Measurement method of average blasting lumpiness

Abstract

The invention discloses a method for measuring average blasting lumpiness, which comprises the following steps of: S1, carrying out an on-site rock blasting test, and carrying out multi-point camera shooting identification on a muck pile after the blasting test by using an unmanned aerial vehicle; s2, performing multi-point sampling on the blast heap after blasting, and performing screening calculation on the sampled rock mass by adopting screening equipment or manual screening to obtain an actual screening value of the average blasting lumpiness; s3, performing image recognition processing on the picture shot by the unmanned aerial vehicle to obtain an image recognition value of the blasting average lumpiness; s4, performing multiple bursting tests to obtain multiple groups of data, and correcting the image recognition data by using the statistical analysis data to obtain a fitting correction relationship; and S5, after field blasting, an unmanned aerial vehicle is used for shooting an image, recognition processing is carried out, and the fitting relation is used for correction, so that the average lumpiness of each blasting can be obtained. The method is high in pertinence, wide in applicability and easy and convenient to operate, the method combining image processing and manual screening is effectively utilized, the screening result is used for correcting the image processing result, then the accurate prediction result can be obtained according to the correction relation and the image processing result, the precision is high when the blasting lumpiness is predicted, and the prediction accuracy is high. The method adapts to blasting lumpiness prediction under different complex conditions, and is economical and efficient.

Description

Technical Field

[0001] The invention relates to the technical fields of blasting engineering and block size measurement, in particular to a method for measuring average blasting block size. Background Art

[0002] In the construction of water conservancy and hydropower or artificial sand and gravel aggregates, there are high requirements for the block size distribution and particle size of the blasted rocks. However, due to the influence of factors such as engineering geological conditions and explosive performance, the blasting block size distribution is often difficult to control and difficult to meet the design gradation distribution requirements. In the construction of water conservancy and hydropower dam projects, the uneven coefficient of dam material block size and the curvature coefficient of the screening mass accumulation curve need to strictly meet the design requirements; in mining production, the blasting block size needs to strictly control the large block rate and powder ore rate to meet the requirements of shoveling and transportation. Therefore, how to reasonably design blasting parameters in combination with blasting geological conditions to obtain rock blasting block size that meets the requirements; at the same time, how to measure the rock block size of the blast pile after blasting is a practical problem that has been studied in the field of rock blasting dynamics.

[0003] Since the 20th century, domestic and foreign scholars have done a lot of research on the prediction of blasting fragmentation. They have established many prediction methods for blasting fragmentation by applying stress wave theory, energy theory and statistical analysis methods, and established many prediction methods and prediction models. The commonly used prediction model is the Kuz-Ram model, but its prediction results have large errors under different lithological conditions. The methods for evaluating the fragmentation of blasting pile rocks can basically be divided into direct methods and indirect methods. The direct method includes the commonly used screening method, the secondary blasting rock block statistical method, and the direct measurement method. The screening method is suitable for the case where the screening amount is small and requires high precision, but at the same time, the screening work will cause interference to normal mining and excavation operations and increase costs. The statistical method and the direct measurement method have obvious defects of incomplete evaluation and low precision respectively. The indirect method includes the relevant data measurement method, computer simulation method, empirical distribution function method and photogrammetry method. The correlation data measurement method can only obtain a relatively single evaluation index about the rock block size of the blast pile, and cannot reflect the distribution law of the blast pile block size well; the photogrammetry method needs to take pictures of the rock blocks in each layer of the blast pile, and the operation is very complicated; the computational simulation tends to use the existing theory to derive and establish a mathematical model that reflects the complex transient blasting. The empirical distribution function method is currently more successfully applied, but its application scope is limited to the site and is costly and labor-intensive. Summary of the invention

[0004] In order to solve the above problems, the purpose of the patent of this invention is to provide a method for measuring the average blasting block size. The method combines photogrammetry and manual screening. Only the blocks on the surface of the blast pile are photographed for image recognition and software processing, and the accurate value obtained by manual screening is used to correct it. After obtaining the statistical relationship, it is only necessary to use photogrammetry to photograph and process the surface rock blocks, and a more accurate average blasting block size can be calculated through the relationship.

[0005] To achieve the above object, the present invention provides the following technical solutions: A method for measuring average blasting fragmentation, characterized by comprising: S1, select reasonable blasting parameters, conduct on-site rock blasting tests, and use drones to perform multi-point camera recognition of the blast pile after the blasting test; S2, take samples at multiple points on the blast pile after blasting, and use screening machines and manual screening to screen the sampled rock mass to calculate the actual screening value of the average blasting blockiness; S3, using image processing software to process and identify the photos taken by the drone, and using the software to read the block size data to obtain the image recognition value of the average block size of the blasting; S4, performing multiple blasting tests, repeating steps S1, S2, and S3 to obtain multiple sets of data, and using the screening statistical analysis data to correct the image recognition data to obtain a fitting correction relationship; S5, after the on-site blasting, the drone is used to take images, identify and process them, and then correct them with the fitting relationship to obtain the average block size of each blasting.

[0006] In the above technical solution, in step S1, a drone is used to perform multi-point camera recognition on the blast pile after the blasting test, specifically: After the blasting test, select 5 to 6 measuring lines from top to bottom, and place reference objects of fixed length at different positions of the blast pile. Generally, a scale ruler can be used. When using a drone to photograph the surface of the blast pile, try to ensure that each area has a relatively high-definition image. When shooting, try to keep the camera lens parallel to the blast pile, and exclude the sky, ground, etc. from the lens.

[0007] In the above technical solution, the reference object selected during the on-site shooting should have an obvious color difference with the rock blocks after blasting to facilitate image processing; 10 to 20 representative photos are selected for processing after each blasting.

[0008] In the above technical solution, the sampling and screening calculation in step S2, the specific screening steps are as follows: After taking photos of each blasting test, samples are collected from six locations, including the upper, middle and lower parts in front of the blast pile in the blasting test, and the upper, middle and lower parts between two blast holes in the same row. The samples are screened and weighed by screening equipment or manually to obtain the screening value of the average blasting block size.

[0009] In the above technical solution, in step S3, the block size data is read by software to obtain block size grading and average block size, specifically: Select 10 to 20 high-definition photos taken by the drone in step S1, and import the blasting block size pictures into the image recognition software. Generally, you can choose to use WipFrag software to perform preliminary identification of block size distribution, and manually correct the incorrectly identified edges in the image. Combine multiple image data to export the blasting block size distribution curve and obtain the blasting average block size data.

[0010] In the above technical solution, the step S4 is specifically as follows: The blasting parameters are changed on site to repeat the blasting test for many times. Generally, 5 to 6 blasting tests can be carried out. After each blasting test, steps S1, S2, and S3 are repeated to obtain the grading curve and average block size obtained by screening calculation for each blasting test and the grading curve and average block size obtained by image recognition. The screening data and the image recognition data are fitted with the average block size as a variable, and the actual screening results are used to optimize and correct the results of the image recognition processing to establish a fitting relationship between the two.

[0011] In the above technical solution, the step S5 is specifically as follows: In the subsequent blasting, after the blasting mining is completed, a drone is used to take photos of the blast pile after the blasting. The photos are processed by software to obtain the average blasting fragmentation. The average fragmentation calculated by fitting the relationship is the predicted value of the average blasting fragmentation.

[0012] Compared with the prior art, the present invention combines photogrammetry and manual screening, conducts multiple groups of blasting tests on site, photographs the surface of the blast pile by drone after the test, and manually screens the blast pile samples. After obtaining the data of multiple tests, the average block size data obtained by manual screening is used to correct the average block size data obtained by photogrammetry identification, and a statistical relationship is established between the average block size obtained by photogrammetry of the surface blocks and the actual average block size of the entire blast pile. In subsequent production, it is only necessary to photograph the rock blocks on the surface of the blast pile by drone after each blast, identify and process the photos by software, and convert the calculated average block size through the previously established statistical relationship to obtain a more accurate average blasting block size. This method is relatively simple. After obtaining the statistical relationship, it is only necessary to photograph the blocks on the surface of the blast pile each time to obtain the average blasting block size. There is no need to photograph, process and calculate each layer of the blast pile after each blast. It is convenient and fast, and the average blasting block size after each blast can be measured more accurately. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 This is a picture of the software recognition result of the photo fragmentation distribution in a method for measuring average blasting fragmentation of the present invention; Figure 2 A blasting block size grading curve diagram processed by software in a method for measuring average blasting block size of the present invention; DETAILED DESCRIPTION

[0014] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the following further explains how the present invention is implemented in conjunction with the accompanying drawings and specific implementation methods.

[0015] A limestone ore field adopts open-pit step blasting for blasting mining. It is necessary to measure the average block size of the blast pile after each blasting. Therefore, the method of the present invention is used to measure the average block size of the blasting.

[0016] A method for predicting average blasting fragmentation comprises the following steps: S1, select reasonable blasting parameters, conduct on-site rock blasting tests, and use drones to perform multi-point camera recognition of the blast pile after the blasting test; S2, sampling the blast pile at multiple points after blasting, and screening the sampled rock mass by manual screening to calculate the actual screening value of the average blasting blockiness; S3, using image processing software to process and identify the photos taken by the drone, and using the software to read the block size data to obtain the image recognition value of the average block size of the blasting; S4, a total of 10 blasting tests were carried out, and steps S1, S2, and S3 were repeated to obtain multiple sets of data. The screening values ​​of the 10 tests were a 1 ~a10 , the image recognition values ​​are b 1 ~b 10 , and use the screening statistical analysis data to correct the image recognition data to obtain the fitting correction relationship; S5, after the on-site blasting, the drone is used to take images, identify and process them, and then correct them with the fitting relationship to obtain the average block size of each blasting.

[0017] Finally, it should be noted that the above description is only an embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly used in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for measuring average blasting fragmentation, characterized in that: include: S1, select reasonable blasting parameters, conduct on-site rock blasting tests, and use drones to perform multi-point camera recognition of the blast pile after the blasting test; S2, take samples at multiple points on the blast pile after blasting, and use screening machines and manual screening to screen the sampled rock mass to calculate the actual screening value of the average blasting blockiness; S3, using image processing software to process and identify the photos taken by the drone, and using the software to read the block size data to obtain the image recognition value of the average block size of the blasting; S4, performing multiple blasting tests, repeating steps S1, S2, and S3 to obtain multiple sets of data, and using the screening statistical analysis data to correct the image recognition data to obtain a fitting correction relationship; S5, after the on-site blasting, the drone is used to take images, identify and process them, and then correct them with the fitting relationship to obtain the average block size of each blasting.

2. A method for measuring average blasting fragmentation, characterized in that: In step S1, a drone is used to perform multi-point camera recognition on the blast pile after the blasting test, specifically: After the blasting test, select 5 to 6 measuring lines from top to bottom, and place reference objects of fixed length at different positions of the blast pile. Generally, a scale ruler can be used. When using a drone to photograph the surface of the blast pile, try to ensure that each area has a relatively high-definition image. When shooting, try to keep the camera lens parallel to the blast pile, and exclude the sky, ground, etc. from the lens.

3. The method for measuring average blasting fragmentation according to claim 2, characterized in that: The reference objects selected during on-site photography should have obvious color differences from the rocks after blasting to facilitate image processing; 10 to 20 representative photos should be selected for processing after each blasting.

4. A method for measuring average blasting fragmentation, characterized in that: The sampling and screening calculation in step S2, the specific screening steps are as follows: After taking photos of each blasting test, samples are collected from six locations, including the upper, middle and lower parts in front of the blast pile in the blasting test, and the upper, middle and lower parts between two blast holes in the same row. The samples are screened and weighed by screening equipment or manually to obtain the screening value of the average blasting block size.

5. A method for measuring average blasting fragmentation, characterized in that: In step S3, the block size data is read by software to obtain block size grading and average block size, specifically: Select 10 to 20 high-definition photos taken by the drone in step S1, and import the blasting block size pictures into the image recognition software. Generally, you can choose to use WipFrag software to perform preliminary identification of block size distribution, and manually correct the incorrectly identified edges in the image. Combine multiple image data to export the blasting block size distribution curve and obtain the blasting average block size data.

6. A method for measuring average blasting fragmentation, characterized in that: The step S4 is specifically as follows: The blasting parameters are changed on site to repeat the blasting test for many times. Generally, 5 to 6 blasting tests can be carried out. After each blasting test, steps S1, S2, and S3 are repeated to obtain the grading curve and average block size obtained by screening calculation for each blasting test and the grading curve and average block size obtained by image recognition. The screening data and the image recognition data are fitted with the average block size as a variable, and the actual screening results are used to optimize and correct the results of the image recognition processing, so as to establish a fitting relationship between the two.

7. A method for measuring average blasting fragmentation, characterized in that: The step S5 is specifically as follows: In the subsequent blasting, after the blasting mining is completed, a drone is used to take photos of the blast pile after the blasting. The photos are processed by software to obtain the average blasting fragmentation. The average fragmentation calculated by fitting the relationship is the predicted value of the average blasting fragmentation.

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