Method for evaluating the fragmentation of an open pit blast

Abstract

The application discloses an evaluation method for open-pit mine blasting block size, and belongs to the technical field of mining engineering, comprising the following steps: obtaining ore and rock samples in blasting piles after blasting, and building the piles into laboratory blasting piles; collecting nuclear magnetic imaging data of N similar water-retaining models of the blasting piles based on a nuclear magnetic instrument; pre-processing the nuclear magnetic image data of the N similar water-retaining models of the blasting piles, and three-dimensionally reconstructing the internal structure of the similar water-retaining models of the blasting piles to form a three-dimension block size distribution average curve; calculating the ratio of the surface block size distribution curve of the laboratory blasting piles and the three-dimension block size distribution average curve to obtain a correction coefficient, and correcting the surface grading curve of the blasting piles on site; performing normalization processing on the corrected block size grading curve of the blasting piles, dividing n discrete points according to a certain particle size interval, calculating the difference value RMSE between the actual value and the fitting value based on the n discrete points, and then performing uniformity grade division to realize the evaluation of the internal block uniformity of the blasting piles on site.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of mining engineering, and relates to a method for evaluating open-pit mine blasting fragmentation. BACKGROUND

[0002] In open-pit mine blasting operation, the uniformity of the blasting pile has important significance for optimizing the blasting design, improving the crushing efficiency and reducing the subsequent processing cost. The traditional pile evaluation methods such as manual visual inspection, photo shooting and screening test have three significant shortcomings: first, the evaluation means is highly subjective and has poor repeatability; second, there is a lack of quantitative evaluation of the internal structure of the pile; and third, it cannot effectively feedback and link with the actual blasting parameters, resulting in a lack of scientific basis for blasting design adjustment, high ore dilution rate, low crushing efficiency and high total cost of mining and selection. With the in-depth promotion of the concept of “blasting instead of crushing and crushing instead of grinding” in mines, there is an urgent need for a non-destructive, repeatable and quantitative evaluation method for the uniformity of the pile to support the optimization of the blasting parameters and the control of the blasting effect.

[0003] The pile fragmentation distribution curve directly reflects the distribution of the different particle sizes of the crushed stones in the pile, and is one of the important indexes for evaluating the blasting effect. In combination with the nuclear magnetic imaging technology, the internal pore structure of the pile is further analyzed, and the indirect evaluation of the actual pile structure characteristics is realized. SUMMARY

[0004] To solve the above problems, the technical scheme adopted by the application is as follows: a method for evaluating open-pit mine blasting fragmentation, comprising the following steps:

[0005] S1: obtaining the ore and stone samples in the blasting pile after blasting, and building a laboratory pile by piling up the samples;

[0006] S2: analyzing the surface image of the laboratory pile, extracting the pile fragmentation data, obtaining the surface fragmentation distribution curve of the laboratory pile, and determining the distribution of the crushed stones on the surface of the laboratory pile;

[0007] S3: performing nuclear magnetic imaging data collection on N similar water-retaining models of the pile based on a nuclear magnetic instrument;

[0008] S4: preprocessing the nuclear magnetic image data of the N similar water-retaining models of the pile, and performing three-dimensional reconstruction on the internal structure of the similar water-retaining models of the pile, extracting the stone point cloud data, and forming a three-dimensional fragmentation distribution average curve;

[0009] S5: performing ratio calculation on the surface fragmentation distribution curve of the laboratory pile and the three-dimensional fragmentation distribution average curve to obtain a correction coefficient, and correcting the surface grading curve of the on-site pile;

[0010] S6: Divide the corrected blast pile block size distribution curve into n discrete points according to a certain particle size range, calculate the difference value RMSE between the two-dimensional curve and the three-dimensional curve of the n discrete points, and then classify the uniformity level to realize the evaluation of the block uniformity inside the blast pile.

[0011] Furthermore, the construction process of the explosion-simulation water-retention model is as follows:

[0012] Samples were taken from the laboratory blast pile, and each layer of sampled gravel was filled into a cylindrical standard rubber mold to form a standard blast pile model.

[0013] The standard model of the blast pile was sealed in two sections with permeable stones. Then, a vacuum water-retaining press was used to retain water in the similar model of the blast pile, resulting in a similar water-retaining model of the blast pile.

[0014] Furthermore, the expression for the porosity model of the burst-type water-retaining model is as follows:

[0015]

[0016] in: M Overall porosity; V R The volume of the crushed stone; V T For model volume; M R This refers to the microscopic porosity of crushed stone.

[0017] Furthermore, when the porosity of the porosity model is ≥60%, nuclear magnetic resonance imaging data is acquired.

[0018] Furthermore, the formula for the correction coefficient is as follows:

[0019]

[0020] The formula for the on-site block size distribution after correction factor is as follows:

[0021]

[0022] in: R i This is a correction factor; P 3D ( d i () represents a three-dimensional block size distribution; P 2D ( d i () represents a two-dimensional block degree distribution; P ( d ) represents the corrected block size distribution.

[0023] Further, the uniformity level division process is as follows:

[0024] When RMSE < 0.005, it is characterized that the block distribution in a certain particle size range in the blast pile is very uniform;

[0025] When 0.005≤RMSE < 0.01, it is characterized that the block distribution in the blast pile is relatively uniform;

[0026] When 0.01≤RMSE < 0.015, it is characterized that the block distribution in the blast pile is generally uniform;

[0027] When RMSE≥0.015, it is characterized that the block distribution in the blast pile is not uniform.

[0028] Further, the process of obtaining the ore and rock sample in the finished blast pile to build the laboratory blast pile is as follows:

[0029] From the surface of the blast pile after blasting, the topmost horizontal layer or the bottommost horizontal layer is selected, and a plurality of sampling points are arranged at the same interval;

[0030] Each point collects a unit volume of ore and rock, and is uniformly numbered;

[0031] According to the mine shovel loading operation structure, the entire blast pile is divided into a plurality of horizontal layers according to the vertical layer thickness;

[0032] Each layer is sampled according to the above method, and all the sampling samples are mixed uniformly to build a laboratory blast pile.

[0033] The method for evaluating the blasting block size of the open-pit mine provided by the application is based on the nuclear magnetic resonance imaging technology, realizes the three-dimensional non-destructive detection and high-precision characterization of the internal pore structure of the blast pile standard model, breaks through the limitations of the traditional surface observation method, and provides a new technical approach and key basis for quantitatively evaluating the internal uniformity characteristics of the blasting block.

[0034] The method constructs a laboratory blast pile standard model, and draws a three-dimensional block size distribution average curve by the nuclear magnetic resonance method, establishes a quantitative correlation between the two-dimensional block size distribution of the model surface and the internal three-dimensional true state, calibrates the precision of the two-dimensional surface grading curve of the field blast pile by using the correction coefficient, effectively solves the error existing in the inference of the internal overall block size distribution by single surface measurement, and greatly improves the accuracy of the overall block size evaluation of the field blast pile.

[0035] The method fully utilizes the nuclear magnetic resonance imaging technology to evaluate the uniformity of the blast pile pores, can effectively characterize the uniformity characteristics of the blast pile, and provides a reference basis for the evaluation and parameter optimization of the mine blasting effect. BRIEF DESCRIPTION OF DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0037] Figure 1 is a flowchart of the method;

[0038] Figure 2 is a standard model of a blast pile;

[0039] Figure 3 is a schematic diagram of a vacuum press;

[0040] Figure 4 is a calibration diagram of a nuclear magnetic resonance device;

[0041] Figure 5 is a comparison diagram of two-dimensional and three-dimensional block size distribution. DETAILED DESCRIPTION

[0042] It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict, and the present application will be described in detail below with reference to the drawings and in combination with the embodiments.

[0043] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below in combination with the drawings of the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. The description of the at least one exemplary embodiment is actually only illustrative, but not as any limitation on the present application and its application or use. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0044] An evaluation method of open-pit mine blasting block size, comprising the following steps:

[0045] S1: obtaining a sample of ore and rock fragments in a completed blast pile, and building a laboratory blast pile by stacking;

[0046] S2: based on the surface image of the laboratory blast pile, extracting the blast pile block size data to obtain the surface block size distribution curve of the laboratory blast pile, and determining the distribution of the surface rock fragments of the laboratory blast pile;

[0047] S3: based on the nuclear magnetic instrument, collecting nuclear magnetic imaging data of N similar water-retention models of the blast pile; N≥3;

[0048] S4: Preprocess the N similar water-retaining model nuclear magnetic resonance image data of the blast pile, and three-dimensionally reconstruct the internal structure of the similar water-retaining model of the blast pile, extract the gravel point cloud data, and form a three-dimensional block size distribution average curve;

[0049] S5: Calculate the correction coefficient by ratio calculation of the surface block size distribution curve of the laboratory blast pile and the three-dimensional block size distribution average curve, and correct the surface grading curve of the field blast pile;

[0050] S6: Divide the corrected blast pile block size grading curve into n discrete points according to a certain particle size interval, calculate the difference value RMSE of the values on the two-dimensional curve and the values on the three-dimensional curve, and then perform uniformity grade division to realize the evaluation of the uniformity of the internal block of the field blast pile.

[0051] The steps S1 / S2 / S3 / S4 / S5 / S6 are sequentially executed;

[0052] The process of obtaining the ore gravel samples in the finished blast pile and building the laboratory blast pile is as follows:

[0053] From the surface of the blast pile just after blasting, select the topmost horizontal layer or the bottommost horizontal layer, and arrange a plurality of sampling points at the same interval;

[0054] Collect a unit volume of ore gravel at each point, and uniformly number them;

[0055] According to the mine shovel loading operation structure, the entire blast pile is divided into a plurality of horizontal layers with a vertical layer thickness of 5 meters;

[0056] Each layer is sampled according to the above method, and all the sampling samples are mixed uniformly to build the laboratory blast pile.

[0057] The process of extracting the blast pile block size data based on the laboratory blast pile surface image to obtain the laboratory blast pile surface block size distribution curve and determine the distribution of the laboratory blast pile surface gravel is as follows:

[0058] The image processing method is used to preprocess the laboratory small blast pile image, including denoising, contrast enhancement, etc., to improve the image quality.

[0059] Subsequently, the edge detection, image segmentation and other technologies are used to accurately extract the relevant data of the small blast pile surface block size from the processed image, including the shape and size information of the block, and draw the blast pile surface block size distribution curve.

[0060] Figure 2 is a standard model image of the blast pile;

[0061] The construction process of the similar water-retaining model of the blast pile is as follows:

[0062] The laboratory blast pile is sampled, and the sampled crushed stone of each layer is filled in a cylindrical standard rubber mold to form a blast pile standard model;

[0063] The blast pile standard model is sealed by water-permeable stones, and the blast pile similar model is water-protected by using a vacuum water pressure machine to obtain a blast pile similar water-protected model. Figure 3 is a schematic diagram of a vacuum pressure machine;

[0064] Further, the process of collecting nuclear magnetic imaging data of N blast pile similar water-protected models based on a nuclear magnetic instrument is as follows:

[0065] Before use, the nuclear magnetic instrument is debugged by free induction decay and multi-pulse sequence to determine parameters such as waiting time and radio frequency pulse frequency. After debugging, the instrument needs to be calibrated to establish the relationship between the nuclear magnetic unit volume signal and the porosity of the ore rock.

[0066] Figure 4 is a calibration diagram of a nuclear magnetic resonance device;

[0067] Five sand body samples with porosities of 1%, 5%, 10%, 20% and 30% are used for calibration, and a linear fitting relationship between the volume proportion of the sand sample and the signal amplitude is obtained by testing. After the instrument is debugged, the porosity of the blast pile similar water-protected model after water protection is measured.

[0068] The expression of the porosity model of the blast pile similar water-protected model is as follows:

[0069] (1)

[0070] wherein: M is the overall porosity; V R is the volume of crushed stone; V T is the volume of the model; M R is the microscopic porosity of the crushed stone.

[0071] When the porosity of the porosity model is greater than or equal to 60%, nuclear magnetic imaging data is collected.

[0072] In order to accurately obtain the pore distribution inside the model, the blast pile standard model after production is scanned finely every 2 cm along the Z-axis direction; in order to avoid the influence of the end water-permeable stones on the imaging results, the imaging results of the two ends are excluded in the subsequent analysis, and finally 8 nuclear magnetic imaging data are obtained. For each group of models, segmented measurement is performed to capture the differences in crushed stone size and pore distribution at different positions.

[0073] Further, the N similar water conservation model nuclear magnetic image data of the blast pile is preprocessed, and the internal structure of the similar water conservation model of the blast pile is three-dimensionally reconstructed to extract the gravel point cloud data and form a three-dimensional block size distribution average curve as follows:

[0074] Image preprocessing needs to standardize the gray value, and adopts a Gaussian filtering + threshold segmentation method to separate the gravel and pores; image registration and splicing adopt Nu-MRI image processing software to construct a three-dimensional point cloud model. Then, a clustering method (DBSCAN) is used to identify independent blocks, calculate their volume or equivalent spherical diameter, and draw a three-dimensional block size distribution curve of the blast pile.

[0075] Figure 5 is a comparison chart of two-dimensional and three-dimensional block size distribution;

[0076] For the same particle size interval of 5mm interval, the numerical ratio of each section of the two-dimensional and three-dimensional curves is calculated, and the correction coefficient formula of each section is shown in equation (2); the corrected field blast pile block size distribution formula is shown in equation (3):

[0077] (2)

[0078] (3)

[0079] Wherein: R i is the correction coefficient; P 3D is the three-dimensional block size distribution; d i is the two-dimensional block size distribution; P 2D is the corrected block size distribution. d i P d

[0080] The corrected blast pile block size grading curve is divided into n discrete points according to the particle size interval of 5mm, the difference value RMSE between the value on the two-dimensional curve and the value on the three-dimensional curve of the n discrete points is calculated, and the formula is shown in equation (4); according to the obtained RMSE data, the block uniformity level evaluation is established, as shown in Table 1:

[0081]

[0082] Table 1 Block uniformity level evaluation

[0083]

[0084] ​​​When the uniformity level is I, the block uniformity is evaluated as very uniform; when the uniformity level is II, the block uniformity is evaluated as relatively uniform; when the uniformity level is III, the block uniformity is evaluated as generally uniform; and when the uniformity level is IV, the block uniformity is evaluated as non-uniform.

[0085] The method further comprises: performing classified mapping based on the uniformity level and historical blasting parameters to establish a blasting parameter recommendation database.

[0086] The database takes the uniformity level as an input index and outputs a recommended blasting parameter combination corresponding to the uniformity level.

[0087] The parameters include unit charge quantity, hole spacing, hole depth and delay time.

[0088] The process of classified mapping of the uniformity level and historical blasting parameters is as follows: when the evaluation result is uniformity level III or IV, the system preferentially recommends a combination of increasing unit charge quantity or reducing hole spacing to enhance the uniformity of the broken block; and when the level is I or II, the system recommends maintaining the current parameters or appropriately reducing the charge strength.

[0089] Embodiment 1

[0090] A certain open-pit iron mine is mined, and the on-site blast pile data is collected. The non-uniformity coefficient of the blast pile is calculated to be 4.24, and the curvature coefficient is 1.39. Subsequently, the blast pile is sampled according to the method described in the patent, and a standard model of the blast pile is prepared. These models are placed in a specific environment for 12 hours of water retention to ensure sufficient penetration of the internal moisture. Subsequently, the nuclear magnetic instrument is used to measure the porosity and nuclear magnetic imaging of the models after water retention, and the pore distribution information inside the models is obtained. According to this information, the technical personnel calculate the RMSE value of each model, and compare it with the block uniformity level evaluation table (Table 1) to obtain the uniformity level of each model.

[0091] As shown in Figure 1 , the evaluation method of the block size of the open-pit mine blasting of the present application comprises the following steps:

[0092] Step 1: Select the topmost horizontal layer or the bottommost horizontal layer from the surface of the just-blasted blast pile, and arrange a plurality of sampling points (sample every 2m, a total of 5-10 points) at the same interval; collect a unit volume of ore and rock (such as 500ml) at each point and uniformly number them; divide the entire blast pile into a plurality of horizontal layers with a vertical layer thickness of 5 meters according to the mine shovel loading operation structure; sample each layer according to the above method; mix all the sampling samples uniformly and stack them into a small blast pile in the laboratory.

[0093] Step 2: Analyze the surface image of the small blast pile based on image processing algorithms, extract the aggregate size data, draw the surface aggregate size distribution curve of the small blast pile, and determine the distribution of the small blast pile surface aggregate.

[0094] Step 3: Sample the small blast pile according to the method in Step 1, and fill the sampled aggregate of each layer into a standard rubber mold (Φ100mm x 200mm) to form a standard model.

[0095] Step 4: Use water-permeable stones to seal the two sections of the model, and use a vacuum water pressure machine to maintain water for 12 hours in the similar model of the blast pile to ensure uniform and stable water distribution inside the model.

[0096] Step 5: Calibrate the nuclear magnetic instrument, then measure the porosity of the water-maintained model in Step 3, and preliminarily evaluate whether the porosity of the model meets the conditions of nuclear magnetic imaging.

[0097] Step 6: According to the complex distribution of the aggregate inside the model, perform a fine scan every 2 cm interval, remove the data at both ends, and retain 8 segments of nuclear magnetic imaging data.

[0098] Step 7: Preprocess the nuclear magnetic image data (including denoising, gray scale normalization, edge enhancement, etc.), and reconstruct the internal structure of the model in three dimensions through the Nu-Mag nuclear magnetic resonance image processing software to form a complete aggregate structure model, extract the aggregate point cloud data, and draw the three-dimensional aggregate size distribution curve of the model.

[0099] Step 8: Calculate the ratio of the two types of gradation curves in Step 2 and Step 7 to obtain the correction coefficient, and correct the surface gradation curve of the blast pile.

[0100] Step 9: Divide the corrected aggregate size gradation curve of the blast pile into n discrete points according to a 5mm particle size interval, and calculate the difference (RMSE) between the actual value and the fitted value at these points. Establish a unified evaluation system through the RMSE fitting error, divide the uniformity level into four levels, and evaluate the uniformity of the internal structure of the blast pile.

[0101] Step 10: According to the evaluation results of the uniformity level of the blast pile obtained in Step 9, classify and map different levels with actual blasting parameters (including charge weight, hole spacing, hole depth, explosive type, etc.), and construct a blasting parameter recommendation database.

[0102] In step 1, after the blasting is completed, a representative typical horizontal layer is selected on the surface of the blast pile, and 5-10 sampling points are arranged along the layer at an interval of 2 meters. A unit volume of ore and rock sample (such as 500 mL) is collected at each point and numbered uniformly. According to the structure of the mine shovel loading operation, the entire blast pile is divided into several horizontal layers with a layer height of 5 meters, and the above sampling process is repeated for each layer. All the rock samples of the layer are mixed uniformly to form a representative small blast pile structure model in the laboratory.

[0103] In step 2, the image processing method is used to pre-process the image of the small blast pile in the laboratory, including denoising, contrast enhancement, etc., to improve the image quality. Then, using edge detection, image segmentation and other techniques, the relevant data of the small blast pile surface block size are accurately extracted from the processed image, including the shape and size information of the block, and the blast pile surface block size distribution curve is drawn.

[0104] In step 3, the laboratory small blast pile is sampled again according to the sampling method of step 1, and the sampled rock is loaded into a 100x200mm cylindrical rubber mold to make a blast pile standard model.

[0105] In step 4, the vacuum water saturation machine is used to keep the model water for more than 12 hours under a negative pressure of 20-25 MPa. To avoid the internal rock from falling off during water retention, water-permeable stones are placed at both ends of the model to allow water to penetrate into the rock. During the water retention process,

[0106] First, ensure that valves V1, V2, V3, V4 and K1, K5, K4 are fully open, and K2 is returned; then perform the assembly operation:

[0107] 1) Close K4, add the blast pile standard model, and inject water into bin 1, then close K1;

[0108] 2) Close V1, inject water into bin 2 (water level should not exceed the height of the adjacent cylinder), and close K5;

[0109] 3) Close V4 and K3, start the motor (observe the vacuum gauge to be near -0.1);

[0110] 4) Close V2 and V3, open V1, V4 and K5;

[0111] 5) Close V4, rotate K2 to the top position;

[0112] 6) Close V1, slightly open V4 (half buckle) and adjust K2, so that the pressure gauge stabilizes at 20-25 MPa;

[0113] 7) Finally, open K3 counterclockwise, and complete the model water retention preparation work.

[0114] The step 5, the nuclear magnetic instrument is debugged by free induction decay and multi-pulse sequence before use, and parameters such as waiting time and radio frequency pulse frequency are determined. After debugging, the instrument needs to be calibrated to establish the relationship between the nuclear magnetic unit volume signal and the porosity of the ore and rock. Five sand sample standards with porosities of 1%, 5%, 10%, 20% and 30% are used for calibration, and the linear fitting relationship between the volume ratio of the sand sample and the signal amplitude is obtained by testing; after the instrument is debugged, the porosity of the model with good water retention is measured.

[0115] According to the data in step 6, the overall porosity model of the model is established, as shown in the following formula. The porosity of the model is preliminarily evaluated, and the porosity exceeding 60% has the condition of nuclear magnetic imaging.

[0116] The expression of the porosity model of the similar water-retention model of the blast pile is as follows:

[0117]

[0118] Among them: M is the overall porosity; V R is the volume of the broken stone; V T is the volume of the model; M R is the micro-porosity of the broken stone.

[0119] In step 6, in order to accurately obtain the pore distribution inside the model, during the test, the model is scanned finely every 2 cm along the Z-axis direction of the model; in order to avoid the influence of the water-permeable stone at both ends on the imaging result, the imaging results at both ends are excluded in the subsequent analysis, and finally 8 pieces of nuclear magnetic imaging data are obtained. For each group of models, segmented measurement is performed to capture the difference in broken stone size and pore distribution at different positions.

[0120] In step 7, the image preprocessing needs to standardize the gray value, and the Gaussian filtering + threshold segmentation method is used to separate the broken stone and the pore. Image registration and splicing adopt the Nu Mai nuclear magnetic resonance image processing software to construct a three-dimensional point cloud model. Then the independent block is identified by clustering method (DBSCAN), the volume or equivalent spherical diameter is calculated, and the three-dimensional block size distribution curve of the blast pile is drawn. The particle size distribution data points extracted from each layer of image are fitted into an overall smooth curve as a “prediction curve”.

[0121] In step 8, for the same particle size interval (5 mm interval), the ratio of the values of each segment of the two-dimensional and three-dimensional curves is calculated, and the correction coefficient formula of each segment is as follows:

[0122]

[0123] The modified on-site blasting pile size distribution formula is as follows:

[0124]

[0125] Wherein: R i is a correction factor; P 3D is a three-dimensional pile size distribution; d i is a two-dimensional pile size distribution; P 2D is a modified pile size distribution; d i is a correction factor; P d is a modified pile size distribution;

[0126] In step 9, the modified blasting pile size grading curve in step 8 is normalized, divided into n discrete points according to the particle size interval of 5 mm, and the difference value RMSE of the value on the two-dimensional curve and the value on the three-dimensional curve is calculated. The formula is as follows; according to the obtained RMSE data, the block uniformity level evaluation is established, as shown in Table 1.

[0127]

[0128] Table 1 Block uniformity level evaluation

[0129]

[0130] When the uniformity level is I, the block uniformity evaluation is very uniform; when the uniformity level is II, the block uniformity evaluation is relatively uniform; when the uniformity level is III, the block uniformity evaluation is generally uniform; and when the uniformity level is IV, the block uniformity evaluation is not uniform.

[0131] In step 10, according to the blasting uniformity level evaluation result obtained in step 9, different levels are associated with historical blasting parameters for correlation analysis, and a blasting parameter recommendation database is established. The database takes the uniformity level as the input index, and outputs the corresponding recommended blasting parameter combination, including unit charge, hole spacing, hole depth, and delay time, etc.

[0132] According to the block uniformity level evaluation, the uniformity index RMSE=0.0074, which belongs to the II uniformity level, and the uniformity evaluation is relatively uniform. After the evaluation result is imported as an input parameter into the blasting parameter recommendation database, the system suggests maintaining the current blasting parameter configuration for continuous operation without parameter adjustment, which meets the balance requirement of economy and crushing effect.

[0133] Example 2

[0134] ​A certain open-pit iron mine was mined, and the data of the blast pile on site was collected. The non-uniformity coefficient of the blast pile gravel was calculated to be 4.36, and the curvature coefficient was 1.29. Subsequently, the blast pile was sampled according to the method described in the patent, and a standard model of the blast pile was made. These models were placed in a specific environment for 12 hours of water retention to ensure sufficient penetration of moisture inside. After that, the nuclear magnetic instrument was used to measure the porosity and nuclear magnetic imaging of the models after water retention, and the pore distribution information inside the models was obtained. According to this information, the technical personnel calculated the RMSE value of each model, and compared it with the block uniformity grade evaluation table (Table 1) to obtain the uniformity grade of each model.

[0135] According to the block uniformity grade evaluation, the uniformity index RMSE = 0.013 belongs to the III uniformity grade, and the uniformity evaluation is general uniformity. After inputting this result into the blasting parameter recommendation database, the system suggests optimizing the current blasting parameters, and preferentially adjusting and appropriately increasing the unit charge to improve the blast pile uniformity and improve the overall crushing effect.

[0136] Example 3

[0137] A certain open-pit iron mine was mined, and the data of the blast pile on site was collected. The non-uniformity coefficient of the blast pile gravel was calculated to be 5.39, and the curvature coefficient was 1.56. Subsequently, the blast pile was sampled according to the method described in the patent, and a standard model of the blast pile was made. These models were placed in a specific environment for 12 hours of water retention to ensure sufficient penetration of moisture inside. After that, the nuclear magnetic instrument was used to measure the porosity and nuclear magnetic imaging of the models after water retention, and the pore distribution information inside the models was obtained. According to this information, the technical personnel calculated the RMSE value of each model, and compared it with the block uniformity grade evaluation table (Table 1) to obtain the uniformity grade of each model.

[0138] According to the block uniformity grade evaluation, the uniformity index RMSE = 0.0069 belongs to the II uniformity grade, and the uniformity evaluation is relatively uniform. After inputting this evaluation result into the blasting parameter recommendation database as an input parameter, the system suggests maintaining the current blasting parameter configuration for continuous operation without the need for parameter adjustment, which meets the balance requirement of economy and crushing effect.

[0139] Finally, it should be noted that the above examples are only used to illustrate the technical solutions of the present application, and are not limited thereto. Although the present application has been described in detail with reference to the foregoing examples, those skilled in the art should understand that the technical solutions described in the foregoing examples can still be modified, or some or all of the technical features can be replaced by equivalents. Such modifications or replacements do not change the essence of the corresponding technical solutions beyond the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method of evaluating fragmentation in a surface mine, characterized by: The method comprises the following steps: S1: Obtain the ore rock sample in the blasting pile, and build the laboratory blasting pile; S2: Analyze the surface image of the laboratory blasting pile, extract the blasting pile size data, obtain the surface size distribution curve of the laboratory blasting pile, and determine the distribution of the surface rock of the laboratory blasting pile; S3: Based on the nuclear magnetic instrument, nuclear magnetic imaging data of N similar water-retention models of the blasting pile are collected; S4: The nuclear magnetic image data of the N similar water-retention models of the blasting pile are preprocessed, the internal structure of the similar water-retention model of the blasting pile is three-dimensionally reconstructed, the rock point cloud data are extracted, and a three-dimensional size distribution average curve is formed; S5: The surface size distribution curve of the laboratory blasting pile and the three-dimensional size distribution average curve are ratio calculated to obtain a correction coefficient, and the surface grading curve of the blasting pile is corrected; S6: The corrected blasting pile size grading curve is uniformly divided into n discrete points according to a certain particle size interval, the difference value RMSE of the value on the two-dimensional curve and the value on the three-dimensional curve of the n discrete points is calculated, uniformity grade division is performed, and the internal block uniformity of the blasting pile is evaluated.

2. A method of evaluating fragmentation in a surface mine blast according to claim 1, characterised in that: The construction process of the similar water-retention model of the blasting pile is as follows: The laboratory blasting pile is sampled, and the sampled rock of each layer is filled in a cylindrical standard rubber mold to form a blasting pile standard model; The two sections of the blasting pile standard model are sealed with water-permeable stones, and the water-retention of the similar model of the blasting pile is performed by using a vacuum water-retention press to obtain the similar water-retention model of the blasting pile.

3. A method of evaluating fragmentation in a surface mine blast according to claim 1 characterised in that: The expression of the porosity model of the similar water-retention model of the blasting pile is as follows: where: M is the bulk porosity; V R is the volume of the crushed stone; V T is the volume of the model; M R is the micro-porosity of the crushed stone.

4. A method of evaluating fragmentation in a surface mine blast according to claim 3, characterised in that: When the porosity of the porosity model is greater than or equal to 60%, nuclear magnetic imaging data collection is performed.

5. A method of evaluating fragmentation in a surface mine blast according to claim 1 characterised in that: The correction coefficient formula is as follows: The corrected blasting pile size distribution formula after correction of the correction coefficient is as follows: wherein: R i is a correction factor; P 3D d i is a three-dimensional size distribution; P 2D d i is a two-dimensional size distribution; P d is a corrected size distribution.​​​ 6. A method of evaluating fragmentation in a surface mine blast according to claim 1 characterised in that: The uniformity grade division process is as follows: When RMSE is less than 0.005, it is indicated that the block distribution in a certain particle size range in the blasting pile is very uniform; When 0.005≤RMSE<0.01, it is indicated that the block distribution in the blasting pile is relatively uniform; When 0.01≤RMSE<0.015, it is indicated that the block distribution in the blasting pile is generally uniform; When RMSE is greater than or equal to 0.015, it is indicated that the block distribution in the blasting pile is not uniform.

7. A method of evaluating fragmentation in a surface mine blast according to claim 1 characterised in that: The process of obtaining the ore rock sample in the blasting pile and building the laboratory blasting pile is as follows: Select the topmost horizontal layer or the bottommost horizontal layer from the surface of the blasting pile, and arrange a plurality of sampling points at the same interval; Collect a unit volume of ore rock at each point, and uniformly number them; According to the mine shovel loading operation structure, the entire blasting pile is divided into a plurality of horizontal layers according to the vertical layer thickness; Each layer is sampled according to the above method, all the sampling samples are uniformly mixed, and the laboratory blasting pile is built.

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