A method for predicting the utilization rate of blast holes in a mine

Abstract

The present invention discloses a method for predicting the utilization rate of blast holes in a mine, comprising the following steps: obtaining blasting design parameters; based on the blasting design parameters, conducting a blasting test to obtain the utilization rate of blast holes after blasting; based on the utilization rate of blast holes, using statistical methods to analyze the variation characteristics of blasting parameters in the dimension of mine characteristic parameters, and obtaining the objective law of mine blasting by constructing a blasting database system; based on the objective law of mine blasting, obtaining a prediction model for the utilization rate of blast holes; inputting the data to be measured into the prediction model for the utilization rate of blast holes to obtain the prediction result of the utilization rate of blast holes. The prediction of the present invention has high accuracy and strong practicability.

Description

Technical Field

[0001] The present invention belongs to the technical field of mine blasting, and particularly relates to a method for predicting the utilization rate of blast holes in mine blasting. Background Art

[0002] Mine blasting is a commonly used means for mining mineral resources at home and abroad. However, there are problems such as high cost, low blasting efficiency, and large potential safety hazards in blasting mining. Therefore, reducing blasting costs, improving blasting quality, and enhancing the safety factor of blasting operations have always been the main research directions in mine blasting mining.

[0003] Traditional blasting operation methods basically all use traditional measurement methods to obtain blast area parameters, and then rely on experience to calculate the utilization rate of blast holes and the charge amount. This often leads to difficulties in accurately predicting the utilization rate of blast holes, unreasonable hole layout plans, and poor fragmentation effects. In addition, there are many and complex factors affecting the utilization rate of blast holes, and it is very difficult for traditional blasting operation methods to reasonably determine the key indicators affecting the blasting utilization rate. Summary of the Invention

[0004] Aiming at the deficiencies of the prior art, the present invention proposes a method for predicting the utilization rate of blast holes in mine blasting, which has high prediction accuracy and strong practicability.

[0005] To achieve the above object, the present invention provides the following solution:

[0006] A method for predicting the utilization rate of blast holes in mine blasting, comprising the following steps:

[0007] Obtain blasting design parameters;

[0008] Based on the blasting design parameters, conduct a blasting test to obtain the utilization rate of blast holes after blasting;

[0009] Based on the utilization rate of blast holes, use statistical methods to analyze the variation characteristics of blasting parameters in the dimension of mine characteristic parameters. By constructing a blasting database system, obtain the objective laws of mine blasting. Based on the objective laws of mine blasting, obtain a prediction model for the utilization rate of blast holes;

[0010] Input the data to be measured into the prediction model for the utilization rate of blast holes to obtain the prediction result of the utilization rate of blast holes.

[0011] Preferably, the blasting design parameters include: drilling equipment, blast hole layout parameters, blasting parameters, material consumption and cost, and drilling efficiency.

[0012] Preferably, the method for conducting a blasting test based on the blasting design parameters to obtain the utilization rate of blast holes after blasting includes:

[0013] Based on the blasting design parameters, blast holes are designed on the surface of the pre-blasted mine blasting area;

[0014] Each blast hole forms a blast hole network. After the blast holes are drilled, the hole spacing and hole radius of the blast holes are detected;

[0015] Based on the hole spacing and the hole radius, the hole utilization rate after blasting is obtained.

[0016] Preferably, the method for obtaining the hole utilization rate after blasting based on the hole spacing includes:

[0017] Determine the hole spacing and row spacing of the blast holes;

[0018] Based on the blast hole spacing and the row spacing, the area of the blasting area is obtained;

[0019] Obtain the compressive strength of the rock in the blasting area;

[0020] Based on the compressive strength of the rock in the blasting area, study whether the damage degree of the explosive can meet the requirements, and obtain the superimposed stress in the blasting area;

[0021] Based on the area of the blasting area and the superimposed stress in the blasting area, obtain the arrangement method of the blast holes;

[0022] Based on the arrangement method of the blast holes, obtain the length of the blast holes filled with explosives and the total length of the blast holes;

[0023] Based on the length of the blast holes filled with explosives and the total length of the blast holes, obtain the hole utilization rate after blasting.

[0024] Preferably, the method for obtaining the hole utilization rate after blasting based on the hole radius includes:

[0025] Obtain the blast hole arrangement form;

[0026] Based on the blast hole arrangement form, obtain the compressive strength reached by the rock stress within the blasting radius of each blast hole;

[0027] Based on the compressive strength reached by the rock stress within the blasting radius of each blast hole, determine the effective area of the blast hole blasting;

[0028] Based on the effective area of the blast hole blasting, obtain the hole utilization rate after blasting.

[0029] Preferably, the method for analyzing the variation characteristics of blasting parameters in the dimension of mine characteristic parameters by using statistical methods and obtaining the objective laws of mine blasting through constructing a blasting database system includes:

[0030] Select the topography of the blasting area, the physical and mechanical properties and geological structure characteristics of the ore and rock in the blasting area, and the explosive explosion performance as the data analysis objects;

[0031] By combining the data analysis object with the advantages of precise positioning of RTK technology, through the analysis of various factors affecting the blasting effect, the dynamic and precise acquisition of on-site terrain parameters and actual blast hole parameters is completed, and real-time adjustment and optimization are carried out to achieve the integration of precise positioning and blasting design, and then the objective laws of mine blasting are obtained.

[0032] Preferably, the method for obtaining the prediction model of blast hole utilization rate based on the objective laws of mine blasting includes:

[0033] Collect the objective laws of mine blasting and their corresponding influencing factor parameters, and the influencing factor parameters include blasting design parameters and mine mechanical parameters;

[0034] Conduct a sensitivity analysis of the influencing factor parameters using the MIV algorithm to screen out the main influencing parameters of the objective laws of mine blasting;

[0035] Take the main influencing parameters of the objective laws of mine blasting as input values and the objective laws of mine blasting as output values to establish an LSTM neural network prediction model, and conduct training and testing;

[0036] Use the PSO algorithm to optimize the weights and biases of the LSTM neural network prediction model to improve the prediction accuracy;

[0037] Based on the neural network prediction model optimized by training and testing, establish a prediction model of blast hole utilization rate to achieve the prediction of blast hole utilization rate.

[0038] Preferably, the LSTM neural network prediction model includes: an input layer, a hidden layer, and an output layer;

[0039] The input layer is used to input the main influencing parameters of the objective laws of mine blasting and sort them in chronological order;

[0040] The hidden layer is used to iteratively learn the short-term and long-term semantic features of time series data;

[0041] The output layer is used to output the prediction result;

[0042] The LSTM neural network also includes LSTM network parameters;

[0043] The LSTM network parameters include the learning rate, the number of iterations, and the stepsize.

[0044] Compared with the prior art, the beneficial effects of the present invention are:

[0045] The present invention provides a method for predicting the utilization rate of blast holes in a mine, which includes obtaining blasting design parameters; conducting a blasting test based on the blasting design parameters to obtain the utilization rate of blast holes after blasting; analyzing the variation characteristics of blasting parameters in the dimension of mine characteristic parameters based on the utilization rate of blast holes, obtaining the objective law of mine blasting by constructing a blasting database system, and obtaining a prediction model for the utilization rate of blast holes based on the objective law of mine blasting; inputting the data to be measured into the prediction model for the utilization rate of blast holes to obtain the prediction result of the utilization rate of blast holes. The prediction method of the present invention has high prediction accuracy and strong practicability. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions of the present invention, the accompanying drawings required for use in the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can also obtain other drawings based on these drawings without creative efforts.

[0047] Figure 1 is a schematic flow chart of a method for predicting the utilization rate of blast holes in a mine according to an embodiment of the present invention;

[0048] Figure 2 is a schematic structural diagram of a blasting database system according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0049] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, rather than all, of the embodiments of the present invention. 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 protection scope of the present invention.

[0050] In order to make the above objects, features, and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0051] Embodiment 1

[0052] As Figure 1 shown, the present invention provides a method for predicting the utilization rate of blast holes in a mine, including the following steps:

[0053] Obtain blasting design parameters;

[0054] Based on the blasting design parameters, conduct a blasting test to obtain the utilization rate of blast holes after blasting;

[0055] Based on the blasthole utilization rate, statistical methods are used to analyze the variation characteristics of blasting parameters under the dimension of mine characteristic parameters. By building a blasting database system, the objective laws of mine blasting are obtained. Based on the objective laws of mine blasting, a blasthole utilization prediction model is obtained.

[0056] The data to be tested is input into the blasthole utilization rate prediction model to obtain the prediction result of blasthole utilization rate.

[0057] In this embodiment, the blasting design parameters include: drilling equipment, blasthole layout parameters, blasting parameters, material consumption and cost, and drilling efficiency.

[0058] Drilling equipment includes: rotary drills and open-pit down-the-hole drills. The rotary drills are driven by electricity or internal combustion, and are crawler-driven, top-rotating, continuously pressurized, and use compressed air to remove slag. They are equipped with dry or wet dust removal systems and use rotary drill bits as rock drilling tools. The open-pit down-the-hole drill uses an impactor that dives into the hole and directly impacts the drill bit, while the rotary machine is outside the hole, driving the drill rod to rotate and drilling into the ore and rock.

[0059] Blast hole layout parameters: Design the hole spacing and row spacing in the blasting area and increase the density according to the surrounding rock strength.

[0060] Blasting parameters: if the number of blastholes is increased by one, using a 250-tooth roller drill and drilling a hole of 15m, the charge of one blasthole in the blasting area will increase by 300-500kg, the blasting effect will be improved, the rate of large blocks will be reduced, and the utilization rate of the explosives in the blastholes will be increased.

[0061] Material consumption and cost: consumption of explosives, loss of drilling equipment, etc.

[0062] Factors affecting drilling efficiency: step height, step slope angle: generally 60°~75°, slope top line and slope bottom line, chassis resistance line, over-depth: depth beyond the step bottom plate, hole spacing and row spacing, hole edge distance (slope safety distance), charging length and blocking length.

[0063] In this embodiment, based on the blasting design parameters, a blasting test is performed to obtain the blasthole utilization rate after blasting, which includes:

[0064] Based on the blasting design parameters, the blasting area drilling holes are designed on the surface of the pre-blasted mine blasting area;

[0065] Each blast hole forms a blast hole network, and the hole spacing and hole radius of the blast holes are tested after the blast holes are drilled;

[0066] Based on the hole spacing and hole radius, the blasthole utilization rate after blasting is obtained.

[0067] In this embodiment, based on the hole spacing, the method for obtaining the blasthole utilization rate after blasting includes:

[0068] Determine the hole spacing and row spacing of the blast holes;

[0069] Based on the hole spacing and row spacing, obtain the area of the blasting area;

[0070] Obtain the compressive strength of the rock in the blasting area;

[0071] Based on the compressive strength of the rock in the blasting area, study whether the degree of damage of the explosive can meet the requirements, and obtain the superimposed stress in the blasting area;

[0072] Based on the area of the blasting area and the superimposed stress in the blasting area, obtain the arrangement method of the blast holes;

[0073] Based on the arrangement method of the blast holes, obtain the length of the blast holes filled with explosives and the total length of the blast holes;

[0074] Based on the length of the blast holes filled with explosives and the total length of the blast holes, obtain the hole utilization rate after blasting.

[0075] Specifically, when the value range of the hole spacing a of the blast holes is R~2R and the row spacing W<R, the double-hole blasting fracture zone covers all the rock media in the single-hole blasting area. At this time, the area of the single-hole blasting area is S = aw. To study whether the degree of damage of the explosive can meet the requirements, the row spacing W of the stress superposition during double-hole blasting should be lower than the radius R. When W<R<a, the area of the single-hole blasting area is S = aW, and the double-hole blasting fragmentation zone just covers all the rock masses in the single-hole blasting area. The superposition of the double-hole blasting fragmentation zones reaches the rock fragmentation bearing capacity. At this time, it can be considered that the rocks in the explosion influence area of the blast holes are all fragmented. Therefore, determine the value of a with the maximum value of S. From the geometric relationship, a = 1.23R can be obtained; substituting the effective blasting radius R = 1.48m, then a = 1.82m, so the row spacing W = 1.175m.

[0076] In this embodiment, the method for obtaining the hole utilization rate after blasting based on the blast hole radius includes:

[0077] Obtain the blast hole arrangement form;

[0078] Based on the blast hole arrangement form, obtain the compressive strength reached by the rock stress within the blasting radius of each blast hole;

[0079] Based on the compressive strength reached by the rock stress within the blasting radius of each blast hole, determine the effective area of the blast hole blasting;

[0080] Based on the effective area of the blast hole blasting, obtain the hole utilization rate after blasting.

[0081] Specifically, taking the multi-row blast hole layout as the research object, the double-row rectangular blast hole layout and the double-row triangular blast hole layout are analyzed respectively. During the blasting of the double-row rectangular blast holes and the double-row triangular blast holes, the rock stress within the blasting radius of each blast hole reaches the ultimate compressive strength, indicating that all the rock in this area is broken. According to the research, outside the blasting influence range, the stress decreases layer by layer; under the combined action of the stress waves at the ends of the two rows, the stress in some areas also reaches the compressive strength, resulting in rock fragmentation. Based on the influence ranges of the two layout methods, the effective areas of the double-row blast holes with triangular distribution and rectangular distribution are 27.43 and 28.30 m 2 . Since the row spacing of the triangular blast hole distribution is 1.57 m and the row spacing of the rectangular blast hole distribution is 1.82 m, it follows that the effective blasting area of the double-row rectangular blast hole layout is 3.11% larger than that of the double-row triangular blast hole layout.

[0082] In this embodiment, the method of using statistical methods to analyze the variation characteristics of blasting parameters in the dimension of mine characteristic parameters and obtaining the objective laws of mine blasting by constructing a blasting database system includes:

[0083] Selecting the topography of the blast area, the physical and mechanical properties and geological structure characteristics of the ore and rock in the blast area, and the explosive performance as the data analysis objects;

[0084] Combining the data analysis objects with the advantages of precise positioning by RTK technology, analyzing various factors affecting the blasting effect, completing the dynamic and precise acquisition of on-site terrain parameters and actual blast hole parameters, and adjusting and optimizing in real time to achieve the integration of precise positioning and blasting design, thereby obtaining the objective laws of mine blasting.

[0085] Specifically, the stope database of this blasting software is designed using the database product Access of Microsoft Corporation. As a powerful MIS system development tool, it has the characteristics of a friendly interface, easy to learn and use, simple development, and flexible interfaces. Since the data processing of this software is not much and the speed requirement is not very strict, using an Access database as the background database can fully meet the needs. The database structure is as Figure 2 shown.

[0086] Main functions of the database: - According to the coordinate data actually measured on-site in each stope, the computer automatically generates, stores, and outputs various terrain lines in real time according to attributes, and stores the coordinates of the actually measured points on the stope surface and various geological attribute parameters of the ore and rock in each area (such as ore and rock types, physical and mechanical properties, and geological structure characteristic parameters, etc.) in the form of a table in the database; - During the blasting design process, it can automatically query, identify, and calculate and process the ore and rock types, distribution ranges, volumes, and various physical and mechanical property parameters in a given area of the stope; - Automatically query and process graphic objects (including drawing lines and graphics, etc.) according to the instructions sent by each functional module of the blasting design, and automatically perform corresponding graphic boundary processing and statistical analysis and calculation related to graphic attributes.

[0087] In this embodiment, the method for obtaining the prediction model of the hole utilization rate based on the objective laws of mine blasting includes:

[0088] Collect the objective laws of mine blasting and their corresponding influencing factor parameters. The influencing factor parameters include blasting design parameters and mine mechanical parameters;

[0089] Perform sensitivity analysis of the influencing factor parameters using the MIV algorithm to screen out the main influencing parameters of the objective laws of mine blasting;

[0090] Take the main influencing parameters of the objective laws of mine blasting as input values and the objective laws of mine blasting as output values to establish an LSTM neural network prediction model, and perform training and testing;

[0091] Use the PSO algorithm to optimize the weights and biases of the LSTM neural network prediction model to improve the prediction accuracy;

[0092] Based on the neural network prediction model optimized by training and testing, establish a prediction model for the hole utilization rate to achieve the prediction of the hole utilization rate.

[0093] Specifically, the sensitivity analysis of the MIV algorithm includes the following steps: (1) Construct a BP neural network model, take the objective laws of mine blasting as the output quantity, and the influencing factor parameters as the input quantity to train and test the BP neural network model; (2) Increase and decrease a certain influencing factor parameter, keep the other influencing factor parameters unchanged, and use all the influencing factor parameter data as the input quantity to train the BP neural network model to obtain the output quantity; (3) Calculate the average influence value MIV corresponding to the adjusted parameter according to the output quantity, compare the MIV values of each influencing factor parameter, and screen out the main influencing parameters.

[0094] Specifically, the LSTM neural network prediction model includes: an input layer, a hidden layer, and an output layer;

[0095] The input layer is used to input the main influencing parameters of the objective laws of mine blasting and sort them in chronological order;

[0096] The hidden layer is used to iteratively learn the short-term and long-term semantic features of time series data;

[0097] The output layer is used to output the prediction result;

[0098] The LSTM neural network also includes LSTM network parameters;

[0099] The LSTM network parameters include the learning rate, the number of iterations, and the stepsize.

[0100] The embodiments described above are only descriptions of the preferred embodiments of the present invention, and do not limit the scope of the present invention. Without departing from the design spirit of the present invention, various deformations and improvements made by those of ordinary skill in the art to the technical solutions of the present invention shall fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for predicting the utilization rate of mine blasting holes, characterized in that: It includes the following steps: Obtain blasting design parameters; Based on the blasting design parameters, conduct a blasting test to obtain the hole utilization rate after blasting; Based on the hole utilization rate, use statistical methods to analyze the variation characteristics of blasting parameters in the dimension of mine characteristic parameters. By constructing a blasting database system, obtain the objective laws of mine blasting. Based on the objective laws of mine blasting, obtain a prediction model for the hole utilization rate; Input the data to be measured into the prediction model for the hole utilization rate to obtain the prediction result of the hole utilization rate; The method for conducting a blasting test based on the blasting design parameters to obtain the hole utilization rate after blasting includes: Based on the blasting design parameters, design blast holes on the surface of the pre-blast mine blast area; Each blast hole forms a blast hole network. After the blast holes are drilled, detect the hole spacing and hole radius of the blast holes; Based on the hole spacing and the hole radius, obtain the hole utilization rate after blasting; The method for obtaining the hole utilization rate after blasting based on the hole spacing includes: Determine the hole spacing and row spacing of the blast holes; Based on the hole spacing and the row spacing, obtain the area of the blast area; Obtain the compressive strength of the rock in the blast area; Based on the compressive strength of the rock in the blast area, study whether the degree of damage of the explosive can meet the requirements, and obtain the superimposed stress in the blast area; Based on the area of the blast area and the superimposed stress in the blast area, obtain the layout method of the blast holes; Based on the layout method of the blast holes, obtain the length of the blast holes filled with explosives and the total length of the blast holes; Based on the length of the blast holes filled with explosives and the total length of the blast holes, obtain the hole utilization rate after blasting; When the value range of the hole spacing a of the blast hole is R~2R and the row spacing W<R, the double-hole blast fracture zone covers all the rock media in the single-hole blast area. At this time, the area of the single-hole blast area is S = aw; study whether the degree of damage of the explosive can meet the requirements. The row spacing W of the stress superposition during double-hole blasting should be lower than the radius R; when W<R<a, the area of the single-hole blast area is S = aW, and the double-hole blast fragmentation zone just covers all the rock masses in the single-hole blast area. The superposition of the double-hole blast fragmentation zone reaches the rock fragmentation bearing capacity; at this time, it is considered that all the rocks in the blast hole explosion influence area are fragmented; therefore, determine the value of a with the maximum value of S. From the geometric relationship, a = 1.23R; substituting the effective blast radius R = 1.48m, then a = 1.82m, so the row spacing W = 1.175m.

2. The method for predicting the utilization rate of mine blasting holes according to claim 1, characterized in that: The blasting design parameters include: drilling equipment, blast hole layout parameters, blasting parameters, material consumption and cost, and drilling efficiency.

3. The method for predicting the utilization rate of mine blasting holes according to claim 1, characterized in that: The method for obtaining the hole utilization rate after blasting based on the hole radius includes: Obtain the blast hole layout form; Based on the blast hole layout form, obtain the compressive strength reached by the rock stress within the blast radius of each blast hole; Based on the compressive strength reached by the rock stress within the blast radius of each blast hole, determine the effective area of the blast hole blasting; Based on the effective area of the blast hole blasting, obtain the hole utilization rate after blasting.

4. The method for predicting the utilization rate of mine blasting holes according to claim 1, characterized in that: The method for using statistical methods to analyze the variation characteristics of blasting parameters in the dimension of mine characteristic parameters and obtaining the objective laws of mine blasting by constructing a blasting database system includes: The topography of the blasting area, the physical and mechanical properties and geological structural characteristics of the ore and rock in the blasting area, and the blasting performance of explosives were selected as the data analysis objects; Combining the data analysis object with the advantages of precise positioning of RTK technology, through analyzing various factors affecting the blasting effect, the dynamic and precise collection of on-site terrain parameters and actual blasthole parameters is completed, and real-time adjustment and optimization are carried out to achieve the integration of precise positioning and blasting design, and then obtain the objective laws of mine blasting.

5. The method for predicting mine blasting hole utilization rate according to claim 1, characterized in that: Based on the objective law of mine blasting, the method for obtaining the blasthole utilization rate prediction model includes: Collect objective laws of mine blasting and their corresponding influencing factor parameters, including blasting design parameters and mine mechanics parameters; Conduct MIV algorithm sensitivity analysis on influencing factor parameters and screen out the main influencing parameters of the objective laws of mine blasting; Taking the main influencing parameters of the objective laws of mine blasting as input values ​​and the objective laws of mine blasting as output values, an LSTM neural network prediction model is established, and training and testing are carried out; Use the PSO algorithm to optimize the weights and biases of the LSTM neural network prediction model to improve prediction accuracy; Based on the neural network prediction model optimized after training and testing, a blasthole utilization prediction model is established to realize blasthole utilization prediction.

6. The method for predicting the utilization rate of mine blasting holes according to claim 5, characterized in that: The LSTM neural network prediction model includes: an input layer, a hidden layer and an output layer; The input layer is used to input the main influencing parameters of the objective laws of mine blasting and sort them in chronological order; The hidden layer is used to iteratively learn the short-range and long-range semantic features of the time series data; The output layer is used to output the prediction result; The LSTM neural network also includes LSTM network parameters; The LSTM network parameters include learning rate, number of iterations and stepsize.

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