Method for predicting sintered ore structure and method for producing sintered ore using the same

Abstract

Proposed are: a sintered ore structure prediction method which enables sintered ore structures, such as a mineral structure and a pore structure of sintered ore, to be ascertained and managed online; and a sintered ore production method which uses the prediction method. This prediction method is for predicting sintered ore structures of sintered ore which is produced by charging an endlessly moving pallet carriage of a Dwight-Lloyd type sintering machine with a sintering material to form a charged layer and by sintering the charged layer, and the method predicts the sintered ore structures by using history of sintering temperatures in the charged layer, said history being obtained from sintered ore production conditions and a heat-transfer model. In addition, sintered ore production conditions under which the sintered ore structures predicted by the aforementioned sintered ore structure prediction method match predetermined sintered ore structures are identified, and the sintered ore is produced under the identified production conditions.

Description

[Technical field]

[0001] The present invention relates to a method for predicting the structure of sintered ore used as a raw material for a blast furnace, and a method for producing sintered ore using the prediction method. [Background technology]

[0002] The quality of sintered ore, such as its strength and reducibility, depends on the mineral texture and pore structure in the sintered ore. The mineral texture and pore structure of sintered ore are influenced by the sintering temperature history, which is determined by the raw material conditions and operating conditions. Controlling the mineral texture and pore structure of sintered ore is important to ensure the quality of sintered ore, but to measure the mineral texture and pore structure, it is necessary to sample the sintered ore after production offline and evaluate it by cross-sectional observation or XRD, etc., so online management is not possible.

[0003] As a method for measuring the sintering temperature history of the sintering raw material charging layer during sinter ore production, for example, Patent Document 1 discloses a method for managing the operating state by calculating feature values ​​from temperature data in the height direction actually measured by a thermocouple. However, it was practically difficult to install thermocouples on an actual endless moving pallet cart and measure data continuously, or to measure daily in a batch system. In addition, this method requires feedback action, which results in lost opportunities for operational improvement, so there was an issue that feedforward action could not be proposed.

[0004] As a method for estimating the sintering temperature history, a heat transfer model has already been formulated in Non-Patent Document 1. For example, Patent Document 2 discloses a method for calculating the temperature history with a relatively high degree of accuracy by using the heat transfer model of Non-Patent Document 1, even when carbonaceous materials with different combustibility are used. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2013-44491 A [Patent Document 2] JP 2015-137368 A [Non-patent literature]

[0006] [Non-Patent Document 1] Bengyan et al., Analysis of Sintering Operation, Iron and Steel, Vol. 56 (1970), No. 3, pp. 371-381 [Non-Patent Document 2] Koichiro Ohno et al., Effect of coke combustion rate equation on numerical simulation of temperature distribution estimation in sintering process bed, Iron and Steel, Vol. 101, (2015), No. 1, P19-P24 Summary of the Invention [Problem to be solved by the invention]

[0007] Thus, although a heat transfer model for estimating the sintering temperature history is known, no technology has been disclosed for predicting the mineral structure and pore structure of sintered ore. As mentioned above, in order to grasp the mineral structure and pore structure, it is necessary to collect sintered ore after production offline and evaluate it by cross-sectional observation or XRD. Therefore, there was a problem that the mineral structure and pore structure that affect the quality of sintered ore cannot be managed online. In addition, since the analysis is of sintered ore that has already been produced, it is limited to feedback action, and the problem of lost opportunities for operational improvement cannot be solved, so feedforward action is an issue.

[0008] The present invention has been made in view of the above circumstances, and an object of the present invention is to propose a method for predicting sintered ore structure, which can grasp and manage the sintered ore structure, such as the mineral structure and pore structure, online, and a method for producing sintered ore using the same. [Means for solving the problem]

[0009] The present invention relates to a method for predicting the structure of sintered ore produced by charging sintering raw materials onto an endless movable pallet cart of a Dwight Lloyd type sintering machine to form a charging layer and sintering the charging layer, the method predicting the sintered ore structure using a sintering temperature history in the charging layer obtained from the sintered ore production conditions and a heat transfer model.

[0010] In the method for predicting the structure of sintered ore according to the present invention configured as described above, (1) Using, as the manufacturing conditions of the sintered ore, the component concentration, particle size and blending amount of the raw materials blended in the sintered raw material, the speed of the pallet cart, the layer thickness of the charging bed and the negative pressure; (2) The manufacturing conditions of the sintered ore further include at least one of a gaseous fuel injection amount, an oxygen injection amount, and a circulating exhaust gas amount. (3) predicting the sintered ore structure using a correspondence relationship between a sintering temperature history and a sintered ore structure that is obtained in advance; (4) The sintered ore structure is the content of calcium ferrite in the sintered ore and / or the porosity of the sintered ore; This is believed to be a more preferable solution.

[0011] The present invention also relates to a method for producing sintered ore using the above-mentioned method for predicting sintered ore structure, which specifies production conditions for sintered ore under which the sintered ore structure predicted using the method for predicting sintered ore structure becomes a predetermined sintered ore structure, and produces the sintered ore under the specified production conditions. Effect of the Invention

[0012] By implementing the method for predicting the sintered ore texture according to the present invention, the sintered ore texture can be predicted in a short time, and the sintered ore texture, such as the mineral texture and pore structure, can be grasped and managed online. Furthermore, by setting the sintered ore production conditions so that the predicted sintered ore texture becomes the target sintered ore texture, the sintered ore texture can be controlled, and high-quality sintered ore can be produced. [Brief description of the drawings]

[0013] [Figure 1] FIG. 1 is a schematic diagram showing an example of a sintered ore manufacturing facility in which the method for predicting a sintered structure according to the present embodiment can be implemented. [Diagram 2] 1 is a graph showing an example of a sintering temperature history obtained from the relationship between the sintering temperature and the sintering time of the sintering bed. [Diagram 3] 1 is a graph showing an example of a method for calculating a temperature history index from a sintering temperature history. [Figure 4] 1 is a graph showing an example of the correlation between the content of calcium ferrite and a temperature history index. [Diagram 5] 1 is a graph showing an example of a correlation between predicted and measured calcium ferrite contents. [Figure 6] 4 is a graph showing an example of a change over time in the calcium ferrite content of produced sintered ore. [Figure 7] 11 is a graph showing another example of a method for calculating a temperature history index from a sintering temperature history. [Figure 8] 1 is a graph showing an example of a correspondence relationship between porosity and a temperature history index. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] Hereinafter, the embodiments of the present invention will be described in detail. Note that the following embodiments are merely examples of devices and methods for embodying the technical ideas of the present invention, and are not intended to limit the configuration to those described below. In other words, the technical ideas of the present invention can be modified in various ways within the technical scope described in the claims.

[0015] <Sintered ore manufacturing equipment to which the present invention is applied> 1 is a schematic diagram showing an example of a sintered ore manufacturing facility 1 in which the sintered structure prediction method according to this embodiment can be implemented. The sintered ore manufacturing facility 1 has a drum mixer 2, which is a granulating device, a sintering machine 3, a crusher 4, a cooler 5, and a sieving device 6. Sintering raw materials including iron-containing raw materials, auxiliary raw materials, and coagulating agents such as carbonaceous materials and coke powder are granulated in the drum mixer 2 after granulation water is added. The granulated sintering raw materials are transported to the sintering machine 3.

[0016] The sintering machine 3 is, for example, a Dwight Lloyd type sintering machine. The sintering machine 3 has a sintering material supply device 11, an endless moving pallet cart 12, an ignition furnace 13, and a wind box 14. The granulated sintering material is charged from the sintering material supply device 11 to the pallet cart 12, and a charging layer of the sintering material is formed. The coagulant contained in the surface layer of the charging layer is ignited in the ignition furnace 13, and the air in the charging layer is sucked downward through the wind box 14, so that the combustion melting zone in the charging layer moves downward. Due to this movement of the combustion melting zone, the charging layer is sintered to become a sintered cake.

[0017] When the air in the sintering bed is sucked downward through the wind box 14, gaseous fuel and / or oxygen-enriched air may be supplied from above the sintering bed. The gaseous fuel is any combustible gas selected from blast furnace gas, coke oven gas, converter gas, city gas, natural gas, methane gas, ethane gas, propane gas, and mixtures thereof.

[0018] The sinter cake is crushed by a crusher 4 and cooled by a cooler 5. The crushed sinter cake is sieved by a sieving device 6 into sinter ore with a particle size of 5 mm or more and return ore with a particle size of less than 5 mm. The return ore is used again as a sinter raw material. In this way, sinter ore is produced.

[0019] <Method for predicting sintered ore texture according to the present invention> In the method for predicting the sintered ore structure according to the present embodiment, the sintered ore structure of the sintered ore produced in the sintered ore production facility 1 is predicted. The prediction of the sintered ore structure involves first (1) calculating the sintering temperature history using the sintered ore production conditions and a heat transfer model, and then (2) predicting the sintered ore structure using the calculated sintering temperature history. In a preferred embodiment, the sintered ore structure of the sintered ore is predicted using a correspondence relationship between the sintering temperature history and the sintered ore structure that is obtained in advance.

[0020] <(1) Calculation of sintering temperature history> The sintering temperature history is calculated using the method described in Non-Patent Document 2, which is a known method. Specifically, the sintering temperature history is calculated using the component concentrations, particle sizes, and mixing amounts of the iron-containing raw materials, auxiliary raw materials, and coagulants mixed in the sintering raw materials, the pallet cart speed, the layer thickness of the charging layer, the sintering ore production conditions including negative pressure, and a heat transfer model. In this embodiment, the heat transfer model is, for example, a solid phase heat balance equation (the following equation (1)) and a gas phase heat balance equation (the following equation (2)) derived from the energy conservation equation.

[0021]

number

[0022]

number

[0023] In the above formulas (1) and (2), ρ s is the density of the solid [kg / m 3 ] and C p·s is the specific heat of the solid [J / (kg×K)], and T s is the temperature of the solid [K], t is time [sec], d is the average particle size [m], and ε a is the void fraction [-], and h is the convection heat transfer coefficient [J / (m 2 ×s×K)], T g is the gas temperature [K], k s is the solid thermal conductivity [J / (m 2×s×K), where Z is the coordinate [m]. Q is the reaction heat [J / s] of each substance contained in the sintering raw material, and the reaction heat is calculated by multiplying the reaction heat of each substance by the reaction rate. In the above formula (2), ρ g is the density of the gas [kg / m 3 ] and C p·g is the specific heat of the gas [J / (kg×K)], u is the gas flow velocity [m / s], T is the temperature [K], and k g is the gas thermal conductivity [J / (m 2 ×s×K).

[0024] Density of solid ρ s and the density of the gas, ρ g The density of the solid is ρ s Using the values ​​listed below as provisional values ​​of the density of the gas, ρ g The following values ​​are used as provisional values ​​for the specific heat of solids, C p·s and the specific heat of the gas, C p·g The values ​​described below are used for each.

[0025] <Solid physical properties (using hematite)>

number

[0026] <Gas properties (air used)>

number

[0027] Each physical property will be explained below. Temperature of the solid, T s is the current calculated temperature of the solid, and the gas temperature T g is the calculated temperature of the current gas. Time t is a set value determined by the time interval over which the temperature change is calculated using the model. The average particle size d is the actual measured value of the average particle size of the granulated sintering raw material. Porosity ε a A tentative value is used. Porosity ε aThe provisional value of is "0.5". The convection heat transfer coefficient h can be calculated by calculating the air volume from the negative pressure, porosity, and average particle size, and then using the air volume and the Lanz-Marshall equation. Solid thermal conductivity k s The values ​​described above are used. The reaction heat Q can be calculated using the concentration, particle size, and amount of the components mixed in the sintering raw material, the reaction heat of each component, and the reaction rate. The gas flow velocity u can be calculated using the negative pressure, porosity, and average particle size. The negative pressure is the actual value measured by a pressure gauge installed in the wind box. The thermal conductivity k of the gas g The values ​​described above are used for .

[0028] The speed of the pallet cart is preset as a manufacturing condition of the sintered ore and is used to determine the ignition time (time exposed to high temperature) and the time from the start of the calculation to the end of the calculation. The layer thickness is also preset as a manufacturing condition of the sintered ore and is used to determine the time from the start of the calculation to the end of the calculation.

[0029] In addition, when using a sintering machine having a gaseous fuel injection device or an oxygen gas injection device, the reaction heat Q in equation (1) may be corrected using one or more of the operating conditions, namely, the amount of gaseous fuel injected, the amount of oxygen gas injected, and the amount of circulating exhaust gas.

[0030] In the above formulas (1) and (2), the above values ​​and T s and T g When you enter the current temperature, the temperature change after the set time interval (Δt: for example, 1 second) is calculated. s and T g The initial temperature is 1300°C, which is the temperature of the ignition furnace. For example, if the time interval is 1 second and the calculation time is 30 minutes, 1800 pieces of temperature data are obtained, and a graph showing the sintering temperature history as shown in Figure 2 can be created using the temperature data.

[0031] <(2) Prediction of sinter structure> As will be described in order below, the sintering temperature history calculated in (1) is used to predict the sintered ore structure, in this case the calcium ferrite content in the sintered ore and the porosity of the sintered ore.

[0032] <Prediction of calcium ferrite content in sinter> The sintering temperature history of the sintering bed is calculated using formulas (1) and (2) and operation data. Since the center of the sintering bed is considered to have an average sintering temperature, the sintering temperature history of the center of the sintering bed height (300 mm point when the layer thickness is 600 mm) is calculated, and the high temperature holding time of 1200 to 1350°C is calculated as temperature history index 1 from the temperature history. Temperature history index 1 can be calculated by subtracting Δt2 from Δt1 in Figure 3.

[0033] Since calcium ferrite is formed at 1200°C or higher and melts and decomposes at temperatures above 1350°C, it can be said that the temperature history index 1 correlates with the content of calcium ferrite contained in sintered ore. Therefore, if an experiment is conducted in advance to measure the content of calcium ferrite contained in sintered ore with a known temperature history index 1 by XRD and a correspondence relationship between the high-temperature holding time and the calcium ferrite contained in the sintered ore as shown in Figure 4 is obtained in advance, the content of calcium ferrite contained in the sintered ore can be predicted from the correspondence relationship and the temperature history index 1. Here, the content of calcium ferrite in the sintered ore is an example of the sintered ore structure.

[0034] As shown in Fig. 4, the relationship between the calcium ferrite content and the temperature history index 1 may vary depending on the CaO content of the sintering raw material. Therefore, it is preferable to obtain the relationship between the calcium ferrite content and the temperature history index 1 for each CaO content. This makes it possible to predict the calcium ferrite content in the sintered ore with high accuracy.

[0035] In addition, the relationship between the calcium ferrite content and the temperature history index 1 may vary depending on the Al2O3 content in the sintering raw material, similar to CaO. Therefore, it is preferable to obtain the relationship between the calcium ferrite content and the temperature history index 1 for each Al2O3 content. This allows the calcium ferrite content in the sintered ore to be predicted with even higher accuracy.

[0036] FIG. 5 is a graph showing the correlation between the predicted and measured calcium ferrite content. The predicted calcium ferrite content is a value calculated from the temperature history index 1, the CaO content, and the graph shown in FIG. 4, and the measured calcium ferrite content is a measurement value obtained by XRD measurement of the calcium ferrite content contained in the sintered ore. As shown in FIG. 5, the coefficient of determination (R 2 ) was 0.84, confirming that the calcium ferrite content in sintered ore can be predicted with high accuracy.

[0037] In this way, if the calcium ferrite content can be predicted, it is possible to adjust the production conditions of sintered ore so that the calcium ferrite content of the produced sintered ore becomes a predetermined target calcium ferrite content.

[0038] FIG. 6 is a graph showing the change over time in the calcium ferrite content of the sintered ore produced. The production conditions of the sintered ore, in which the calcium ferrite content was 25-30% by mass, were changed to 35-40% by mass. Specifically, the amount of coke fines mixed was increased as a production condition of the sintered raw material so that the temperature history index 1 corresponds to a time corresponding to a calcium ferrite content of 35-40% by mass. As a result, the calcium ferrite content of the sintered ore produced after the production conditions were changed was 35-40% by mass, and the production of sintered ore with high TI strength was realized. The TI strength (tumbler strength) can be measured by the method described in JIS M 8712:2017.

[0039] For example, when there are two operating conditions for adjusting the sintered ore production conditions, a two-dimensional matrix table as shown in Table 1 below is created, and the production conditions are determined so that the temperature history index is 1 corresponding to the target calcium ferrite content. Note that the example shown in Table 1 shows an example in which a two-dimensional matrix table with a temperature history index of 1 is created under two conditions (air volume and coke powder content), but the present invention is not limited to this, and a three-dimensional matrix table with three conditions may be created.

[0040] [Table 1]

[0041] <Prediction of porosity in sintered ore> From this sintering temperature history, an integral value of a region of 1200°C or higher in the graph of the sintering temperature history may be calculated as temperature history index 2. The integral value of the region of 1200°C or higher is the region indicated by the shaded area in FIG.

[0042] When the molten liquid is generated and flows, the pores are filled, so it can be said that the temperature history index 2 correlates with the porosity of the sintered ore. Therefore, if the porosity of sintered ore with a known temperature history index 2 is measured in advance using the procedure below, and the correspondence relationship between the temperature history index 2 and the porosity contained in the sintered ore (Figure 8) is experimentally determined, the porosity of the sintered ore can be predicted from the correspondence relationship and the temperature history index 2. The porosity of sintered ore is another example of the sintered ore structure.

[0043] The porosity of sintered ore can be measured by the following procedures S11 and S12. (S11) The sinter S1 is crushed and sieved to a particle size of +1mm-2mm. As a crushing method, it is preferable to use a crushing device such as a disk mill or jaw crusher that does not crush any further the material crushed to a predetermined particle size or less. (S12) The pore size distribution of the obtained sintered ore having a particle size of +1 mm-2 mm is measured by mercury intrusion porosimetry in accordance with JIS R 1655:2003, and the porosity and average pore size are calculated from the cumulative pore volume of pores with diameters of 3.6 nm to 200 μm.

[0044] FIG. 8 is a graph showing the relationship between porosity and temperature history index 2. As shown in FIG. 8, the relationship between porosity and temperature history index 2 may vary depending on the CaO content contained in the sintering raw material. For this reason, it is preferable to obtain the relationship between porosity and temperature history index 2 for each CaO content. This allows the porosity of the sintered ore to be predicted with high accuracy.

[0045] Similarly to the calcium ferrite content, the above-mentioned correspondence can be used to adjust the manufacturing conditions of sintered ore so that the porosity of the sintered ore to be produced becomes a predetermined porosity. The manufacturing conditions of sintered ore may be adjusted using a matrix table such as that shown in Table 1, similar to the calcium ferrite content.

[0046] <Regarding the method for producing sintered ore according to the present invention> By implementing the above-mentioned method for predicting the sintered ore texture, the sintered ore texture can be predicted in a short time, and the sintered ore texture, such as the mineral texture and pore structure, can be grasped and managed online. Furthermore, by setting the sintered ore production conditions so that the predicted sintered ore texture becomes the target sintered ore texture, the sintered ore texture can be controlled, and high-quality sintered ore can be produced. [Industrial Applicability]

[0047] According to the method for predicting sintered ore texture of the present invention, the sintered ore texture, such as the mineral texture and pore structure of the sintered ore, can be grasped and managed online, and is industrially useful, along with a sintered ore manufacturing method using the sintered ore texture prediction method. [Explanation of symbols]

[0048] 1. Sintered ore manufacturing facility 2. Drum Mixer 3. Sintering machine 4 Crusher 5. Cooler 6 Sieving device 11 Raw material supply device 12 Pallet Trolley 13 Ignition furnace 14 Windbox

Claims

1. A method for predicting the structure of sintered ore produced by charging sintering raw materials into an endless movable pallet cart of a Dwight Lloyd type sintering machine to form a charging layer and sintering the charging layer, comprising: The sintered ore structure is the calcium ferrite content in the sintered ore and / or the porosity of the sintered ore, and the sintered ore structure is predicted using a sintering temperature history in the sintering bed obtained from the sintered ore production conditions and a heat transfer model.

2. The method for predicting the structure of sintered ore according to claim 1, wherein the production conditions of the sintered ore include the component concentration, particle size and amount of the raw materials mixed in the sintered raw material, the speed of the pallet cart, the layer thickness of the charging layer and the negative pressure.

3. 3. The method for predicting the structure of sintered ore according to claim 2, further comprising using at least one of an amount of gaseous fuel injected, an amount of oxygen injected, and an amount of circulating exhaust gas as the production conditions of the sintered ore.

4. The method for predicting the sintered ore structure according to any one of claims 1 to 3, further comprising predicting the sintered ore structure using a correspondence relationship between a sintering temperature history and a sintered ore structure that is obtained in advance.

5. A method for producing sintered ore using the method for predicting sintered ore texture according to any one of claims 1 to 3, Identifying a production condition of sintered ore such that the sintered ore texture predicted by the method for predicting the sintered ore texture is a predetermined sintered ore texture; A method for producing sintered ore, comprising producing the sintered ore under the specified production conditions.

6. A method for producing sintered ore using the method for predicting the sintered ore texture according to claim 4, Identifying a production condition of sintered ore such that the sintered ore texture predicted by the method for predicting the sintered ore texture is a predetermined sintered ore texture; A method for producing sintered ore, comprising producing the sintered ore under the specified production conditions.

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