Customized intelligent blasting management method and system

Abstract

The invention discloses a customized intelligent blasting management method and system, and relates to the technical field of intelligent blasting, and the method comprises the steps: 1, obtaining site data: carrying out the historical data investigation of a mine region needing intelligent blasting by a worker, and carrying out the live-action shooting of the mine region through an unmanned plane; the method comprises the following steps: 1, determining the requirements of an owner, determining the blasting purpose, determining the rock blasting lumpiness grade, determining the property of an initiating explosive device, and determining a rock lumpiness particle size grading curve required by the owner, 2, transmitting the shot data to a computer by an unmanned aerial vehicle in a wireless data transmission mode, and collecting and preprocessing mine rock mass data and blasting data by the computer, establishing a blasting database; the quantitative relation between the rock lumpiness grading curve and the energy consumption, working efficiency and blasting parameters of the downstream production chain is systematically analyzed, customized blasting design software is developed, and the precision of blasting parameter design is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent blasting, and in particular to a customized intelligent blasting management method and system. Background Art

[0002] As the requirements for blasting operations in open-pit mines, seaport terminal construction, airport construction, reclamation and dam construction projects become increasingly higher, the traditional standardized step blasting design is increasingly unable to meet the requirements. How to achieve satisfactory blasting results under different blasting projects, different blasting requirements of the same blasting project, different blasting environments, and different blasting media conditions, customized blasting design is imperative. The defects of traditional blasting design can be seen from the above two traditional blasting design methods:

[0003] (1) The unit consumption control method uses personal or industry experience to select the q value, and the resistance line control method uses the formula W = (25-40)d to calculate the W value. Both methods are estimated based on experience and then finally determined after several field tests;

[0004] (2) The blastability of rocks in the mine blasting area varies greatly. If the blasting parameters remain unchanged, it is difficult to meet the mine's requirements for resource conservation, environmental friendliness, low carbon and high efficiency, and cost reduction and efficiency improvement;

[0005] (3) Mines are generally large in scale and the blasting intensity is very high, so there is no time and energy for a large number of test blasts;

[0006] (4) The purpose and requirements of mine blasting change over time, and the blasting parameters must also change over time;

[0007] (5) As the equipment configuration and process of the downstream production chain of the mine change, the blasting parameters also need to be adjusted. To this end, we propose a customized intelligent blasting management method and system. Summary of the invention

[0008] The purpose of the present invention is to provide a customized intelligent blasting management method and system to solve the problems raised in the above background technology.

[0009] To achieve the above object, the present invention provides the following technical solutions:

[0010] A customized intelligent blasting management method,

[0011] Step 1: Acquisition of site data: The staff needs to conduct a historical data survey of the mining area where intelligent blasting is required, and use drones to take real-life photos of the mining area;

[0012] Step 2: Determine the rock blasting block size classification based on the owner's requirements and the purpose of blasting, determine the properties of the pyrotechnics, and determine the rock block size distribution curve required by the owner.

[0013] Step 2: The drone can transmit the captured data to the computer through wireless data transmission. The computer will collect and pre-process the mine rock data and blasting data to establish a blasting database;

[0014] Step 3: The computer will construct a digital 3D rock model of the blasting area based on the mine rock data;

[0015] Step 4: Transfer the constructed digital 3D rock model and blasting database to BlastSprite software. BlastSprite software can perform preliminary determination of blasting parameters, analyze blasting pile rock grading curve using blasting parameters, analyze blasting pile rock image, and customize blasting parameter analysis.

[0016] Step 5: Actual measurement and analysis of blasted rock fragmentation: All data about rock fragments are input into the blasted rock fragmentation measurement and analysis software, and the blasted rock fragmentation is measured and analyzed through it.

[0017] A customized intelligent blasting management system: comprising a data acquisition module, the data acquisition module is electrically connected to an information processing module through an output, the information processing module is electrically connected to a blasting information acquisition module through an output, the blasting information acquisition module is electrically connected to a three-dimensional model construction module through an output, the three-dimensional model construction module is electrically connected to a key feature extraction module through an output, the key feature extraction module is electrically connected to an intelligent decision-making module through an output, the intelligent decision-making module is electrically connected to a safety risk judgment module through an output, the safety risk judgment module is electrically connected to a blasting risk management module through an output, and the blasting risk management module is electrically connected to a blasting effect evaluation module through an output.

[0018] Further: The BlastSprite software is a blasting rock fragmentation prediction and analysis software. The BlastSprite software relies on the Microsoft.NET 4.0 framework, uses C# as the development language, and is developed using the Visual Studio 2022 platform. The operating environment: .net 4.0framework, operating system: win 7 / 8 / 10 / 11.

[0019] Further: the main page of the blasting rock fragmentation prediction and analysis software includes five major areas: "drawing area", "parameter adjustment area", "prediction result display area", "file marking area" and "software configuration area".

[0020] Furthermore: the drawing area mainly displays three types of graphs, namely "conventional particle size graph", "logarithmic particle size graph" and "histogram".

[0021] Furthermore: the parameter adjustment area mainly adjusts in real time a total of fourteen variable parameters of the rock blocks, including "drilling hole diameter", "maximum block size", "drilling accuracy", "minimum resistance line", "hole spacing", "step height", "blocking length", "explosive consumption per unit", "single hole charging amount", "rock coefficient", "relative weight power", "hole distribution coefficient", "charging coefficient" and "block size".

[0022] Further: The prediction result display area is mainly adjusted according to the parameters of the rock block, and then the "average block size" is obtained through real-time calculation. ","Characteristic block size x0,""Block size distribution unevenness coefficient C u "," Shape coefficient of block size distribution curve C c There are six prediction results in total, including "uniformity index n" and "rock grading small block coefficient S".

[0023] Furthermore: the file marking area mainly records four related elements of the blasting situation, namely "blasting time", "blasting location", "blasting platform" and "blasting number", and the software configuration area is mainly used to import and export various parameter data of rock blocks, consult help documents, and perform multiple configuration operations for the software.

[0024] Further: The blasting rock block size measurement and analysis software is based on the Microsoft.NET 4.0 framework, uses C# as the development language, and is developed using the Visual Studio 2022 platform. The operating environment: net 4.0framework, operating system: win 7 / 8 / 10 / 11.

[0025] Furthermore: the main interface of the blasting rock fragmentation measurement and analysis software is divided into five major areas: "drawing area", "parameter adjustment area", "measurement result display area", "file marking area" and "software configuration area".

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] This customized intelligent blasting management method and system systematically analyzes the quantitative relationship between rock block size distribution curve and energy consumption, work efficiency and blasting parameters of the downstream production chain, develops customized blasting design software, realizes the precision of blasting parameter design, and can change with the changes of mining enterprise sales plan, rock characteristics, explosive performance and equipment and process of downstream production chain. Research and propose blasting effect evaluation indicators directly related to energy consumption and work efficiency of downstream production chain;

[0028] We use advanced technologies such as drone dispatching systems, rock mass 3D scanning modeling and card adjustment to construct mine surface models and mine value models. We comprehensively consider parameters such as ore grade, particle size and rock hardness, and accurately match the models and processes of downstream crushing machinery and equipment to achieve the goal of green mine construction with the lowest crushing energy consumption, highest mining efficiency, highest resource utilization and lowest overall mining cost.

[0029] Through the scientific optimization of process flows such as production planning, blasting design, equipment selection, construction organization, and quality monitoring, a complete accurate construction management system for step blasting has been established, breaking through the technical bottleneck of precise control of blasting quality and low efficiency in connecting related processes, thus improving the level of green production technology in mines. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 It is a schematic diagram of the operation of the present invention;

[0031] Figure 2 It is a schematic diagram of the system flow of the present invention;

[0032] Figure 3 It is a schematic diagram of the arrangement of blasting holes of the present invention;

[0033] Figure 4 This is a diagram of the uneven uncoupled charge structure of the collapse blasting technology of the present invention;

[0034] Figure 5 This is a relationship diagram between the small-pieceness coefficient of the explosive pile rock blocks of the present invention and the unit power consumption of mechanical crushing. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] Embodiment 1:

[0037] See also Figure 1-5 ,The present invention provides a technical solution: a customized intelligent blasting management method, the main tasks of customized blasting design for open-pit mines include: preliminary preparation, rock block curve fitting, preliminary determination of blasting parameters, comparison and determination of blasting parameters in the database, blasthole layout design, charge structure design, blasthole connection design, delay time, sequence setting, detonation point setting, detonation simulation, throwing direction analysis, and generation of blasting design report;

[0038] Step 1: Acquisition of site data: The staff needs to conduct a historical data survey of the mining area where intelligent blasting is required, and use drones to take real-life photos of the mining area;

[0039] Step 2: Determine the rock blasting block size classification based on the owner's requirements and the purpose of blasting, determine the properties of the pyrotechnics, and determine the rock block size distribution curve required by the owner.

[0040] Step 2: The drone can transmit the captured data to the computer through wireless data transmission. The computer will collect and pre-process the mine rock data and blasting data to establish a blasting database;

[0041] Step 3: The computer will build a digital three-dimensional rock model of the blasting area based on the mining rock data. The blast pile image can be obtained through the camera function, or digital image files such as *.jpg, *.bmp, *.png, *.gif can be opened from the hard disk. The image can be adjusted to the best proportion by setting the scale. For ease of setting, the image can be rotated 90°, noise can be removed, and other pre-processing operations can be performed. After the image is adjusted to the best proportion, the rock blocks can be stroked through various tools in the toolbox. During this period, it is necessary to frequently switch various tools to perform multiple repairs on the contour line, such as closing the rock block contour line and filling the background. The blast pile rock blocks after stroke processing need to use a variety of digital image processing technologies such as image thresholding, area marking, and block coloring. This operation requires a short waiting time depending on the image size. After the rock block image is successfully marked, three-dimensional modeling can be performed for each rock block. This model can more intuitively display the three-dimensional effect of the rock block;

[0042] Step 4: Transfer the constructed digital 3D rock model and blasting database to BlastSprite software. BlastSprite software can perform preliminary determination through blasting parameters, analyze blast pile rock block grading curve using blasting parameters, analyze blast pile rock block images, and customize blasting parameter analysis. When the rock blocks are successfully marked, the rock block distribution data of the entire blast pile is obtained. At this time, the results can be displayed in tables or charts to facilitate further analysis of the blasting conditions.

[0043] Step 5: Actual measurement and analysis of blasted rock fragmentation: All data about rock fragments are input into the blasted rock fragmentation measurement and analysis software, and the blasted rock fragmentation is measured and analyzed through it.

[0044] Step blasting design includes: geometric parameters and charge distribution parameter design. Geometric parameters such as Figure 3 As shown, the geometric parameters

[0045] (1) Step height H, m;

[0046] (2) Step surface inclination angle α;

[0047] (3) drilling inclination angle β;

[0048] (4) front resistance line W, m;

[0049] (5) Spacing between blastholes, a, m;

[0050] (6) Blast hole spacing, b, m;

[0051] (7) Width of the top edge of the front row of holes, m;

[0052] (8) Drilling depth L, m;

[0053] (9) Blockage length h0;

[0054] (10) Drilling depth h1;

[0055] (11) Length of lower charge h2;

[0056] (12) Upper charge length h3;

[0057] (13) Allow the maximum resistance line Wm,m;

[0058] (14) Drilling diameter Φ, mm;

[0059] (15) Charge diameter d, mm.

[0060] Drug dispensing parameters

[0061] (1) Single hole burden area S, m2;

[0062] (2) Linear density of lower charge q2, kg / m;

[0063] (3) Linear density of upper charge q3, kg / m;

[0064] (4) Linear density of single charge q1, kg / m;

[0065] (5) Average unit explosive consumption q, kg / m;

[0066] (6) Total charge per hole Q, kg;

[0067] (7) Single hole lower charge Q2, kg;

[0068] (8) Total charge in the upper part of a single hole Q3, kg.

[0069] There are many empirical design methods and they are very common. In many years of engineering practice, the unit consumption control method and the resistance line control method are simple, convenient and have clear physical concepts. The former is mostly used for the design of single charge (fully coupled charge) in the hole, and the latter is mostly used for the design of compound charge (fully coupled charge at the bottom or the uncoupled coefficient is close to 1.0, uncoupled charge at the top, and the charge per meter is half of the charge per meter at the bottom);

[0070] After calculating the preliminary blasting parameters, compare them in the software database to find the best blasting parameters.

[0071] There are generally three types of models that describe the distribution of blast pile rock blocks, namely energy theory model, stress wave theory model and fragmentation distribution function model. After analyzing and comparing the advantages and disadvantages and applicable conditions of the existing fragmentation models, it is considered that the Kuz-Ram model is more reasonable in the analysis of gradation of blast pile rock blocks in step blasting. Its advantages:

[0072] (1) The model establishes a quantitative relationship between various blasting parameters and the fragmentation distribution of blasted rocks, which facilitates the quantitative analysis of these parameters and the fragmentation distribution of blasted rocks.

[0073] (2) The model combines form and numbers, and can directly use the results of mathematical calculations to draw the distribution curve of the rock fragmentation in the blast pile, which is visual and easy to promote and apply.

[0074] (3) The model introduces the concept of rock coefficient, which reflects the influence of rock physics, mechanical properties and rock joints and fissures on the distribution of rock fragments in the blast pile. However, the rock coefficient requires statistical analysis of the physics and rock joints and fissures of the rock at the blasting site, and the error of arbitrary value is large.

[0075] 1. Prediction of rock fragmentation using the Kuz-Ram model

[0076] The Kuz-Ram model is the most widely used blasting effect (blasting pile gradation) prediction model. The model is named after Kuznetsov and Rosin-Rammler. The former model studies the average size of blasting, while the latter studies the distribution characteristics of size.

[0077] 1) Rosin-Rammler curve

[0078] The Rosin-Rammler curve is generally recognized to be able to give a suitable description of the crushing of blasted rocks. The curve expression is:

[0079]

[0080] or

[0081] Where:

[0082] Rsi——Ratio of rock blocks on the sieve, that is, the ratio of rock blocks with a particle size greater than x;

[0083] Rx——Ratio of undersize rock, that is, the ratio of rock with particle size less than x;

[0084] xi——sieve hole size (cm), indicating the maximum particle size of the rock under the sieve or the minimum particle size of the rock on the sieve;

[0085] xe——characteristic size (cm), that is, the size of the block with an undersize accumulation rate of 63.21%. It generally reflects the size of the blast pile ore block.

[0086] n——uniformity index.

[0087] 2) The uniformity index n is a function of the mesh parameters and can be calculated using the following formula:

[0088]

[0089]

[0090] ΔW=e·H (4-5)

[0091] L=HH d (4-6)

[0092] Where: W——minimum resistance line (m);

[0093] Φ——blasthole diameter (mm);

[0094] ΔW – standard error of rock drilling accuracy (m), the average distance of the bottom of the hole from the designed position;

[0095] e——drilling accuracy (%);

[0096] m——spacing factor, hole spacing / minimum resistance line;

[0097] a——hole spacing (m);

[0098] L——length of the explosive package above the bottom plate elevation (m);

[0099] H——step height (m);

[0100] Hd——Drilling hole blocking length (m)

[0101] 3) Kuznetsov equation: V.E. Kuznetsov proposed an equation to express the average block size of the explosion. With explosive energy and rock mass

[0102] Empirical equations related to the physics, mechanical properties and development of joints and fissures:

[0103]

[0104] V0=aWH (4-8)

[0105]

[0106]

[0107] Where: - Average crushing size, which is described in detail as the size of the sieve holes at which 50% of the rocks pass through the sieve and 50% of the rocks remain on the sieve;

[0108] K is the rock coefficient. Its value is related to the physical and mechanical properties of the rock mass and the development of joints and fissures. It can be 4-6 for medium-hard rock with developed joints and fissures, 7-9 for medium-hard rock with undeveloped joints and fissures, 10-11 for hard rock with developed joints and fissures, and 12-14 for hard rock with undeveloped joints and fissures.

[0109] q——explosive consumption per unit (kg / m3);

[0110] V0——the volume of rock crushed per hole (m3);

[0111] Q——TNT equivalent of the energy of each Chinese medicine package (kg);

[0112] Qe——actual charge per hole (kg);

[0113] E——Relative weight power of explosives: 100 for ammonium nitrate explosive, 100-105 for No. 2 rock explosive, 115 for TNT explosive, 115 for ammonium antimony explosive, and 135 for emulsion explosive;

[0114] Substituting (4-8), (4-9), and (4-10) into (4-7), the Kuznetsov equation becomes:

[0115]

[0116] 4) Characteristic size x e Calculation:

[0117] is a point on the Rosin-Rammler curve, that is, when R = 0.5, the corresponding rock fragmentation value. Formula (2-1) becomes:

[0118]

[0119] Therefore:

[0120]

[0121] 2. Prediction Steps

[0122] The above formula derivation combines the Rosin-Rammler curve and the Kuznetsov equation to form the Kuz-Ram mathematical model. How to use it:

[0123] (1) Substitute the actual blasting parameters into equation (4-11) to obtain

[0124] (2) Calculate the value of n from formula (4-3);

[0125] (3) Substitute and n into equation (4-13) to find xe

[0126] (4) With xe, we can use formula (4-1) to calculate the proportion of rock blocks of various particle sizes in the blast pile and draw the blast pile rock particle size distribution curve.

[0127] The characteristic parameters of the rock fragmentation distribution curve of blast pile are widely used in the stone mining of breakwater and rockfill dam. Currently, the commonly used characteristic parameters are fragmentation uniformity index n, non-uniformity coefficient Cu and curvature coefficient Cc.

[0128] 1. Uniformity index n

[0129] The uniformity index n expresses the steepness and curvature of the block distribution line. The value of n is calculated by formula (4-3). From the formula, it can be seen that n is a function of the hole network parameters and has nothing to do with the energy released by the explosives and the physical and mechanical properties of the rock, and the degree of crack development; it is usually taken as 0.8 to 2.2. According to actual experience and formula analysis, the following conclusions can be drawn:

[0130] (1) The larger the n value, the smaller the curvature of the curve, the smoother the curve, the more uniform the size of the blast pile rock, and the less powder ore and oversized rock.

[0131] (2) When the n value is small, the curve is curved and the line is steep. The rock size in the blast pile is uneven, and the rock size in the middle is relatively small, indicating that there are more powder ore and super-large ore. When the n value is less than 0.8, the workload of secondary crushing is too large, so the n value is required to be greater than 0.8.

[0132] (3) The n value decreases as the ratio of the minimum resistance line to the blasthole diameter increases;

[0133] (4) The n value decreases as the ratio of the average distance of the bottom of the borehole from the design to the minimum resistance line increases.

[0134] (5) The value of n increases with the increase of the ratio of charge length to step height.

[0135] (6) The n value increases with the ratio of the hole spacing to the minimum resistance line.

[0136] 2. The uneven coefficient Cu and curvature coefficient Cc of the blast pile rock fragmentation distribution

[0137] The coefficient of unevenness Cu and the coefficient of curvature Cc are widely used in rock mining for rockfill dams.

[0138] (1) Calculation formula of non-uniformity coefficient Cu:

[0139]

[0140] (2) Calculation formula of curvature coefficient Cc:

[0141]

[0142] In the formula: x60, x30, x10 are the block sizes corresponding to the cumulative amount under the sieve of 60%, 30%, and 10%, respectively.

[0143] When the rock fragmentation of the blast pile satisfies the RR distribution, equations (4-14) and (4-15) can be rewritten as follows:

[0144]

[0145]

[0146] (1) For the mining of rockfill materials for rockfill dams, the qualified grade of materials requires a Cu value greater than 10 and a Cc value of 1 to 3.

[0147] (2) It can be seen from equations (4-16) and (4-17) that the size of Cu and Cc values ​​is only related to the change of the blasting block uniformity index n.

[0148] After a large number of on-site bench blasting tests, we changed the blasting parameters, analyzed the relationship between the size and distribution of the rock in the blast pile and the power consumption of mechanical crushing, and intuitively found that when the proportion of small-sized rocks in the blast pile is large, the power consumption of mechanical crushing tends to decrease. Further data analysis verified the above intuitive findings. Therefore, the concept of the small-size coefficient of blast pile rock is proposed.

[0149] 1. Concept of small fragmentation coefficient of blast pile rock

[0150] The small-block coefficient of blast pile rock refers to the percentage of small-block rock in the blast pile rock to the entire blast pile rock. Calculation formula:

[0151]

[0152] Where:

[0153] RM——The maximum rock ratio required under the screen, that is, the ratio of rock blocks with a size less than the maximum size xm;

[0154] R0.6M——The ratio of the maximum rock blocks under the screen is 60%, that is, the ratio of the rock blocks with a size less than 0.6*xm;

[0155] R0.5——The ratio of undersize powder, that is, the ratio of rock blocks with a particle size of less than 0.5 cm;

[0156] 2. Engineering Application

[0157] The mining depth of a large-scale sand and gravel aggregate mine is +249.72m~+6m. The production scale is 4.74 million cubic meters / year (about 12.27 million tons / year). It is mainly composed of crystalline glassy tuff, rhyolite porphyry and sedimentary tuff.

[0158] 1) Requirements for step blasting

[0159] The purpose of blasting in this project is to provide qualified blocks of stone, and the rate of large blocks cannot exceed 3% (blocks above 800mm are large blocks).

[0160] 2) Blasting parameters

[0161] Charge structure such as ( Figure 4 ), the deep hole is divided into upper and lower parts for charging, and the charge amount per meter in the lower section is 1.2 to 2.2 times that of the charge amount per meter in the upper section (different charging diameters in the upper and lower sections).

[0162] Typical blasting parameters are shown in the table:

[0163]

[0164] 3) Mechanical crushing process

[0165] The primary crushing consists of two PG4265 gyratory crushers with a capacity of 1,500 tons per hour, the secondary crushing consists of two HP500 cone crushers with a capacity of 750 tons per hour and two CS660 cone crushers with a capacity of 750 tons per hour, the fine crushing equipment consists of HP500 cone crushers and CS660 cone crushers with a capacity of 5,700 tons per hour, and the sand making equipment is a B9100SE vertical shaft crusher with a capacity of 360 tons per hour.

[0166] 4) Impact of small-particle coefficient of blast pile on operating costs

[0167] After one year of blasting tests, the total amount of crushing, electricity consumption and explosives used were calculated each month (see Table 4.4).

[0168] Table 4.4 Total crushing volume, power consumption and explosives consumption

[0169]

[0170] 4.3. Relationship between the small-size coefficient of blast pile rock grading and the power consumption of mechanical crushing of rocks

[0171] After calculation and data fitting, the relationship between the unit power consumption D (kWh / ton) of mechanical crushing and the small block coefficient s of the blast pile rock was obtained (Formula (4-19)) and Figure 5 .

[0172] D=-0.029s+3.9989

[0173] R=0.7335

[0174] As can be seen from the figure:

[0175] (1) The small-pieceness coefficient of the blast pile rock is inversely proportional to the unit power consumption of rock mechanical crushing, with a correlation of 0.7335, and the fitting curve is highly correlated;

[0176] (2) The larger the small-pieceness coefficient of the blasted rock, the smaller the unit power consumption of the rock mechanical crushing;

[0177] (3) If the small-piece coefficient is increased from 50% to 60%, the mechanical crushing process can save 0.29 kWh of electricity per ton of stone

[0178] A customized intelligent blasting management system: comprising a data acquisition module, the data acquisition module is electrically connected to an information processing module through an output, the information processing module is electrically connected to a blasting information acquisition module through an output, the blasting information acquisition module is electrically connected to a three-dimensional model construction module through an output, the three-dimensional model construction module is electrically connected to a key feature extraction module through an output, the key feature extraction module is electrically connected to an intelligent decision-making module through an output, the intelligent decision-making module is electrically connected to a safety risk judgment module through an output, the safety risk judgment module is electrically connected to a blasting risk management module through an output, and the blasting risk management module is electrically connected to a blasting effect evaluation module through an output.

[0179] Among them, preferably, the BlastSprite software is a blasting rock fragmentation prediction and analysis software. The BlastSprite software relies on the Microsoft.NET 4.0 framework, uses C# as the development language, and is developed using the Visual Studio 2022 platform. The operating environment: .net 4.0framework, operating system: win 7 / 8 / 10 / 11.

[0180] Preferably, the main page of the blasting rock fragmentation prediction and analysis software includes five major areas: "drawing area", "parameter adjustment area", "prediction result display area", "file marking area" and "software configuration area".

[0181] Preferably, the drawing area mainly displays three types of graphs, namely, "conventional particle size graph", "logarithmic particle size graph" and "histogram".

[0182] Embodiment 2:

[0183] Reference Figure 1 , this embodiment is different from the first embodiment in that: the parameter adjustment area mainly adjusts the fourteen variable parameters of the rock block, namely, "drilling hole diameter", "maximum block size", "drilling accuracy", "minimum resistance line", "hole spacing", "step height", "blocking length", "explosive consumption", "single hole charge", "rock coefficient", "relative weight power", "hole distribution coefficient", "charge coefficient" and "block size" in real time; the prediction result display area mainly performs real-time calculation based on the parameters of the rock block after adjustment to obtain the "average block size" ","Characteristic block size x0,""Block size distribution unevenness coefficient C u "," Shape coefficient of block size distribution curve C c ”, “uniformity index n” and “rock grading small block coefficient S” for a total of six prediction results; the file marking area mainly records the four related elements of the blasting situation, namely “blasting time”, “blasting location”, “blasting platform” and “blasting number”. The software configuration area is mainly used to import and export various parameter data of rock blocks, consult help documents, and perform multiple configuration operations on the software; the blasting rock block size measurement and analysis software is based on the Microsoft.NET 4.0 framework, uses C# as the development language, and is developed using the Visual Studio 2022 platform. The operating environment: net4.0framework, operating system: win 7 / 8 / 10 / 11; the main interface of the blasting rock block size measurement and analysis software is divided into 5 major blocks: “drawing area”, “parameter adjustment area”, “measurement result display area”, “file marking area” and “software configuration area”.

[0184] The electrical appliances mentioned in this article are all connected to an external power source through wires.

[0185] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A customized intelligent blasting management method, characterized by: Step 1: Acquisition of site data: The staff needs to conduct a historical data survey of the mining area where intelligent blasting is required, and use drones to take real-life photos of the mining area; Step 2: According to the requirements of the owner and the purpose of blasting, determine the rock blasting block size classification, determine the properties of the pyrotechnics, and determine the rock block size distribution curve required by the owner; Step 2: The drone can transmit the captured data to the computer through wireless data transmission. The computer will collect and pre-process the mine rock data and blasting data to establish a blasting database; Step 3: The computer will construct a digital 3D rock model of the blasting area based on the mine rock data; Step 4: Transfer the constructed digital 3D rock model and blasting database to BlastSprite software. BlastSprite software can perform preliminary determination of blasting parameters, analyze blasting pile rock grading curve using blasting parameters, analyze blasting pile rock image, and customize blasting parameter analysis. Step 5: Explosion rock fragmentation measurement and analysis: All the data about the rock fragments are input into the blasting rock fragmentation measurement and analysis software, and the blasting rock fragmentation is measured and analyzed through it; A customized intelligent blasting management system: comprising a data acquisition module, the data acquisition module is electrically connected to an information processing module through an output, the information processing module is electrically connected to a blasting information acquisition module through an output, the blasting information acquisition module is electrically connected to a three-dimensional model construction module through an output, the three-dimensional model construction module is electrically connected to a key feature extraction module through an output, the key feature extraction module is electrically connected to an intelligent decision-making module through an output, the intelligent decision-making module is electrically connected to a safety risk judgment module through an output, the safety risk judgment module is electrically connected to a blasting risk management module through an output, and the blasting risk management module is electrically connected to a blasting effect evaluation module through an output.

2. A customized intelligent blasting management method according to claim 1, characterized in that: The BlastSprite software is a blasting rock fragmentation prediction and analysis software. The BlastSprite software relies on the Microsoft.NET 4.0 framework, uses C# as the development language, and is developed using the VisualStudio 2022 platform. The operating environment: .net 4.0framework, operating system: win 7 / 8 / 10 / 11.

3. A customized intelligent blasting management method according to claim 2, characterized in that: The main page of the blasting rock fragmentation prediction and analysis software includes five major areas: "drawing area", "parameter adjustment area", "prediction result display area", "file marking area" and "software configuration area".

4. A customized intelligent blasting management method according to claim 3, characterized in that: The drawing area mainly displays three types of graphs: "conventional particle size graph", "logarithmic particle size graph" and "histogram".

5. A customized intelligent blasting management method according to claim 3, characterized in that: The parameter adjustment area is mainly for real-time adjustment of fourteen variable parameters including "drilling hole diameter", "maximum block size", "drilling accuracy", "minimum resistance line", "hole spacing", "step height", "blocking length", "explosive consumption per unit", "single hole charging amount", "rock coefficient", "relative weight power", "hole distribution coefficient", "charging coefficient" and "block size".

6. A customized intelligent blasting management method according to claim 3, characterized in that: The prediction result display area is mainly based on the parameters of the rock block, and real-time calculation is performed to obtain the "average block size" ", "characteristic block size x0", "block size distribution unevenness coefficient C u "、"The shape coefficient of the blockiness distribution curve C c ”, “uniformity index n” and “rock grading small block coefficient S”, a total of six prediction results.

7. A customized intelligent blasting management method according to claim 3, characterized in that: The file marking area is mainly used to record the four relevant elements of the blasting situation, namely "blasting time", "blasting location", "blasting platform" and "blasting number". The software configuration area is mainly used to import and export various parameter data of rock blocks, consult help documents, and perform multiple configuration operations for the software.

8. The customized intelligent blasting management method according to claim 1, characterized in that: The blasting rock fragmentation measurement and analysis software is based on the Microsoft.NET 4.0 framework, uses C# as the development language, and is developed using the Visual Studio 2022 platform. The operating environment: net 4.0framework, operating system: win 7 / 8 / 10 / 11.

9. A customized intelligent blasting management method according to claim 1, characterized in that: The main interface of the blasting rock fragmentation measurement and analysis software is divided into five major areas: "drawing area", "parameter adjustment area", "measurement result display area", "file marking area" and "software configuration area".

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