Pig iron production method

Abstract

A pig iron manufacturing method of one aspect of the present invention manufactures pig iron using a blast furnace having a tuyere, wherein the pig iron manufacturing method includes: a process of alternately stacking a first layer containing a raw material of ore and a second layer containing coke in the blast furnace; a process of charging coke in a central portion of the blast furnace; and a process of reducing and melting the raw material of ore of the stacked first layer while blowing auxiliary fuel into the blast furnace using hot air blown from the tuyere, wherein in the stacking process, the charging process is performed one or more times during one charging of a stacking unit in which one first layer and one second layer are stacked together, and a ratio R of a mass (ton / ch) of the coke accumulated in the central portion with respect to a mass (ton / ch) of the charged raw material of ore is equal to or greater than a predetermined value α by the one charging.

Description

Technical Field

[0001] This invention relates to a method for manufacturing pig iron. Background Technology

[0002] The following method is well-known: A first layer containing ore and a second layer containing coke are alternately stacked within a blast furnace. While auxiliary fuel is blown into the blast furnace using hot blast from the tuyeres, the ore is reduced and melted to produce pig iron. In this process, the coke serves as a heat source for melting the ore, a reducing agent for the ore, a carburizing agent to lower the melting point of the molten iron, and a spacer to ensure the permeability of the blast furnace. By maintaining permeability using this coke, the unloading of the first and second layers of charge is stabilized, thus achieving stable operation of the blast furnace.

[0003] Hot blast is typically introduced into the blast furnace from its outer perimeter. Upon reaching the center of the blast furnace, the hot blast rises there. When the flow of the rising hot blast in the center is obstructed, permeability easily deteriorates. As a method to ensure permeability in the center, a method of centrally charging coke into the center of the blast furnace has been proposed (e.g., Japanese Patent Application Publication No. 60-56003).

[0004] Existing technical documents

[0005] Patent documents

[0006] Patent Document 1: Japanese Patent Application Publication No. 60-56003 Summary of the Invention

[0007] The problem that the invention aims to solve

[0008] Due to recent requirements to reduce CO2 emissions, further reductions in coke usage during blast furnace operation are sought. While the method of centrally charging coke in the center of the blast furnace improves permeability, a method to maintain permeability with even less coke is desired.

[0009] Based on the above-described situation, the present invention aims to provide a method for producing pig iron that can ensure the flow of hot air in the center of the blast furnace and further reduce the amount of coke used.

[0010] Solution for solving the problem

[0011] One aspect of the present invention discloses a pig iron manufacturing method using a blast furnace with tuyeres. The pig iron manufacturing method includes: alternatingly stacking a first layer containing ore and a second layer containing coke within the blast furnace; charging coke into the center of the blast furnace; and reducing and melting the stacked first layer of ore while simultaneously blowing auxiliary fuel into the blast furnace using hot air blown from the tuyeres. During the stacking process, the charging process is performed once or multiple times during a single charge of a stack unit combining a first layer and a second layer. Through this single charge, the ratio R of the mass (ton / ch) of coke accumulated in the center to the mass (ton / ch) of the charged ore is a predetermined value α or higher.

[0012] In this pig iron manufacturing method, during each charge of the stacked unit (combining the first and second layers) in the stacking process, coke is charged into the center of the blast furnace, thereby easily ensuring the flow of hot blast in the center of the blast furnace. Furthermore, by charging in this single step, the ratio R of the mass (ton / ch) of coke accumulated in the center to the mass (ton / ch) of the charged ore raw material is made to a predetermined value α or higher, thereby improving the permeability of the hot blast. Therefore, even with a reduction in the amount of coke used, the required permeability can be ensured, thus allowing for further reduction in the amount of coke required.

[0013] Preferably, the specified value α is 0.017. By setting the specified value α to this value, breathability can be easily ensured.

[0014] Preferably, the ore raw material in the first layer includes iron ore pellets. When the proportion of the iron ore pellets in the first layer of ore raw material is set to P (mass%), the specified value α is calculated by the following formula 1. The required amount of coke loaded in the center can also be changed according to the stacking angle of the first layer of ore. In particular, the proportion P of the iron ore pellets in the first layer is related to the stacking angle of the first layer of ore. Therefore, by considering the proportion P of the iron ore pellets in the first layer to determine the specified value α, the improvement effect of air permeability can be obtained with high precision.

[0015] α=0.017×(0.001×P+0.97)···1.

[0016] Preferably, the strength of the coke piled in the center is greater than or equal to the strength of the coke contained in the second layer. From the viewpoint of air permeability, high-strength coke is preferred, but on the other hand, high-strength coke is usually expensive, leading to increased manufacturing costs. Therefore, by using high-strength coke only in the center packing, it is possible to suppress the increase in manufacturing costs and improve air permeability.

[0017] Preferably, the average particle size of the coke piled in the center is greater than or equal to the average particle size of the coke contained in the second layer. From the viewpoint of air permeability, a large average particle size of the coke is preferred; however, on the other hand, coke with a large average particle size is generally more expensive, leading to increased manufacturing costs. Therefore, by using coke with a large average particle size only in the center packing, it is possible to suppress the increase in manufacturing costs and achieve improved air permeability.

[0018] Preferably, the method includes: a step of inputting the actual values ​​of an input data set and an output data set as learning data into an artificial intelligence model, and training the artificial intelligence model to predict the temperature data of the molten iron in the future relative to a reference time based on the input data set, wherein the input data set includes at least the temperature and air volume of the hot air, the amount of dissolution loss reaction, the heat release of the furnace wall, the amount of residual pig iron, the temperature of the molten iron, and the ratio R during a predetermined period from a time in the past relative to the reference time; the output data set includes the temperature data of the molten iron obtained in the reduction and melting processes in the future relative to the reference time; a step of obtaining the input data set with the current time as the reference time; a step of inputting the input data set obtained in the obtaining step into the trained artificial intelligence model with the current time as the reference time; and a step of estimating the future temperature of the molten iron using the trained artificial intelligence model, wherein the actual values ​​of the input data set obtained in the obtaining step and the output data set corresponding to the input data set are used as inputs to the learning step. In this way, the temperature of molten iron is estimated by using the learned artificial intelligence model, and additional learning is performed using the actual values ​​of the input data set and the corresponding output data set obtained in the process, thereby enabling the temperature of molten iron to be managed with high accuracy based on the ratio R.

[0019] Here, the "center" of the blast furnace refers to the region within 0.2Z or less of the central axis of the blast furnace when the radius of the furnace mouth is set to Z. The "strength" of the coke refers to the drum strength as specified in JIS-K-2151:2004. Furthermore, "average particle size" refers to the arithmetic mean diameter.

[0020] Invention Effects

[0021] As explained above, by using the pig iron manufacturing method of the present invention, it is possible to ensure the flow of hot air in the center of the blast furnace and further reduce the amount of coke used. Attached Figure Description

[0022] Figure 1 This is a flowchart illustrating a method for manufacturing pig iron according to one embodiment of the present invention.

[0023] Figure 2 It is shown in Figure 1 A schematic diagram of the interior of a blast furnace used in pig iron manufacturing methods.

[0024] Figure 3 yes Figure 2 A schematic enlarged view of the area from the softening zone to the dripping zone.

[0025] Figure 4 This is a graph showing the relationship between the ratio R and the modified K value in the embodiment.

[0026] Figure 5 This is a graph showing the relationship between the coke ratio and the K value in the examples.

[0027] Figure 6 This is a schematic diagram showing the structure of the experimental apparatus for blast furnace charge distribution used in the embodiment.

[0028] Figure 7 This is a graph showing the relationship between the proportion P (alumina pellet ratio) of iron ore pellets and the ore stacking tilt angle θ in the embodiments.

[0029] Figure 8 This is a graph showing the relationship between the coke ratio and the K value, categorized by the proportion P of iron ore pellets in the embodiments. Detailed Implementation

[0030] The following describes the pig iron manufacturing methods according to various embodiments of the present invention.

[0031] [First Implementation Method]

[0032] Figure 1 The method of manufacturing pig iron shown uses Figure 2 The method for producing pig iron using blast furnace 1 shown includes a stacking process S1, a central charging process S2, and a reduction melting process S3.

[0033] Blast Furnace

[0034] Blast Furnace 1 Figure 2 As shown, the blast furnace 1 has tuyeres 1a and tapholes 1b located at the bottom of the furnace. Multiple tuyeres 1a are typically provided. The blast furnace 1 is a counter-current solid-gas vertical shaft furnace. Hot air, with high-temperature or ambient-temperature oxygen added to it as needed, is blown into the furnace through tuyeres 1a, enabling a series of reactions, including the reduction and melting of the ore raw material 11 (described later), and pig iron is removed from the taphole 1b. Furthermore, the blast furnace 1 is equipped with a charging device 2 in the form of a bell and guard plate. This charging device 2 will be described later.

[0035] <Lamination Process>

[0036] In the lamination process S1, such as Figure 2 As shown, a first layer 10 and a second layer 20 are alternately stacked inside blast furnace 1. That is, the number of layers of the first layer 10 and the second layer 20 is two or more.

[0037] (First layer)

[0038] The first layer 10 contains ore raw material 11. In the reduction melting process S3, the ore raw material 11 is heated and reduced by hot air blown in from the tuyeres 1a to become molten iron F.

[0039] Ore raw material 11 refers to ores that become iron ore raw materials, mainly containing iron ore. Examples of ore raw material 11 include calcined ore (iron ore pellets, sinter), lump ore, ore with added carbon, and metals. Furthermore, it is preferable that ore raw material 11 contains aggregate 11a. The following describes the case where ore raw material 11 contains aggregate 11a; however, aggregate 11a is not an essential component, and ore raw material 11 may or may not contain aggregate 11a.

[0040] Aggregate 11a is used to improve the permeability of the softening zone D described later, so that the hot blast can permeate to the center M of the blast furnace 1. Aggregate 11a preferably comprises a reduced iron shaped body (HBI, Hot Briquette Iron) obtained by compressing and forming reduced iron.

[0041] HBI is obtained by forming Direct Reduced Iron (DRI) under hot conditions. DRI has the disadvantage of high porosity and exothermic oxidation during sea transport and outdoor storage. In contrast, HBI has low porosity and is difficult to re-oxidize. After ensuring the permeability of the first layer 10, aggregate 11a functions as a metal, becoming molten iron. Due to its high metallization rate, aggregate 11a does not require reduction, so minimal reduction materials are needed when forming this molten iron. Therefore, CO2 emissions can be reduced. It should be noted that the term "metallization rate" refers to the proportion of metallic iron to the total iron content [mass %].

[0042] As a lower limit for the amount of reduced iron shaped body charged, it is preferably 100 kg per ton of pig iron, more preferably 150 kg. When the amount of reduced iron shaped body charged is less than the lower limit, the permeability assurance function of the aggregate 11a in the softening zone D may not be fully realized in the reduction melting process S3. On the other hand, the upper limit for the amount of reduced iron shaped body charged is appropriately determined within a range that does not result in excessive aggregate and reduced aggregate effect, but the upper limit for the amount of reduced iron shaped body charged is, for example, 700 kg per ton of pig iron.

[0043] The lower limit of the ratio of the average particle size of the reduced iron shaped body to the average particle size of the ore raw material 11b (excluding aggregate 11a) is preferably 1.3, more preferably 1.4. Figure 3 As shown, a portion of the ore raw material 11b, excluding the aggregate 11a of the first layer 10, melts and moves downwards into the blast furnace 1 as dripping slag 12. While the ore raw material 11b, excluding the aggregate 11a, softens and shrinks, the high-melting-point reduced iron shaped body does not soften. When the reduced iron shaped body, which is significantly larger than the ore raw material 11b (excluding the aggregate 11a), is mixed as aggregate 11a, the aggregate effect of the reduced iron shaped body readily manifests, suppressing overall layer shrinkage of the first layer 10. Therefore, by setting the average particle size ratio to the lower limit or above, it is possible to ensure... Figure 3 The hot air flow path, as indicated by the arrow, improves the permeability of the reduction melting process S3. On the other hand, the upper limit of the aforementioned average particle size ratio is preferably 10, more preferably 5. When the aforementioned average particle size ratio exceeds the upper limit, it becomes difficult to uniformly mix the reduced iron form in the first layer 10, and segregation may increase.

[0044] Furthermore, when the reduced iron molten iron contains alumina, the upper limit of the alumina content in the reduced iron molten iron is preferably 1.5% by mass, more preferably 1.3% by mass. When the alumina content exceeds the upper limit, it may be difficult to ensure the permeability of the lower part of the furnace due to the increased melting point and viscosity of the slag. Therefore, by setting the alumina content in the reduced iron molten iron below the upper limit, the increase in the amount of coke 21 used can be suppressed. It should be noted that the alumina content can also be 0% by mass, that is, the reduced iron molten iron may not contain alumina, but the lower limit of the alumina content is preferably 0.5% by mass. When the alumina content is less than the lower limit, the reduced iron molten iron becomes expensive, and the production cost of pig iron may increase.

[0045] In the first layer 10, in addition to the ore raw material 11, by-product raw materials such as limestone, dolomite, and silica can also be loaded together. In addition, in the first layer 10, besides the ore raw material 11, small particles of coke obtained from screening coke are usually mixed in.

[0046] (Second layer)

[0047] The second layer 20 contains coke 21.

[0048] Coke 21 serves as a heat source for melting ore raw material 11, generates CO gas as a reducing material required for the reduction of ore raw material 11, acts as a carburizing agent to lower the melting point when carburized into molten iron, and serves as a spacer to ensure the permeability of blast furnace 1.

[0049] (Cascading method)

[0050] Various methods can be used to alternately stack the first layer 10 and the second layer 20. Here, we take a layer equipped with... Figure 2 The method will be explained using a blast furnace 1 as an example of a raw material charging device 2 (hereinafter also referred to as "raw material charging device 2") with a bell and guard plate as shown.

[0051] The raw material charging device 2 is located at the top of the furnace. That is, the first layer 10 and the second layer 20 are charged from the top of the furnace. The raw material charging device 2 is as follows: Figure 2 As shown, it has a feeding cup 2a, a feeding bell 2b, and a guard plate 2c.

[0052] The feeding cup 2a is filled with the raw materials. When the first layer 10 is loaded, the raw materials constituting the first layer 10 are filled into the feeding cup 2a. When the second layer 20 is loaded, the raw materials constituting the second layer 20 are filled.

[0053] The feeding bell 2b is a downwardly extending cone shape and is fitted inside the feeding bell cup 2a. The feeding bell 2b can move up and down (in... Figure 2 In the diagram, the state of moving upwards is represented by a solid line, and the state of moving downwards is represented by a dashed line. When the feed bell 2b moves upwards, it seals the lower part of the feed bell cup 2a; when it moves downwards, it creates a gap on the extension of the side wall of the feed bell cup 2a.

[0054] The protective plate 2c is positioned below the charging bell 2b on the furnace wall of the blast furnace 1. When the charging bell 2b is moved downwards, the raw material falls through the aforementioned gap, but the protective plate 2c is a rebound plate used to bounce the falling raw material. In addition, the protective plate 2c is configured to move inwards and outwards towards the interior of the blast furnace 1.

[0055] The first layer 10 can be stacked using the material loading device 2 as follows. It should be noted that the same applies to the second layer 20. Furthermore, the stacking of the first layer 10 and the second layer 20 is performed alternately.

[0056] First, with the feed bell 2b positioned at the top, the raw material of the first layer 10 is loaded into the feed cup 2a. With the feed bell 2b at the top, the lower part of the feed cup 2a is sealed, thus filling the feed cup 2a with the aforementioned raw material. It should be noted that the filling amount is set as the layering amount for each layer. If the capacity of the feed cup 2a is not sufficient for the layering amount, the first layer 10 can be layered multiple times. This single layering process is referred to as a "batch."

[0057] Next, the charging bell 2b is moved downwards. This creates a gap between the charging bell and the charging cup 2a, allowing the raw material to fall through this gap towards the furnace wall and collide with the protective plate 2c. The raw material, after colliding with and bouncing off the protective plate 2c, is then loaded into the furnace. Because of the bounce off the protective plate 2c, the raw material falls as it moves towards the inside of the furnace, flowing towards the center of the furnace from its point of impact and accumulating. The protective plate 2c is configured to move inwards and outwards towards the interior of the blast furnace 1, thus adjusting the position of the falling raw material by moving the protective plate 2c inwards and outwards. This adjustment allows the first layer 10 to accumulate into a desired shape.

[0058] <Center loading process>

[0059] In the central loading process S2, coke 31 is loaded into the central part M of the blast furnace 1. Through the loading of this coke 31, as... Figure 2 The central layer 30 is formed as shown. It should be noted that, in addition to loading coke 31 into the central part M, a small amount of ore raw materials may also be mixed in and loaded.

[0060] In the stacking process S1 (stacking process), one or more center loading processes S2 (loading process) are performed during one feeding of a stacked unit that combines a first layer 10 and a second layer 20. This feeding is a cycle in which the first layer 10 and the second layer 20 are stacked one layer each. For example, if the first layer 10 and the second layer 20 are processed in two batches, the first batch of the first layer 10, the second batch of the first layer 10, the first batch of the second layer 20, and the first batch of the second layer 20 are combined into one feeding.

[0061] The order in which the center loading process S2 is performed within a single feeding cycle can be appropriately determined based on various conditions. For example, the center loading process S2 can be performed as the initial process of a single feeding cycle, or it can be performed twice before the first layer 10 and the second layer 20 are stacked. Furthermore, if the first layer 10 and the second layer 20 are processed in two batches, it can be performed twice: once between the first batch of the first layer 10 and the second batch of the first layer 10, and once between the second batch of the second layer 20 and the first batch of the first layer 10.

[0062] (coke)

[0063] The coke 31 can be coke with the same properties as the coke 21 in the second layer 20, or it can be coke with different properties. When using coke with different properties, the strength of the coke 31 piled in the center M is preferably higher than that of the coke 21 contained in the second layer 20. From the viewpoint of air permeability, high strength coke is preferred, but on the other hand, high-strength coke is usually expensive, leading to an increase in manufacturing costs. Therefore, by mainly using high-strength coke for center loading, it is possible to suppress the increase in manufacturing costs and improve air permeability. It should be noted that "coke piled in the center" mainly refers to the coke loaded in the center loading process S2, but for example, when the second layer is stacked, if coke piles up in the center due to rolling or the like, this coke is included in the coke piled in the center. That is, "coke piled in the center" refers to the coke piled in the center after a single loading, and its source is not limited. Here, in order to ensure that the strength of the coke 31 piled in the central part M is greater than or equal to the strength of the coke 21 contained in the second layer 20, the coke 31 loaded in the central part loading process is equivalent to having a greater strength than the coke 21 contained in the second layer 20. When the coke 21 in the second layer 20 piles up in the central part M due to rolling or the like, this coke can be considered to have the same strength as the coke 21 in the second layer 20.

[0064] Furthermore, the average particle size of the coke 31 deposited in the central portion M is preferably greater than or equal to the average particle size of the coke 21 contained in the second layer 20. From the viewpoint of air permeability, a larger average particle size of the coke is preferred; however, on the other hand, coke with a larger average particle size is generally more expensive, leading to an increase in manufacturing costs. Therefore, by using coke with an average particle size larger than that used in the stacking process S1 primarily in the central loading process S2, it is possible to suppress the increase in manufacturing costs and improve air permeability.

[0065] It should be noted that, particularly preferably, the strength of the coke 31 piled in the central part M is greater than or equal to the strength of the coke 21 contained in the second layer 20, and the average particle size of the coke 31 piled in the central part M is greater than or equal to the average particle size of the coke 21 contained in the second layer 20.

[0066] (Cascading method)

[0067] The stacking of the central layer 30 can be performed using various methods, as long as the ratio R described later can be set to a predetermined value α or higher. However, for example, it can be performed using a raw material charging device 2 in the same manner as the first layer 10 and the second layer 20. Specifically, it is preferable to use the raw material charging device 2 to stack a portion of the central layer 30 (a thickness equivalent to that of the immediately following first layer 10 or second layer 20) in the central part M of the blast furnace 1.

[0068] In this pig iron manufacturing method, through a single feeding, the ratio R of the mass (ton / ch) of coke 31 piled in the central part M to the mass (ton / ch) of the ore raw material 11 charged is a predetermined value α or higher. It should be noted that, for example, if multiple central part charging processes S2 are performed within a single feeding, the ratio R refers to the ratio of the total quantity of coke 31 to the total quantity of ore raw material 11 charged in a single feeding. Furthermore, the "mass of ore raw material charged" primarily refers to the ore raw material 11 charged in the first layer 10 during the stacking process S1, but it also includes ore raw material in other layers. In other words, the "mass of ore raw material charged" is the total mass of ore raw material charged in a single feeding, and its source is not limited.

[0069] The specified value α can be set to 0.017. By setting the specified value α to this value, breathability can be easily ensured.

[0070] When the ore raw material 11 in the first layer 10 contains iron ore pellets, 0.017 can also be used as the specified value α. However, when the proportion of the iron ore pellets in the ore raw material 11 in the first layer 10 is set to P (mass%), the specified value α is preferably calculated by the following formula 1. Here, "iron ore pellets" refers to those made by using iron ore powder of tens of μm as raw material to improve quality according to properties suitable for blast furnace use (e.g., size, strength, reducibility, etc.).

[0071] α=0.017×(0.001×P+0.97)···1

[0072] To improve permeability, it is desirable to form a central column of coke 31 in the central part M of the blast furnace 1. Specifically, it is preferable to charge the coke 31 in the central charging process S2 in such a way that the thickness of the first layer 10 near the center is greater than the thickness of the central column, which is determined by the charging mass of the ore raw material 11 charged in a single charge and the ore stacking inclination angle; that is, the coke 31 in the central part M protrudes from the first layer 10. It should be noted that the "ore stacking inclination angle" refers to the angle of the inclined surface of the ore stack (first layer 10, etc.) relative to the horizontal.

[0073] The first layer 10 is typically stacked at an angle, with the central portion M decreasing in height. Here, sinter and lump ore are amorphous and have a relatively wide particle size distribution, while iron ore pellets are spherical and have a more concentrated particle size. Therefore, iron ore pellets tend to roll towards the central portion M more easily than sinter and lump ore. When the proportion of iron ore pellets is increased, the ore stacking angle tends to decrease. At this point, the first layer 10 tends to flatten, and the central portion M becomes relatively thicker. Therefore, it is preferable to increase the proportion of iron ore pellets by increasing the ratio of coke 31 (ton / ch) packed into the center relative to the ore raw material 11 (ton / ch) of the first layer 10, thereby relatively increasing the amount of coke 31. The inventors of this invention studied the correlation between the proportion P of iron ore pellets in the first layer 10 and the ore stacking angle of the first layer 10, and concluded that by considering the proportion P of iron ore pellets in the first layer 10 and determining the specified value α based on Equation 1 above, an improvement in permeability can be obtained with high precision.

[0074] <Reduction Melting Process>

[0075] In the reduction melting process S3, auxiliary fuel is blown into the blast furnace using hot air blown from the tuyeres 1a, while the first layer 10 of ore raw material 11 is reduced and melted. It should be noted that the blast furnace operation is continuous, and the reduction melting process S3 is carried out continuously. On the other hand, the stacking process S1 and the central charging process S2 are carried out intermittently. Depending on the reduction and melting status of the first layer 10 and the second layer 20 in the reduction melting process S3, a new first layer 10, a second layer 20, and a central layer 30 that should be processed by the reduction melting process S3 are added.

[0076] Figure 2 This shows the state during the reduction melting process S3. For example... Figure 2 As shown, under the influence of hot air from tuyeres 1a, a tuyeres circulation zone A is formed near tuyeres 1a. This tuyeres circulation zone A is a cavity where coke 21 rotates and exists in a significantly sparse state. Inside the blast furnace 1, the temperature of this tuyeres circulation zone A reaches a maximum of 2000°C. Adjacent to the tuyeres circulation zone A, inside the blast furnace 1, there is a core B, which serves as a pseudo-stagnant zone for coke. Furthermore, from the core B upwards, there are sequentially a dripping zone C, a softening zone D, and a blocky zone E.

[0077] The temperature inside blast furnace 1 rises from the top towards the tuyeres circulation zone A. Specifically, the temperature increases in the order of the blocky zone E, the softening zone D, and the dripping zone C. For example, the blocky zone E is above 20°C but below 1200°C, while the core B is above 1200°C but below 1600°C. It should be noted that the temperature of the core B varies radially, and there are instances where the temperature in the center of core B is lower than that in the dripping zone C. Furthermore, by ensuring stable flow of hot air in the central part M of the furnace, an inverted V-shaped softening zone D is formed, ensuring both permeability and reducibility within the furnace.

[0078] Inside blast furnace 1, iron ore feedstock 11 is first reduced by heating in the lumpy zone E. In the softening zone D, the ore reduced in the lumpy zone E softens and shrinks. The softened and shrunken ore descends as dripping slag and moves towards the dripping zone C. In the reduction-melting process S3, the reduction of ore feedstock 11 mainly proceeds in the lumpy zone E, and the melting of ore feedstock 11 mainly occurs in the dripping zone C. It should be noted that in the dripping zone C and the furnace core B, the descending liquid iron oxide FeO directly reacts with the carbon in the coke 21 for direct reduction.

[0079] The aggregate 11a containing the reduced iron shaped body exerts its aggregate effect in the softening zone D. That is, even when the ore has softened and shrunk, the high-melting-point reduced iron shaped body does not soften, ensuring that the hot blast can reliably pass through the ventilation path to the center of the blast furnace 1.

[0080] Additionally, in the hearth section, molten iron F, formed from the reduced iron, accumulates, and molten slag G accumulates on top of this molten iron F. Both the molten iron F and the molten slag G can be removed from the taphole 1b.

[0081] Examples of auxiliary fuels that can be introduced through tuyeres 1a include finely pulverized coal (which has been ground to a particle size of 50 μm), heavy oil, and natural gas. These auxiliary fuels function as heat sources, reducing agents, and carbon additives. In other words, they replace the spacer function of coke 21.

[0082] <Advantages>

[0083] In this pig iron manufacturing method, during each charging of the stacking unit that combines the first layer 10 and the second layer 20 of the stacking process S1, coke 31 is charged into the center M of the blast furnace 1, thereby easily ensuring the flow of hot blast in the center M of the blast furnace 1. Furthermore, through this single charging, the ratio R of the mass (ton / ch) of coke 31 accumulated in the center M to the mass (ton / ch) of the ore raw material 11 is a predetermined value α or higher, thereby improving the permeability of the hot blast. Therefore, even with a reduction in the amount of coke used, the required permeability can be ensured, thus further reducing the amount of coke required.

[0084] [Second Implementation]

[0085] Another embodiment of the present invention provides a method for manufacturing pig iron using... Figure 2 The method for producing pig iron in a blast furnace 1 with tuyeres 1a, as shown, includes a process of alternately stacking a first layer 10 containing ore 11 and a second layer 20 containing coke 21 within the blast furnace 1 (stacking process); a process of charging coke 31 into the center M of the blast furnace 1 (center charging process); and a process of reducing and melting the stacked first layer 10 of ore 11 while blowing auxiliary fuel into the blast furnace 1 using hot air blown from tuyeres 1a (reduction and melting process). In the stacking process, the center charging process is performed once or more during one charge of stacking a stacked unit that combines a first layer 10 and a second layer 20. Through this single charge, the ratio R of the mass (ton / ch) of coke 31 accumulated in the center M to the mass (ton / ch) of ore 11 is a predetermined value α or higher. Furthermore, this pig iron production method includes a learning process, an acquisition process, an input process, an estimation process, and a control process.

[0086] The above-described lamination process, the above-described center loading process, and the above-described reduction and melting process are the same as the lamination process S1, the center loading process S2, and the reduction and melting process S3 in the first embodiment, so detailed descriptions are omitted.

[0087] (Learning the process)

[0088] The above learning process is as follows: the actual values ​​of the input data set and the output data set are input into the artificial intelligence model as learning data, and the artificial intelligence model is trained by predicting the temperature data of the molten iron F in the future relative to the reference time based on the input data set. The input data set includes at least the temperature and air volume of the hot air from a time in the past relative to the reference time to a specified period of the reference time, the heat emitted from the furnace wall (i.e., the heat released from the furnace wall), the heat generated by the dissolution loss reaction (i.e., the amount of dissolution loss reaction), the amount of residual pig iron, the temperature of the molten iron F, and the ratio R. The output data set includes the temperature data of the molten iron F obtained in the reduction and melting processes in the future relative to the reference time.

[0089] In addition to the temperature of the hot air and the temperature of the molten iron F, the above input data set preferably also includes the moisture content of the hot air, the coke ratio, and the auxiliary fuel ratio (preferably the pulverized coal ratio when the auxiliary fuel includes pulverized coal) from the viewpoint of improving prediction accuracy.

[0090] In the above learning process, the reference time is a point in the past, and any time further past the reference time can be any point in time. Furthermore, any time further in the future than the reference time is at least earlier than the current time. Therefore, the values ​​of both the input and output data sets can be set to measured values. Additionally, for a series of time-series data from the past to the future, the reference time can be changed, i.e., the time at which past and future data are separated can be altered.

[0091] Furthermore, the input data set preferably also includes data from moments further in the future than the aforementioned reference time (but further in the past than the present). The temperature of the molten iron F after the aforementioned reference time, which becomes the object of prediction, can be changed through deliberate control of the aforementioned input data set after the aforementioned reference time. Thus, by also using this data for the learning of the artificial intelligence model, a highly accurate prediction model can be created.

[0092] The aforementioned input data set and output data set can be acquired by sensors installed in blast furnace 1. In this case, for example, for the same type of input data, sensors can be installed at different locations, and the data can be acquired as location-dependent data.

[0093] The aforementioned input data set and output data set, serving as actual values, are input into the artificial intelligence model as learning data. Furthermore, the artificial intelligence model learns by predicting the temperature data of molten iron F in the future, closer to the reference time, based on the aforementioned input data set. Specifically, a prediction model for predicting the temperature data of molten iron F is constructed. In constructing the prediction model, well-known prediction techniques related to machine learning (AI) can be used. Specifically, the aforementioned input data set and output data set can be used to enable the model to learn the correlation between the input data set and the output data set, thereby constructing the prediction model. Among these, deep learning, which utilizes a multi-layered neural network, is preferably employed as the machine learning method.

[0094] In this pig iron manufacturing method, the actual values ​​of the input data set obtained in the acquisition process described later and the corresponding output data set are used as inputs to the learning process. By using a pre-learned artificial intelligence model for prediction, and simultaneously continuing to learn using the input data set and output data set generated sequentially through the operation of blast furnace 1, the prediction accuracy of the artificial intelligence model can be improved.

[0095] (Acquiring process)

[0096] In the above acquisition process, the current time is used as the reference time to acquire the input data set. Specifically, the same method as the method used in the above learning process for acquiring the input data set can be used, for example, using the same sensor to acquire the input data set.

[0097] (Input process)

[0098] In the above input process, the input data set obtained in the above acquisition process is input into the learned artificial intelligence model with the current time as the reference time. In the above input process, the reference time is set to the current time and the artificial intelligence model is used. Therefore, a time that is further in the future than the reference time is also a future time in the real world. The temperature of the molten iron F predicted in the estimation process described later becomes the temperature that should come in the future.

[0099] (Estimated process)

[0100] In the aforementioned estimation process, the learned artificial intelligence model is used to estimate the future temperature of molten iron F. Since the artificial intelligence model is a fully learned model, it can estimate the future temperature of molten iron F with good accuracy.

[0101] (Control process)

[0102] In the aforementioned control process, the set values ​​of the items included in the aforementioned input data set are changed based on the estimated temperature of the molten iron F obtained in the aforementioned estimation process. Particularly in this pig iron manufacturing method, when the ratio R is too large, the molten iron temperature decreases, potentially causing rapid cooling. Therefore, it is important to appropriately control the estimated future temperature of the molten iron F and to avoid rapid cooling.

[0103] Specifically, in the aforementioned estimation process, when predicting a decrease in the temperature of molten iron F, the aforementioned artificial intelligence model can, for example, estimate parameters that can effectively prevent a decrease in the temperature of molten iron F (rapid cooling) based on the temperature of the hot air, air volume and moisture content, coke ratio, pulverized coal ratio, and the aforementioned ratio R, and then control the process. In particular, it is preferable to control the process in a way that prevents the ratio R from becoming too high.

[0104] It should be noted that the aforementioned control process is not essential and can be omitted. In this case, the artificial intelligence model only estimates the temperature of the molten iron F. Furthermore, the operator studies and implements specific countermeasures based on the estimated results.

[0105] <Advantages>

[0106] In this molten iron manufacturing method, the temperature of the molten iron F is estimated using a learned artificial intelligence model, and further learning is performed using the actual values ​​of the input data sets obtained in the process and the corresponding output data sets. This allows for high-precision management of the molten iron F temperature based on the aforementioned ratio R. Therefore, stable blast furnace operation can continue.

[0107] [Other Implementation Methods]

[0108] It should be noted that the present invention is not limited to the above-described embodiments.

[0109] In the above embodiments, the pig iron manufacturing method may also include other processes. For example, the pig iron manufacturing method may also include a process of finely pulverizing powder from reduced iron briquettes and coal. In this case, it is preferable to use the fine powder obtained from the fine pulverization process as the auxiliary fuel. The reduced iron briquettes are partially broken and become powder due to handling processes, etc. Such powder reduces the permeability of the blast furnace, making it unsuitable for use as the first layer. Furthermore, the powder has a large specific surface area, thus it is easily oxidized to iron oxide. When auxiliary fuel containing this iron oxide is blown in through the tuyeres, permeability can be improved. Therefore, by finely pulverizing powder from reduced iron briquettes together with coal and using the fine powder containing the finely pulverized powder and the coal as auxiliary fuel blown in through the tuyeres, the effective utilization of the reduced iron briquettes can be achieved, and the permeability of the blast furnace can be improved.

[0110] As described above, the stacking process using a bell and guard plate has been explained, but other methods can also be used. One such method is the bellless method. In the bellless method, a rotary chute can be used, and stacking can be performed while adjusting its angle. In this case, the center loading process can be performed continuously before and after the second layer stacking. For example, a method can be used where the amount of coke is gradually increased as the second layer stacks towards the center, and the center loading process is performed continuously; or a method can be used where the amount of coke is gradually decreased as the center loading process continues, and the second layer stacking is performed continuously.

[0111] In the second embodiment described above, the actual values ​​of the input data set obtained in the acquisition process and the corresponding output data set are used as inputs to the learning process. However, it is also possible to configure the structure so that these actual values ​​are not used as inputs to the learning process. That is, the artificial intelligence model built once in the learning process can be used continuously without additional learning, remaining as is.

[0112] Furthermore, in the second embodiment described above, it is preferred to control the ratio R in a way that prevents it from becoming too high during the control process. The control process described above uses a method based on the future temperature of the molten iron F estimated by the estimation process, but it can also be based on other parameters, such as the real-time temperature of the molten iron F. That is, the pig iron manufacturing method can also include a control process that controls the ratio R in a way that prevents the temperature of the molten iron from decreasing. This control process can suppress the disadvantage of the ratio R becoming too high.

[0113] Example

[0114] The present invention will be further described in detail below through embodiments, but the present invention is not limited to these embodiments.

[0115] <Ratio R>

[0116] Using operational data from the blast furnace, the relationship between the ratio R of the mass (ton / ch) of coke accumulated in the central part of the blast furnace after a single charge to the mass (ton / ch) of the ore feedstock and the total K value was investigated.

[0117] Set the furnace top pressure to P1 (kPa), the air supply pressure to P2 (kPa), and the furnace belly gas volume to BOSH (Nm³). 3 When the total K value is ( / min), it is represented by the following Equation 2. The lower the total K value, the more excess there is in terms of air permeability, and conversely, the operation of reducing the coke ratio can be carried out.

[0118] [Mathematical Expression 1]

[0119]

[0120] The following relationship exists between the total K value and the lump coke ratio:

[0121] Total K value = -0.0042 × lump coke ratio + 3.8054···3

[0122] Therefore, according to Equation 3, the total K value is corrected using the value when the lump coke ratio is 270 kg / tp (corrected total K value), and the relationship between this corrected total K value and the ratio R is calculated. The results are then... Figure 4 As shown in the figure. It should be noted that "lump coke" refers to coke with a large particle size on a sieve for the purpose of ensuring air permeability.

[0123] according to Figure 4 The results show that the corrected total K value decreases as the ratio R increases, especially when the ratio R is greater than the specified value α = 0.017, the corrected total K value becomes low. Therefore, the operating data are divided into R < 0.017 and R ≥ 0.017, and the relationship between the coke ratio and the total K value is plotted. The results are then... Figure 5 As shown in the image.

[0124] according to Figure 5 It can be seen that by setting R≥0.017, the total K value decreases, and the permeability improves. Therefore, the coke ratio can be reduced until the total K value reaches the upper limit of operation.

[0125] <Relationship between the ratio P of iron ore pellets>

[0126] First, the effect of the proportion P of iron ore pellets on the tilt angle θ of ore stacking was investigated.

[0127] exist Figure 6 The experimental setup 8 for the distribution of blast furnace charge used in this experiment is shown in the figure. Figure 6 The blast furnace charge distribution experimental device 8 shown is a two-dimensional sliced ​​cold-state model simulating a bell-and-guard plate type raw material charging device at a scale of 1 / 10.7. The size of the blast furnace charge distribution experimental device 8 is 1450 mm in height. Figure 8 The length of L1), width 580mm ( Figure 8 The length of L2), and the depth of 100mm (in Figure 8 The length in the direction perpendicular to the paper.

[0128] Labeling of each component of blast furnace charge distribution experimental device 8 Figure 2 The components of the bell-and-guard plate type raw material charging device 2 have the same numbering as those with the same function. Since their functions are identical, detailed descriptions are omitted. Additionally, the blast furnace charge distribution experimental device 8, as shown... Figure 6 As shown, it has a central loading chute 8a for loading coke, which simulates the central loading process.

[0129] After the blast furnace charge distribution experimental device 8 is sequentially loaded with a coke layer 81 as the base, a coke layer 82 as the center, and an ore layer 83, an experimental layer 84 as the ore layer is loaded.

[0130] The raw materials used for loading the experimental layer 84 were sintered ore (particle size 2.8–4.0 mm) to simulate sintered ore and lump ore, and alumina balls to simulate iron ore pellets. Simulated coke (particle size 8.0–9.5 mm) was used for the raw material at a scale of 2 / 11.2.

[0131] Under the above conditions, the ore stacking tilt angle θ was determined by varying the ratio of alumina balls used to simulate iron ore pellets. It should be noted that the target range for the ore stacking tilt angle θ is defined as a dimensionless radius (furnace wall side = 0.00, center side = 1.00) between 0.32 and 0.71. The results were then... Figure 7 As shown in the image.

[0132] according to Figure 7 The results confirmed that when the proportion of iron ore pellets (the ratio of alumina pellets) increased by 10%, the ore stacking tilt angle θ tended to decrease by about 1 degree.

[0133] Next, using the operational data of the blast furnace, the operational data were divided into two categories: R < 0.017 × (0.001 × P + 0.97) and R ≥ 0.017 × (0.001 × P + 0.97), and the relationship between the coke ratio and the total K value was plotted. The results were then displayed in... Figure 8 As shown in the image.

[0134] according to Figure 8 The results show that by considering the proportion P of iron ore pellets, the improvement effect on air permeability can be judged with high accuracy.

[0135] Industrial applicability

[0136] By using the pig iron manufacturing method of the present invention, it is possible to ensure the flow of hot air in the center of the blast furnace and further reduce the amount of coke used.

[0137] Explanation of reference numerals in the attached figures

[0138] 1 Blast Furnace

[0139] 1a Wind Entrance

[0140] 1b Iron tapping hole

[0141] 2 Raw material loading device

[0142] 2a Glass Cup

[0143] 2b Feeding Bell

[0144] 2c protective plate

[0145] 10 First Floor

[0146] 11. Ore Raw Materials

[0147] 11a Aggregate

[0148] 11b Ore raw materials other than aggregates

[0149] 12 dripping slag

[0150] 20 Second Floor

[0151] 21 Coke

[0152] 30. Central layer

[0153] 31 Coke

[0154] 8. Experimental apparatus for the distribution of blast furnace charge

[0155] 8a Center insertion groove

[0156] 81 Coke Layer

[0157] 82 Central coke layer

[0158] 83 Ore Layer

[0159] 84 Experimental Layer

[0160] A. Air circulation area

[0161] B hearth

[0162] C. Dripping band

[0163] D Softening band

[0164] E block band

[0165] F Molten Iron

[0166] G Molten Slag

[0167] M is the central part.

Claims

1. A method for manufacturing pig iron, wherein pig iron is manufactured using a blast furnace with tuyeres, wherein, The method for manufacturing pig iron includes: The process of alternately stacking a first layer containing ore raw materials and a second layer containing coke in the blast furnace; The process of charging coke into the center of the blast furnace; and The process involves using hot air blown from the tuyeres to blow auxiliary fuel into the blast furnace while simultaneously reducing and melting the first layer of ore raw materials. The ore raw material in the first layer contains iron ore pellets. The pig iron manufacturing method further includes the step of calculating α using the following formula 1 when the proportion of iron ore pellets in the first layer of ore raw materials is set to P (mass%). In the stacking process, during one feeding of a stacking unit that combines a first layer and a second layer, the loading process is performed one or more times. By feeding the material in one go, the ratio R of the mass (ton / ch) of coke piled in the center to the mass (ton / ch) of the ore feedstock is greater than or equal to α, thereby reducing the amount of coke used and ensuring the required permeability. α＝0.017×（0.001×P＋0.97）　···1 It should be noted that the coke piled up in the center is mainly the coke charged in the process of loading coke into the center of the blast furnace, but also includes the coke that piles up in the center due to rolling when the second layer is stacked.

2. The method for manufacturing pig iron according to claim 1, wherein, The strength of the coke piled in the center is greater than or equal to the strength of the coke contained in the second layer.

3. The method for manufacturing pig iron according to claim 1, wherein, The average particle size of the coke deposited in the center is greater than or equal to the average particle size of the coke contained in the second layer.

4. The method for manufacturing pig iron according to claim 1, wherein, The method for manufacturing pig iron includes: The process involves inputting the actual values ​​of the input data set and the output data set as learning data into an artificial intelligence model, and enabling the artificial intelligence model to learn by predicting the temperature data of molten iron in the future relative to a reference time based on the input data set. The input data set includes at least the temperature and air volume of the hot air, the amount of dissolution loss reaction, the heat release of the furnace wall, the amount of residual pig iron, the temperature of the molten iron, and the ratio R during a specified period from a time in the past relative to the reference time. The output data set includes the temperature data of the molten iron obtained in the reduction and melting processes in the future relative to the reference time. The process of obtaining the input data set using the current time as the reference time; The process of inputting the input data set obtained in the aforementioned process into the learned artificial intelligence model, with the current time as the reference time; and The process of enabling the learned artificial intelligence model to estimate the future temperature of the molten iron. The actual values ​​of the input data set and the corresponding output data set obtained in the acquired process are used as inputs for the learned process.

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