Particle size control device and particle size control method

Abstract

A particle size control device and method are provided that can accurately analyze and control the particle size of raw materials. [Solution] The present invention relates to a particle size control device that includes a conveying section for conveying raw materials, a sorting section for separating small particles from the raw materials and leaving large particles that are larger than the small particles, an imaging section that is arranged facing the conveying section to acquire images of the large particles, and an analysis section for analyzing the particle size distribution of the raw materials from the images acquired by the imaging section, and a particle size control method applied to the device.

Description

[Technical Field]

[0001] The present invention relates to a particle size control device and method, and more particularly to a particle size control device and method that can accurately analyze and control the particle size of raw materials. [Background technology]

[0002] The process for producing metallurgical coke is as follows: Various types of coal stored in a yard are crushed according to their type and mixed in a pre-calculated ratio to produce a coal blend. The coal blend is then loaded into a coke oven and carbonized at high temperature to produce coke. The particle size distribution of the crushed coal is an important factor that affects the quality of the coke.

[0003] In other words, when producing a coal blend, if the crushed coals are not mixed uniformly according to the blending ratio calculated taking into account the caking properties, fluidity, etc. of each coal, coke of the desired quality cannot be produced in the coke oven. In order to mix the crushed coals uniformly, the particle size of the crushed coals must be controlled within a certain range.

[0004] In the past, to control the particle size of crushed coal, a predetermined amount of sample was taken from the crushed coal, dried, and then the dried coal was sorted by particle size to evaluate the particle size distribution. However, this conventional method has the problem that the evaluation results vary depending on the sampling method and number of times.

[0005] The background art of the present invention is described in the following patent documents. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Republic of Korea Patent Registration No. 10-1625962 [Patent Document 2] Republic of Korea Patent Registration No. 10-1673273 Summary of the Invention [Problem to be solved by the invention]

[0007] The present invention provides a particle size control apparatus and method that can accurately analyze and control the particle size of raw materials. [Means for solving the problem]

[0008] A particle size control device according to an embodiment of the present invention comprises a conveying unit for conveying raw materials, a sorting unit for separating small particles from the raw materials and leaving large particles that are larger than the small particles, an imaging unit arranged to face the conveying unit for acquiring images of the large particles, and an analysis unit for analyzing the particle size distribution of the raw materials from the images acquired by the imaging unit.

[0009] The particle size control device may include a return unit connected to the sorting unit and positioned above the conveying unit to return the sorted small particles onto the large particles whose images were acquired.

[0010] The particle size control device may include a control section for adjusting the supply conditions of the subsequent raw material to be supplied to the transport section, using the particle size distribution analyzed by the analysis section.

[0011] The conveying section may include a hopper that receives a supply of raw material, and a conveyor having a belt for continuously conveying the raw material discharged from the hopper.

[0012] The sorting unit may include a suction device having an open surface facing the conveyor so as to suck in small particles, and a suction pump connected to the suction device.

[0013] The screening section may include a sieve having a plurality of openings formed therein for sucking small particles from the raw material.

[0014] The aperture size of the openings may be in the range of more than 0 mm and less than 3 mm.

[0015] The sieves may be positioned continuously in the width direction of the belt within a range of 10% to 90% of the width of the belt that transports the raw material.

[0016] The sorting section may include either a first sorter for causing small particles to sink relative to large particles from the upper surface of the raw material, or a second sorter for causing small particles to roll down along the upper surface of the raw material while separating them from the large particles.

[0017] The imaging area of ​​the imaging unit may include the entire width of the belt that transports the raw material.

[0018] The number of the hoppers may be multiple to receive multiple types of raw materials, and the conveyors may include multiple first conveyors connected to each hopper and a second conveyor connected to the multiple first conveyors, and the sorting unit and the imaging unit may be arranged on the side of the multiple first conveyors.

[0019] The sorting unit may be arranged on the side of one or more first conveyors selected from the plurality of first conveyors, and the imaging unit may be arranged on the side of the conveyor on which the sorting unit is arranged.

[0020] The imaging unit may acquire an image of the large particles from which the small particles have been separated, and the analysis unit may identify individual large particles from the captured image, analyze their particle size distribution, and determine the overall particle size distribution of the raw material using the analyzed particle size distribution of the large particles.

[0021] The analysis unit may derive the area of ​​the identified large particles, classify the large particles into different particle sizes based on their area, calculate the total area ratio on the acquired image for each of the classified large particles, convert the calculated total area ratio for each of the classified large particles into a weight ratio based on data previously learned by the artificial intelligence, analyze the weight ratio for each of the classified large particles using the particle size distribution of the large particles, calculate the weight ratio of the sorted small particles using the weight ratio for each of the large particles, and calculate the overall particle size distribution of the raw material using the weight ratio for each of the large particles and the weight ratio for the small particles.

[0022] The analysis unit may divide the large particles into a plurality of groups according to their particle sizes, analyze the weight ratio of the large particles for each group using the particle size distribution of the large particles, and determine the overall particle size distribution of the raw material using the weight ratio of the large particles for each group and the weight ratio of the small particles.

[0023] The analysis unit may use the crushing characteristics of the plurality of raw materials to apply the particle size distribution determined from the raw material transported in the selected first transporter to all of the plurality of raw materials.

[0024] The management unit may compare the overall particle size distribution of the raw material analyzed by the analysis unit with a predetermined standard particle size distribution, and based on the comparison result, control the crushing conditions of the subsequent raw material to be supplied to the conveying unit, thereby managing the quality of the subsequent raw material.

[0025] A particle size control method according to an embodiment of the present invention includes the steps of preparing raw materials, transporting the prepared raw materials, separating the transported raw materials into small particles and large particles larger than the small particles, capturing images of the large particles, analyzing the particle size distribution of the large particles from the captured images, and determining the particle size distribution of the raw materials using the particle size distribution of the large particles.

[0026] The step of transporting the prepared raw material may include a step of transporting the prepared raw material at a speed in the range of 0.1 to 0.15 m / s.

[0027] The process of separating the transported raw material into small particles and large particles larger than the small particles may include a process of sucking the small particles from the upper surface of the raw material and leaving the large particles, and the process of acquiring an image may include a process of acquiring an image of the large particles from which the small particles have been separated from the upper surface of the raw material, and a process of discharging the separated small particles onto the large particles on the upper surface of the raw material after the process of acquiring an image.

[0028] The step of analyzing the particle size distribution of the large particles from the captured image may include the steps of: calculating the areas of the large particles from the image of the large particles and classifying the large particles into different particle sizes based on their areas; calculating a total area ratio on the captured image for each classified large particle; and converting the total area ratio calculated for each classified large particle into a weight ratio.

[0029] The step of classifying the large particles into different particle sizes according to area may include a step of dividing the classified large particles into a plurality of groups according to their particle sizes, and the step of calculating the total area ratio and the step of converting to the weight ratio may be performed for each classified group.

[0030] The step of determining the particle size distribution of the raw material using the particle size distribution of the large particles may include a step of determining the weight ratio of the sorted small particles when converting the total area ratio determined for each of the separated large particles into a weight ratio, and a step of determining the overall particle size distribution of the raw material using the weight ratio of each of the large particles and the weight ratio of the small particles.

[0031] The step of converting the total area ratio determined for each large particle into a weight ratio may include a step of predicting a weight ratio for each distinguished large particle according to the total area ratio determined for each large particle using a particle size distribution model of the raw material generated based on data previously learned by an artificial intelligence, and replacing the total area ratio determined for each large particle with the predicted weight ratio for each large particle. The step of determining the weight ratio of the sorted small particles may include a step of determining the weight ratio of the large particles by adding up the predicted weight ratios for each large particle, and a step of setting the weight ratio that sums up with the weight ratio of the large particles to be 100 percent as the weight ratio of the small particles.

[0032] The step of preparing the raw materials includes a step of preparing a plurality of raw materials having different Hardgrove Grindability Index (HGI), the step of transporting the prepared raw materials includes a step of transporting each of the plurality of raw materials, and the steps of sorting the transported raw materials into small particles and large particles larger than the small particles, the step of photographing the large particles to obtain images, the step of analyzing the particle size distribution of the large particles from the photographed images, and the step of determining the particle size distribution of the raw material using the particle size distribution of the large particles may be performed on at least one or more raw materials selected from the plurality of raw materials.

[0033] The particle size control method may include, after performing the step of determining a particle size distribution of a selected raw material for the raw material, applying the particle size distribution of the selected raw material to all of the plurality of raw materials using the Hardgrove Grindability Index of each of the plurality of raw materials.

[0034] The step of preparing the raw material may include a step of crushing the raw material, and after the step of determining the particle size distribution of the raw material, may include a step of utilizing the determined particle size distribution of the raw material in a step of preparing a subsequent raw material.

[0035] The step of utilizing the obtained particle size distribution in the step of preparing the subsequent raw material may include the steps of: comparing the obtained particle size distribution of the raw material with a predetermined reference particle size distribution; controlling the crushing conditions of the subsequent raw material based on the comparison result; and crushing the subsequent raw material under the controlled crushing conditions. [Effects of the Invention]

[0036] According to an embodiment of the present invention, by capturing images of the raw materials while they are being conveyed and analyzing the particle size distribution of the raw materials from the captured images, the particle size distribution of the raw materials can be analyzed quickly in real time before blending the raw materials. Furthermore, before capturing the raw materials, in order to prevent small particles from exaggerating and distorting the image, small particles are sorted out from the conveyed raw materials, leaving large particles, and then capturing the large particles, the boundaries between the raw material particles become clearly visible, resulting in a clear image. Therefore, the particle size distribution of the raw materials can be accurately analyzed from the clear image.

[0037] Furthermore, the particle size distribution of the subsequent raw material can be smoothly controlled based on the accurate analysis results of the particle size distribution. Therefore, while repeatedly receiving and processing raw materials, the particle size distribution of the subsequent raw material to be processed can be continuously controlled so as to be a desired particle size distribution, and the quality of the processed raw material can always be maintained at a desired quality level. This makes it possible to minimize variations in the quality of the coke produced in the subsequent coke production process using the raw materials. [Brief explanation of the drawings]

[0038] [Figure 1] 1 is a diagram illustrating a raw material processing facility equipped with a particle size control device according to an embodiment of the present invention. [Figure 2] 1 is a side view of a particle size control device according to an embodiment of the present invention. [Figure 3] 1 is a plan view of a particle size control device according to an embodiment of the present invention. [Figure 4] FIG. 2 is a schematic diagram of a sorting unit according to an embodiment of the present invention. [Figure 5] 6 is a photograph for explaining the operation of a sorting unit according to an embodiment of the present invention. [Figure 6] 1 is a photograph and a graph illustrating an analysis unit according to an embodiment of the present invention. [Figure 7]FIG. 2 is a flowchart illustrating a particle size management method according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0039] Hereinafter, embodiments of the present invention will be described in more detail with reference to the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, and may be embodied in various different forms. The following embodiments are provided solely to complete the disclosure of the present invention and to fully convey the scope of the invention to those skilled in the art. In order to explain the embodiments of the present invention, the drawings may be exaggerated, and parts irrelevant to the description may be omitted from the drawings, and the same reference numerals in the drawings refer to the same elements.

[0040] The present invention relates to a particle size control device and method. Hereinafter, an embodiment of the present invention will be described in detail, taking as an example a case where the particle size control device and method are applied to a raw material processing facility that processes raw materials for producing coke in a steelmaking operation. Needless to say, the particle size control device and method according to the embodiment of the present invention can also be applied to various raw material processing facilities that process a variety of raw materials. For example, the particle size control device and method according to the embodiment of the present invention can also be applied to a raw material processing facility that processes iron ore, limestone, etc.

[0041] The particle size control apparatus and method according to the embodiment of the present invention can accurately analyze and control the particle size of raw materials. Needless to say, the particle size control apparatus and method according to the embodiment of the present invention may be used only to accurately analyze the particle size of raw materials. In such a case, the particle size control apparatus and method according to the embodiment of the present invention may be referred to as a particle size analysis apparatus and method.

[0042] FIG. 1 is a diagram illustrating a raw material processing facility to which a particle size control device and method according to an embodiment of the present invention are applied.

[0043] A raw material processing facility according to an embodiment of the present invention will be briefly described with reference to FIG.

[0044] The raw material processing equipment according to the embodiment of the present invention can process raw materials for producing coke. For example, the raw material may be coal. Meanwhile, coal may be variously referred to as single coal, coking coal, etc. The raw material may be of various types, for example, coal varieties. For example, the raw material processed by the raw material processing equipment may be of 6 to 12 types of coal. Needless to say, the number of coal varieties may be large. Here, the raw material may have different properties such as caking property, fluidity, and crushability depending on the coal type.

[0045] The raw materials may be transported by, for example, a ship 10 and piled up in a yard by coal type. At this time, a raw material coal preparation facility 20 may be installed in the yard. The raw materials may be passed through the raw material coal preparation facility 20 to remove foreign matter such as gangue from the raw materials. Thereafter, the raw materials may be supplied to a raw material processing facility, or may be crushed and mixed in the raw material processing facility to produce blended coal.

[0046] The raw material processing facility may be a facility for crushing raw materials by coal type and mixing the crushed raw materials by coal type at a predetermined blending ratio to produce blended coal. The raw material processing facility includes a raw material crushing device 30 and a particle size control device 1000. Here, the particle size control device 1000 may also be referred to as a raw material blending device. In other words, processing may mean crushing and blending of raw materials. Needless to say, the raw material processing facility may process raw materials in various ways.

[0047] The raw material crushing device 30 may be an impact type raw material crushing device 30. The raw material crushing device 30 may crush the raw material in various ways. For example, the raw material crushing device 30 may be equipped with a hammer crusher. In this case, the hammer crusher may be equipped with a rotating shaft, a hammer, and a rebound plate. The hammer crusher may rotate the hammer using the rotating shaft, drop the raw material between the hammer and the rebound plate, and crush the raw material by striking it with the hammer and the rebound plate. Meanwhile, the raw material may have different crushability depending on the coal type. Furthermore, the particle size distribution of the crushed raw material may differ depending on the crushability.

[0048] The raw material crushing device 30 can alternately receive raw material supplies by coal type. Therefore, the raw material crushing device 30 can crush raw material supplies by coal type. Furthermore, the raw material crushed alternately by coal type in the raw material crushing device 30 can be supplied to the particle size control device 1000 and produced as blended coal.

[0049] The hammer and the repulsion plate may be worn during the crushing of the raw materials, and the distance between the hammer and the repulsion plate may change due to impact, which may result in a change in the particle size distribution of the crushed raw materials.

[0050] Furthermore, if the particle size distribution of the raw materials varies, it is difficult to uniformly mix the raw materials in the coal blend when the particle size control device 1000 mixes raw materials crushed by coal type in a predetermined blending ratio to produce a coal blend. If the raw materials are not uniformly mixed, there is a concern that the quality of the produced coke will be reduced when the coal blend is carbonized at high temperature to produce coke in a coke production facility that is a downstream facility of the raw material processing facility.

[0051] Therefore, according to an embodiment of the present invention, the particle size control device 1000 alternately receives raw materials crushed by coal type from the raw material crushing device 30, blends these to produce blended coal, analyzes the particle size distribution of the raw materials, feeds the results back to the raw material crushing device 30, and controls the crushing conditions for the subsequent raw materials to be supplied from the raw material crushing device 30 to the particle size control device 1000, thereby controlling the quality of the subsequent raw materials.

[0052] At this time, the raw material crushing device 30 can control the operating conditions of the hammer crusher according to the raw material crushing conditions. For example, the rotation speed of the hammer, the distance between the hammer and the repulsion plate, etc. can be controlled. This makes it possible to adjust the particle size of the raw material to be crushed. Therefore, the particle size distribution of the subsequent raw material that is crushed in the raw material crushing device 30 and then supplied to the particle size control device 1000 can be controlled to a desired particle size distribution.

[0053] Meanwhile, the blended coal produced in the raw material processing equipment 30, 1000 may be supplied to coke production equipment 40, 50. The coke production equipment 40, 50 may include a coke oven 40 and a dry quenching chamber 50. The blended coal may be charged into the coke oven 40 and carbonized at high temperature to produce red-hot coke. The produced red-hot coke is supplied to the dry quenching chamber 50 and quenched to turn into coke. The produced coke may be charged into molten iron production equipment, for example, a blast furnace equipment 60, and used to produce molten iron. Meanwhile, the coke oven gas generated in the coke production equipment 40, 50 is supplied to a gas refining equipment 70, where it is refined, and then supplied to the coke production equipment 40, 50 and the blast furnace equipment 60, where it can be used as fuel.

[0054] 2 and 3 are a side view and a plan view of a particle size control device according to an embodiment of the present invention.

[0055] The particle size control device 1000 according to the embodiment of the present invention will be described in detail with reference to FIGS.

[0056] The particle size control device 1000 according to an embodiment of the present invention can receive raw materials crushed by coal type, produce a blended raw material from the raw materials, accurately analyze the particle size of the received raw materials, and adjust the supply conditions of the subsequent raw materials.

[0057] 2 and 3, a particle size control device 1000 according to an embodiment of the present invention includes a conveying unit 100 for conveying raw materials M1, M2, M3, M4, M5, M6, M7, and M8, a sorting unit 200 for separating small particles from the raw materials and leaving large particles that are larger than the small particles, an imaging unit 300 arranged to face the conveying unit 100 for acquiring images of the large particles, and an analysis unit 400 for analyzing the particle size distribution of the raw materials from the images acquired by the imaging unit 300.

[0058] The particle size control device 1000 may also include a return unit 500 connected to the sorting unit 200 and disposed above the conveying unit 100 in order to return the sorted small particles onto the large particles whose images have been acquired, and a control unit 600 for adjusting the supply conditions of the subsequent raw material to be supplied to the conveying unit 100 using the particle size distribution analyzed by the analyzing unit 400. In this case, the supply conditions may be crushing conditions.

[0059] The raw material is a raw material, such as coal, that is crushed in the raw material crushing device 30 and then supplied to the particle size control device 1000. The raw material may consist of a plurality of particles. At this time, the raw material particles may be sorted into small particles and large particles.

[0060] Specifically, among the raw material particles, particles having a particle size in the range of more than 0 and less than 3 mm are defined as small particles, and particles having a particle size in the range of 3 mm or more are defined as large particles. More specifically, the particle size range of large particles may be 3 mm or more and 15 mm or less.

[0061] The raw material contains a certain amount of moisture, which may cause aggregation between raw material particles. If the particle size is greater than 0 and less than 3 mm, the moisture may cause significant aggregation. For example, multiple particles with a particle size less than 3 mm may aggregate and appear as a single particle with a particle size of 3 mm or more. Therefore, the particle size may be distorted in the captured image.

[0062] In addition, raw materials are often black in color, and black has the property of absorbing light, making it difficult to distinguish between particles. In this case, if the particle size is less than 3 mm, it is very difficult to distinguish the boundaries between particles in the captured image. If multiple particles with a size less than 3 mm are positioned around a particle with a size of 3 mm or more, the particle with a size of 3 mm or more may appear larger than its actual size. Therefore, the particle size may be exaggerated in the captured image.

[0063] Therefore, particles having a diameter of more than 0 and less than 3 mm, which may exaggerate or distort the particle size of the raw material when the raw material is imaged, are defined as small particles. By removing the small particles from the large particles and then imaging the raw material from which the small particles have been removed, it is possible to prevent the particle diameter from being exaggerated or distorted in the image taken, and to obtain a clear image in which the particle diameter is clearly captured.

[0064] Alternatively, the particle size range of the large particles may be subdivided into multiple intervals. In this case, the multiple intervals may include a first large particle interval of 3 mm or more and less than 5 mm, a second large particle interval of 5 mm or more and less than 10 mm, and a third large particle interval of 10 mm or more and less than 15 mm. These multiple intervals can be used to analyze the particle size distribution of the raw material.

[0065] The conveying section 100 is a conveying section 100 for conveying and blending raw materials, and may include a hopper 110 for receiving a supply of raw materials, and conveyors 120, 130 having a belt 121 for continuously conveying the raw materials continuously discharged from the hopper 110.

[0066] The hoppers 110 may receive and store raw materials from the raw material crushing device 30 and discharge the stored raw materials to the conveyor 120 at a predetermined discharge rate. The number of hoppers 110 may be multiple to receive multiple types of raw materials. Here, multiple types may refer to multiple coal types. The number of hoppers 110 may be the same as the number of raw material coal types. For example, if the raw material coal types are eight, the number of hoppers 110 may also be eight. Thus, the multiple hoppers 110 may store and discharge raw materials of different coal types. For example, when the raw materials include hard coking coal, soft coking coal, etc., the hopper 110 storing the hard coking coal and the hopper 110 storing the soft coking coal may be different from each other. Meanwhile, at least one hopper 110 among the multiple hoppers 110 may be dedicated to raw materials whose coal types frequently change and alternately store these raw materials. On the other hand, if the raw material contains only one type of coal, the number of hoppers 110 may be one.

[0067] The multiple hoppers 110 may be arranged on both sides of the width direction of the second conveyor 130 described below, and may be aligned in the longitudinal direction of the second conveyor 130. In this case, the width direction and the longitudinal direction may intersect each other, or may intersect with the vertical direction, respectively. The multiple hoppers 110 may be connected to multiple raw material crushing devices 30, respectively.

[0068] Each hopper 110 may have a storage space therein for storing raw material and may have a discharge outlet formed at the bottom. A feeder (not shown) for adjusting the discharge rate of the raw material may be provided at the discharge outlet of each hopper 110. The discharge rate of the raw material may differ depending on the type of coal, and each hopper 110 may operate its own feeder in accordance with the predetermined discharge rate of the raw material stored in the hopper to discharge the raw material at a predetermined discharge rate. In this case, the feeder may discharge the raw material so that the upper surface of the raw material discharged onto the first conveyor 120 (described below) is flat. The upper surface of the raw material may also be referred to as the upper surface of the raw material.

[0069] The conveyors 120 and 130 can weigh the discharged amounts of raw materials while conveying the raw materials discharged from the plurality of hoppers 110, and mix the weighed discharged amounts of raw materials at a predetermined blending ratio. The conveyors 120 and 130 can also supply blended raw materials, for example, blended coal, produced by mixing a plurality of coal types of raw materials at a predetermined blending ratio to the coke oven 40. The conveyors 120 and 130 may also be referred to as continuous weighing feeders (CWF).

[0070] The conveyors 120, 130 may be arranged to connect the multiple hoppers 110 and the coke oven 40. The conveyors 120 may also include multiple first conveyors 120 connected to each of the hoppers 110, and a second conveyor 130 connected to the multiple first conveyors 120. On the other hand, when the raw material contains only a single coal type and there is only one hopper 110, the conveyors 120 may include only the first conveyor 120.

[0071] The multiple first conveyors 120 serve to convey and weigh the raw materials discharged by coal type. The number of the multiple first conveyors 120 may be the same as the number of the multiple hoppers 110. The multiple first conveyors 120 may be disposed below the hoppers 110 that store the raw materials that they intend to convey and weigh. The multiple first conveyors 120 may also extend toward the second conveyor 130. In this case, the direction in which the multiple first conveyors 120 extend may be aligned with the width direction of the second conveyor 130.

[0072] The first conveyor 120 may include a plurality of rollers 122 arranged in the direction in which the first conveyor 120 extends, and a belt 121 wound around the plurality of rollers 122 so as to be movable in the direction in which the first conveyor 120 extends. The first conveyor 120 may also include a load cell (not shown) connected to the belt 121 between the hopper 110 and the sorting unit 200 to measure the amount of raw material discharged onto the belt 121. In this case, the discharge amount may refer to, for example, the weight of raw material discharged per unit time. When a difference is detected between the discharge amount of raw material measured by the load cell and a predetermined discharge amount of the raw material, the first conveyor 120 adjusts the running speed of the belt 121 to control the supply speed of raw material from the first conveyor 120 to the second conveyor 130, thereby achieving the same effect as adjusting the amount of raw material discharged from the hopper 110.

[0073] Meanwhile, when a difference is found between the discharge amount of the raw material measured by the load cell and the predetermined discharge amount of the raw material, the first conveyor 120 may transmit the difference value to the hopper 110 storing the raw material, and the hopper 110 to which the difference value is transmitted may adjust the discharge amount of the raw material by controlling the operating conditions of the feeder installed at the discharge outlet.

[0074] The speed at which the belt 121 travels may be in the range of 0.1 to 0.15 m / s. Therefore, the belt 121 can transport the raw materials at a speed in the range of 0.1 to 0.15 m / s. This allows the raw materials to be smoothly discharged from the hopper 110 to the belt 121 at a specified discharge rate, and the imaging unit 300 can capture images of the raw materials on the belt 121 to obtain clear images of the raw materials. That is, if the belt 121 travels at a speed higher than 0.15 m / s, it may be difficult for the load cell to accurately measure the discharged amount of raw materials, and it may be difficult for the imaging unit 300 to smoothly capture images of the raw materials on the belt 121. Furthermore, if the belt 121 travels at a speed lower than 0.1 m / s, the raw materials discharged from the hopper 110 at a specified discharge rate may accumulate on the belt 121 and overflow outside the belt 121.

[0075] The second conveyor 130 continuously receives and mixes the measured amounts of raw materials, blending them evenly according to the blending ratio. The second conveyor 130 also conveys the blended coal produced by mixing the raw materials to the coke oven 40. The second conveyor 130 may be disposed below the plurality of first conveyors 120. The second conveyor 130 may be connected to the ends of each of the plurality of first conveyors 120. Here, "connected" means that the raw materials can move. That is, the second conveyor 130 may be disposed so as to pass through the range where the raw materials fall from the ends of each of the plurality of first conveyors 120. The second conveyor 130 may extend in the direction in which the plurality of first conveyors 120 are arranged, and its end may be connected to the coke oven 40.

[0076] The second conveyor 130 may have substantially the same structure as the first conveyor 120. That is, the second conveyor 130 may include a plurality of second rollers 132 arranged in the direction in which the second conveyor 130 extends, and a second belt 131 disposed so as to be able to run on the plurality of second rollers 132. Meanwhile, the speed at which the second belt 131 runs may be higher than or equal to the speed at which the belt 121 runs. The width of the second belt 131 may be wider than the width of the belt 121.

[0077] The sorting unit 200 separates small particles from the raw material before capturing an image of the raw material, and allows large particles, which are larger than the small particles, to remain. In other words, by separating small particles and leaving large particles, the sorting unit 200 can prevent the small particles from exaggerating or distorting the image captured by the imaging unit 300. This allows the imaging unit 300 to capture a high-quality image of the raw material.

[0078] The sorting unit 200 may be disposed on the conveyors 120, 130 so as to be in contact with the conveyed raw materials or spaced a predetermined height from the conveyed raw materials. Specifically, the sorting unit 200 may be disposed above the first conveyor 120 or may be in contact with or spaced from the upper surface of the raw materials on the first conveyor 120.

[0079] The sorting unit 200 may separate small particles and retain large particles in various ways. For example, the sorting unit 200 may use suction to separate small particles on the upper surface of the raw material from the raw material and retain large particles on the upper surface of the raw material. In this case, "separating" may mean being separated from the raw material on the first conveyor 120, and "remaining" may mean being left behind on the first conveyor 120. The sorting unit 200 removes small particles from the raw material on the upper surface of the raw material and collects them in the sorting unit 200, allowing large particles to remain on the upper surface of the raw material.

[0080] The sorting unit 200 can also use sinking to cause small particles on the upper surface of the raw material to sink relative to large particles, leaving the large particles on the upper surface of the raw material. The sorting unit 200 can also use falling of small particles to cause small particles on the upper surface of the raw material to roll down along the upper surface of the raw material, leaving the large particles on the upper surface of the raw material.

[0081] Hereinafter, an embodiment of the present invention will be described based on the case where the sorting unit 200 uses suction to cause large particles to remain on the upper surface of the raw material.

[0082] On the other hand, the sorting unit 200 may be arranged on the side of a plurality of first conveyers 120. In this case, the number of sorting units 200 may be one or more. Also, the sorting unit 200 may be arranged on the side of one or more first conveyers 120 selected from the plurality of first conveyers 120. For example, if there are three sorting units 200, the three sorting units 200 may be arranged on the side of three conveyers 120 selected from the plurality of first conveyers 120, respectively. Also, if there is only one sorting unit 200, it may be arranged on the side of one conveyer 120 selected from the plurality of first conveyers 120. Needless to say, the number of sorting units 200 may be the same as the number of first conveyers 120.

[0083] Various criteria may be used to select the first conveyor 120 on which the sorting section 200 should be located. For example, a first conveyor 120 for transporting strong coking coal and a first conveyor 120 for transporting weak coking coal may be selected based on the caking property of the raw material transported by the first conveyor 120, or two sorting sections 200 may be located on each of the two selected first conveyors 120. Furthermore, there may be more than one criterion for selecting the first conveyor 120 on which the sorting section 200 should be located. For example, two first conveyors 120 may be selected based on the caking property of the raw material, and a first conveyor 120 for transporting raw material whose coal type changes frequently may be selected based on the frequency of changes in the raw material coal type, resulting in a total of three first conveyors 120 being selected.

[0084] On the other hand, the sorting unit 200 may be arranged to be movable. For example, a conveyor such as a crane (not shown) or a rail (not shown) may be arranged on the side of the multiple first conveyors 120, and the sorting unit 200 may be arranged to be movable above the conveyor. Therefore, when the selection criteria for the first conveyors 120 are changed, the position of the sorting unit 200 can be changed. On the other hand, the imaging unit 300 and the returning unit 500 may also be arranged to be movable so that they can be moved to the same positions as the sorting unit 200. Needless to say, the sorting units 200 may all be arranged above the multiple first conveyors 120, and only the sorting unit 200 arranged above the selected first conveyor 120 may be selectively operated.

[0085] Fig. 4 is a schematic diagram of a sorting unit according to an embodiment of the present invention, and Fig. 5 is a photograph for explaining the operation of a sorting unit according to an embodiment of the present invention. Here, "A" in Fig. 5 is a photograph of raw material passing through part "A" shown in Fig. 2, and "B" in Fig. 5 is a photograph of raw material passing through part "B" shown in Fig. 2.

[0086] 3 and 4, the sorting unit 200 is configured to be able to suck small particles on the upper surface of the raw material using suction, and may include a suction device 210 having an opening on the surface facing the conveyor 100 so as to suck the small particles, a suction pipe 230 for connecting the suction device 210 to the return unit 500, and a suction pump 240 connected to the suction device 210. Here, the sorting unit 200 may further include a sieve 220 having a plurality of openings H formed therein for sucking small particles from the raw material.

[0087] The suction device 210 is a suction device 210 for providing a suction space above the upper surface of the raw material that enables the creation of negative pressure for sucking in small particles, and may be disposed upward away from the belt 121 of the first conveyor 120, between the hopper 110 and the imaging unit 300. The suction device 210 may be positioned continuously in the width direction of the belt 121 within a range of 10% to 90% of the width of the belt 121 that conveys the raw material. That is, the suction device 210 may be separated from both edge portions of the belt 121 in the width direction of the belt 121, and may extend between both edge portions of the belt 121 so as to cross the belt 121 in the width direction. This makes it possible to prevent outside air present near both edge portions of the belt 121 from flowing excessively into the suction device 210.

[0088] The suction pipe 230 serves to allow small particles of the raw material sucked into the suction device 210 to flow into the return unit 500. One end of the suction pipe 230 may be connected to the upper part of the suction device 210, and the other end may be connected to the return unit 500. In addition, a suction pump 240 may be attached to one side of the suction pipe 230.

[0089] The suction pump 240 is a suction pump 240 for creating a negative pressure inside the suction device 210 via the suction pipe 230, and may create a negative pressure inside the suction pipe 230 at a predetermined pressure lower than atmospheric pressure to create a negative pressure inside the suction device 210. The suction pump 240 can also create a flow inside the suction pipe 230 for transporting small particles from one end of the suction pipe 230 to the other end. This allows the small particles sucked into the suction device 210 to pass through the suction pipe 230 and flow into the return section 500.

[0090] Sieve 220 may be attached to the opening at the bottom of suction device 210. Sieve 220 may have a plurality of openings H, and the mesh size D of openings H may be in the range of more than 0 mm and less than 3 mm. Therefore, small particles having a particle size in the range of more than 0 mm and less than 3 mm can pass through openings H of sieve 220 and be sucked into suction device 210, while larger particles can be filtered by sieve 220 and remain on the upper surface of the raw material. Meanwhile, sieve 220 may be positioned continuously in the width direction of belt 121 in the range of 10% to 90% of the width of belt 121 that conveys the raw material.

[0091] If the screening section 200 does not have a sieve 220, the magnitude of the negative pressure in the suction device 210 may be adjusted using a suction pump 240 so that only small particles are sucked from the upper surface of the raw material, while large particles remain.

[0092] On the other hand, in order to prevent raw material particles from adhering to the surface of the sieve 220 and blocking the openings H, the sieve 220 may be shaken or moisture may be supplied to the surface of the sieve 220 for lubrication.

[0093] 5, image A, which is an image of the upper surface of the raw material before it passes through the lower side of the sorting unit 200, shows that the boundaries between particles are difficult to distinguish due to small particles. Also, image B, which is an image of the upper surface of the raw material after it passes through the lower side of the sorting unit 200, shows that the boundaries between particles are clearly distinguishable in image B as the small particles are removed from the upper surface of the raw material.

[0094] That is, the sorting unit 200 exposes large particles on the upper surface of the raw material before imaging the raw material, thereby enabling the analysis unit 400 to easily identify individual particles of the raw material within the image of the upper surface of the raw material that has been captured.

[0095] In the following, a modified embodiment of the present invention will be described based on the case where the sorting unit 200 uses sinking to cause large particles to remain on the upper surface of the raw material.

[0096] In a modified example of the present invention, the sorting section 200 may include a first sorter (not shown) for causing small particles from the upper surface of the raw material to sink relative to large particles. The first sorter may include a plurality of hook members spaced apart along the width of the first conveyor 120. The hook members may be arranged with their curved portions facing downward and inserted a predetermined depth into the raw material from the upper surface. Grooves may be formed between the hook members. In this case, large particles may be placed in the upper part of the grooves, and small particles may accumulate between the grooves. For example, small particles may escape between adjacent hook members, some of which may quickly accumulate between the grooves, while the rest may form the bottom of the grooves. In this case, large particles may not quickly escape between adjacent hook members, but may rise a predetermined height along the surface of the hook members and fall under their own weight. Some of the large particles may be placed on top of the small particles between the grooves, and the rest may form the top of the grooves.

[0097] This allows the small particles to sink to a relatively lower height than the large particles, and allows the large particles to float to a higher height than the small particles.

[0098] Hereinafter, other modifications of the embodiment of the present invention will be described based on the fact that the sorting unit 200 allows the falling of small particles and leaves the large particles on the upper surface of the raw material.

[0099] In another variation of the present invention, the sorting section 200 may include a second sorter (not shown) for separating small particles from large particles by rolling them down along the upper surface of the raw material. The second sorter may include a slope former. The slope former is disposed below the first conveyor 120 on the hopper 110 side and can receive the lower surface of the belt 121 of the first conveyor 120 at an angle in the width direction. Therefore, in the area where the second sorter is located, the raw material can be placed on the belt 121 at an angle in the width direction by a predetermined angle, and the upper surface of the raw material can be inclined in the width direction, forming a slope. In this case, as the belt 120 moves, relatively light small particles can roll down along the slope and separate from the large particles, while relatively heavy large particles can maintain their position on the slope. That is, as the small particles fall from the upper surface of the raw material, the small particles can separate from the large particles while escaping from the slope of the upper surface of the raw material, and the large particles can remain on the upper surface of the raw material.

[0100] 2, the imaging unit 300 can capture an image of the upper surface of the raw material, specifically, an image of large particles on the upper surface of the raw material. The imaging unit 300 can also capture images of large particles by continuously or periodically capturing images of the upper surface of the raw material from which small particles have been removed, and can transmit the captured images of large particles to the analysis unit 400.

[0101] The imaging unit 300 may include various types of cameras selected within a range of resolution capable of capturing images of the raw material and distinguishing large particles of 3 mm or larger. The imaging unit 300 may be arranged to face the conveying unit 100. Specifically, the imaging unit 300 may be arranged on the side of the multiple first conveyors 120. More specifically, the imaging unit 300 may be arranged above the first conveyor 120 in which the sorting unit 200 is located, facing the first conveyor. The imaging unit 300 may also be arranged to face the downstream side of the sorting unit 200, based on the direction in which the belt 121 conveys the raw material. In other words, the imaging unit 300 may be spaced away from the sorting unit 200 in the direction in which the raw material moves. On the other hand, the imaging area of ​​the imaging unit 300 may include the entire width of the belt 121 conveying the raw material. Therefore, the imaging unit 300 can capture images of the raw materials being transported by the belt 121 in the width direction of the belt 121 without any omissions while passing under the imaging unit 300, and can obtain an image of the upper surface of the raw materials, for example, an image of large particles from which small particles have been sorted out.

[0102] FIGS. 6(a) and 6(b) are a photograph and a graph for explaining the analysis unit according to the embodiment of the present invention.

[0103] 2 and 6, the analysis unit 400 can identify individual large particles from the image captured by the imaging unit 300, analyze the particle size distribution, and determine the overall particle size distribution of the raw material using the analyzed particle size distribution of the large particles. The analysis unit 400 can also be connected to the imaging unit 300 and the management unit 600.

[0104] The analysis unit 400 may calculate the area of ​​the identified large particles, classify the large particles into different particle sizes by area, and calculate the total area ratio of each of the classified large particles on the acquired image. In this case, the analysis unit 400 may use artificial intelligence.

[0105] For example, the analysis unit 400 may use a deep learning algorithm as artificial intelligence (AI), particularly the U-Net algorithm. The U-Net algorithm is an example of a deep learning algorithm used to process images and is not intended to limit the type of algorithm. That is, the analysis unit 400 may use various algorithms, such as fully convolutional networks (FCN), DeepLab V3+, atrous convolution, spatial pyramid pooling, encoder-decoder, and depthwise separable convolution, as long as they are capable of applying semantic segmentation techniques.

[0106] Needless to say, the analysis unit 400 may use image analysis methods such as entropy, entrance surface dose (ESD), mutual information, etc. in addition to image analysis methods based on artificial intelligence (AI). Furthermore, the analysis unit 400 may use image analysis methods such as entropy, entrance surface dose (ESD), mutual information, etc. in combination with image analysis methods based on artificial intelligence (AI).

[0107] The analysis unit 400 may convert the total area ratio determined for each distinguished large particle into a weight ratio based on data previously learned by the artificial intelligence, and analyze the weight ratio for each distinguished large particle as a particle size distribution of the large particles. The analysis unit 400 may also determine the weight ratio of the sorted small particles using the weight ratio for each large particle, and determine the overall particle size distribution of the raw material using the weight ratio for each large particle and the weight ratio for the small particles.

[0108] For example, FIG. 6(b) shows an exemplary graph of the overall particle size distribution of the raw material determined by the analysis unit 400. The horizontal axis of the graph indicates the relative particle size of the raw material particles. The scale 1 on the horizontal axis corresponds to the smallest particle size of the raw material, and the scale 1000 on the horizontal axis corresponds to the largest particle size of the raw material. The vertical axis on the left side of the graph corresponds to a bar graph and indicates the weight distribution of the raw material by particle size. The vertical axis on the right side of the graph corresponds to a line graph and indicates the cumulative fraction of the weight distribution of the raw material by particle size. Meanwhile, as shown in the graph, the particle size distribution of the raw material particles may have normal distribution characteristics.

[0109] 6(b), the analysis unit 400 can determine the overall particle size distribution of the raw material from the image captured by the imaging unit 300 based on data previously learned by the artificial intelligence. That is, the particle size distribution of the raw material determined by the analysis unit 400 may be the distribution of weights of the raw material by size. Meanwhile, to avoid repetition, details of the method by which the analysis unit 400 determines the overall particle size distribution of the raw material will be described below while explaining the particle size control method according to an embodiment of the present invention.

[0110] Meanwhile, the analysis unit 400 can classify the classified large particles into a plurality of groups according to particle size, analyze the weight ratio of the large particles for each group using the particle size distribution of the large particles, and determine the particle size distribution of the entire raw material using the weight ratio of the large particles for each group and the weight ratio of the small particles. Furthermore, the analysis unit 400 can apply the particle size distribution determined from the raw material transported to the selected first transporter 120 to the entire raw material using the crushing characteristics of the raw materials. This will be described in detail below when describing the particle size management method according to an embodiment of the present invention.

[0111] 2, the returning unit 500 serves to return small particles onto the large particles whose images have been captured. That is, the returning unit 500 receives small particles that are sucked into the sorting unit 200 from the raw material upstream of the imaging unit 300 based on the direction in which the raw material is transported, and returns the small particles onto the large particles of the raw material downstream of the imaging unit 300.

[0112] In other words, the return section 500 can prevent a reduction in the overall supply of raw material supplied onto the second conveyor 130 for the production of blended raw materials by returning small particles that were sorted out from the raw material before the raw material was imaged onto the raw material after the raw material is imaged.

[0113] The returning unit 500 may be disposed above the conveying unit 100. Specifically, the returning unit 500 may be disposed above the first conveying unit 120, among the plurality of first conveying units 120, on which the sorting unit 200 is disposed. The number of returning units 500 may be plural. In this case, the number of returning units 500 may be the same as the number of sorting units 200. The returning unit 500 may be connected to the sorting unit 200. In this case, the returning unit 500 may have an inlet connected to the sorting unit 200 and an outlet disposed downstream of the imaging unit 300 based on the direction in which the raw material is conveyed. Here, the inlet may be an opening through which the raw material passes first, and the outlet may be an opening through which the raw material passes later. The inlet of the returning unit 500 may be connected to the suction pipe 230 of the sorting unit 200. In addition, the discharge port of the returning section 500 may open downward at the terminal end side of the first conveyor 120 in which the returning section 500 is arranged. The small particles may flow from the sorting section 200 into the inlet of the returning section 500, pass through a passage connecting the inlet and outlet of the returning section 500, be discharged from the outlet of the returning section 500, and return to above the large particles of raw material.

[0114] The management unit 600 can adjust the supply conditions of the subsequent raw material to be supplied to the conveying unit 100 using the particle size distribution analyzed by the analysis unit 400. The management unit 600 may be connected to the analysis unit 400 and a controller of the raw material crushing device 30.

[0115] That is, the management unit 600 receives the analysis results from the analysis unit 400, compares the overall particle size distribution of the raw material analyzed by the analysis unit 400 with a preset reference particle size distribution, and based on the comparison results, controls the controller of the raw material crushing device 30 to control the crushing conditions for the subsequent raw material to be supplied to the conveying unit, thereby managing the quality of the subsequent raw material.

[0116] If the particle size distribution analyzed by the analysis unit 400 is at least partially different from a preset reference particle size distribution, the management unit 600 may adjust the raw material crushing conditions as the supply conditions for the subsequent raw material to be supplied to the conveyance unit 100. For example, if the particle size distribution of small particles in the particle size distribution analyzed by the analysis unit 400 is larger than the reference particle size distribution for small particles, the management unit 600 may adjust the raw material crushing conditions by increasing the gap between the hammer and the rebound plate by a predetermined distance to reduce the amount of small particles and increase the amount of large particles when crushing the subsequent raw material. The management unit 600 may also transmit the adjusted raw material crushing conditions to the controller of the raw material crushing device 30. Therefore, the raw material crushing device 30 may operate the controller in accordance with the transmitted raw material crushing conditions to increase the gap between the hammer and the rebound plate by a predetermined distance, thereby reducing the amount of small particles and increasing the amount of large particles in the crushed raw material.

[0117] Hereinafter, a particle size control method according to an embodiment of the present invention will be described in detail. In this regard, the content that overlaps with the above description of the particle size control apparatus according to an embodiment of the present invention will be briefly described or omitted.

[0118] FIG. 7 is a flowchart of a granularity management method according to an embodiment of the present invention.

[0119] 1 to 7, a particle size control method according to an embodiment of the present invention includes a step of preparing raw material (S100), a step of transporting the prepared raw material (S200), a step of sorting the transported raw material into small particles and large particles larger than the small particles (S300), a step of capturing an image of the large particles (S400), a step of analyzing the particle size distribution of the large particles from the captured image (S500), and a step of determining the particle size distribution of the raw material using the particle size distribution of the large particles (S600).

[0120] In addition, the particle size control method according to an embodiment of the present invention may include, after the step of determining the particle size distribution of the raw material using the particle size distribution of the large particles, a step (S700) of utilizing the determined particle size distribution of the raw material in the step of preparing a subsequent raw material.

[0121] The particle size control method according to the embodiment of the present invention can accurately analyze and control the particle size distribution of raw materials. Therefore, the blending ratio of the raw materials produced from the raw materials can be accurately adjusted to a predetermined blending ratio. Furthermore, the variation in the quality of the coke produced from the raw material blend can be minimized.

[0122] The raw material may be coal for producing coke. The raw material may be a plurality of raw materials. The plurality of raw materials may be different coal types.

[0123] First, the step of preparing raw materials (S100) is performed. The step of preparing raw materials (S100) may include a step of preparing a plurality of raw materials having different Hardgrove Grindability Indexes (HGI). Here, the Hardgrove Grindability Index may be an index indicating the quality of crushability of coal. For example, the Hardgrove Grindability Index may be expressed as a numerical value, and the larger the numerical value, the better the crushability. When raw materials are crushed under the same conditions, the larger the numerical value of the Hardgrove Grindability Index, the better the raw materials are crushed and the larger the amount of small particles that can be generated. The raw materials may have different Hardgrove Grindability Indexes depending on the type of coal. In other words, multiple raw materials with different Hardgrove Grindability Indexes may mean multiple raw materials of different coal types. The multiple raw materials may be piled up in the yard 20.

[0124] Furthermore, the process of preparing raw materials (S100) may include a process of crushing multiple raw materials by coal type. At this time, raw materials stacked by coal type in the yard 20 may be supplied to the raw material crushing device 30 and crushed. Specifically, multiple raw materials may be supplied to the raw material crushing device 30 alternately by coal type to be crushed alternately by coal type, or multiple raw materials to be crushed alternately may be supplied to the particle size control device 1000 and stored in multiple hoppers 110 by coal type.

[0125] Thereafter, the process of conveying the prepared raw materials (S200) is performed. At this time, the process of conveying the prepared raw materials (S200) may include a process of conveying each of the prepared raw materials and a process of mixing and conveying the conveyed raw materials. That is, the raw materials may be discharged from the plurality of hoppers 110 to the plurality of first conveyors 120 by coal type, and the raw materials may be conveyed to the plurality of first conveyors 120 by coal type.

[0126] In this case, when discharging the plurality of raw materials onto the plurality of first conveyors 120, the plurality of raw materials may be discharged onto the plurality of first conveyors 120 so that the upper surface of each raw material is flat on the first conveyor 120 onto which each raw material is discharged.

[0127] Furthermore, when the multiple discharged raw materials are transported to the multiple first conveyors 120, the raw materials being transported may be weighed to measure the discharge amount of the raw materials, and the measured discharge amount may be compared with the predetermined discharge amount of each raw material. Based on the comparison result, the speed at which the first conveyor 120 transports the raw materials or the speed at which the hopper 110 discharges the raw materials may be adjusted.

[0128] Alternatively, the multiple raw materials may be transported to the multiple first transporters 120 at a speed ranging from 0.1 to 0.15 m / s. If the raw material transport speed is slower than 0.1 m / s, it may be difficult to discharge the raw material onto the first transporter 120 in an amount that corresponds to the specified discharge amount of the raw material. If the raw material transport speed is higher than 0.15 m / s, it may be difficult to obtain a clear image when capturing an image of the raw material during transport. This may make it difficult to smoothly perform the image acquisition step (S400) of the subsequent steps.

[0129] Thereafter, the raw materials may be discharged from the plurality of first conveyors 120 to the second conveyor 130, and the raw materials may be mixed on the second conveyor 130 at a predetermined blending ratio to produce a blended raw material, for example, blended coal, or the produced blended raw material may be continuously conveyed to the second conveyor 130 and supplied to the coke oven 40. Meanwhile, the raw materials may be replenished to the plurality of hoppers 110 by repeatedly preparing the raw materials while conveying the prepared raw materials.

[0130] During the step of conveying the prepared raw material (S200), for at least one raw material selected from the plurality of raw materials being conveyed, the following steps may be performed: a step of sorting the conveyed raw material into small particles and large particles larger than the small particles (S300); a step of capturing an image of the large particles (S400); a step of analyzing the particle size distribution of the large particles from the captured image (S500); and a step of determining the particle size distribution of the raw material using the particle size distribution of the large particles (S600).

[0131] When selecting raw materials, strong coking coal, slightly coking coal, and non-coking coal may be selected depending on the caking property of the raw materials. Also, raw materials of coal types that are frequently replaced may be selected. In other words, the criteria for selecting raw materials may vary, and the number of raw materials selected may also vary. Needless to say, multiple raw materials may all be selected.

[0132] The following description of the present invention will be continued based on the case where one raw material is selected. Needless to say, the following description is equally applicable to the case where two or more raw materials are selected, and to the case where all raw materials are selected.

[0133] During the process of conveying the prepared raw material, a process (S300) of separating the conveyed raw material into small particles and large particles larger than the small particles is performed. At this time, the process (S300) of separating the conveyed raw material into small particles and large particles larger than the small particles may include a process of sucking small particles from the upper surface of the raw material and leaving large particles. This process may be performed on the first conveyor 120 and on the raw material being conveyed along the first conveyor 120. That is, the sorting unit 200 provided on the first conveyor 120 may be operated to suck small particles from the upper surface of the raw material and leave large particles.

[0134] In this case, small particles may be particles having a particle diameter of more than 0 mm and less than 3 mm. Large particles may be particles having a particle diameter of 3 mm or more. Specifically, large particles may be particles having a particle diameter of 3 mm or more and 15 mm or less. The particle diameter standard for separating small particles from large particles may be determined according to the imaging capability of the imaging unit 300, for example, the resolution. For example, when imaging raw materials, the imaging unit 300 may select the smallest particle that can be distinguished as a separate particle from the captured raw material particles, and use that particle diameter as the particle diameter standard for separating small particles from large particles.

[0135] In other words, the imaging unit 300 sucks in and removes small particles that are difficult to distinguish as individual particles from the upper surface of the raw material, leaving large particles behind, thereby enabling a clear image to be obtained in the subsequent image acquisition process.

[0136] For example, photograph "A" in Figure 5 is a photograph of the top surface of the raw material when the small particles were not removed from the top surface. Photograph "B" in Figure 5 is a photograph of the remaining large particles after the small particles were removed from the top surface of the raw material. Comparing the two photographs, it is clear that removing the small particles provides a clearer image of the top surface of the raw material.

[0137] The raw material being conveyed is sorted into small particles and large particles larger than the small particles, and then a process (S400) is performed in which the large particles are imaged and images are acquired. The process (S400) in which the large particles are imaged and images are acquired may be performed by the imaging unit 300 downstream of the sorting unit 200 on the first conveyor 120. This process may also include a process in which the large particles from which the small particles have been sorted are imaged and images of the large particles are acquired. After this process, the process may also include a process in which the sorted small particles are discharged onto the large particles on the upper surface of the raw material.

[0138] That is, as the raw material is conveyed along the first conveyor 120 and passes through the sorting section 200 to remove small particles from the upper surface, the upper surface of the raw material from which the small particles have been removed may be imaged by the imaging section 300 to obtain an image of the large particles. After this, the raw material may continue to be conveyed along the first conveyor 120 and pass through the imaging section 300, at which point the small particles may be discharged from the upper surface of the raw material. This process may be performed by operating the return section 500 connected to the sorting section 200, moving the small particles sucked into the sorting section 200 along the return section 500 at a speed equal to or substantially equal to the speed at which the raw material is conveyed, and then discharging them from the downstream side of the imaging section 300 onto the upper surface of the raw material. Needless to say, the sucked small particles may be discharged onto the second conveyor 130 and returned to the raw material. This process prevents the sucked small particles from changing the blending ratio of the raw material blend produced from the raw material. Meanwhile, the process of capturing images of large particles may be performed continuously or periodically, and the subsequent processes may also be performed continuously or periodically.

[0139] After capturing an image of large particles, a process of analyzing the particle size distribution of the large particles from the captured image, for example, the image of the large particles, is performed (S500). This process may include a process of calculating the area of ​​the large particles from the image of the large particles and classifying the large particles into different particle sizes based on their area, a process of calculating the total area ratio on the captured image for each classified large particle, and a process of converting the total area ratio calculated for each classified large particle into a weight ratio. Here, these processes may be performed in the analysis unit 400.

[0140] The area of ​​the large particles may be calculated from the image of the large particles, and the large particles may be classified into different particle sizes based on their area. First, the large particles may be identified from the image of the large particles. In this case, for example, the image of the large particles may be segmented using an image analysis method based on artificial intelligence (AI) to clearly identify each large particle as a separate particle from the image of the large particles (see (a) of FIG. 6).

[0141] The image analysis method may be a U-Net algorithm. Needless to say, various types of image analysis methods may be used. Furthermore, image analysis methods other than those based on artificial intelligence may also be used, such as entropy, entrance surface dose, and mutual information.

[0142] After this, if the large particles are clearly identified as separate particles from the image of the large particles, the area of ​​each identified large particle may be calculated. That is, the area of ​​each large particle may be calculated as the area of ​​the pixels occupied by each identified large particle from the image of the large particles. Needless to say, various methods for calculating the area of ​​the large particles may be used.

[0143] After that, once the areas of the identified large particles are calculated, the large particles may be classified into different particle sizes according to their areas. For example, the identified large particles may be classified into different particle sizes according to their areas, and classified into large particles numbered 1 to k. Meanwhile, since the large particles are classified into different particle sizes according to their areas, the number of large particles numbered 1 may be one or more, the number of large particles numbered k may be one or more, or the number of at least one large particle located between the numbered 1 and the numbered k may be one or more. Needless to say, there may be a single large particle among the numbered 1 to k large particles.

[0144] Meanwhile, the process of calculating the area of ​​each of the identified large particles and classifying the large particles into different particle sizes based on the area may further include a process of classifying the identified large particles into a plurality of groups according to their particle sizes, which will be described below by way of example.

[0145] For example, after determining the area of ​​each identified large particle, the large particles are classified into different particle sizes according to their area. When large particles 1 to k are identified from the image of the large particles, the area (mm 2 If the size of each particle falls within the range of 3x3 to 15x15, the identified large particles can be divided into a first group of 3x3 or more and less than 5x5, a second group of 5x5 or more and less than 10x10, and a third group of 10x10 or more and 15x15 or less. In this case, the first group may include identified large particles numbered 1 to i, the second group may include identified large particles numbered i+1 to j, and the third group may include identified large particles numbered j+1 to k.

[0146] In this case, subsequent processes, such as determining a total area ratio on an image captured for each of the large particles and converting the determined total area ratio for each of the large particles into a weight ratio, may be performed for each of the separated groups. Similarly, the process of determining a particle size distribution of a raw material using the particle size distribution of the large particles and the process of utilizing the determined particle size distribution of the raw material in a process of preparing a subsequent raw material may also be performed for each of the separated groups.

[0147] Meanwhile, the following description of the present invention will be based on the case where the process of classifying large particles into different particle sizes based on area does not include the process of dividing the divided large particles into a plurality of groups according to their particle sizes. Needless to say, the following description is equally applicable to the case where the process of classifying large particles into different particle sizes based on area includes the process of dividing the divided large particles into a plurality of groups according to their particle sizes.

[0148] Once the large particles are classified into different particle sizes by area using the above process, the total area ratio of each classified large particle in the captured image (i.e., the image of the large particles) can be calculated. First, the total area of ​​the image of the large particles can be calculated. In this case, the total pixel area of ​​the image of the large particles can be calculated as the total area of ​​the image of the large particles. Then, the total area of ​​the image of the largest large particle or the largest large particle, etc. can be calculated. In this case, the total area can be calculated as the pixel area of ​​the image of the largest large particle or the largest large particle, etc. After this, the total area of ​​the image of the large particles for each large particle number can be calculated in the same manner, from the second largest particle to the kth large particle. Then, the ratio of the total area of ​​the image of the large particles for each large particle number or the large particle, etc., to the total area of ​​the image of the large particles can be calculated to calculate the total area ratio of each classified large particle in the captured image (image of the large particles).

[0149] After determining the total area ratios on the captured images for each large particle, the total area ratios determined for each large particle may be converted into weight ratios. The process of converting the total area ratios determined for each large particle into weight ratios may include predicting weight ratios for each large particle according to the total area ratios determined for each large particle using a particle size distribution model of the raw material generated based on data previously learned by the artificial intelligence, and replacing the total area ratios determined for each large particle with the predicted weight ratios for the large particles.

[0150] The raw material particle size distribution model is a mathematical and statistical model constructed to predict the weight ratio of large particles when the area ratio of large particles classified into different particle sizes by area on an image of the large particles is known, and may be a model constructed by artificial intelligence based on training data. The training data may include operational data derived from actual steelmaking operation information, experimental data prepared through crushing experiments using coal, etc. Here, the operational data and experimental data may include non-standard data such as photographs of crushed coal, and standard data such as the crushed particle size of the coal, the weight of the crushed coal by particle size, and the coal Hardgrove grindability index, which are matched with the photographs. Furthermore, such training data may be learned using a deep learning method as artificial intelligence. Needless to say, the method of training the AI ​​to the training data and the specific algorithm used for learning may vary.

[0151] That is, the total area ratios of the first through k large particles may be input into a raw material particle size distribution model, and the total weight ratios of the first through k large particles may be predicted and output. For example, if the area ratio of the largest particle to the total area of ​​the large particle image is A1%, the area ratio of the second largest particle is A2%, and the area ratio of the K large particle is AK%, these area ratios may be input into the raw material particle size distribution model. Furthermore, the weight ratio of the largest particle to the total weight of the raw material may be predicted as B1 wt%, the weight ratio of the second largest particle may be predicted as B2 wt%, and the weight ratio of the K large particle may be predicted as BK wt%, and the predicted weight ratios may be output. The total area ratios calculated for each large particle may then be replaced with the predicted weight ratios for each large particle. Through these processes, the predicted weight ratios for each large particle distinguished from the raw material may be analyzed as the particle size distribution of the large particles.

[0152] After analyzing the particle size distribution of the large particles and analyzing the weight ratio of the large particles to the weight of the raw material for each large particle classified into different particle sizes by area, a step of determining the particle size distribution of the raw material using the particle size distribution of the large particles (S600) is performed. This step may include a step of determining the weight ratio of small particles sorted from the upper surface of the raw material before capturing an image of the large particles, and a step of determining the overall particle size distribution of the raw material using the weight ratio of the large particles and the weight ratio of the small particles.

[0153] First, a process of determining the weight ratio of the separated small particles may be performed. Specifically, when the total area ratio determined for each of the separated large particles is converted into a weight ratio, a process of determining the weight ratio of the separated small particles may be performed.

[0154] In this case, the weight ratio of the sorted small particles may be determined by adding up the predicted weight ratios for each large particle to determine the weight ratio of the large particles, and then determining the weight ratio of the small particles that, when added together with the weight ratio of the large particles, equals 100 percent, specifically 100 weight percent. For example, the weight ratios of large particles No. 1 through No. K may be added up to determine the overall weight ratio of the large particles relative to the total weight of the raw material. Here, both the large particles and the small particles are raw material particles, and if a raw material particle is not a large particle, it corresponds to a small particle, and similarly, if a raw material particle is not a small particle, it corresponds to a large particle. In other words, the large particles and the small particles are in a mutually complementary relationship. Therefore, the weight ratio that, when added together with the weight ratio of the large particles, equals 100 percent, specifically 100 weight percent, may be the weight ratio of the small particles relative to the total weight of the raw material. For example, if the value obtained by subtracting the total weight ratio of large particles numbered 1 to K (B1wt% + B2wt% + ... + BKwt%) from 100 weight percent (100wt%) is Cwt%, then Cwt% can be calculated as the weight ratio of small particles.

[0155] After determining the weight ratio of small particles, a process of determining the particle size distribution of the entire raw material may be performed. That is, the particle size distribution of the entire raw material may be determined using the weight ratio of each large particle and the weight ratio of the small particles. For example, the weight ratio of small particles to large particles numbered 1 to K may be used as the particle size distribution of the entire raw material. That is, the particle size distribution determined by this process may be the weight distribution of each distinguished particle.

[0156] Once the particle size distribution of the selected raw material is determined, a process is performed in which the particle size distribution of the selected raw material is applied to all of the raw materials using the Hardgrove crushability index of each of the raw materials. That is, the Hardgrove crushability index of each of the raw materials may be known. Needless to say, the Hardgrove crushability index may be determined manually by performing crushing experiments on the raw materials. Furthermore, the distribution of crushed particle sizes of the raw materials may change with a trend as the Hardgrove crushability index of the raw material changes. In this case, the change in the particle size distribution of the crushed raw material with a change in the Hardgrove crushability index of the raw material may be derived as a mathematical relational expression for each of the small particles and the large particles, respectively. Needless to say, the change in the particle size distribution of the crushed raw material with a change in the Hardgrove crushability index of the raw material may be derived in the form of a lookup table constructed from measured data, or for each of the small particles and the large particles, respectively.

[0157] Therefore, by utilizing a relational equation, lookup table, etc. prepared in advance so that the change in particle size distribution of the crushed raw material due to the change in the Hardgrove crushability index of the raw material becomes known, and the Hardgrove crushability index of each of the multiple raw materials, the particle size distribution of the selected raw material can be applied to all of the multiple raw materials, and the particle size distribution of each of the multiple raw materials can be determined.

[0158] After determining the particle size distribution of each of the plurality of raw materials, the method performs a step (S700) of utilizing the determined particle size distribution of the raw materials in a step of preparing subsequent raw materials. Specifically, the determined particle size distribution of each of the plurality of raw materials may be compared with a predetermined standard particle size distribution, and the crushing conditions for the subsequent raw materials may be controlled based on the comparison results, and the subsequent raw materials may be crushed under the controlled crushing conditions. Here, the standard particle size distribution is a desired particle size distribution of each raw material that, when a raw material blend is produced by blending the plurality of raw materials at a predetermined blending ratio, allows each raw material to be uniformly mixed in the raw material blend, and when coke is produced from the produced raw material blend, the coke quality is desired. However, the standard particle size distribution may vary depending on the characteristics of the raw materials.

[0159] For example, if multiple raw materials are designated as the first raw material M1 through the eighth raw material M8, the particle size distribution of the first raw material M1 is first compared with the reference particle size distribution of the first raw material M1. In this case, the particle size distribution of small particles in the particle size distribution of the first raw material M1 may be larger than the reference particle size distribution for small particles, and the particle size distribution of at least some of the distinguished large particles may be smaller than the reference particle size distribution for the large particles. In this case, the first raw material M1 may have been crushed to a greater extent than desired in the raw material crushing device 30. Therefore, to reduce the degree of crushing of the subsequent first raw material M1 in the raw material crushing device 30, the crushing conditions for the subsequent first raw material M1 are controlled, such as by reducing the rotational speed of the hammer to a predetermined rotational speed and widening the gap between the hammer and the repulsion plate to a predetermined gap. Needless to say, the reverse is also possible. Alternatively, the raw material crushing device 30 may be controlled under controlled crushing conditions, so that when the raw material is crushed in the raw material crushing device 30, the first raw material M1 is crushed under the controlled crushing conditions.

[0160] Similarly, the particle size distribution of each raw material from the second raw material M2 to the eighth raw material M8 may be compared with the standard particle size distribution for each raw material, and the crushing conditions for each subsequent raw material may be controlled based on the results, and each subsequent raw material may be crushed under the controlled crushing conditions. This allows the subsequent first raw material M1 to the subsequent eighth raw material M8 to be prepared with an adjusted degree of crushing, and the process from conveying the prepared raw materials to subsequent processes can be carried out using the prepared raw materials. This allows the subsequent raw materials to satisfy the standard particle size distribution, and by producing a raw material blend using the subsequent raw materials that satisfy the standard particle size distribution and producing coke from the produced raw material blend, it is possible to minimize variation in the quality of the raw material blend and coke.

[0161] Meanwhile, according to a modified embodiment of the present invention, before the process of conveying the prepared raw material is performed, a predetermined experiment can be performed to verify and ensure the consistency of the raw material particle size distribution model used to analyze the particle size distribution of large particles, and the results can be used to complement the raw material particle size distribution model.

[0162] For example, small amounts of raw materials, each of which does not affect the raw material blend ratio of a blended raw material produced from multiple raw materials, are collected from multiple positions in multiple hoppers, and then transported to a laboratory set up to conduct predetermined experiments to verify and ensure the consistency of the raw material particle size distribution model.

[0163] The collected raw materials are then piled on a designated table in the laboratory with a designated area and height for each type of coal, and a suction device installed in the laboratory is used to suck in raw material particles with a diameter of less than 3 mm from the upper surface of each pile of raw material. Images of the upper surface of each pile are then captured. The captured images, an image analysis method based on artificial intelligence (AI), and a raw material particle size distribution model are used to analyze the particle size distribution of raw material particles with a diameter of 3 mm or more, and the particle size distribution of each collected raw material is determined. This is referred to as the analyzed particle size distribution.

[0164] Next, the raw material particles with a particle size of less than 3 mm that have been sucked from each of the multiple raw materials are returned to the upper surface of each raw material, and then each raw material is subjected to particle size sorting according to particle size, for example, using a screen installed in the laboratory.The weights of the raw materials that have been size-sorted according to particle size are measured using a predetermined weight measuring device installed in the laboratory, and the particle size distribution of each raw material is determined using the weight measurement results.This is called the measured particle size distribution.

[0165] Thereafter, the analyzed particle size distribution and the measured particle size distribution are compared for each of the plurality of raw materials and for each particle size of each raw material, and if the maximum value of the difference is, for example, 3 wt% or less, it is determined that the raw material particle size distribution model according to the embodiment of the present invention is consistent.

[0166] On the other hand, if the comparison result shows a difference exceeding 3 wt%, it is determined that the raw material particle size distribution model according to the embodiment of the present invention must be supplemented. Therefore, a predetermined calibration algorithm for supplementing the raw material particle size distribution model can be designed and reflected in the raw material particle size distribution model. Various methods for designing the calibration algorithm can be adopted, and there is no particular limitation. Meanwhile, the above-described experiment may be repeated 20 or more times using the same method to ensure the reliability of the experimental results.

[0167] The above-described embodiments of the present invention are intended to explain the present invention and not to limit it. It should be noted that the configurations and methods disclosed in the above-described embodiments of the present invention may be combined and modified in various forms by combining or interchanging with each other, and such modifications are also considered to fall within the scope of the present invention. That is, the present invention may be embodied in various different forms within the scope of the claims and the technical concepts equivalent thereto, and those skilled in the art to which the present invention pertains should understand that various embodiments are possible within the scope of the technical concepts of the present invention. [Explanation of symbols]

[0168] 10 ships 20 Raw coal preparation equipment 30 Raw material crushing equipment 40 Coke manufacturing equipment (coke oven) 50 Coke manufacturing equipment (dry quenching chamber) 60 Blast furnace equipment 70 Gas purification equipment 100 Conveying section 110 Hopper 120 First Carrier 121 Belt 122 Roller 130 Second Carrier 131 Second Belt 132 Second Roller 200 Sorting Department 210 Suction unit 220 sieve 230 Suction pipe 240 Suction Pump 300 Imaging unit 400 Analysis Department 500 Return section 600 Management Department 1000 particle size control device

Claims

1. a conveying unit for conveying the raw material; a sorting unit for sorting small particles from the raw material and leaving large particles larger than the small particles; an imaging unit positioned to face the transport unit for capturing an image of the large particle; an analysis unit for analyzing the particle size distribution of the raw material from the image acquired by the imaging unit; Equipped with A particle size control device characterized by comprising a return unit connected to the sorting unit and positioned above the conveying unit to return the sorted small particles onto the large particles whose images were acquired.

2. 2. The particle size control device according to claim 1, further comprising a control unit for adjusting the supply conditions of the subsequent raw material to be supplied to the transport unit using the particle size distribution analyzed by the analysis unit.

3. The conveying unit is a hopper for receiving the raw material; a conveyor having a belt for continuously conveying the raw material discharged from the hopper; The particle size control device according to claim 1, further comprising:

4. 4. The particle size control device according to claim 3, wherein the sorting unit comprises a suction device having an open surface facing the conveyor so as to suck in the small particles, and a suction pump connected to the suction device.

5. 5. The particle size control device according to claim 3, wherein the sorting unit has a sieve having a plurality of openings formed therein for sucking the small particles from the raw material.

6. 6. The particle size control device according to claim 5, wherein the openings have a mesh size in the range of more than 0 mm and less than 3 mm.

7. 6. The particle size control device according to claim 5, wherein the sieves are positioned continuously in the width direction of the belt, within a range of 10% to 90% of the width of the belt that transports the raw material.

8. 4. The particle size control device according to claim 3, wherein the sorting section comprises either a first sorter for causing the small particles to sink from the upper surface of the raw material relative to the large particles, or a second sorter for causing the small particles to roll down along the upper surface of the raw material and separate them from the large particles.

9. 8. The particle size control device according to claim 7, wherein an imaging area of ​​the imaging unit includes the entire width of the belt that transports the raw material.

10. The number of the hoppers is plural so as to receive the supply of the plural types of raw materials, respectively; the conveyor includes a plurality of first conveyors connected to each of the hoppers and a second conveyor connected to the plurality of first conveyors; The particle size control device according to claim 3 , wherein the sorting unit and the imaging unit are arranged on the side of the plurality of first conveyors.

11. the sorting unit is disposed on the side of one or more first transporters selected from the plurality of first transporters, The particle size control device according to claim 10 , wherein the imaging unit is disposed on the side of the first conveyor on which the sorting unit is disposed.

12. A conveying section for conveying raw materials; a sorting unit for sorting small particles from the raw material and leaving large particles larger than the small particles; an imaging unit positioned to face the transport unit for capturing an image of the large particle; an analysis unit for analyzing the particle size distribution of the raw material from the image acquired by the imaging unit; Equipped with the imaging unit acquires an image of the large particles from which the small particles have been separated, The particle size control device is characterized in that the analysis unit identifies individual large particles from the captured image, analyzes their particle size distribution, and determines the overall particle size distribution of the raw material using the analyzed particle size distribution of the large particles.

13. The analysis unit The area of ​​the identified large particles is calculated, the large particles are classified into different particle sizes according to the area, and a total area ratio on the acquired image is calculated for each of the classified large particles. The total area ratio calculated for each of the classified large particles is converted into a weight ratio based on data previously learned by the artificial intelligence, and the weight ratio for each of the classified large particles is analyzed using the particle size distribution of the large particles. The particle size control device according to claim 12, wherein the weight ratio of the separated small particles is calculated using the weight ratio of the large particles, and the overall particle size distribution of the raw material is calculated using the weight ratio of the large particles and the weight ratio of the small particles.

14. 14. The particle size control device of claim 13, wherein the analysis unit divides the large particles into a plurality of groups according to their particle sizes, analyzes the weight ratio of the large particles for each group using the particle size distribution of the large particles, and determines the overall particle size distribution of the raw material using the weight ratio of the large particles for each group and the weight ratio of the small particles.

15. The particle size control device according to claim 11, characterized in that the analysis unit applies the particle size distribution determined from the raw material transported to the selected first transporter to all of the raw materials using the crushing characteristics of the raw materials.

16. 3. The particle size control device according to claim 2, wherein the control unit compares the overall particle size distribution of the raw material analyzed by the analysis unit with a predetermined reference particle size distribution, and controls the crushing conditions of the subsequent raw material to be supplied to the conveying unit based on the comparison result, thereby controlling the quality of the subsequent raw material.

17. The process of preparing raw materials, conveying the prepared raw material; A step of separating the conveyed raw material into small particles and large particles larger than the small particles; imaging the large particles to obtain an image; analyzing the particle size distribution of the large particles from the captured image; determining the particle size distribution of the raw material using the particle size distribution of the large particles; Including, The step of separating the conveyed raw material into the small particles and the large particles larger than the small particles includes: sucking the small particles from the upper surface of the feedstock and retaining the large particles; The step of acquiring the image includes: acquiring an image of the large particles from which the small particles have been separated from the upper surface of the feedstock; After the step of acquiring the image, Discharging the separated small particles onto the upper surface of the raw material above the large particles.

18. The step of transporting the prepared raw material includes:

18. The particle size control method according to claim 17, further comprising the step of conveying the prepared raw material at a speed in the range of 0.1 to 0.15 m / s.

19. The step of analyzing the particle size distribution of the large particles from the captured image includes: deriving the areas of the large particles from the images of the large particles and classifying the large particles into different particle sizes according to the areas; calculating a total area ratio on the captured image for each of the distinguished large particles; converting the total area ratio determined for each of the large particles into a weight ratio; The method for particle size control according to claim 17, further comprising:

20. The process of classifying large particles into different particle sizes according to the area includes: The method includes a step of classifying the large particles into a plurality of groups according to their particle sizes, 20. The method of claim 19, wherein the process of calculating the total area ratio and the process of switching to the weight ratio are performed for separate groups.

21. The step of determining the particle size distribution of the raw material using the particle size distribution of the large particles includes: determining a weight ratio of the sorted small particles when converting the total area ratio determined for each of the separated large particles into a weight ratio; determining the overall particle size distribution of the raw material using the weight ratio of the large particles and the weight ratio of the small particles; The method for particle size control according to claim 19, further comprising:

22. The process of converting the total area ratio determined for each large particle into a weight ratio is as follows: a step of predicting a weight ratio of each of the large particles according to the total area ratio determined for each of the large particles using a particle size distribution model of the raw material generated based on data previously learned by an artificial intelligence, and replacing the total area ratio determined for each of the large particles with the predicted weight ratio for each of the large particles, The step of determining the weight ratio of the sorted small particles includes: calculating the weight ratio of the large particles by adding up the weight ratios predicted for each of the large particles; a step of setting a weight ratio of the small particles to a weight ratio that will add up to 100 percent when combined with the weight ratio of the large particles; The method for particle size control according to claim 21, further comprising:

23. The step of preparing the raw material includes: providing a plurality of said raw materials having different Hardgrove Crushability Index (HGI); The step of transporting the prepared raw material includes: conveying each of the plurality of raw materials; The steps of separating the conveyed raw material into the small particles and the large particles larger than the small particles, capturing an image of the large particles, analyzing the particle size distribution of the large particles from the captured image, and determining the particle size distribution of the raw material using the particle size distribution of the large particles are: The particle size control method according to claim 19, wherein the method is carried out on at least one or more kinds of raw materials selected from the plurality of raw materials.

24. After performing the step of determining the particle size distribution of the selected raw material, 24. The particle size control method of claim 23, further comprising applying the particle size distribution of the selected raw material to the entirety of the plurality of raw materials using the Hardgrove Grindability Index for each of the plurality of raw materials.

25. The step of preparing the raw material includes: crushing the raw material; After the step of determining the particle size distribution of the raw material, 25. The particle size control method according to claim 17, further comprising a step of utilizing the determined particle size distribution of the raw material in a step of preparing a subsequent raw material.

26. The process of utilizing the subsequent raw material in the process of preparing the subsequent raw material is comparing the determined particle size distribution of the raw material with a predetermined reference particle size distribution; controlling the crushing conditions of the subsequent raw material based on the comparison result; grinding the subsequent feedstock under controlled grinding conditions; The method for particle size control according to claim 25, comprising:

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