Method, system and device for estimating specific surface area of irregular rock particles

Abstract

The present invention provides a method, system and device for estimating the specific surface area of irregular rock particles, relating to the technical field of ore and rock particle crushing. The method includes: visually classifying according to the shape characteristics of irregular rock particles; conducting multi-angle three-dimensional laser scanning tests on irregular rock particles of different shape types to obtain point cloud data, reconstructing the irregular rock particle model, and obtaining the three-axis dimensions, surface area and volume of the irregular rock particle model; introducing the Heywood volume shape factor and the surface area shape factor to characterize the shape of irregular rock particles, and calculating the Heywood surface area shape factor and the Heywood volume shape factor of each irregular rock particle according to the three-axis dimensions, surface area and volume; fitting the statistical relationship of the above shape factors; and estimating the specific surface area of the to-be-tested irregular rock particles according to the statistical relationship, the volume and the particle size of the to-be-tested irregular rock particles. The present invention can quickly estimate the specific surface area of irregular rock particles.

Description

Technical Field

[0001] The present invention relates to the technical field of ore and rock particle crushing, and particularly to a method, system and device for estimating the specific surface area of irregular rock particles. Background Art

[0002] The blasting or mechanical crushing of ore and rock is a process in which internal cracks in ore and rock continuously expand, converge under the action of external loads, and cut the ore and rock into rock particles of different sizes and shapes. It is a phenomenon of state instability of rock driven by energy. During the process of ore and rock particle crushing, the crushing energy is the energy required to cause macroscopic damage and fracture of the rock, and it is one of the main effective components of the externally input energy. It can be seen that the calculation of the crushing energy is the key to the evaluation of energy utilization efficiency.

[0003] During the process of ore and rock blasting or mechanical crushing, the crushing energy is further divided into surface crushing energy and internal fracture energy. At present, it is difficult to measure the propagation path of internal microcracks in ore and rock, and the research on internal fracture energy is still relatively difficult. In this context, the surface crushing energy that drives the formation of new free surfaces of ore and rock particles has become an important index for calculating the energy utilization efficiency during the process of ore and rock blasting and mechanical crushing. According to Griffith's crushing theory, the calculation of the unit crushing energy during the process of ore and rock crushing is closely related to the unit surface energy of ore and rock (also known as the critical energy release rate) and the specific surface area (SSA) of the newly formed crushed particles. Therefore, the calculation / determination of the specific surface area of ore and rock particles has become one of the key issues in the evaluation of energy utilization efficiency during the process of blasting or mechanical crushing.

[0004] According to the definition, the specific surface area is the surface area possessed by particles per unit mass or unit volume, and the calculation formula is as follows:

[0005]

[0006] In the formula, S F is the external surface area of the particle, V F is the volume of the particle, and ρ is the rock density.

[0007] According to the current testing technology, the existing commercial testing equipment is mainly applicable to the determination of the specific surface area of small particle sizes. For non-powdery particles with a particle size < 0.5 mm, the flow microcalorimetry method is mostly used to measure their specific surface area; for powder particles (particle size less than 0.075 mm), the BET gas (mostly nitrogen, krypton or argon) adsorption method, solution adsorption method, mercury intrusion method and air permeability experiment are mostly used to determine their specific surface area. For particles with a particle size > 1.0 mm, due to the limitations of the sensitivity of laboratory analysis equipment and other factors, there is a lack of specific surface area testing instruments. In the case of known particle sizes, the equivalent model method is mostly used to calculate their specific surface area.

[0008] At present, the commonly used equivalent models for specific surface area calculation mainly include several models such as spheres, cubes, ellipsoids, regular tetrahedrons, and tetrakaidecahedrons. Among them, for the sake of calculation convenience, the cube model and the sphere model are used the most. However, affected by the unpredictability of the internal microcrack distribution of ore and rock and the complexity of the blasting and mechanical crushing processes, the crushed ore and rock particles are typical irregular particles with a wide particle size distribution. Compared with the particle size, it is more difficult to characterize the visual shape, angularity, and surface texture features of irregular particles, resulting in greater difficulties in calculating and measuring their surface area, and the specific surface area error calculated by simply equating them to the cube model and the sphere model is relatively large.

[0009] Therefore, CN201810586789.1 discloses a method for determining the specific surface area of graded materials based on three-dimensional laser scanning and image processing technologies. This method uses three-dimensional laser scanning technology, image processing technology, and the equivalent ellipsoid model method respectively to obtain the specific surface area data of rock blocks larger than 50 mm and 5 - 50 mm, and finally establishes a specific surface area curve to calculate the specific surface area of wide-particle-size blasted and crushed blocks. CN202111071183.2 discloses a method for modeling the specific surface area parameters of shale based on BP neural network. This method requires using a large number of geological classification and evaluation parameters as training data, establishing a continuous specific surface area data curve using the mapping relationship, and finally evaluating the longitudinal specific surface area change of single-well shale through the specific surface area data curve.

[0010] Existing specific surface area testing equipment and the specific surface area determination methods disclosed in the above-mentioned related invention patents can, to a certain extent, meet the calculation of the specific surface area of particles under corresponding particle sizes and have certain engineering practical value.

[0011] However, looking at the above-mentioned testing equipment or determination methods comprehensively, there are still the following deficiencies:

[0012] (1) Existing measuring instruments are mainly applicable to the specific surface area testing of small particles or powdery particles with a particle size < 1 mm, and most of the test data include the external surface area and the internal surface area of pores. The test data is larger than the actual specific surface area, which is likely to overestimate the energy utilization efficiency of the crushing process.

[0013] (2) The angularity and surface texture of rock particles after blasting or mechanical crushing are complex, and there are a certain amount of needle-like and flaky particles in the stockpile. The equivalent model for specific surface area calculation has a large difference from the actual shape of rock particles, and the specific surface area calculated based on the assumption of the hexahedron or sphere model is bound to cause a large error. Summary of the Invention

[0014] The purpose of the present invention is to provide a method, system, and equipment for estimating the specific surface area of irregular rock particles to solve the problem of large errors in specific surface area calculation in the prior art.

[0015] To achieve the above object, the present invention provides the following solutions:

[0016] A method for estimating the specific surface area of irregular rock particles, comprising:

[0017] Randomly select a plurality of irregular rock particles and perform visual classification according to the shape characteristics of the irregular rock particles;

[0018] Perform multi-angle three-dimensional laser scanning tests on irregular rock particles of different shape types to obtain point cloud data;

[0019] Reconstruct an irregular rock particle model based on the point cloud data, and obtain the three-axis dimensions, surface area, and volume of the irregular rock particle model; the three-axis dimensions include the particle size;

[0020] Introduce the Heywood volume shape factor and the surface area shape factor to characterize the shape of the irregular rock particles, and calculate the Heywood surface area shape factor and the Heywood volume shape factor of each irregular rock particle according to the three-axis dimensions, the surface area, and the volume;

[0021] Fit the statistical relationships of the Heywood surface area shape factor and the Heywood volume shape factor of irregular rock particles of different shape types;

[0022] Obtain the volume and particle size of the irregular rock particle to be measured, and estimate the specific surface area of the irregular rock particle to be measured according to the statistical relationship, the volume, and the particle size of the irregular rock particle to be measured.

[0023] Optionally, randomly select a plurality of irregular rock particles and perform visual classification according to the shape characteristics of the irregular rock particles, specifically including:

[0024] Divide the material pile into an upper layer, a middle layer, and a lower layer, and arrange 3 to 5 sampling areas in each layer;

[0025] Refer to the coning and quartering method, and divide each of the sampling areas into 4 regions;

[0026] Sample in two regions on the diagonal to generate a large sample; the total number of irregular rock particles randomly selected in each large sample is greater than 150;

[0027] Divide the irregular rock particles included in all the large samples into hexahedrons, pentahedrons, tetrahedrons, irregular polyhedrons, and needle-like and flaky particles according to the shape characteristics; among them, the irregular polyhedron is an irregular rock particle with more than 6 polygon sides.

[0028] Optionally, perform multi-angle three-dimensional laser scanning tests on irregular rock particles of different shape types to obtain point cloud data, specifically including:

[0029] Obtain the particle sizes of irregular-shaped rock particles of different shape types;

[0030] Carry out multi-angle three-dimensional laser scanning tests on the irregular-shaped rock particles with particle sizes greater than 10 cm on site to obtain point cloud data;

[0031] Carry out multi-angle three-dimensional laser scanning tests on the irregular-shaped rock particles with particle sizes in the range of 5 cm to 10 cm indoors to obtain point cloud data.

[0032] Optionally, obtain the volume and particle size of the irregular-shaped rock particles to be measured, specifically including:

[0033] Measure the volume of the irregular-shaped rock particles to be measured by the drainage method;

[0034] Measure the particle size of the irregular-shaped rock particles to be measured using a dimension measuring tool.

[0035] Optionally, the specific surface area is:

[0036]

[0037] where SSA is the specific surface area; K S is the Heywood surface area shape factor; K V is the Heywood volume shape factor; x k is the particle size; ρ is the rock density.

[0038] An irregular-shaped rock particle specific surface area estimation system, comprising:

[0039] An irregular-shaped rock particle selection and visual classification module, used to randomly select a plurality of irregular-shaped rock particles and perform visual classification according to the shape characteristics of the irregular-shaped rock particles;

[0040] A point cloud data acquisition module, used to perform multi-angle three-dimensional laser scanning tests on irregular-shaped rock particles of different shape types to obtain point cloud data;

[0041] An irregular-shaped rock particle model reconstruction module, used to reconstruct an irregular-shaped rock particle model according to the point cloud data and obtain the three-axis dimensions, surface area, and volume of the irregular-shaped rock particle model; the three-axis dimensions include the particle size;

[0042] A Heywood shape factor calculation module, used to introduce the Heywood volume shape factor and the surface area shape factor to characterize the shape of the irregular-shaped rock particles, and calculate the Heywood surface area shape factor and the Heywood volume shape factor of each of the irregular-shaped rock particles according to the three-axis dimensions, the surface area, and the volume;

[0043] A statistical relationship fitting module for fitting the statistical relationships of the Heywood surface area shape factor and the Heywood volume shape factor of irregularly shaped rock particles of different shape types;

[0044] A specific surface area estimation module for obtaining the volume and particle size of the to-be-tested irregularly shaped rock particles, and estimating the specific surface area of the to-be-tested irregularly shaped rock particles according to the statistical relationships, the volume and the particle size of the to-be-tested irregularly shaped rock particles.

[0045] Optionally, the irregularly shaped rock particle selection and visual classification module specifically includes:

[0046] A sampling area layout unit for dividing a material pile into an upper layer, a middle layer and a lower layer, and arranging 3 to 5 sampling areas in each layer;

[0047] A region division unit for dividing each of the sampling areas into 4 regions with reference to the coning and quartering method;

[0048] A sampling unit for sampling in two diagonal regions to generate a bulk sample; the total number of randomly selected irregularly shaped rock particles in each bulk sample is greater than 150;

[0049] A division unit for dividing the irregularly shaped rock particles included in all the bulk samples into hexahedrons, pentahedrons, tetrahedrons, irregular polyhedrons and needle-like and flaky particles according to their shape characteristics; among them, the irregular polyhedron is an irregularly shaped rock particle with the number of sides greater than 6.

[0050] Optionally, the specific surface area is:

[0051]

[0052] where SSA is the specific surface area; K S is the Heywood surface area shape factor; K V is the Heywood volume shape factor; x k is the particle size; ρ is the rock density.

[0053] An electronic device includes a memory and a processor, the memory is used for storing a computer program, and the processor runs the computer program to enable the electronic device to execute the method for estimating the specific surface area of irregularly shaped rock particles according to any one of the above.

[0054] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for estimating the specific surface area of irregularly shaped rock particles according to any one of the above is realized.

[0055] According to the specific embodiments provided by the present invention, the following technical effects are disclosed: The present invention provides a method, system and device for estimating the specific surface area of irregular rock particles. The Heywood volume shape factor and the surface area shape factor are introduced to characterize the shape of the irregular rock particles. According to the three-axis dimensions, surface area and volume of the reconstructed irregular rock particle model, the Heywood surface area shape factor and the Heywood volume shape factor of each irregular rock particle are calculated. At this time, only by obtaining the volume and particle size of the irregular rock particle to be measured, the specific surface area of the irregular rock particle to be measured can be quickly estimated according to the statistical relationship between the Heywood surface area shape factor and the Heywood volume shape factor, the volume of the irregular rock particle to be measured and the particle size. Thus, the surface breakage energy and the energy utilization efficiency in the breakage process of the ore-rock particles can be quickly calculated.

[0056] In addition, the irregular rock particles are rich in angularity and have complex surface textures, making it difficult to measure the surface area / specific surface area. Both the Heywood surface area shape factor and the Heywood volume shape factor are calculated from the three-dimensional model reconstructed from the three-dimensional point cloud data. The difference between the calculated equivalent model and the actual rock particle shape is greatly reduced, and the accuracy of specific surface area estimation is greatly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0058] Figure 1 It is a flowchart of the method for estimating the specific surface area of irregular rock particles provided by the present invention;

[0059] Figure 2 It is a schematic diagram of the distribution of the sampling areas of irregular rock particles in the muck pile provided by the present invention;

[0060] Figure 3 It is a schematic diagram of the layout of the three-dimensional laser scanning stations for irregular rock particles provided by the present invention and the established typical three-dimensional model of irregular rock particles;

[0061] Figure 4 It is the Heywood surface area shape factor K provided by the present invention s Mean value schematic diagram;

[0062] Figure 5 It is the Heywood volume shape factor K provided by the present invention v Mean value schematic diagram. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0063] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. 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.

[0064] The object of the present invention is to provide a method, system and device for estimating the specific surface area of irregular rock particles, which can quickly estimate the specific surface area of irregular rock particles.

[0065] 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 in conjunction with the accompanying drawings and specific embodiments.

[0066] Embodiment 1

[0067] As Figure 1 shown, the present invention provides a method for estimating the specific surface area of irregular rock particles, including:

[0068] Step 101: Randomly select a plurality of irregular rock particles and perform visual classification according to the shape characteristics of the irregular rock particles.

[0069] In practical applications, to ensure the representativeness of sampling and reduce the difference between the representative sample and the original material, during sampling, 3 - 5 sampling points should be arranged in the upper, middle and lower layers of the stockpile respectively. For each sampling point, referring to the coning and quartering method, each sampling area is generally divided into 4 areas, and sampling is carried out in two areas on the diagonal to form a large sample. The total number of irregular rock particles in a large sample randomly selected from the stockpile should be no less than 150 grains.

[0070] The irregular rock particles are classified into 5 categories according to their appearance shape characteristics: hexahedron, pentahedron, tetrahedron, irregular polyhedron and needle - like and flaky particles.

[0071] Among them, rock particles with a polygon number > 6 are irregular polyhedrons, and rock particles with L / S > 3 are needle - like and flaky particles. And the needle - like and flaky particles can be visually classified first and then re - classified according to L / S. L is the longest dimension of the circumscribed cuboid of the irregular rock particle; S is the smallest dimension of the circumscribed cuboid of the irregular rock particle.

[0072] Step 102: Perform multi - angle three - dimensional laser scanning tests on irregular rock particles of different shape types to obtain point cloud data.

[0073] In practical applications, for irregular rock particles with a particle size greater than 10 cm, a multi-angle three-dimensional laser scanning test can be carried out on-site in combination with the site layout. For irregular rock particles with a particle size of 5 - 10 cm, a multi-angle three-dimensional laser scanning test can be carried out indoors, and the scanning angles can preferably be 4 - 5.

[0074] Step 103: Reconstruct the irregular rock particle model based on the point cloud data, and obtain the three-axis dimensions, surface area, and volume of the irregular rock particle model; the three-axis dimensions include the particle size.

[0075] In practical applications, the three-axis dimensions of irregular rock particles are characterized by the three-axis dimensions (L, I, S) of the minimum circumscribed cube of the particles, and the screening particle size x k is characterized by the intermediate dimension I, and the surface area and volume are accurately calculated by the constructed three-dimensional model, where I is the intermediate dimension of the circumscribed cuboid of the irregular rock particle.

[0076] Step 104: Introduce the Heywood volume shape factor and the surface area shape factor to characterize the shape of the irregular rock particle, and calculate the Heywood surface area shape factor and the Heywood volume shape factor of each irregular rock particle according to the three-axis dimensions, the surface area, and the volume.

[0077] Step 105: Fit the statistical relationships of the Heywood surface area shape factor and the Heywood volume shape factor of irregular rock particles of different shape types.

[0078] In practical applications, according to the difference in the measured values of the surface area and volume of irregular rock particles of different shapes, the statistical relationships of the surface area shape factor and the volume shape factor of irregular rock particles of different shapes are fitted.

[0079] Step 106: Obtain the volume and particle size of the irregular rock particle to be measured, and estimate the specific surface area of the irregular rock particle to be measured according to the statistical relationship, the volume, and the particle size of the irregular rock particle to be measured.

[0080] In practical applications, the intermediate dimension (i.e., the particle size) of the irregular rock particle is simply measured using size measuring tools such as a tape measure and a vernier caliper, and the volume of the irregular rock particle is quickly measured using the drainage method.

[0081] The main principle of the present invention is as follows:

[0082] By introducing the Heywood volume shape factor and the surface area shape coefficient to characterize the shape of the irregular rock particle, the surface area S k of the irregular rock particle with a particle size of x F can be expressed as:

[0083] S F= K S1 6x k 2 (2)

[0084]

[0085] The volume V of the irregularly shaped rock particles with a particle size of x k can be expressed as: F can be expressed as:

[0086]

[0087]

[0088] where K S1 , K S2 is the Heywood surface area shape factor considering the error between the shape of the irregularly shaped rock particles and that of a smooth cube and a sphere, and K V1 , K V2 is the Heywood volume shape factor considering the error between the shape of the irregularly shaped rock particles and that of a smooth cube and a sphere.

[0089] According to equations (2) to (5), the specific surface area SSA of the irregularly shaped rock particles with a particle size of x k can be expressed as:

[0090]

[0091] where SSA is the specific surface area; K s and K v are the Heywood surface area shape factor and the Heywood volume shape factor respectively; ρ is the rock density.

[0092] The irregularly shaped rock particles have rich angularity and complex surface textures, making the measurement or calculation of their surface area relatively complex, but the measurement of volume and particle size is relatively simple. According to equation (6), establishing the statistical relationship between the Heywood surface area and volume shape factors, the surface area of the irregularly shaped rock particles can be quickly estimated through the measured data of particle size and volume, and then their specific surface area can be quickly estimated.

[0093] Example 2

[0094] Taking some medium-weathered and weakly weathered granite irregularly shaped rock particles in South China as an example, in a certain urban rail transit parking lot in South China, deep-hole bench blasting was used for excavation, and the exposed strata were mainly medium-weathered and weakly weathered granite. During the excavation of the parking lot, multiple deep-hole blasting tests were carried out, and after blasting, some irregularly shaped rock particles were randomly selected from the muck pile according to the method described in Example 1 for shape classification tests and three-dimensional laser scanning tests, and the triaxial dimensions, surface area, volume, and specific surface area data of rock particles with different shapes were obtained.

[0095] A method for rapidly estimating the specific surface area of irregular rock particles, comprising the following steps:

[0096] Step 1, sample from a large pile of materials, randomly select a certain number of irregular rock particles, and visually classify them according to their shape characteristics.

[0097] After the rock mass in this project is excavated by blasting, 3 sampling points are respectively set at the upper, middle and lower parts of the muck pile. Each sampling point is generally divided into 4 areas of 1.5m×1.5m. Samples are taken from two diagonal areas to form a large sample. Finally, 9 sub-samples are combined into a large sample. The distribution of the sampling areas is as Figure 2 shown.

[0098] According to the collected samples of irregular rock particles, they are classified into 5 categories: hexahedron, pentahedron, tetrahedron, irregular polyhedron and needle-like and flaky particles according to their appearance shape characteristics. The quantity statistics of rock particles of various shapes are shown in Table 1.

[0099] Table 1 Statistical results of shape classification test of irregular rock particles

[0100]

[0101] Step 2, conduct a multi-angle three-dimensional laser scanning test on the irregular rock particles, reconstruct the three-dimensional model of the irregular rock particles by using the obtained point cloud data, and obtain their three-axis dimensions (L, I, S), surface area and volume data by using the three-dimensional model.

[0102] After the shape classification test, the irregular rock particles with a particle size < 10 cm are taken back to the indoor for multi-angle three-dimensional laser scanning test, and the irregular rock particles with a particle size ≥ 10 cm are subjected to three-dimensional laser scanning test at the blasting test site. A total of 4 scanning stations are respectively set up for the whole three-dimensional laser scanning test. The layout of the scanning stations for the three-dimensional laser scanning test and the three-dimensional model of typical irregular rock particles established by using the point cloud data are as Figure 3 shown.

[0103] Step 3, use the intermediate size I to calculate the Heywood surface area shape factor K s and the Heywood volume shape factor K v of each irregular rock particle, and calculate the average values of K s and K v of irregular rock particles of different shape classifications after excluding extreme outliers.

[0104] According to the three-axis dimensions, surface area and volume data of irregular rock particles of various shapes obtained in Step 2, use Equations (2) - (5) to calculate the Heywood surface area shape factor K sThe mean value, as Figure 4 shown, is the Heywood volume shape factor K v The mean value, as Figure 5 shown.

[0105] Step 4: According to the measured data, fit the statistical relationships between the surface area shape factor and the volume shape factor of irregularly shaped rock particles with different shapes.

[0106] According to Figures 3 to 4 the relevant data in s and the Heywood volume shape factor K v when the irregularly shaped rock particles are equivalent to cube and sphere models, there is a statistical relationship shown in Equation (7):

[0107]

[0108] In this project, when the irregularly shaped rock particles with shapes of hexahedron, pentahedron, tetrahedron and irregular polyhedron are equivalent to cube models, λ = 0.986; when equivalent to sphere models, λ = 1.220; when the needle-like and flaky irregularly shaped rock particles are equivalent to cube models, λ = 1.035; when equivalent to sphere models, λ = 1.275.

[0109] Step 5: In practical applications, simply measure the volume and triaxial dimensions of the irregularly shaped rock particles. According to the statistical relationship between the fitted surface area shape factor and the volume shape factor, the surface area of the irregularly shaped rock particles can be quickly estimated, and then the specific surface area of the irregularly shaped rock particles can be quickly calculated.

[0110] In the subsequent energy consumption calculation and optimization process of this project, tools such as a tape measure can be used to simply measure the intermediate dimension of the irregularly shaped rock particles, and the drainage method can be used to quickly measure the volume of the irregularly shaped rock particles. Based on this, the Heywood volume shape factor K v can be quickly calculated according to the equivalent model, and then the Heywood surface area shape factor K s can be quickly obtained by using the mapping relationship established in Equation (7). Combining the calculated Heywood surface area shape factor K s and the Heywood volume shape factor K v , the specific surface area of the irregularly shaped rock particles can be quickly estimated by using Equation (6).

[0111] Example 3

[0112] In order to execute the method corresponding to the above Example 1 to achieve the corresponding functions and technical effects, a system for estimating the specific surface area of irregularly shaped rock particles is provided below.

[0113] A system for estimating the specific surface area of irregularly shaped rock particles, comprising:

[0114] Irregular rock particle selection and visual classification module, which is used to randomly select multiple irregular rock particles and conduct visual classification according to the shape characteristics of the irregular rock particles.

[0115] Point cloud data acquisition module, which is used to conduct multi-angle three-dimensional laser scanning tests on irregular rock particles of different shape types to obtain point cloud data.

[0116] Irregular rock particle model reconstruction module, which is used to reconstruct an irregular rock particle model according to the point cloud data and obtain the three-axis dimensions, surface area and volume of the irregular rock particle model; the three-axis dimensions include particle size.

[0117] Heywood shape factor calculation module, which is used to introduce the Heywood volume shape factor and surface area shape factor to characterize the shape of the irregular rock particle, and calculate the Heywood surface area shape factor and Heywood volume shape factor of each irregular rock particle according to the three-axis dimensions, the surface area and the volume.

[0118] Statistical relationship fitting module, which is used to fit the statistical relationship between the Heywood surface area shape factor and the Heywood volume shape factor of irregular rock particles of different shape types.

[0119] Specific surface area estimation module, which is used to obtain the volume and particle size of the to-be-tested irregular rock particle, and estimate the specific surface area of the to-be-tested irregular rock particle according to the statistical relationship, the volume and the particle size of the to-be-tested irregular rock particle.

[0120] Optionally, the irregular rock particle selection and visual classification module specifically includes:

[0121] Sampling area layout unit, which is used to divide the material pile into upper, middle and lower layers, and arrange 3 to 5 sampling areas in each layer.

[0122] Area division unit, which is used to divide each sampling area into 4 areas with reference to the coning and quartering method.

[0123] Sampling unit, which is used to sample in two diagonal areas to generate a large sample; the total number of randomly selected irregular rock particles in each large sample is greater than 150.

[0124] Division unit, which is used to divide the irregular rock particles included in all the large samples into hexahedrons, pentahedrons, tetrahedrons, irregular polyhedrons and needle-like and flaky particles according to the shape characteristics; among them, the irregular polyhedron is an irregular rock particle with the number of polygons greater than 6.

[0125] Optionally, the specific surface area is:

[0126]

[0127] Among them, SSA is the specific surface area; K S is the Heywood surface area shape factor; K V is the Heywood volume shape factor; x k is the particle size; ρ is the rock density.

[0128] An embodiment of the present invention provides an electronic device including a memory and a processor. The memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to execute the method for estimating the specific surface area of irregular rock particles provided in Embodiment 1.

[0129] In practical applications, the above-mentioned electronic device may be a server.

[0130] In practical applications, the electronic device includes: at least one processor, a memory, a bus, and a communication interface.

[0131] Among them: the processor, the communication interface, and the memory complete communication with each other through the communication bus.

[0132] The communication interface is used to communicate with other devices.

[0133] The processor is used to execute a program, and specifically can execute the method described in the above embodiment.

[0134] Specifically, the program may include program code, and the program code includes computer operation instructions.

[0135] The processor may be a central processing unit CPU, or a specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present invention. One or more processors included in the electronic device may be of the same type of processor, such as one or more CPUs; or may be of different types of processors, such as one or more CPUs and one or more ASICs.

[0136] The memory is used to store the program. The memory may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk memory.

[0137] Based on the description of the above embodiments, an embodiment of the present application provides a storage medium, on which computer program instructions are stored, and the computer program instructions can be executed by a processor to implement the method described in any embodiment.

[0138] The special-shaped rock particle specific surface area estimation system provided by the embodiments of the present application exists in various forms, including but not limited to:

[0139] (1) Mobile communication devices: These devices are characterized by having mobile communication functions and mainly aim to provide voice and data communication. Such terminals include: smart phones (such as iPhone), multimedia phones, functional phones, and low-end phones, etc.

[0140] (2) Ultra-mobile personal computer devices: These devices belong to the category of personal computers, have computing and processing functions, and generally also have mobile Internet access performance. Such terminals include: PDA, MID, and UMPC devices, etc., such as iPad.

[0141] (3) Portable entertainment devices: These devices can display and play multimedia content. Such devices include: audio and video players (such as iPod), handheld game consoles, e-books, and smart toys and portable in-vehicle navigation devices.

[0142] (4) Other electronic devices with data interaction functions.

[0143] So far, specific embodiments of the present subject matter have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recited in the claims may be performed in a different order and still achieve the desired result. Additionally, the processes depicted in the figures do not necessarily require the particular order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing may be advantageous.

[0144] The systems, devices, modules, or units illustrated in the above embodiments may be specifically implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or any combination of these devices.

[0145] For the convenience of description, when describing the above device, various units are described separately according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in one or more software and / or hardware. Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) containing computer-usable program code.

[0146] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the specified functions in Figure 1 one or more of the processes Figure 1 or a plurality of processes and / or blocks

[0147] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device that implements the specified functions in Figure 1 one or more of the processes Figure 1 or a plurality of processes and / or blocks

[0148] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the specified functions in Figure 1 one or more of the processes Figure 1 or a plurality of processes and / or blocks

[0149] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and a memory.

[0150] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0151] Computer-readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM),

[0152] Digital Versatile Disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, disk storage or other magnetic storage devices

[0153] Or any other non-transmission medium that can be used to store information that can be accessed by a computing device. According to the definition in this article, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0154] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0155] The present application may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific transactions or implement specific abstract data types. The present application may also be practiced in distributed computing environments where transactions are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0156] In the present specification, the various embodiments are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. For the same or similar parts among the various embodiments, reference can be made to each other. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple. For the relevant parts, reference can be made to the description in the method section.

[0157] In this article, specific examples are used to elaborate on the principles and implementation manners of the present invention. The descriptions of the above embodiments are only used to help understand the method of the present invention and its core idea. At the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. A method for estimating the specific surface area of irregularly shaped rock particles, characterized in that, it includes: Randomly select a plurality of irregularly shaped rock particles and perform visual classification according to the shape characteristics of the irregularly shaped rock particles; Perform multi-angle three-dimensional laser scanning tests on irregularly shaped rock particles of different shape types to obtain point cloud data; Reconstruct the irregularly shaped rock particle model based on the point cloud data, and obtain the three-axis dimensions, surface area, and volume of the irregularly shaped rock particle model; the three-axis dimensions include the particle size; Introduce the Heywood volume shape factor and the surface area shape factor to characterize the shape of the irregularly shaped rock particles, and calculate the Heywood surface area shape factor and the Heywood volume shape factor of each irregularly shaped rock particle according to the three-axis dimensions, the surface area, and the volume; Fit the statistical relationships of the Heywood surface area shape factor and the Heywood volume shape factor of irregularly shaped rock particles of different shape types; Obtain the volume and particle size of the irregularly shaped rock particles to be measured, and estimate the specific surface area of the irregularly shaped rock particles to be measured according to the statistical relationship, the volume, and the particle size of the irregularly shaped rock particles to be measured.

2. The method for estimating the specific surface area of irregularly shaped rock particles according to claim 1, characterized in that, Randomly select a plurality of irregularly shaped rock particles and perform visual classification according to the shape characteristics of the irregularly shaped rock particles, specifically including: Divide the material pile into upper, middle, and lower layers, and arrange 3 to 5 sampling areas in each layer; Refer to the coning and quartering method and divide each sampling area into 4 regions; Sample in two diagonal regions to generate a large sample; the total number of irregularly shaped rock particles randomly selected in each large sample is greater than 150; Divide the irregularly shaped rock particles included in all the large samples into hexahedrons, pentahedrons, tetrahedrons, irregular polyhedrons, and needle-like and flaky particles according to the shape characteristics; among them, the irregular polyhedron is an irregularly shaped rock particle with more than 6 polygon sides.

3. The method for estimating the specific surface area of irregularly shaped rock particles according to claim 1, characterized in that, Perform multi-angle three-dimensional laser scanning tests on irregularly shaped rock particles of different shape types to obtain point cloud data, specifically including: Obtain the particle sizes of irregularly shaped rock particles of different shape types; Perform multi-angle three-dimensional laser scanning tests on the irregularly shaped rock particles with a particle size greater than 10 cm on-site to obtain point cloud data; Perform multi-angle three-dimensional laser scanning tests on the irregularly shaped rock particles with a particle size in the range of 5 cm to 10 cm indoors to obtain point cloud data.

4. The method for estimating the specific surface area of irregularly shaped rock particles according to claim 1, characterized in that, Obtain the volume and particle size of the irregularly shaped rock particles to be measured, specifically including: Measure the volume of the irregularly shaped rock particles to be measured by the drainage method; Measure the particle size of the irregularly shaped rock particles to be measured by a size measuring tool.

5. The method for estimating the specific surface area of irregularly shaped rock particles according to claim 1, characterized in that, The specific surface area is: Among them, SSA is the specific surface area; K S is the Heywood surface area shape factor; K V is the Heywood volume shape factor; x k is the particle size; ρ is the rock density.

6. An estimation system for the specific surface area of irregularly shaped rock particles, characterized in that, it includes: Irregular rock particle selection and visual classification module, which is used to randomly select multiple irregular rock particles and conduct visual classification according to the shape characteristics of the irregular rock particles; Point cloud data acquisition module, which is used to conduct multi-angle three-dimensional laser scanning tests on irregular rock particles of different shape types to obtain point cloud data; Irregular rock particle model reconstruction module, which is used to reconstruct the irregular rock particle model according to the point cloud data and obtain the three-axis dimensions, surface area and volume of the irregular rock particle model; the three-axis dimensions include particle size; Heywood shape factor calculation module, which is used to introduce the Heywood volume shape factor and the surface area shape factor to characterize the shape of the irregular rock particle, and calculate the Heywood surface area shape factor and the Heywood volume shape factor of each irregular rock particle according to the three-axis dimensions, the surface area and the volume; Statistical relationship fitting module, which is used to fit the statistical relationship between the Heywood surface area shape factor and the Heywood volume shape factor of irregular rock particles of different shape types; Specific surface area estimation module, which is used to obtain the volume and particle size of the irregular rock particle to be measured, and estimate the specific surface area of the irregular rock particle to be measured according to the statistical relationship, the volume and the particle size of the irregular rock particle to be measured.

7. The irregular rock particle specific surface area estimation system according to claim 6, characterized in that, The irregular rock particle selection and visual classification module specifically includes: Sampling area layout unit, which is used to divide the material pile into upper, middle and lower layers, and arrange 3-5 sampling areas in each layer; Area division unit, which is used to divide each sampling area into 4 areas with reference to the coning and quartering method; Sampling unit, which is used to sample in two diagonal areas to generate a large sample; the total number of randomly selected irregular rock particles in each large sample is greater than 150; Division unit, which is used to divide the irregular rock particles included in all the large samples into hexahedrons, pentahedrons, tetrahedrons, irregular polyhedrons and needle-like and flaky particles according to the shape characteristics; among them, the irregular polyhedron is an irregular rock particle with the number of polygons greater than 6.

8. The irregular rock particle specific surface area estimation system according to claim 6, characterized in that, The specific surface area is: Among them, SSA is the specific surface area; K S is the Heywood surface area shape factor; K V is the Heywood volume shape factor; x k is the particle size; ρ is the rock density.

9. An electronic device, characterized in that, it includes a memory and a processor, the memory is used to store a computer program, and the processor runs the computer program so that the electronic device executes the irregular rock particle specific surface area estimation method according to any one of claims 1-5.

10. A computer-readable storage medium, characterized in that, it stores a computer program, and when the computer program is executed by a processor, it implements the irregular rock particle specific surface area estimation method according to any one of claims 1-5.

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