total charge amount of each explosive type under each parameter combination to be optimized based on a preset selection principle, and outputting the final scheme.

[0034] Another object of the present invention is to provide a system for optimizing a scheme based on automated blasting. The present invention solves the problems that the existing automated blasting optimization system is difficult to accurately evaluate the blasting effect and has low efficiency in optimizing parameter configuration under complex geological conditions. By quantitatively analyzing the energy action process and combining the three-dimensional geological structure to predict the dynamic stability of the target area, the accuracy of judging the blasting effect is improved. At the same time, efficient combination optimization of multi-dimensional blasting parameters is realized, and while meeting complex blasting targets, the reliability and intelligent level of the automated blasting scheme are significantly improved.

[0035] As a preferred scheme of a system for optimizing a scheme based on automated blasting according to the present invention, it is characterized by including: a collection unit for obtaining the automated blasting scheme uploaded by the lower computer and the three-dimensional geological structure of the blasting object.

[0036] An analysis unit for performing energy analysis on the blasting parameters in the automated blasting scheme according to the three-dimensional geological structure.

[0037] A prediction unit for predicting the blasting target through the energy analysis to obtain the predicted completion situation of the blasting target under the current scheme.

[0038] An optimization unit for optimizing the blasting parameters by using the blasting target to obtain the optimal scheme of automated blasting.

[0039] An output unit that separately sends the obtained expected completion status and the optimal solution to the lower computer.

[0040] A computer device includes a memory and a processor. The memory stores a computer program. It is characterized in that when the processor executes the computer program, the steps of the described method for optimizing a blasting-based automation solution are implemented.

[0041] A computer-readable storage medium stores a computer program. It is characterized in that when the computer program is executed by a processor, the steps of the described method for optimizing a blasting-based automation solution are implemented.

[0042] Advantages of the present invention: By constructing a propagation and accumulation model of blasting entropy, a quantitative analysis of energy release, transfer during blasting and its impact on geological structures is realized, breaking through the problem of difficult prediction of blasting effects in traditional blasting designs. Based on three-dimensional geological structure modeling and medium strength marking, the system can accurately identify the blasting target area and its stability changes, and realize the dynamic prediction of the completion status of the blasting target. Through a parameter optimization mechanism, the system quickly screens out the optimal blasting solution that meets the constraint conditions from various combinations of explosive types, initiation times and charge amounts, effectively improving the optimization efficiency and accuracy. The final solution can be synchronously sent to the automated blasting equipment to realize a closed-loop control from blasting design, optimization to execution, significantly improving the automation level, construction safety and resource utilization efficiency of blasting operations, and being applicable to refined and intelligent blasting scenarios under complex geological conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0044] Figure 1 It is the overall flowchart of a method for optimizing a blasting-based automation solution provided by an embodiment of the present invention.

[0045] Figure 2 It is a schematic diagram of a blasting target of a method for optimizing a blasting-based automation solution provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0046] To make the above objects, features, and advantages of the present invention more apparent and understandable, the following provides a detailed description of the specific embodiments of the present invention in conjunction with the accompanying drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0047] Example 1, referring to Figure 1 and Figure 2 , which is the first embodiment of the present invention. This embodiment provides a method for optimizing an automated blasting plan, including:

[0048] S1: Obtain the automated blasting plan uploaded by the lower computer and the three-dimensional geological structure of the blasting object.

[0049] Furthermore, the automated blasting plan includes a blasting target, a blasting location (used for information recording and engineering logs), the position of each blasting hole in the three-dimensional geological structure, and the blasting parameters of each blasting hole. The blasting target includes the area that needs to be damaged or removed in the blasting task. Here, the "blasting object" refers to the mountain or other object to be blasted. Blasting object > Blasting target.

[0050] The three-dimensional geological structure is the acquisition of basic data through existing means. Through geological structure survey technology, a spatial data model is formed after digitizing the spatial distribution, physical properties, and structural characteristics of underground rock and soil masses. The three-dimensional geological structure refers to a spatial data model formed after digitizing and visualizing the spatial distribution, physical properties, structural characteristics, etc. of underground rock and soil masses in a geographic coordinate system. This structure expresses geological information such as rock layer boundaries, joint fractures, holes, weak zones, and groundwater levels in the form of three-dimensional grids, voxels, point clouds, isosurfaces, etc., and is the basic data environment for automatic calculation and intelligent optimization of blasting parameters.

[0051] The acquisition methods include, but are not limited to, seismic wave reflection method, resistivity tomography, borehole core testing, and ground penetrating radar scanning; the three-dimensional geological structure is composed of multiple spatial unit bodies. The system assigns a geological strength value to each spatial unit based on the measured or deduced data corresponding to each unit. The geological strength value is used to reflect the compressive capacity of the rock mass, the degree of joint fracture, or the blasting energy consumption requirements; the geological strength marking result is used as one of the input variables for blasting parameter optimization to control the adaptive generation of charge structure, hole pattern density, and delay strategy.

[0052] At that time, the automated blasting plan included information such as the blasting target, blasting location, spatial positions of each blasting hole, and blasting parameters. In particular, the mapping of each blasting hole position in the three-dimensional geological structure provided a coordinate reference for subsequent calculation of the energy propagation path and judgment of the action effect. The blasting target clearly specified the area to be damaged or removed in the blasting task and was the core input of the objective function in the entire optimization process. Geological strength values were assigned to each spatial unit to characterize the mechanical properties and blasting response characteristics of the rock mass in that area, thereby providing a basis for high-precision structural response for energy simulation and parameter optimization.

[0053] By deeply integrating the blasting task, spatial structure, and parameter data, it provides data support and a structural model foundation for subsequent blasting entropy analysis, prediction of target completion degree, and automatic optimization, ensuring that the system has geological perception ability and precise control ability, and promoting the intelligent upgrade of blasting design from "experience-based decision-making" to "data-driven + model-supported".

[0054] S2: According to the three-dimensional geological structure, perform energy analysis on the blasting parameters in the automated blasting plan.

[0055] Among them, the energy analysis includes analyzing whether the blasting target can be completed by constructing the concept of blasting entropy and analyzing the propagation and accumulation of the blasting entropy. The blasting entropy includes obtaining the functional relationship between the energy released during explosive explosion and the charge amount by fitting the charge amount and the energy released during explosive explosion for each type of explosive, as the type-A functional relationship. The fitting data of the type-A functional relationship mainly comes from the following three types of channels: explosion performance test data reports of explosive manufacturing enterprises, military industries, and civilian explosive research institutions; monitoring systems in actual engineering blasting (such as microseismic monitoring, particle size distribution analysis, flying rock distance, etc.); using blasting mechanics simulation tools (such as ANSYS-AUTODYN, LS-DYNA) to simulate the explosion process of different explosives in different environments and extract the corresponding energy values. Taking the explosive type and charge amount in the actual blasting parameters as inputs; calling the fitted function model, which is the blasting energy of this hole.

[0056] For each of the blasting parameters (each hole has a parameter, that is to say, this matching and calculation process is carried out for each hole), in the type-A functional relationship, after matching the function relationship a through the explosive type, input the charge amount into the function relationship a, and output the energy released during explosive explosion as the blasting entropy of the blasting parameter.

[0057] Analyzing the propagation and accumulation of the blasting entropy includes detonating the explosives in each blasting hole on the time axis through the detonation time; assuming that when the explosives in each blasting hole explode, the blasting entropy starts from the bottom of the blasting hole and propagates radially.

[0058] It should be noted that in engineering blasting, the explosive is usually loaded in a bottom-up structure, that is, the explosive charges are loaded from the bottom of the hole upwards, and the initiation points are mostly set at the bottom of the hole or the bottom of the explosive charge. Once detonated, the explosive instantaneously releases energy, forming a high-speed shock wave, and the wave source is located in the central area at the bottom of the blasting hole. At this time, the energy propagates in all directions in the geological medium in the form of a spherical wave. However, due to the limitation of the hole wall, the waveform will be reflected, diffracted or reduced in different directions, but its propagation direction is initially divergent outwards (i.e., radially). Therefore, setting that "the blasting entropy starts from the bottom of the hole and propagates radially" is a physical modeling method that conforms to the initial release process of the actual explosion energy. The three-dimensional geological structure is usually divided into spatial grid units. If the propagation path of the blasting entropy is established starting from the bottom of the hole, the "spherical diffusion" or "anisotropic energy propagation" can be more efficiently simulated in the coordinate space; the radial propagation model can combine the C-type function relationship to model the layer-by-layer attenuation of the blasting entropy from the current coordinate to the adjacent coordinate direction, forming a "time + space" propagation sequence.

[0059] If the bottom of the blasting hole is taken as the initial point and propagated radially in all directions, it can ensure that the blasting entropy expands along the actual physical path, and then form a multiple superposition of entropy energy in the target area, which is convenient for subsequent statistics of "whether a certain area reaches the damage condition".

[0060] By fitting the functional relationship between the attenuation of the blasting entropy at the same coordinate position in different media and the magnitude of the blasting entropy, the B-type function relationship is obtained. It should be noted that the degree of energy attenuation in different media is different. By fitting the functional relationship between the attenuation of the blasting entropy when the blasting entropy propagates from the current coordinate position to the next coordinate position and the magnitude of the blasting entropy at the current coordinate position during the propagation process, the C-type function relationship is obtained.

[0061] It should be noted that the purpose of the B-type function relationship is to find the attenuation behavior model of the unit blasting entropy value in the in-situ stable state in different media (such as hard rock, soft rock, sand layer, aquifer). The data is obtained through engineering measured data (through microseismic, wave velocity, pressure inversion), numerical simulation (such as the blasting energy attenuation module of LS-DYNA), experimental determination (simulating blasting by filling different media in the experimental chamber), etc., and is obtained by fitting according to the obtained data. The purpose of the C-type function relationship is to find the attenuation rule when the blasting entropy propagates from one spatial unit to another spatial unit, reflecting the "spatial transfer" characteristic of entropy. By constructing the mapping relationship between the entropy value of the current coordinate and the entropy value of the next coordinate, combining the medium parameters and the propagation distance, and performing curve fitting through simulation data or measured data, the blasting entropy attenuation function on the spatial propagation path is formed.

[0062] Using the C-type function relationship, on the time axis, according to the energy propagation speed, the blasting entropy is propagated at each coordinate position of the three-dimensional geological structure; during the propagation process, the blasting entropy at each coordinate position is accumulated, and using the B-type function relationship, the accumulated blasting entropy at each coordinate position is attenuated; the blasting entropy of each coordinate on the time axis is obtained.

[0063] It should be known that by constructing a spatio-temporal propagation model of blasting entropy driven by the energy propagation speed and combining with the characteristics of geological media, the dynamic modeling of the propagation path and attenuation behavior of blasting energy in three-dimensional space is realized. On this basis, the system can simulate the change process of the blasting entropy of each coordinate unit on the time axis, and then judge whether each area reaches the damage condition. In this way, the "energy influence range" and "effect achievement degree" that are difficult to predict in traditional blasting can be quantified into an entropy response model at the coordinate level, improving the accuracy of blasting prediction and the scientific nature of parameter optimization.

[0064] The calculation of the propagation and attenuation of the blasting entropy of each coordinate is as follows:

[0065] Initialization: Calculate the initial blasting entropy of each blast hole 。

[0066] Propagation simulation: Calculate the arrival time of each coordinate point according to the propagation speed.

[0067] Energy transmission: Calculate the entropy value after propagation and attenuation using the C-type function.

[0068] Energy accumulation: Accumulate the entropy values of multiple blast holes at each coordinate point.

[0069] Medium attenuation: Perform attenuation using the B-type function to obtain the final blasting entropy.

[0070] Time series update: Perform step-by-step iteration on the time axis to form a global propagation map.

[0071] Energy from the blast hole propagates to the point The propagation time is:

[0072] ;

[0073] The propagation arrival time is:

[0074] ;

[0075] The blasting entropy propagated from blast hole j to coordinate point i is:

[0076] ;

[0077] Assume the coordinate point Affected by multiple blasting holes, the cumulative entropy is:

[0078] ;

[0079] ;

[0080] Among them, represents the initial blasting entropy value released by the -th blasting hole at the moment of initiation, which is calculated from the explosive type and the charge amount through a fitting function (i.e., the A-type function relationship). represents the position coordinates of the blasting hole, is the initiation time of this hole. The blasting entropy starts from the position of the blasting hole and diffuses outward at a certain energy propagation speed, which is determined by the type of geological medium where the entropy propagates, denoted as . The propagation distance is determined by the distance from the blasting hole to any coordinate point in the three-dimensional geological structure . The propagation process of the blasting entropy in space will decay, and the entropy value gradually decreases with the propagation distance and the medium characteristics. This process is represented by the C-type function relationship, denoted as . When a coordinate point is affected by the entropy waves of multiple blasting holes, its cumulative entropy value is the sum of the blasting entropies under all paths, denoted as . On this basis, to consider the absorption and dissipation of energy by the medium itself, it is also necessary to introduce the B-type function relationship to attenuate the cumulative entropy value, and obtain the blasting entropy value of the final coordinate point at time , expressed as , such as using the exponential decay model: , where is the attenuation coefficient of the current medium type . The entire propagation calculation process can be iteratively completed under the discrete time step , so as to obtain the evolution process of the blasting entropy of each point in the three-dimensional space on the time axis.

[0081] Furthermore, a comprehensive analysis is carried out on the blasting entropy of each coordinate. For each medium, a stability threshold is preset. Among the coordinate positions (x, y, z), if the blasting entropy is greater than the corresponding stability threshold, it is determined that the position (x, y, z) is unstable; otherwise, it is determined to be stable.

[0082] Statistical analysis is performed on all unstable coordinate positions. If in the region T, the density of unstable coordinates is greater than the preset value 1, it is predicted that the region T is damaged; if in any plane R (equivalent to a partial resection), the density of unstable coordinates is greater than the preset value 2, it is predicted that the part outside the plane R is removed. Such as Figure 2As shown, the shaded area represents the blasting target. If the density of unstable coordinates in the plane where the dashed line is located is greater than the preset value of 2, the blasting target will be directly cut off (at this time, the required energy is the least and the cost is definitely the lowest, but the feasibility is relatively low. Therefore, it is necessary to optimize the parameters. If the cutting is achieved, it will become the optimal solution).

[0083] On the time axis, when any area or plane achieves the destruction or removal of the blasting target, it is synchronized in the three-dimensional geological structure, and continuous analysis is carried out based on the synchronized three-dimensional geological structure until the blasting ends, achieving the accumulation of the damaged or removed parts in the three-dimensional geological structure.

[0084] After the blasting ends, if the blasting target does not exist in the synchronized three-dimensional geological structure, it is determined that the blasting target is completed; otherwise, it is determined that the blasting fails. In fact, this is the comparison between the cumulative damaged part and the target damaged part; when the actual cumulative part contains the target part, it is considered successful. In this embodiment, at the same time, the "extra damaged part" will be measured, that is, the difference between the measured cumulative part and the target part (measured part - target part). When the blasting target is completed, this value is a positive number, indicating that there is an extra broken part; usually, a threshold is set for this part. If it is greater than this threshold, it means over-blasting. Controlling the extra broken part to be less than this threshold is used as a constraint condition during the blasting process. If the initial plan exceeds this threshold, a reminder and a warning need to be issued. At the same time, during the parameter optimization process, it is directly used as a constraint condition to ensure that the "extra damaged part" of the blasting plan is not greater than this threshold (it can be a preset value according to each plan; it can also be a preset percentage: the ratio of the volume of the "extra damaged part" to the volume of the blasting target).

[0085] If the "extra damaged part" is negative, it means that the blasting fails.

[0086] The stability threshold includes a threshold for judging whether the blasting entropy can affect the structural stability for each measurement part represented by each coordinate in different media.

[0087] In this embodiment, based on the dynamic response analysis of the blasting entropy of each coordinate point in the three-dimensional geological structure, a real-time and spatial judgment mechanism for the damage state of the blasting target is realized, and a digital model reflecting the dynamic evolution of the blasting process is constructed by gradually synchronizing and accumulating, which is used to guide the evaluation and optimization of the automated blasting plan.

[0088] During the actual blasting process, the damage to the target area is a continuous process that does not occur instantaneously, and its effect often depends on the combined action of multi-point energy superposition and geological structure response. Therefore, it is difficult to accurately control whether the intermediate process of blasting achieves the engineering goal only relying on the final state evaluation.

[0089] By presetting the structural stability thresholds for different geological media, the blasting entropy at each coordinate point is compared with the threshold to determine whether the point is unstable, and a stability evaluation model at the microscopic coordinate level is constructed. Further, by statistically analyzing the density of unstable points in a macroscopic region or plane, it is determined whether the target region meets the destruction conditions or whether effective removal has been achieved, so as to aggregate the responses of points into the criteria for achieving the objectives of surfaces and volumes.

[0090] In addition, to support continuous blasting control at multiple times and multiple stages, the system synchronously updates each determined damaged area to the three-dimensional geological structure model, and continues subsequent blasting simulation and entropy propagation analysis based on the new structural state, realizing the closed-loop iteration and cumulative modeling of structural changes and energy field responses. This design enables the entire system to dynamically track the destruction progress of the target, and in real time during the blasting process, determine whether the blasting is completed, providing a basis for decision-making and an optimization direction, and improving the response speed, judgment accuracy, and automation level of the system.

[0091] S3: Predict the blasting target through the energy analysis to obtain the expected completion of the blasting target under the current plan.

[0092] S4: Use the blasting target to optimize the blasting parameters to obtain the optimal plan for automated blasting.

[0093] For each type of blasting parameter, preset the step size during adjustment; calculate the feasible values of each type of blasting parameter; for each blast hole, the feasible values of the explosive type: 。

[0094] For each blast hole, the feasible values of the initiation time: 。

[0095] For each blast hole, the feasible values of the charge amount: 。

[0096] Among them, represents the kth explosive type, and k represents the number of optional explosive types; represents the qth optional moment of the initiation time on the time axis; q represents the number of optional moments of the initiation time in the blast hole; Denote the e-th optional charge amount in the blast hole; e represents the optional values of the charge amount in the blast hole. Before optimizing the parameters of the blasting plan, for each blasting parameter (such as explosive type, initiation time, charge amount), the preset adjustment step and the set of feasible values are constructed according to the actual engineering conditions and system constraints to generate a candidate set of parameter combinations for each blast hole in the parameter space. This candidate set serves as the search basis for the optimization algorithm, ensuring that the parameter optimization process is only carried out within the engineering allowable range, improving the solution efficiency and ensuring the feasibility. In an automated blasting system, the parameter configuration of each blast hole needs to meet various constraints such as safety, geological response, and explosive characteristics. For example, the type of explosive must match the in-hole medium conditions and water resistance requirements; the initiation time must be allocated within a controllable range; the charge amount must be controlled within the allowable density of the explosive and the hole volume limit. Therefore, the present invention sets an "optional range" and a "step size" for each blasting parameter, and generates a "set of optional values for parameters" for each hole accordingly.

[0097] Arbitrarily select one parameter from KL, KQ, and KZ respectively for combination to obtain a set of blasting parameters as the parameter combination to be evaluated; for the parameter combination to be evaluated, predict the completion situation of the blasting target to obtain all parameter combinations to be evaluated that meet the constraint conditions and are expected to complete the blasting target, as the parameter combinations to be optimized.

[0098] For each parameter combination to be optimized, sum the charge amounts of each explosive type to obtain the total charge amount of all explosive types used and each explosive type under each parameter combination to be optimized.

[0099] The constraint condition is: the cumulative volume of the damaged or removed part - the volume of the blasting target ≤ the preset value θ.

[0100] By combining in the preset set of feasible values of blasting parameters (explosive type KL, initiation time KQ, charge amount KZ), construct multiple groups of blasting parameter combinations to be evaluated, and conduct predictive analysis on the completion situation of the blasting target for each group of combinations, and further screen out high-quality solutions that meet the engineering constraint conditions as the solution set to be optimized for subsequent solution selection and output.

[0101] In traditional blasting design, parameters are often set unidirectionally based on manual experience, and it is difficult to systematically evaluate the synergistic effects between combinations. The present invention constructs a discrete set of feasible values for each blast hole and uses a combination algorithm to combine any set of parameters among KL, KQ, and KZ to generate a candidate set of solutions, improving the coverage and intelligence of parameter exploration.

[0102] Based on the generated parameter combinations, the system simulates the blasting completion situation for each combination through the blasting entropy propagation mechanism to identify whether it can meet the damage determination conditions of the target area. At the same time, engineering constraint conditions are introduced, that is, the difference between the cumulative damaged area volume and the blasting target volume shall not exceed the preset threshold θ, so as to control the degree of "extra damage" and prevent excessive energy release while the plan completes the task.

[0103] This design not only realizes the automatic judgment of whether the blasting target is completed, but also introduces the "safety margin" judgment logic through the quantitative control of excessive damage, providing a hard constraint boundary for plan screening and subsequent optimization, and improving the rationality of the plan, on-site implementability and stability of system optimization.

[0104] S5: Send the obtained predicted completion situation and the optimal plan to the lower computer respectively for the plan guidance of automated blasting.

[0105] According to the total charge of each type of explosive under each parameter combination to be optimized, select the optimal plan according to the preset selection principle (which can be the least amount of explosive, or the least cost. It can also be the least cost under the existing inventory constraints), and output the final plan.

[0106] In this embodiment, the objective function:

[0107] .

[0108] That is: Total cost = Usage amount of various explosives Unit price, and find the minimum value among all plans that meet the conditions.

[0109] Inventory constraint (hard constraint): .

[0110] That is: The usage amount of any explosive in any plan shall not exceed the inventory.

[0111] Blasting target completion constraint: The blasting target does not exist in the three-dimensional geological structure after synchronization.

[0112] Extra damage volume limit: .

[0113] Among them, represents taking the minimum value, represents the total cost, represents the unit procurement cost of the i-th type of explosive (unit: yuan / kg), represents the available quantity of the i-th type of explosive in the current inventory (unit: kg). represents the usage amount of the explosive, k represents the type of explosive; represents the proportion of extra damage, represents the volume of the blasting target area, represents the predicted cumulative damaged volume.

[0114] Embodiment 2 is the second embodiment of the present invention, which provides a method for optimizing a scheme based on automated blasting. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through experiments.

[0115] Three different geological sections of a tunnel construction project are selected, representing three typical blasting environments: hard rock area (granite), moderately weathered rock area (gneiss), and interlayer area (shale interbedded with sandstone layer). In each section, the same fragmentation target (volume of about 250 m³) is set, and two schemes are compared and tested: one group is the blasting parameters designed by the traditional manual experience method, and the other group is the optimized scheme generated by this method.

[0116] Test in the hard rock area (granite):

[0117] The test section is located in the second bid section of the main tunnel. The rock mass is intact, and the average uniaxial compressive strength reaches 145 MPa. 72 blasting holes are arranged on site, with a hole depth of 3.2 m and a hole spacing of 1.2 m. The stepped hole arrangement method is adopted.

[0118] In the traditional scheme, the manually designed charge amount is 216 kg, and the proportion of high-explosive-speed explosives used is relatively high. The detonation delay is set to 50 ms (two-stage time sequence). After on-site measurement, the actual fragmented volume is about 278 m³, exceeding the target by 28 m³, and the cost reaches 10,860 yuan. Some side walls show explosive extension exceeding the design line.

[0119] After optimization using this method, the system calculates the blasting entropy propagation model through on-site geological parameters (wave velocity of 2700 m / s), automatically generates a detonation delay of 75 ms, adjusts the explosive structure to mainly emulsified + ANFO, and controls the total amount to 180 kg. After on-site detonation, the measured damaged volume is 266 m³, the additional damaged volume is 16 m³, and the cost is reduced to 9020 yuan.

[0120] Test in the moderately weathered area (gneiss):

[0121] The compressive strength of the rock mass in this section is about 70 MPa, and there are certain weathering fissures. The construction unit adopts the cross-hole arrangement method, and the depth of each group of blasting holes is 2.8 m and the spacing is 1.1 m.

[0122] In the traditional scheme, a mixed explosive scheme (total amount of 190 kg) is designed, and the detonation delay is uniformly set to 25 ms. The results show that the fragmented volume reaches 272 m³, exceeding the target by 22 m³, and the cost is 9540 yuan. In some areas, due to insufficient entropy overlap, fragmentation is incomplete and secondary rock drilling operations increase.

[0123] In the scheme of this method, according to the rock velocity of about 2000m / s and the development characteristics of local fissures in the geological area, the system automatically recommends adjusting the detonation delay to 50ms and reducing the charge to 168kg. The actual blasting effect meets the standard, the crushing volume is 265m³, the additional damage is 15m³, the cost is 8440 yuan, and there is no need for secondary rock drilling. The dust particle ratio after blasting is about 23% lower than that of the manual scheme, indicating that the energy use is more concentrated.

[0124] Interlayer area (soft and hard alternating zone) test:

[0125] This section has the most complex geology, with frequent shale-sandstone interlayers, inconsistent joint directions, and significant changes in wave velocity. The construction section is about 16 meters long, with 85 blasting holes, 0.9 meters apart, and a hole depth of 2.5 meters.

[0126] The traditional solution uses high-explosive velocity explosives + high charge density configuration, with a single-hole charge of up to 2.4kg and a detonation delay of 30ms. The measured crushing volume after blasting reached 289m³, exceeding the target by 39m³. Some areas experienced roof collapse, increasing safety risks and costs of 14,260 yuan. In addition, additional debris cleaning was required on site, delaying construction progress.

[0127] The present invention identifies the interlayer distribution and interface reflection characteristics in the geological model, uses the blasting entropy propagation model to calculate the energy offset trajectory in all directions, automatically adjusts the delay to 65ms, adjusts the charge structure to 202kg, and reduces the overall cost to 10,190 yuan. The measured destruction volume after blasting is 267m³, the additional destruction is 17m³, the boundary control is significantly improved, and no structural damage occurs in the subsequent construction area.

[0128] The above three sets of real-site test results show that this method significantly improves blasting accuracy and energy utilization under various geological conditions. As a key optimization parameter, the detonation delay is no longer manually set or evenly spaced in this method. Instead, it is dynamically solved based on the entropy energy transmission efficiency, structural superposition conditions, and medium reflection characteristics to form a "blasting energy directional focusing" mechanism, avoiding energy redundancy or attenuation caused by the incoordination of blasting wave interference in traditional methods.

[0129] In addition, in each test scenario, this method successfully reduced the total amount of explosives by more than 15%, reduced costs by more than 12%, and achieved effective compression of the additional destruction volume (controlled within <20m³), while no blasting blind area or secondary operation occurred, indicating that the proposed method is not only computationally advanced, but also feasible and economically valuable for on-site execution. Compared with traditional empirical methods, its adaptive ability in complex geological environments, systematic modeling of parameter structures, and precise control of detonation delay all show clear novelty and creativity.

[0130] Embodiment 3, the third embodiment of the present invention, is different from the previous two embodiments in that:

[0131] If the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that makes a contribution to the prior art, or a part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROMs, Read-Only Memories), random access memories (RAMs, Random Access Memories), magnetic disks, or optical discs that can store program codes.

[0132] The logic and / or steps represented in the flowchart or described in other ways herein, for example, can be considered as a definite sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or in combination with these instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0133] More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection part (electronic device) having one or more wirings, a portable computer disk cartridge (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, then editing, interpreting, or processing it in other suitable ways as necessary, and then storing it in a computer memory.

[0134] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits with logic gate circuits for implementing logical functions on data signals, application specific integrated circuits with suitable combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0135] Embodiment 4 is the fourth embodiment of the present invention. This embodiment provides a scheme optimization system based on automated blasting, including: a collection unit that acquires the automated blasting scheme uploaded by the lower computer and the three-dimensional geological structure of the blasting object; an analysis unit that performs energy analysis on the blasting parameters in the automated blasting scheme according to the three-dimensional geological structure; a prediction unit that predicts the blasting target through the energy analysis to obtain the expected completion situation of the blasting target under the current scheme; an optimization unit that optimizes the blasting parameters by using the blasting target to obtain the optimal scheme for automated blasting; and an output unit that respectively sends the obtained expected completion situation and the optimal scheme to the lower computer.

[0136] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

Claims

1. A method for optimizing a scheme based on automated blasting, characterized in that: Including obtaining the automated blasting plan uploaded by the lower computer and the three-dimensional geological structure of the blasting object; According to the three-dimensional geological structure, perform energy analysis on the blasting parameters in the automated blasting plan; Predict the blasting target through the energy analysis to obtain the expected completion situation of the blasting target under the current plan; Utilize the blasting target to optimize the blasting parameters to obtain the optimal plan for automated blasting; Send the obtained expected completion situation and the optimal plan to the lower computer respectively for the plan guidance of automated blasting; The energy analysis includes analyzing whether the blasting target can be completed by constructing the concept of blasting entropy and analyzing the propagation and accumulation of the blasting entropy; The parameter optimization includes presetting the step size during adjustment for each type of blasting parameter and calculating the feasible values of each type of blasting parameter; For each type of blasting parameter, randomly select a feasible value of one parameter for combination to obtain a set of blasting parameters as the parameter combination to be evaluated. Predict the completion situation of the blasting target for the parameter combination to be evaluated, and obtain all the parameter combinations to be evaluated that meet the constraint conditions and are expected to complete the blasting target as the parameter combinations to be optimized; For each parameter combination to be optimized, sum the charge amounts of each type of explosive to obtain all the types of explosives used and the total charge amount of each type of explosive under each parameter combination to be optimized; The constraint condition is: the cumulative volume of the damaged or removed part - the volume of the blasting target ≤ the preset value θ; The blasting entropy includes obtaining the functional relationship between the energy released during explosive detonation and the charge amount by fitting the charge amount and the energy released during explosive detonation for each type of explosive as the type-A functional relationship; For each of the blasting parameters, after matching the functional relationship a through the explosive type in the type-A functional relationship, input the charge amount into the functional relationship a to output the energy released during explosive detonation as the blasting entropy of the blasting parameter; Analyzing the propagation and accumulation of the blasting entropy includes detonating the explosives in each blast hole on the time axis through the initiation time. Assume that when the explosives in each blast hole explode, the blasting entropy starts from the bottom of the blast hole and propagates radially; Obtain the type-B functional relationship by fitting the functional relationship between the attenuation of the blasting entropy at the same coordinate position in different media and the magnitude of the blasting entropy; Obtain the type-C functional relationship by fitting the functional relationship between the attenuation of the blasting entropy during propagation from the current coordinate position to the next coordinate position and the magnitude of the blasting entropy at the current coordinate position; Utilize the type-C functional relationship to propagate the blasting entropy at each coordinate position of the three-dimensional geological structure on the time axis according to the energy propagation speed; During the propagation process, accumulate the blasting entropy at each coordinate position and utilize the type-B functional relationship to attenuate the accumulated blasting entropy at each coordinate position; Obtain the blasting entropy of each coordinate on the time axis.

2. The method for optimizing a scheme based on automated blasting according to claim 1, characterized in that: The automated blasting plan includes a blasting target, a blasting location, the position of each blasting hole in the three-dimensional geological structure, and the blasting parameters of each blasting hole; The blasting target includes the area that needs to be damaged or removed in the blasting task; The three-dimensional geological structure includes a spatial data model formed by digitizing the spatial distribution, physical properties, and structural characteristics of underground rock and soil masses through geological structure survey techniques.

3. The method for optimizing a scheme based on automated blasting according to claim 2, wherein: The blasting parameters include explosive type, initiation time, and charge amount.

4. The method for optimizing a scheme based on automated blasting according to claim 3, wherein: The predicted completion situation includes comprehensively analyzing the blasting entropy of each coordinate, presetting a stability threshold for each medium. In the coordinate position (x, y, z), if the blasting entropy is greater than the corresponding stability threshold, it is determined that the position (x, y, z) is unstable; otherwise, it is determined to be stable; Count all the unstable coordinate positions. If in area T, the density of unstable coordinates is greater than the preset value 1, it is predicted that area T is damaged; if in any plane R, the density of unstable coordinates is greater than the preset value 2, it is predicted that the part outside plane R is removed; On the time axis, when any area or plane achieves the damage or removal of the blasting target, it is synchronized in the three-dimensional geological structure, and continuous analysis is carried out based on the synchronized three-dimensional geological structure until the blasting ends, realizing the accumulation of the damaged or removed part in the three-dimensional geological structure; After the blasting ends, if the blasting target does not exist in the synchronized three-dimensional geological structure, it is determined that the blasting target is completed; Otherwise, it is determined that the blasting fails; The stability threshold includes a threshold for judging whether the blasting entropy can affect the structural stability for each measurement part represented by a coordinate in different media.

5. The method for optimizing a scheme based on automated blasting according to claim 1, wherein: For each blast hole, the feasible values of explosive type: ; For each blast hole, the feasible values of detonation time are: ; In each blast hole, the feasible values of the charge amount: ; Among them, represents the k-th explosive type, where k represents the number of optional explosive types; represents the q-th optional moment on the time axis for the detonation time; q represents the number of optional moments for the detonation time in the blast hole; represents the e-th optional charge amount in the blast hole; e represents the optional values of the charge amount in the blast hole.

6. The method for optimizing a scheme based on automated blasting according to claim 1, wherein: The optimal plan includes selecting the optimal plan according to the total charge amount of each explosive type under each combination of parameters to be optimized based on a preset selection principle and outputting the final plan.

7. An optimization system for a scheme based on automated blasting, which applies an optimization method for a scheme based on automated blasting as described in any one of claims 1 to 6, characterized in that, It includes: An acquisition unit that obtains the automated blasting plan uploaded by the lower computer and the three-dimensional geological structure of the blasting object; An analysis unit that performs energy analysis on the blasting parameters in the automated blasting plan according to the three-dimensional geological structure; A prediction unit that predicts the blasting target through the energy analysis to obtain the predicted completion situation of the blasting target under the current plan; An optimization unit that optimizes the blasting parameters using the blasting target to obtain the optimal plan for automated blasting; An output unit that respectively sends the obtained predicted completion situation and the optimal plan to the lower computer.

8. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it realizes the steps of a method for optimizing a plan based on automated blasting according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it realizes the steps of a method for optimizing a plan based on automated blasting according to any one of claims 1 to 6.

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