Quantitative evaluation method for blasting effect

Abstract

The invention belongs to the technical field of open-pit mining of mines, and particularly discloses a quantitative evaluation method for a blasting effect, which comprehensively considers key indexes such as punching rate, inbound boulder rate, ore particle size distribution and root rate, and finally evaluates the blasting effect of a muck pile through the comprehensive score of each index, so as to realize optimization of punching blasting design and construction process, and improve the blasting effect of the muck pile. Therefore, the blasting effect is improved, comprehensive and objective evaluation of the blasting effect is achieved, limitation of single index evaluation is effectively avoided, automation of the evaluation process is achieved through assistance of the intelligent management and control platform, the efficiency of evaluation work is remarkably improved, and the influence of human factors on the evaluation result is reduced. The accuracy and the reliability of the evaluation result are ensured, a quantitative evaluation reference is provided for the quality of the blasting effect, the condition of poor blasting effect can be identified in time, and the design and the construction process of perforation blasting are optimized in time, so that the blasting effect is remarkably improved, the production cost is effectively reduced, and the production efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of open-pit mining in mines, and specifically discloses a quantitative evaluation method for blasting effect. Background Art

[0002] Blasting mining is a widely used and efficient mining method in open-pit mines. Its principle is to use the explosive effect of explosives to break the ore body. Blasting work is an important link in the mining process of open-pit mines. As a core technical parameter in the mining field, the quality of blasting has an important impact on the production efficiency and production cost of other technological links such as shoveling, transportation, and ore dressing in mines, and directly affects the subsequent shoveling process of ore and the overall mining efficiency. Therefore, the design of blasting parameters and the evaluation of blasting quality are the basis for other operations and an important way to reduce the comprehensive mining cost and ensure the safe and efficient operation of mines.

[0003] The traditional evaluation of blasting effect mainly relies on manual observation and empirical judgment. This method has significant subjectivity and is difficult to achieve precise quantification. Summary of the Invention

[0004] To solve the problems in the background art, the present invention discloses a quantitative evaluation method for blasting effect. By means of video intelligent monitoring technology, intelligent algorithm for ore particle size entering the mine, and unmanned aerial vehicle inspection technology, a blasting effect evaluation model is established, and various evaluation indicators are comprehensively considered to obtain a quantitative evaluation result, analyze and evaluate the blasting effect after blasting, realize the standardization and automation of evaluation, ensure the accuracy and credibility of evaluation, and provide a powerful tool for the refined management of mine mining.

[0005] To achieve the above invention purpose, the present invention adopts the following technical solutions: A quantitative evaluation method for blasting effect conducts quantitative analysis based on four evaluation indicators: punching rate, large block rate entering the station, ore particle size distribution, and rock root rate, so as to achieve the precise evaluation of the blasting effect, and includes the following steps: (1) Use video dynamic artificial intelligence recognition technology to measure the punching rate of the blasting area, and upload the data to the intelligent control platform for processing. Among them, the punching rate is the ratio of the number of punched holes to the total number of holes in the blasting area; (2) Use the intelligent algorithm for ore particle size entering the mine to scan and analyze the longest side and area of the ore in the blasting area, and then calculate the ore particle size, determine the large block rate and particle size distribution characteristics of the ore, and then upload the obtained data to the intelligent control platform. Among them, the large block rate entering the station is the ratio of the area of large blocks above 1 m on the ore trucks entering the station to the sum of the area of the scanning and recognition area; the ore particle size distribution can be calculated through the D80 interval of the ore particle size; the rock root rate is realized by calculating the number of rock roots; (3) Use a drone to conduct inspection scans on the rock roots in the blasting area, count the number of rock roots, and upload the obtained data to the intelligent control platform. The rock root rate refers to the number of rock roots. (4) According to the punching rate obtained after processing in step (1), assign a score of 0 - 20 to the blasting effect. (5) According to the large block rate of the incoming ore determined in step (2), assign a score of 0 - 30 to the blasting effect. (6) According to the ore particle size determined in step (2), assign a score of 0 - 40 to the blasting effect. (7) According to the rock root rate obtained in step (3), assign a score of 0 - 20 to the blasting effect. (8) Through the intelligent control platform, based on the scores assigned in steps (4), (5), (6), and (7), conduct a comprehensive evaluation, calculate the total score of the blasting effect in the blasting area. If the total score reaches or exceeds 80 points, it indicates that the blasting effect is excellent and there is no need to optimize the design and construction process of the perforation blasting. On the contrary, if the total score is lower than 80 points, it means that the blasting effect is poor, and at this time, it is necessary to optimize the design and construction process of the perforation blasting to improve the effect.

[0006] Further, in the quantitative evaluation method of the blasting effect, in step (4), when the punching rates are 0, (0, 1%], (1%, 2%], (2%, 3%], (3%, 4%], and greater than 4% respectively, this index is assigned 10, 8, 6, 4, 2, 0 points in sequence.

[0007] Further, in the quantitative evaluation method of the blasting effect, in step (5), when the incoming large block rates are 0, (0, 1%], (1%, 2%], (2%, 3%], (3%, 4%], (4%, 5%], (5%, 6%], (6%, 7%], (7%, 8%], (8%, 9%], and greater than 9% respectively, this index is assigned 30, 27, 24, 21, 18, 15, 12, 9, 6, 3, 0 points in sequence.

[0008] Further, in the quantitative evaluation method of the blasting effect, in step (6), when the ore particle size D80 is (0, 200], (200, 300], (300, 400], (400, 500], (500, 600], (600, 700], (700, 800], and greater than 800 respectively, this index is assigned 0, 20, 35, 40, 30, 20, 10, 0 points in sequence.

[0009] Further, in the quantitative evaluation method for blasting effect, in step (7), when the rock root rates are 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, and greater than 9 respectively, this index is assigned 20, 18, 16, 14, 12, 10, 8, 6, 4, 2, 0 points in sequence.

[0010] Due to the adoption of the above technical solution, the present invention has the following beneficial effects: The quantitative evaluation method for blasting effect of the present invention comprehensively considers key indexes such as the punching rate, the large block rate entering the station, the ore particle size distribution, and the rock root rate, realizes a comprehensive and objective evaluation of the blasting effect, effectively avoids the limitations of single-index evaluation, and through the assistance of the intelligent control platform, realizes the automation of the evaluation process, significantly improves the efficiency of the evaluation work, and reduces the influence of human factors on the evaluation result, ensuring the accuracy and reliability of the evaluation result; In addition, the evaluation method of the present invention provides a quantitative evaluation benchmark for the quality of the blasting effect by establishing clear scoring criteria, helps to timely identify the situation of poor blasting effect, and timely optimize the design and construction process of perforation blasting, thereby significantly improving the blasting effect, effectively reducing production costs and increasing production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 It is a schematic flow chart of the quantitative evaluation method for blasting effect of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0012] The following elaborates on the preferred embodiments of the present invention in detail with reference to the drawings, so that the advantages and features of the present invention can be more easily understood by those skilled in the art, thereby making a clearer and more definite definition of the protection scope of the present invention. Here, it should be noted that in this application, the interval value (a, b] means that the value takes any value in the interval greater than a and less than or equal to b, and [a, b) means that the value takes any value in the interval greater than or equal to a and less than b. Taking the punching rate as (0, 1%] as an example, it means that the punching rate takes any value within the range greater than zero and less than or equal to 1%.

[0013] Combined with the attached Figure 1, This paper elaborates on a quantitative evaluation method for the blasting effect of the present invention. The comprehensive score of each blasting area is set at 100 points. Quantitative analysis is carried out based on four evaluation indicators: the punching rate, the large block rate entering the station, the ore particle size distribution, and the rock root rate. Finally, through the comprehensive scores of each indicator, the blasting effect of the muck pile is evaluated to optimize the perforation blasting design and construction process, thereby improving the blasting effect. Among them, the punching rate is the ratio of the number of punched holes to the total number of holes. Here, it should be noted that punching means that after the explosive explodes in the hole, very little energy acts on the rock, and most of the energy is released through the hole mouth, causing the plugged stemming or fine sand to fly very high, and the phenomenon of flying stemming can be seen. Figuratively speaking, it is punching. Punching will affect the blasting effect. The main reasons for punching are insufficient stemming length, unqualified stemming quality, excessive rock clamping effect, etc.; the large block rate entering the station is the ratio of the area of large block rocks above 1m in the ore truck entering the station to the sum of the areas of the scanning and recognition areas; the ore particle size distribution can be calculated through the ore particle size D80 interval; in blasting engineering, the rock root rate is usually used to describe the proportion of rocks that are not completely broken or do not reach the expected breaking effect after blasting. Here, it should be noted that in the blasting field, rock roots usually refer to the relatively solid and difficult-to-break parts of the rock. These parts often remain in large blocks after the primary blasting and need further treatment. The existence of rock roots may pose obstacles to subsequent construction or mining work. Usually, the rock root rate is equal to the sum of the volumes of all remaining rock roots after the primary blasting divided by the volume of the rock in the blasting area. In the case of a determined blasting area, the volume of the rock in the blasting area is a fixed value. The sum of the volumes of all remaining rock roots is approximately equal to the product of the number of rock roots and the volume of a single rock root, and the ratio of the volume of a single rock root to the volume of the rock in the blasting area is approximately a constant. Therefore, for the sake of simplifying the calculation, in the present invention, the rock root rate is achieved by calculating the number of rock roots; The measurement of the punching rate uses video dynamic artificial intelligence recognition technology, and the data is uploaded to the intelligent control platform for processing. Here, it should be noted that the video dynamic artificial intelligence recognition punching technology is an existing technology, so the video dynamic artificial intelligence recognition technology will not be elaborated in detail here; The intelligent algorithm for the ore particle size entering the mine refers to using the scanning and analysis technology of the longest side and area of the ore to calculate the ore particle size, so as to determine the large block rate and particle size distribution characteristics of the ore, and then upload the obtained data to the intelligent control platform. Here, it should be noted that the analysis method for large block ore at the ore inlet of the crushing station has been applied for a patent. The prior patent application number is: 2025100641668, and the application date is: January 15, 2025. Therefore, the detailed steps will not be elaborated here; The calculation process of the rock root rate involves using drones for inspection, which is achieved by counting the number of rock roots, and uploading the obtained data to the intelligent control platform.

[0014] As an alternative design, it is preferred that for the quantitative evaluation method of the blasting effect, the blasting effect of the blasting area is scored according to the punching rate. When the punching rates are 0, (0, 1%], (1%, 2%], (2%, 3%], (3%, 4%], and greater than 4% respectively, this index is correspondingly assigned 10, 8, 6, 4, 2, 0 points in sequence.

[0015] As an alternative design, it is preferred that for the quantitative evaluation method of the blasting effect, the blasting effect of the blasting area is scored according to the large block rate at the inlet. When the large block rates at the inlet are 0, (0, 1%], (1%, 2%], (2%, 3%], (3%, 4%], (4%, 5%], (5%, 6%], (6%, 7%], (7%, 8%], (8%, 9%], and greater than 9% respectively, the blasting effect index of this blasting area is correspondingly assigned 30, 27, 24, 21, 18, 15, 12, 9, 6, 3, 0 points in sequence.

[0016] As an alternative design, it is preferred that for the quantitative evaluation method of the blasting effect, the blasting effect of the blasting area is scored according to the ore particle size. When the ore particle size D80 is (0, 200], (200, 300], (300, 400], (400, 500], (500, 600], (600, 700], (700, 800], and greater than 800 respectively, this index is correspondingly assigned 0, 20, 35, 40, 30, 20, 10, 0 points in sequence.

[0017] As an alternative design, it is preferred that for the quantitative evaluation method of the blasting effect, the blasting effect is scored according to the rock root rate. When the rock root rates are 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, and greater than 9 respectively, this index is correspondingly assigned 20, 18, 16, 14, 12, 10, 8, 6, 4, 2, 0 points in sequence.

[0018] The intelligent control platform conducts a comprehensive evaluation based on the scores of various indicators and automatically calculates the total score of the blasting area. If the total score reaches or exceeds 80 points, it indicates that the blasting effect is excellent and there is no need to optimize the design and construction process of the perforation blasting; on the contrary, if the total score is lower than 80 points, it means that the blasting effect is poor, and at this time, it is necessary to optimize the design and construction process of the perforation blasting to improve the effect.

[0019] The quantitative evaluation method for the blasting effect of the present invention comprehensively considers key indicators such as the punching rate, the large block rate entering the station, the ore particle size distribution, and the rock root rate. Finally, through the comprehensive scores of various indicators, the blasting effect of the muck pile is evaluated to optimize the design and construction process of the perforation blasting, thereby improving the blasting effect, achieving a comprehensive and objective evaluation of the blasting effect, effectively avoiding the limitations of single-index evaluation, realizing the automation of the evaluation process with the assistance of the intelligent control platform, significantly improving the efficiency of the evaluation work, and reducing the influence of human factors on the evaluation results to ensure the accuracy and reliability of the evaluation results.

[0020] The specific embodiments of the present invention have been described in detail above. It should be understood that those of ordinary skill in the art can make many modifications and variations according to the concept of the present invention without creative labor. Therefore, all technical solutions that can be obtained by those skilled in the art in the technical field of the present invention based on the concept of the present invention through logical analysis, reasoning, or limited experiments on the basis of the prior art should be within the protection scope determined by the claims.

Claims

1. A quantitative evaluation method for blasting effect, characterized in that: Quantitative analysis is carried out based on four evaluation indicators: the punching rate, the large block rate at the inbound station, the ore particle size distribution, and the rock root rate, so as to achieve an accurate assessment of the blasting effect. The steps are as follows: (1) Use video dynamic artificial intelligence recognition technology to measure the punching rate of the blasting area, and upload the data to the intelligent control platform for processing; (2) Use the intelligent algorithm for the incoming ore particle size to scan and analyze the longest side and area of the ore in the blasting area, and then calculate the ore particle size, determine the large block rate and particle size distribution characteristics of the ore, and then upload the obtained data to the intelligent control platform; (3) Use drones to conduct patrol scans on the rock roots in the blasting area, count the number of rock roots, and upload the obtained data to the intelligent control platform; (4) According to the punching rate obtained after processing in step (1), assign 0 - 20 points to the blasting effect; (5) According to the large block rate of the incoming ore determined in step (2), assign 0 - 30 points to the blasting effect; (6) According to the ore particle size determined in step (2), assign 0 - 40 points to the blasting effect; (7) According to the rock root rate obtained in step (3), assign 0 - 20 points to the blasting effect; (8) Through the intelligent control platform, conduct a comprehensive evaluation based on the scores assigned in steps (4), (5), (6), and (7), calculate the total score of the blasting effect in the blasting area. If the total score reaches or exceeds 80 points, it indicates that the blasting effect is excellent and there is no need to optimize the design and construction process of the perforation blasting; on the contrary, if the total score is lower than 80 points, it means that the blasting effect is poor, and at this time, it is necessary to optimize the design and construction process of the perforation blasting to improve the effect.

2. The quantitative evaluation method for blasting effect according to claim 1, characterized in that: In step (4), when the punching rates are 0, (0, 1%], (1%, 2%], (2%, 3%], (3%, 4%], and greater than 4% respectively, this indicator is assigned 10, 8, 6, 4, 2, 0 points in turn.

3. The quantitative evaluation method for blasting effect according to claim 1, characterized in that: In step (5), when the large block rates at the inbound station are 0, (0, 1%], (1%, 2%], (2%, 3%], (3%, 4%], (4%, 5%], (5%, 6%], (6%, 7%], (7%, 8%], (8%, 9%], and greater than 9% respectively, this indicator is assigned 30, 27, 24, 21, 18, 15, 12, 9, 6, 3, 0 points in turn.

4. The quantitative evaluation method for blasting effect according to claim 1, characterized in that: In step (6), when the ore particle size D80 is (0, 200], (200, 300], (300, 400], (400, 500], (500, 600], (600, 700], (700, 800], and greater than 800 respectively, this indicator is assigned 0, 20, 35, 40, 30, 20, 10, 0 points in turn.

5. The quantitative evaluation method for blasting effect according to claim 1, characterized in that: In step (7), when the rock root rates are 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, and greater than 9 respectively, this indicator is assigned 20, 18, 16, 14, 12, 10, 8, 6, 4, 2, 0 points in turn.

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