EP4345178A1 - State estimation method for sintering process, operation guidance method, method for producing sintered ore, state estimation device for sintering process, operation guidance device, sintering operation guidance system, sintering operation guidance server, and terminal device - Google Patents

State estimation method for sintering process, operation guidance method, method for producing sintered ore, state estimation device for sintering process, operation guidance device, sintering operation guidance system, sintering operation guidance server, and terminal device Download PDF

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Publication number
EP4345178A1
EP4345178A1 EP22841997.4A EP22841997A EP4345178A1 EP 4345178 A1 EP4345178 A1 EP 4345178A1 EP 22841997 A EP22841997 A EP 22841997A EP 4345178 A1 EP4345178 A1 EP 4345178A1
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EP
European Patent Office
Prior art keywords
sintering
guidance
physical model
sintering process
operation guidance
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Application number
EP22841997.4A
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German (de)
French (fr)
Inventor
Yoshinari Hashimoto
Satoki YASUHARA
Yuji Iwami
Toshiyuki Hirosawa
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JFE Steel Corp
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JFE Steel Corp
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Publication of EP4345178A1 publication Critical patent/EP4345178A1/en
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    • CCHEMISTRY; METALLURGY
    • C22METALLURGY; FERROUS OR NON-FERROUS ALLOYS; TREATMENT OF ALLOYS OR NON-FERROUS METALS
    • C22BPRODUCTION AND REFINING OF METALS; PRETREATMENT OF RAW MATERIALS
    • C22B1/00Preliminary treatment of ores or scrap
    • C22B1/14Agglomerating; Briquetting; Binding; Granulating
    • C22B1/16Sintering; Agglomerating
    • C22B1/20Sintering; Agglomerating in sintering machines with movable grates
    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F27FURNACES; KILNS; OVENS; RETORTS
    • F27BFURNACES, KILNS, OVENS, OR RETORTS IN GENERAL; OPEN SINTERING OR LIKE APPARATUS
    • F27B21/00Open or uncovered sintering apparatus; Other heat-treatment apparatus of like construction
    • F27B21/02Sintering grates or tables
    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F27FURNACES; KILNS; OVENS; RETORTS
    • F27DDETAILS OR ACCESSORIES OF FURNACES, KILNS, OVENS, OR RETORTS, IN SO FAR AS THEY ARE OF KINDS OCCURRING IN MORE THAN ONE KIND OF FURNACE
    • F27D3/00Charging; Discharging; Manipulation of charge
    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F27FURNACES; KILNS; OVENS; RETORTS
    • F27DDETAILS OR ACCESSORIES OF FURNACES, KILNS, OVENS, OR RETORTS, IN SO FAR AS THEY ARE OF KINDS OCCURRING IN MORE THAN ONE KIND OF FURNACE
    • F27D3/00Charging; Discharging; Manipulation of charge
    • F27D2003/0001Positioning the charge
    • F27D2003/0002Positioning the charge involving positioning devices, e.g. buffers, buffer zones
    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F27FURNACES; KILNS; OVENS; RETORTS
    • F27DDETAILS OR ACCESSORIES OF FURNACES, KILNS, OVENS, OR RETORTS, IN SO FAR AS THEY ARE OF KINDS OCCURRING IN MORE THAN ONE KIND OF FURNACE
    • F27D3/00Charging; Discharging; Manipulation of charge
    • F27D2003/0001Positioning the charge
    • F27D2003/0004Positioning the charge involving devices for measuring the article, the stack of articles or the height of the furnace passage or for adjusting the height of the passage to the charge or for putting the articles in the same position
    • FMECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F27FURNACES; KILNS; OVENS; RETORTS
    • F27DDETAILS OR ACCESSORIES OF FURNACES, KILNS, OVENS, OR RETORTS, IN SO FAR AS THEY ARE OF KINDS OCCURRING IN MORE THAN ONE KIND OF FURNACE
    • F27D3/00Charging; Discharging; Manipulation of charge
    • F27D2003/0001Positioning the charge
    • F27D2003/0018Positioning the charge comprising means to introduce or extract the charge in series of separate containers or zones

Definitions

  • the present disclosure relates to a sintering process state estimation method, an operation guidance method, a method of manufacturing sintered ore, a sintering process state estimation apparatus, an operation guidance apparatus, a sintering operation guidance system, a sintering operation guidance server, and a terminal apparatus.
  • FIG. 1 illustrates an overview of the sintering process.
  • fine ore, coke breeze, limestone, and the like that have been mixed and granulated into sintering raw material (quasiparticles) are charged from the surge hopper.
  • the sintering raw material is melted by the heat of combustion of the coke breeze in the sintering machine, the quasiparticles fuse with each other, and the result is cooled by air drawn in from the top and discharged.
  • the heat pattern during this series of heating and cooling processes has a significant impact on product yield.
  • the heat pattern is the temperature distribution of the sintered material in the machine length direction and thickness direction of the sintering machine.
  • ensuring the residence time (high-temperature holding time) at, for example, 1200°C or more, at which ore melts, has a significant impact on yield. Therefore, feature data such as heat patterns that affect yield are accurately estimated, and features such as the high-temperature holding time are calculated from the feature data. Guidance operation quantities, such as the appropriate raw coke ratio, pallet speed, and the like, for controlling the features to have predetermined values can then be indicated to improve the yield.
  • Patent Literature (PTL) 1 discloses a method of controlling the position of the burn through point (BTP) to be constant.
  • the BTP is the position in the machine length direction at which the temperature of the exhaust gas measured in the wind box at the bottom of the sintering machine is the highest.
  • a sintering process state estimation method and sintering process state estimation apparatus that can estimate the state of the sintering process to a high degree of accuracy. It would also be helpful to provide an operation guidance method, a method of manufacturing sintered ore, an operation guidance apparatus, a sintering operation guidance system, a sintering operation guidance server, and a terminal apparatus that can indicate guidance for yield improvement based on the accurately estimated state of the sintering process.
  • a sintering process state estimation method includes: calculating an observable process variable using a physical model that takes into account a chemical reaction and a heat transfer phenomenon in a sintering process; calculating a deviation between an estimated value and an actual value of the calculated process variable; modifying an unknown parameter of the physical model so that the calculated deviation is reduced; and calculating feature data of the sintering process based on a modified physical model.
  • An operation guidance method includes: calculating a high-temperature holding time of sintered material by using the heat pattern calculated by the sintering process state estimation method according to the aforementioned sintering process state estimation method; and presenting a guidance operation quantity, including at least one of a raw material coke ratio and a pallet speed, to maintain the high-temperature holding time at a predetermined value or higher.
  • a method of manufacturing sintered ore according to an embodiment of the present disclosure includes manufacturing sintered ore using the guidance operation quantity presented by the aforementioned operation guidance method.
  • a sintering process state estimation apparatus includes: a memory configured to store a physical model that takes into account a chemical reaction and a heat transfer phenomenon in a sintering process; a process variable calculator configured to calculate an observable process variable using the physical model; a deviation calculator configured to calculate a deviation between an estimated value and an actual value of the calculated process variable; a model parameter adjustor configured to modify an unknown parameter of the physical model so that the calculated deviation is reduced; and a feature data calculator configured to calculate feature data of the sintering process based on a modified physical model.
  • An operation guidance apparatus includes: a high-temperature holding time calculator configured to calculate a high-temperature holding time of sintered material by using a heat pattern of sintered material in a sintering machine length direction, the heat pattern being the feature data calculated by the sintering process state estimation apparatus according to the aforementioned sintering process state estimation apparatus; and a guidance operation quantity presentation interface configured to present a guidance operation quantity, including at least one of a raw material coke ratio and a pallet speed, to maintain the high-temperature holding time at a predetermined value or higher.
  • a sintering operation guidance system includes a sintering operation guidance server and a terminal apparatus, wherein the sintering operation guidance server includes a performance value acquisition interface configured to acquire a performance value indicating a sintering process operation state; a memory configured to store a physical model that takes into account a chemical reaction and a heat transfer phenomenon in the sintering process; a process variable calculator configured to calculate an observable process variable using the physical model; a deviation calculator configured to calculate a deviation between an estimated value and an actual value of the calculated process variable; a model parameter adjustor configured to modify an unknown parameter of the physical model so that the calculated deviation is reduced; a feature data calculator configured to calculate feature data of the sintering process based on a modified physical model; a high-temperature holding time calculator configured to calculate a high-temperature holding time of sintered material by using a heat pattern of sintered material in a sintering machine length direction, the heat pattern being the feature data; and a guidance operation quantity presentation interface configured
  • a sintering operation guidance server includes: a performance value acquisition interface configured to acquire a performance value indicating a sintering process operation state; a memory configured to store a physical model that takes into account a chemical reaction and a heat transfer phenomenon in the sintering process; a process variable calculator configured to calculate an observable process variable using the physical model; a deviation calculator configured to calculate a deviation between an estimated value and an actual value of the calculated process variable; a model parameter adjustor configured to modify an unknown parameter of the physical model so that the calculated deviation is reduced; a feature data calculator configured to calculate feature data of the sintering process based on a modified physical model; a high-temperature holding time calculator configured to calculate a high-temperature holding time of sintered material by using a heat pattern of sintered material in a sintering machine length direction, the heat pattern being the feature data; and a guidance operation quantity presentation interface configured to present a guidance operation quantity, including at least one of a raw material coke ratio and a pallet speed
  • a terminal apparatus is a terminal apparatus forming part of a sintering operation guidance system together with a sintering operation guidance server, the terminal apparatus including: a guidance operation quantity acquisition interface configured to acquire a guidance operation quantity presented by the sintering operation guidance server; and a display configured to display the acquired guidance operation quantity, wherein the sintering operation guidance server modifies an unknown parameter of a physical model that takes into account a chemical reaction and a heat transfer phenomenon in a sintering process so that a deviation between an estimated value and an actual value of a process variable calculated using the physical model is reduced, and the guidance operation quantity is an operation quantity including at least one of a raw material coke ratio and a pallet speed to maintain a high-temperature holding time of sintered material at a predetermined value or higher, the high-temperature holding time being based on a heat pattern of sintered material in a sintering machine length direction as calculated using the physical model with the modified unknown parameter.
  • a sintering process state estimation method and sintering process state estimation apparatus that can estimate the state of the sintering process to a high degree of accuracy can be provided.
  • an operation guidance method, a method of manufacturing sintered ore, an operation guidance apparatus, a sintering operation guidance system, a sintering operation guidance server, and a terminal apparatus that can indicate guidance for yield improvement based on the accurately estimated state of the sintering process can also be provided.
  • a sintering process state estimation method, an operation guidance method, a method of manufacturing sintered ore, a sintering process state estimation apparatus, an operation guidance apparatus, a sintering operation guidance system, a sintering operation guidance server, and a terminal apparatus are described below with reference to the drawings.
  • the physical model used in the present disclosure is the same as the method described in Reference 1 ( Yamaoka et al. ISIJ International, Vol. 45, No. 4, pp. 522 ) and is formed by a set of partial differential equations that take into account the physical phenomena of the combustion of coke breeze, the thermal decomposition of limestone, and the evaporation of moisture. This model is capable of calculating the state inside a sintering machine.
  • the physical model is a two-dimensional unsteady model that can calculate the temperature distribution (heat pattern) of the sintered material and the distribution of the exhaust gas composition in the machine length and thickness directions of the sintering machine.
  • the position of the BTP can also be determined from the calculated heat pattern.
  • the "BTP position" is also referred to simply as the BTP.
  • the main variables that vary with time among the input variables provided in the physical model are the pallet speed, the exhaust gas flow rate, the raw material bulk density, the raw material moisture ratio, the raw material limestone ratio, and the raw material coke ratio.
  • These input variables can be operating variables or operating factors of the sintering machine.
  • the pallet speed is the speed at which the pallet of the sintering machine illustrated in FIG. 1 moves the sintered material on the pallet.
  • the exhaust gas flow rate is the flow rate per unit time of the exhaust gas from the sintering machine and is regulated by an exhaust fan, for example.
  • the raw material bulk density is the bulk density of the sintering raw material calculated from the layer thickness, the sintering machine width, and the like.
  • the raw material moisture ratio, raw material limestone ratio, and raw material coke ratio are the ratios of moisture, limestone, and coke, respectively, in the sintering raw material.
  • Coke is the main condensation material, and the raw material coke ratio is sometimes referred to as the condensation material ratio.
  • the main output variables of the physical model are BTP and exhaust gas composition.
  • the exhaust gas composition includes the ratios of O 2 , CO 2 , and CO.
  • the output variables may include the temperature below the sintering bed.
  • the output variables, which change from moment to moment using the physical model, are calculated.
  • the time interval for this calculation (the time difference between "t + 1" and "t" in the physical model equations described below) is not particularly limited, but is 5 minutes as an example.
  • the physical model can be expressed by the following Equations (1) and (2).
  • u(t) is the input variable mentioned above, which can be manipulated by the operator operating the sintering machine
  • x(t) is a state variable calculated within the physical model.
  • State variables are, for example, the heat pattern in the sintering machine, the coke reaction rate, and the gas fraction such as CO and CO 2 .
  • the variable y(t) is the aforementioned output variable (process variable), i.e., the BTP, the O 2 ratio and CO 2 ratio in the exhaust gas composition, and the partial combustion rate.
  • the variable y(t) can be defined as the key process variable as follows.
  • y t y 1 t , y 2 t , y 3 t , y 4 t T ⁇ BTP t , X O 2 t , X CO 2 t , ⁇ CO t T
  • the partial combustion rate is the value obtained by dividing CO by (CO + CO 2 ) in the exhaust gas (i.e., CO/(CO + CO 2 )).
  • An increase in the partial combustion rate means that coke gasification (C + CO 2 -> 2CO), which is an endothermic reaction, is activated, meaning that the average temperature level in the sintering process is increasing.
  • C + CO 2 -> 2CO coke gasification
  • other key process variables can be included, such as the temperature below the sintering bed.
  • FIG. 3 is a diagram illustrating an example of key process variables for 30 hours, calculated using the physical model as is.
  • the values calculated using the physical model are indicated by solid lines, and the actual values measured at the actual plant (actual sintering machine) are indicated by dashed lines.
  • the BTP is expressed as the distance [m] from the position of the surge hopper in the direction of pallet movement.
  • the average estimation error for each of the key process variables was calculated at 2.4914 [m] for the BTP, 0.0086 for the O 2 ratio, 0.0086 for the CO 2 ratio, and 0.0169 for the partial combustion rate.
  • the average estimation error is calculated by summing the square of the deviation between the estimated value and the actual values for all of the steps, dividing this sum by the number of steps, and calculating the square root of the quotient. Performing a physical model calculation over an extended time in this way has the problem of introducing non-negligible errors in the estimates (estimation error) with conventional methods.
  • the example in FIG. 3 illustrates 30 hours of data, but to control the sintering process by performing calculations over a longer period of years, the estimation error needs to be reduced.
  • variable elements in the physical model As one or more unknown parameters.
  • Three correction parameters i.e., a correction parameter for exhaust gas flow rate, a correction parameter for raw material bulk density, and a correction parameter for raw material coke ratio, were selected as unknown parameters in the present embodiment for reasons explained below.
  • other variable elements such as the raw material moisture ratio, carbon combustion rate, and coke gasification reaction rate could be set as unknown parameters.
  • the carbon combustion rate depends on the temperature of the solid and on the oxygen concentration in the gas, and the proportionality coefficient in this relationship can be an unknown parameter.
  • the unknown parameters need to be selected according to the raw materials used in the target process, equipment configuration, and the like.
  • the flow rate of the exhaust gas containing CO 2 , CO, and the like is measured at the bottom of the sintering bed.
  • the measured exhaust gas flow rate includes the gas flow rate of so-called air leakage (air leakage flow rate) that does not pass through the sintering bed but through another gap.
  • air leakage flow rate is difficult to measure and difficult to input directly into a physical model. Therefore, it seems reasonable to correct the exhaust gas flow rate in the physical model to match the actual value of the key process variable.
  • V [kg/min] is the actual measurable cutting speed of the raw material.
  • H [m] is the layer thickness of the raw material.
  • W [m] is the sintering machine width.
  • PS [m/min] is a value calculated from the pallet speed.
  • the cutting speed of the raw material is a value measured by the cutting apparatus located upstream of the sintering machine. In other words, the charging rate of the raw material actually being charged into the sintering machine is not measured. It is therefore difficult to accurately estimate the raw material bulk density in the sintering machine. Hence, it seems reasonable to correct the raw material bulk density.
  • the raw coke ratio is affected by how, apart from the condensation material (coke) that is charged to the sintering machine, blast furnace dust and other miscellaneous raw materials containing carbon are blended with the fine ore in the raw material yard in advance. Given the large variation in the blend ratio, it seems reasonable to correct the raw material coke ratio (condensation material ratio).
  • FIG. 4 is a diagram illustrating the response of the process variables when unknown parameters are changed stepwise.
  • FIG. 4 was obtained by changing the aforementioned three correction parameters stepwise after the physical model was continuously subjected to certain operating conditions to reach a steady state.
  • the parameters are modified by steps (a) through (f) below so that the BTP, the O 2 ratio, the CO 2 ratio, and the partial combustion rate match.
  • the algorithm described below is called Moving Horizon Estimation (MHE), but other state estimation methods such as a particle filter and a Kalman filter may also be used.
  • step (a) the state variables and key process variables for the past A steps are calculated by Equations (4) and (5) below.
  • k varies between A and 1.
  • actual values are used as input variables.
  • step (b) x(t - A + 1) is stored for use as the initial condition for the iterative calculation.
  • step (c) the degree of deviation is calculated by Equation (6) below.
  • Equation (6) the degree of deviation is calculated by Equation (6) below.
  • y act is the actual value
  • y cal is the estimated value
  • the modification amounts ⁇ , ⁇ and ⁇ of the unknown parameters are calculated to minimize an evaluation function that superposes the deviation and the above-described step responses of the key process variables for each of the unknown parameters, as illustrated in Equation (7) below.
  • the unknown parameters ⁇ , ⁇ , and ⁇ in Equation (7) respectively correspond to the correction parameter for exhaust gas flow rate, the correction parameter for raw material bulk density, and the correction parameter for raw material coke ratio.
  • a smaller evaluation function corresponds to a smaller deviation.
  • a term is added to the evaluation function to ensure that the unknown parameters are not significantly distant from "1" (see FIG. 6 ).
  • q identifies the key process variable.
  • R q p (s) means the value of the response at s, which is a time step in the step response of q, the key process variable, with respect to p, the unknown parameter.
  • step (e) the unknown parameters are modified as in Equations (8) through (10) below.
  • step (f) the process updates t in the time step to t + 1 and returns to step (a).
  • the modification of unknown parameters is thus performed by sequential arithmetic operations.
  • FIG. 5 is a diagram illustrating an example of key process variables calculated by a physical model that modifies unknown parameters.
  • FIG. 6 is a diagram illustrating an example of the change over time in unknown parameters corresponding to FIG. 5 .
  • the average estimation error for each of the key process variables was calculated at 0.9961 [m] for the BTP, 0.0044 for the O 2 ratio, 0.0047 for the CO 2 ratio, and 0.0064 for the partial combustion rate. In other words, it is clear that modification of the unknown parameters using MHE results in a smaller estimation error as compared to the case in FIG. 3 .
  • Equation (7) it suffices for A in Equation (7) to be determined so that the equivalent of the time required from the input side to the exit side of sintering, for example, can be evaluated. Specifically, 30 to 60 minutes is sufficient. In the example in FIG. 5 , the time step width is 5 minutes, A is 8, and the evaluation time is 40 minutes.
  • the sintering process state estimation apparatus can estimate the BTP and exhaust gas composition with high accuracy by performing the aforementioned modification of the unknown parameters. Highly accurate estimation using such a physical model also improves the estimation accuracy for the calculation of the high-temperature holding time of the sintered material.
  • the high-temperature holding time is the time during which the temperature of the sintered material is held at or above a threshold (such as 1200°C) at which improvement in yield is affected.
  • the operation guidance apparatus can provide guidance to increase the temperature by increasing the raw material coke ratio, for example, so as to ensure the high-temperature holding time.
  • the operation guidance apparatus may also provide guidance to ensure the high-temperature holding time by reducing the pallet speed. It is expected that the operation guidance apparatus will achieve the effect of improved yield by presenting the operator with information (guidance operation quantities) that leads to appropriate action.
  • FIG. 7 is a diagram illustrating example configurations of a sintering process state estimation apparatus 10 and an operation guidance apparatus 20 according to an embodiment.
  • the sintering process state estimation apparatus 10 includes a memory 11, a process variable calculator 12, a deviation calculator 13, a model parameter adjustor 14, and a feature data calculator 15.
  • the operation guidance apparatus 20 includes a memory 21, a high-temperature holding time calculator 22, and a guidance operation quantity presentation interface 23.
  • the sintering process state estimation apparatus 10 acquires actual values (also referred to as measured values), which are various measurements from sensors and the like installed in the sintering machine, and performs calculations using the aforementioned physical model.
  • the operation guidance apparatus 20 acquires the feature data for the sintering process as calculated by the sintering process state estimation apparatus 10, determines the guidance operation quantities, and displays guidance for the operation of the sintering machine on the display 30.
  • the feature data is the heat pattern of the sintered material in the sintering machine length direction.
  • the operation guidance apparatus 20 displays the guidance operation quantities on the display 30 as guidance to ensure the high-temperature holding time.
  • the guidance operation quantities can be at least one operation quantity (quantity to be adjusted) among the raw material coke ratio and the pallet speed, which are required to ensure the high-temperature holding time.
  • the display 30 may be a liquid crystal display (LCD), an organic electroluminescence panel (OLED panel), or other display apparatus.
  • the memory 11 stores a physical model that takes into account chemical reactions and heat transfer phenomena in the sintering process.
  • the memory 11 also stores programs and data related to sintering process state estimation.
  • the memory 11 may include any memory device, such as semiconductor memory devices, optical memory devices, and magnetic memory devices.
  • Semiconductor memory devices may, for example, include semiconductor memories.
  • the memory 11 may include a plurality of types of memory devices.
  • the process variable calculator 12 calculates observable process variables using the physical model.
  • the process variables are the BTP, the O 2 ratio and CO 2 ratio in the exhaust gas composition, and the partial combustion rate.
  • the deviation calculator 13 calculates the deviation between the estimated values and the actual values, in an actual plant, of the calculated process variables.
  • the model parameter adjustor 14 modifies unknown parameters of the physical model so that the calculated deviation is reduced.
  • the feature data calculator 15 calculates feature data of the sintering process based on the modified physical model.
  • the feature data is the heat pattern of the sintered material in the sintering machine length direction.
  • the process variable calculator 12, the deviation calculator 13, and the model parameter adjustor 14 perform operations according to the aforementioned steps (a) through (f) to modify the unknown parameters of the physical model.
  • the unknown parameters are modified by iterative calculations performed while updating time steps, using the aforementioned evaluation function that includes the deviation, the process variables, and the unknown parameters.
  • the feature data calculator 15 calculates the heat patterns using the modified physical model and outputs the heat pattern as feature data to the operation guidance apparatus 20.
  • the memory 21 stores programs and data related to operation guidance.
  • the memory 21 may include any memory device, such as semiconductor memory devices, optical memory devices, and magnetic memory devices.
  • Semiconductor memory devices may, for example, include semiconductor memories.
  • the memory 21 may include a plurality of types of memory devices.
  • the high-temperature holding time calculator 22 calculates the high-temperature holding time of the sintered material by using the heat pattern calculated by the sintering process state estimation apparatus 10.
  • the guidance operation quantity presentation interface 23 presents the guidance operation quantity on the display 30 to maintain the high-temperature holding time at or above the predetermined value.
  • the guidance operation quantity includes at least one of the raw material coke ratio and the pallet speed.
  • the guidance operation quantity presentation interface 23 may, for example, display a 10% increase in the raw material coke ratio on the display 30 as the guidance operation quantity.
  • the guidance operation quantity presentation interface 23 may, for example, display a 5% decrease in pallet speed on the display 30 as the guidance operation quantity.
  • the guidance operation quantity presentation interface 23 may have the sintering process state estimation apparatus 10 calculate the amount of increase in the raw material coke ratio and the amount of decrease in pallet speed using the physical model. In other words, the guidance operation quantity presentation interface 23 may have the sintering process state estimation apparatus 10 perform a simulation using the physical model to determine the guidance operation quantity to be presented.
  • the operator may change the operating conditions of the sintering machine based on the guidance operation quantity displayed on the display 30.
  • Such operation guidance for the sintering machine can be implemented as part of a method of manufacturing sintered ore.
  • the sintering process state estimation apparatus 10 and the operation guidance apparatus 20 may be separate apparatuses or integrated into one apparatus.
  • the memory 11 and the memory 21 may be realized by the same memory device.
  • the sintering process state estimation apparatus 10 and the operation guidance apparatus 20 may be realized by a computer, such as a process computer that controls the operation of a sintering machine or the production of sintered ore, for example.
  • the computer includes, for example, a memory and hard disk drive (memory device), a CPU (processing unit), and a display device such as a display.
  • An operating system (OS) and application programs for carrying out various processes can be stored on the hard disk drive and are read from the hard disk drive into memory when executed by the CPU. Data during processing is stored in memory, and if necessary, on the HDD.
  • OS operating system
  • Various functions are realized through the organic collaboration of hardware (such as the CPU and memory), the OS, and necessary application programs.
  • the memory 11 and the memory 21 may, for example, be realized on a memory device.
  • the process variable calculator 12, the deviation calculator 13, the model parameter adjustor 14, the feature data calculator 15, the high-temperature holding time calculator 22, and the guidance operation quantity presentation interface 23 may be realized by the CPU, for example.
  • the display 30 may, for example, be realized by a display device.
  • FIG. 8 is a flowchart illustrating a sintering process state estimation method according to an embodiment.
  • the sintering process state estimation apparatus 10 outputs the feature data of the sintering process according to the flowchart illustrated in FIG. 8 .
  • the state estimation method illustrated in FIG. 8 may be performed as part of a method of manufacturing sintered ore.
  • the process variable calculator 12 calculates observable process variables using the physical model (step S1, process variable calculation step).
  • the deviation calculator 13 calculates the deviation between the estimated values and the actual values of the calculated process variables (step S2, deviation calculation step).
  • the model parameter adjustor 14 modifies unknown parameters of the physical model so that the deviation is reduced (step S3, model parameter adjustment step).
  • the feature data calculator 15 then calculates feature data based on the modified physical model (step S4, feature data calculation step).
  • FIG. 9 is a flowchart illustrating an operation guidance method according to an embodiment.
  • the operation guidance apparatus 20 presents the guidance operation quantity according to the flowchart illustrated in FIG. 9 .
  • the operation guidance method illustrated in FIG. 9 may be performed as part of a method of manufacturing sintered ore.
  • the high-temperature holding time calculator 22 calculates the high-temperature holding time of the sintered material using the heat pattern calculated as the aforementioned feature data (step S11, high-temperature holding time calculation step).
  • the guidance operation quantity presentation interface 23 presents the guidance operation quantity on the display 30 to maintain the high-temperature holding time at or above the predetermined value (step S12, guidance operation quantity presentation step).
  • FIG. 10 is a diagram illustrating a configuration of a sintering operation guidance system according to an embodiment.
  • the sintering operation guidance system may be configured by a sintering operation guidance server 40 and a terminal apparatus 50, as illustrated by the dashed lines in FIG. 10 , for example.
  • the sintering operation guidance server 40 has the functions of the sintering process state estimation apparatus 10 and the operation guidance apparatus 20 and may, for example, be realized by a computer.
  • the terminal apparatus 50 functions at least as a display 30 and may, for example, be realized by a portable terminal apparatus, such as a tablet, or a computer.
  • the sintering operation guidance server 40 and the terminal apparatus 50 can transmit and receive data to and from each other via a network, such as the Internet.
  • the sintering operation guidance server 40 and the terminal apparatus 50 may be in the same location (for example, within the same plant) or may be physically separated.
  • the sintering operation guidance system is not limited to the above configuration and may, for example, further include an operation data server 60 that aggregates sintering machine operation data (for example, the actual values and operation parameters indicating operation status).
  • the operation data server 60 is capable of communicating with the sintering operation guidance server 40 and the terminal apparatus 50 via a network and may, for example, be realized by a computer that manages the manufacturing of sintered ore.
  • the operation data server 60 may be in the same location as the sintering operation guidance server 40 or the terminal apparatus 50 or may be physically separated.
  • components and the like will be described using the example of a sintering operation guidance system configured to include the sintering operation guidance server 40 and the terminal apparatus 50.
  • the sintering operation guidance server 40 acquires performance values indicating the sintering process operating state, performs calculations using the aforementioned physical model, and calculates the high-temperature holding time of the sintered material using the heat pattern as the calculated feature data.
  • the sintering operation guidance server 40 causes the terminal apparatus 50, which functions as the display 30, to display a guidance operation quantity, including at least one of the raw material coke ratio and the pallet speed, to maintain the high-temperature holding time at a predetermined value or higher.
  • the sintering operation guidance server 40 includes the components of the sintering process state estimation apparatus 10 and the components of the operation guidance apparatus 20 described with reference to FIG. 7 .
  • the sintering operation guidance server 40 includes a memory, a process variable calculator 12, a deviation calculator 13, a model parameter adjustor 14, a feature data calculator 15, a high-temperature holding time calculator 22, and a guidance operation quantity presentation interface 23.
  • the memory stores a physical model that takes into account chemical reactions and heat transfer phenomena in the sintering process, programs and data related to sintering process state estimation, programs and data related to operation guidance, and the like.
  • the process variable calculator 12, the deviation calculator 13, the model parameter adjustor 14, the feature data calculator 15, the high-temperature holding time calculator 22, and the guidance operation quantity presentation interface 23 are the same as in the above explanation.
  • the sintering operation guidance server 40 may also include a performance value acquisition interface to acquire performance values indicating the sintering process operation state.
  • the performance value acquisition interface may acquire the performance values directly from sensors provided in the sintering machine, from the sintering process computer, or the like, or may acquire the performance values via the operation data server 60.
  • the terminal apparatus 50 forms a sintering operation guidance system, together with the sintering operation guidance server 40, and displays the guidance operation quantity.
  • the terminal apparatus 50 includes at least a display 30.
  • the display 30 is the same as described above.
  • the terminal apparatus 50 may include a guidance operation quantity acquisition interface to acquire the guidance operation quantity presented by the sintering operation guidance server 40.
  • the sintering process state estimation method and sintering process state estimation apparatus 10 can, with the aforementioned configuration, estimate the state of the sintering process to a high degree of accuracy.
  • the operation guidance method, the method of manufacturing sintered ore, the operation guidance apparatus 20, the sintering operation guidance system, the sintering operation guidance server 40, and the terminal apparatus 50 according to the present embodiment can indicate guidance for yield improvement based on the accurately estimated state of the sintering process.
  • the operator can change the operating conditions based on the indicated guidance operation quantity to ensure the high-temperature holding time of the sintered material at an early stage and thereby improve the yield.
  • the configurations of the sintering process state estimation apparatus 10 and the operation guidance apparatus 20 illustrated in FIG. 7 are only examples.
  • the sintering process state estimation apparatus 10 and the operation guidance apparatus 20 need not include all of the components illustrated in FIG. 7 .
  • the sintering process state estimation apparatus 10 and the operation guidance apparatus 20 may include components other than those illustrated in FIG. 7 .
  • the operation guidance apparatus 20 may further include the display 30.
  • the unknown parameters in the above embodiment include three correction parameters, but it suffices for at least one parameter to be included. In other words, if at least one unknown parameter of the physical model is modified, the estimation error can be reduced.

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Abstract

A sintering process state estimation method includes a process variable calculation step (S1) of calculating an observable process variable using a physical model that takes into account chemical reactions and heat transfer phenomena in a sintering process, a deviation calculation step (S2) of calculating a deviation between an estimated value and an actual value of the calculated process variable, a model parameter adjustment step (S3) of modifying an unknown parameter of the physical model so that the calculated deviation is reduced, and a feature data calculation step (S4) of calculating feature data of the sintering process based on the modified physical model.

Description

    TECHNICAL FIELD
  • The present disclosure relates to a sintering process state estimation method, an operation guidance method, a method of manufacturing sintered ore, a sintering process state estimation apparatus, an operation guidance apparatus, a sintering operation guidance system, a sintering operation guidance server, and a terminal apparatus.
  • BACKGROUND
  • In the steelmaking industry, the grade of iron ore is declining due to years of mining. The use ratio of fine ore, which has undergone beneficiation at the base of the mine and has a high fineness ratio, has thus increased, as has the importance of the sintering process to manufacture sintered ore by condensing the fine ore before charging to the blast furnace. To ensure the gas permeability of the blast furnace, sintered ore with less than a predetermined particle size is not charged into the blast furnace, but rather baked again in the sintering machine as return ore. An improvement in yield, i.e., the percentage of sintered ore having the predetermined particle size or greater, directly affects the productivity of the sintering machine. Strong demand thus exists for improving yield.
  • FIG. 1 illustrates an overview of the sintering process. At the input side of the sintering machine, fine ore, coke breeze, limestone, and the like that have been mixed and granulated into sintering raw material (quasiparticles) are charged from the surge hopper. The sintering raw material is melted by the heat of combustion of the coke breeze in the sintering machine, the quasiparticles fuse with each other, and the result is cooled by air drawn in from the top and discharged. The heat pattern during this series of heating and cooling processes has a significant impact on product yield. The heat pattern is the temperature distribution of the sintered material in the machine length direction and thickness direction of the sintering machine. In particular, ensuring the residence time (high-temperature holding time) at, for example, 1200°C or more, at which ore melts, has a significant impact on yield. Therefore, feature data such as heat patterns that affect yield are accurately estimated, and features such as the high-temperature holding time are calculated from the feature data. Guidance operation quantities, such as the appropriate raw coke ratio, pallet speed, and the like, for controlling the features to have predetermined values can then be indicated to improve the yield.
  • Here, as a conventional method of controlling the heat pattern, Patent Literature (PTL) 1 discloses a method of controlling the position of the burn through point (BTP) to be constant. In the technology in PTL 1, the BTP is the position in the machine length direction at which the temperature of the exhaust gas measured in the wind box at the bottom of the sintering machine is the highest.
  • CITATION LIST Patent Literature
  • PTL 1: JP 2006-307259 A
  • SUMMARY (Technical Problem)
  • Here, it may be difficult to control the aforementioned high-temperature holding time simply by controlling the position of the BTP to be constant. For example, even if the BTP position is constant, an increase in pallet speed reduces the high-temperature holding time. A conventional method of controlling the heat pattern can thus result in variations in the high-temperature holding time.
  • It would be helpful to provide a sintering process state estimation method and sintering process state estimation apparatus that can estimate the state of the sintering process to a high degree of accuracy. It would also be helpful to provide an operation guidance method, a method of manufacturing sintered ore, an operation guidance apparatus, a sintering operation guidance system, a sintering operation guidance server, and a terminal apparatus that can indicate guidance for yield improvement based on the accurately estimated state of the sintering process.
  • (Solution to Problem)
  • A sintering process state estimation method according to an embodiment of the present disclosure includes: calculating an observable process variable using a physical model that takes into account a chemical reaction and a heat transfer phenomenon in a sintering process; calculating a deviation between an estimated value and an actual value of the calculated process variable; modifying an unknown parameter of the physical model so that the calculated deviation is reduced; and calculating feature data of the sintering process based on a modified physical model.
  • An operation guidance method according to an embodiment of the present disclosure includes: calculating a high-temperature holding time of sintered material by using the heat pattern calculated by the sintering process state estimation method according to the aforementioned sintering process state estimation method; and presenting a guidance operation quantity, including at least one of a raw material coke ratio and a pallet speed, to maintain the high-temperature holding time at a predetermined value or higher.
  • A method of manufacturing sintered ore according to an embodiment of the present disclosure includes manufacturing sintered ore using the guidance operation quantity presented by the aforementioned operation guidance method.
  • A sintering process state estimation apparatus according to an embodiment of the present disclosure includes: a memory configured to store a physical model that takes into account a chemical reaction and a heat transfer phenomenon in a sintering process; a process variable calculator configured to calculate an observable process variable using the physical model; a deviation calculator configured to calculate a deviation between an estimated value and an actual value of the calculated process variable; a model parameter adjustor configured to modify an unknown parameter of the physical model so that the calculated deviation is reduced; and a feature data calculator configured to calculate feature data of the sintering process based on a modified physical model.
  • An operation guidance apparatus according to an embodiment of the present disclosure includes: a high-temperature holding time calculator configured to calculate a high-temperature holding time of sintered material by using a heat pattern of sintered material in a sintering machine length direction, the heat pattern being the feature data calculated by the sintering process state estimation apparatus according to the aforementioned sintering process state estimation apparatus; and a guidance operation quantity presentation interface configured to present a guidance operation quantity, including at least one of a raw material coke ratio and a pallet speed, to maintain the high-temperature holding time at a predetermined value or higher.
  • A sintering operation guidance system according to an embodiment of the present disclosure includes a sintering operation guidance server and a terminal apparatus, wherein the sintering operation guidance server includes a performance value acquisition interface configured to acquire a performance value indicating a sintering process operation state; a memory configured to store a physical model that takes into account a chemical reaction and a heat transfer phenomenon in the sintering process; a process variable calculator configured to calculate an observable process variable using the physical model; a deviation calculator configured to calculate a deviation between an estimated value and an actual value of the calculated process variable; a model parameter adjustor configured to modify an unknown parameter of the physical model so that the calculated deviation is reduced; a feature data calculator configured to calculate feature data of the sintering process based on a modified physical model; a high-temperature holding time calculator configured to calculate a high-temperature holding time of sintered material by using a heat pattern of sintered material in a sintering machine length direction, the heat pattern being the feature data; and a guidance operation quantity presentation interface configured to present a guidance operation quantity, including at least one of a raw material coke ratio and a pallet speed, to maintain the high-temperature holding time at a predetermined value or higher, and the terminal apparatus includes a guidance operation quantity acquisition interface configured to acquire the guidance operation quantity presented by the sintering operation guidance server; and a display configured to display the acquired guidance operation quantity.
  • A sintering operation guidance server according to an embodiment of the present disclosure includes: a performance value acquisition interface configured to acquire a performance value indicating a sintering process operation state; a memory configured to store a physical model that takes into account a chemical reaction and a heat transfer phenomenon in the sintering process; a process variable calculator configured to calculate an observable process variable using the physical model; a deviation calculator configured to calculate a deviation between an estimated value and an actual value of the calculated process variable; a model parameter adjustor configured to modify an unknown parameter of the physical model so that the calculated deviation is reduced; a feature data calculator configured to calculate feature data of the sintering process based on a modified physical model; a high-temperature holding time calculator configured to calculate a high-temperature holding time of sintered material by using a heat pattern of sintered material in a sintering machine length direction, the heat pattern being the feature data; and a guidance operation quantity presentation interface configured to present a guidance operation quantity, including at least one of a raw material coke ratio and a pallet speed, to maintain the high-temperature holding time at a predetermined value or higher.
  • A terminal apparatus according to an embodiment of the present disclosure is a terminal apparatus forming part of a sintering operation guidance system together with a sintering operation guidance server, the terminal apparatus including: a guidance operation quantity acquisition interface configured to acquire a guidance operation quantity presented by the sintering operation guidance server; and a display configured to display the acquired guidance operation quantity, wherein the sintering operation guidance server modifies an unknown parameter of a physical model that takes into account a chemical reaction and a heat transfer phenomenon in a sintering process so that a deviation between an estimated value and an actual value of a process variable calculated using the physical model is reduced, and the guidance operation quantity is an operation quantity including at least one of a raw material coke ratio and a pallet speed to maintain a high-temperature holding time of sintered material at a predetermined value or higher, the high-temperature holding time being based on a heat pattern of sintered material in a sintering machine length direction as calculated using the physical model with the modified unknown parameter.
  • (Advantageous Effect)
  • According to the present disclosure, a sintering process state estimation method and sintering process state estimation apparatus that can estimate the state of the sintering process to a high degree of accuracy can be provided. According to the present disclosure, an operation guidance method, a method of manufacturing sintered ore, an operation guidance apparatus, a sintering operation guidance system, a sintering operation guidance server, and a terminal apparatus that can indicate guidance for yield improvement based on the accurately estimated state of the sintering process can also be provided.
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • In the accompanying drawings:
    • FIG. 1 illustrates an overview of the sintering process;
    • FIG. 2 is a diagram illustrating input/output information of the physical model used in the present disclosure;
    • FIG. 3 is a diagram illustrating an example of key process variables calculated by a physical model without modification of unknown parameters;
    • FIG. 4 is a diagram illustrating the response of the process variables when unknown parameters are changed stepwise;
    • FIG. 5 is a diagram illustrating an example of key process variables calculated by a physical model that modifies unknown parameters;
    • FIG. 6 is a diagram illustrating an example of the change over time in unknown parameters;
    • FIG. 7 is a diagram illustrating example configurations of a sintering process state estimation apparatus and an operation guidance apparatus according to an embodiment;
    • FIG. 8 is a flowchart illustrating a sintering process state estimation method according to an embodiment;
    • FIG. 9 is a flowchart illustrating an operation guidance method according to an embodiment; and
    • FIG. 10 is a diagram illustrating an example configuration of a sintering operation guidance system according to an embodiment.
    DETAILED DESCRIPTION
  • A sintering process state estimation method, an operation guidance method, a method of manufacturing sintered ore, a sintering process state estimation apparatus, an operation guidance apparatus, a sintering operation guidance system, a sintering operation guidance server, and a terminal apparatus according to embodiments of the present disclosure are described below with reference to the drawings. The physical model used in the present disclosure is the same as the method described in Reference 1 (Yamaoka et al. ISIJ International, Vol. 45, No. 4, pp. 522) and is formed by a set of partial differential equations that take into account the physical phenomena of the combustion of coke breeze, the thermal decomposition of limestone, and the evaporation of moisture. This model is capable of calculating the state inside a sintering machine. In the present embodiment, the physical model is a two-dimensional unsteady model that can calculate the temperature distribution (heat pattern) of the sintered material and the distribution of the exhaust gas composition in the machine length and thickness directions of the sintering machine. The position of the BTP can also be determined from the calculated heat pattern. Hereafter, the "BTP position" is also referred to simply as the BTP.
  • As illustrated in FIG. 2, the main variables that vary with time among the input variables provided in the physical model are the pallet speed, the exhaust gas flow rate, the raw material bulk density, the raw material moisture ratio, the raw material limestone ratio, and the raw material coke ratio. These input variables can be operating variables or operating factors of the sintering machine. The pallet speed is the speed at which the pallet of the sintering machine illustrated in FIG. 1 moves the sintered material on the pallet. The exhaust gas flow rate is the flow rate per unit time of the exhaust gas from the sintering machine and is regulated by an exhaust fan, for example. The raw material bulk density is the bulk density of the sintering raw material calculated from the layer thickness, the sintering machine width, and the like. The raw material moisture ratio, raw material limestone ratio, and raw material coke ratio are the ratios of moisture, limestone, and coke, respectively, in the sintering raw material. Coke is the main condensation material, and the raw material coke ratio is sometimes referred to as the condensation material ratio.
  • The main output variables of the physical model are BTP and exhaust gas composition. The exhaust gas composition includes the ratios of O2, CO2, and CO. Here, the output variables may include the temperature below the sintering bed. The output variables, which change from moment to moment using the physical model, are calculated. The time interval for this calculation (the time difference between "t + 1" and "t" in the physical model equations described below) is not particularly limited, but is 5 minutes as an example.
  • The physical model can be expressed by the following Equations (1) and (2). x t + 1 = f x t , u t
    Figure imgb0001
    y t = C x t
    Figure imgb0002
  • Here, u(t) is the input variable mentioned above, which can be manipulated by the operator operating the sintering machine, and x(t) is a state variable calculated within the physical model. State variables are, for example, the heat pattern in the sintering machine, the coke reaction rate, and the gas fraction such as CO and CO2. The variable y(t) is the aforementioned output variable (process variable), i.e., the BTP, the O2 ratio and CO2 ratio in the exhaust gas composition, and the partial combustion rate. The variable y(t) can be defined as the key process variable as follows. y t = y 1 t , y 2 t , y 3 t , y 4 t T BTP t , X O 2 t , X CO 2 t , γ CO t T
    Figure imgb0003
  • The partial combustion rate is the value obtained by dividing CO by (CO + CO2) in the exhaust gas (i.e., CO/(CO + CO2)). An increase in the partial combustion rate means that coke gasification (C + CO2 -> 2CO), which is an endothermic reaction, is activated, meaning that the average temperature level in the sintering process is increasing. Here, other key process variables can be included, such as the temperature below the sintering bed.
  • As in conventional practice, the BTP and exhaust gas composition can be calculated using the physical model as is. FIG. 3 is a diagram illustrating an example of key process variables for 30 hours, calculated using the physical model as is. In FIG. 3, the values calculated using the physical model (estimated values) are indicated by solid lines, and the actual values measured at the actual plant (actual sintering machine) are indicated by dashed lines. Here, the BTP is expressed as the distance [m] from the position of the surge hopper in the direction of pallet movement.
  • The average estimation error for each of the key process variables was calculated at 2.4914 [m] for the BTP, 0.0086 for the O2 ratio, 0.0086 for the CO2 ratio, and 0.0169 for the partial combustion rate. Here, the average estimation error is calculated by summing the square of the deviation between the estimated value and the actual values for all of the steps, dividing this sum by the number of steps, and calculating the square root of the quotient. Performing a physical model calculation over an extended time in this way has the problem of introducing non-negligible errors in the estimates (estimation error) with conventional methods. The example in FIG. 3 illustrates 30 hours of data, but to control the sintering process by performing calculations over a longer period of years, the estimation error needs to be reduced.
  • To reduce estimation errors, it is effective to successively adjust the parameters of the reaction rate of the physical model, the boundary conditions, and the like so that the estimated values match the actual values. It is therefore preferable that the calculation be performed after including variable elements in the physical model as one or more unknown parameters. Three correction parameters, i.e., a correction parameter for exhaust gas flow rate, a correction parameter for raw material bulk density, and a correction parameter for raw material coke ratio, were selected as unknown parameters in the present embodiment for reasons explained below. Here, other variable elements such as the raw material moisture ratio, carbon combustion rate, and coke gasification reaction rate could be set as unknown parameters. For example, the carbon combustion rate depends on the temperature of the solid and on the oxygen concentration in the gas, and the proportionality coefficient in this relationship can be an unknown parameter. The unknown parameters need to be selected according to the raw materials used in the target process, equipment configuration, and the like.
  • The reasons for the selection of the unknown parameters (three correction parameters) in the present embodiment are explained below.
  • In the sintering machine, air is sucked from the top of the sintering bed, and the flow rate of the exhaust gas containing CO2, CO, and the like is measured at the bottom of the sintering bed. The measured exhaust gas flow rate includes the gas flow rate of so-called air leakage (air leakage flow rate) that does not pass through the sintering bed but through another gap. The air leakage flow rate is difficult to measure and difficult to input directly into a physical model. Therefore, it seems reasonable to correct the exhaust gas flow rate in the physical model to match the actual value of the key process variable.
  • Assuming that the raw material bulk density inputted in the physical model is ρ [kg/m3], ρ is calculated by Equation (3) below. ρ = V H × W × PS
    Figure imgb0004
  • Here, V [kg/min] is the actual measurable cutting speed of the raw material. H [m] is the layer thickness of the raw material. W [m] is the sintering machine width. PS [m/min] is a value calculated from the pallet speed. Here, the cutting speed of the raw material is a value measured by the cutting apparatus located upstream of the sintering machine. In other words, the charging rate of the raw material actually being charged into the sintering machine is not measured. It is therefore difficult to accurately estimate the raw material bulk density in the sintering machine. Hence, it seems reasonable to correct the raw material bulk density.
  • The raw coke ratio is affected by how, apart from the condensation material (coke) that is charged to the sintering machine, blast furnace dust and other miscellaneous raw materials containing carbon are blended with the fine ore in the raw material yard in advance. Given the large variation in the blend ratio, it seems reasonable to correct the raw material coke ratio (condensation material ratio).
  • Here, FIG. 4 is a diagram illustrating the response of the process variables when unknown parameters are changed stepwise. FIG. 4 was obtained by changing the aforementioned three correction parameters stepwise after the physical model was continuously subjected to certain operating conditions to reach a steady state.
  • First, when the exhaust gas flow rate was increased by 10%, the BTP shortened, the O2 ratio increased, the CO2 ratio decreased, and the partial combustion rate remained nearly unchanged. When the raw material bulk density was increased by 10%, the BTP lengthened, the O2 ratio decreased, the CO2 ratio increased, and the partial combustion rate remained nearly unchanged. When the raw material coke ratio was increased by 10%, the BTP remained nearly unchanged, the O2 ratio decreased, the CO2 ratio increased slightly, and the partial combustion rate increased.
  • Using the step responses to the unknown parameters obtained as described above, the parameters are modified by steps (a) through (f) below so that the BTP, the O2 ratio, the CO2 ratio, and the partial combustion rate match. The algorithm described below is called Moving Horizon Estimation (MHE), but other state estimation methods such as a particle filter and a Kalman filter may also be used.
  • First, as step (a), the state variables and key process variables for the past A steps are calculated by Equations (4) and (5) below. x t k + 1 = f x t k , u t k
    Figure imgb0005
    y t k + 1 = C x t k + 1
    Figure imgb0006
  • Here, k varies between A and 1. In addition, actual values are used as input variables.
  • As step (b), x(t - A + 1) is stored for use as the initial condition for the iterative calculation.
  • As step (c), the degree of deviation is calculated by Equation (6) below. e t = y act t y cal t
    Figure imgb0007
  • Here, yact is the actual value, and ycal is the estimated value.
  • As step (d), the modification amounts Δα, Δβ and Δγ of the unknown parameters are calculated to minimize an evaluation function that superposes the deviation and the above-described step responses of the key process variables for each of the unknown parameters, as illustrated in Equation (7) below. The unknown parameters α, β, and γ in Equation (7) respectively correspond to the correction parameter for exhaust gas flow rate, the correction parameter for raw material bulk density, and the correction parameter for raw material coke ratio. A smaller evaluation function corresponds to a smaller deviation. Here, a term is added to the evaluation function to ensure that the unknown parameters are not significantly distant from "1" (see FIG. 6). min Δ α , Δ β , Δ γ q = 1 4 n = 0 A e q t n R q α n Δ α R q β n Δβ R q γ n Δγ 2 + α + Δ α 1 2 + β + Δ β 1 2 + γ + Δ γ 1 2
    Figure imgb0008
  • Here, q identifies the key process variable. In the present embodiment, q = 1, 2, 3, and 4 represent the BTP, the O2 ratio, the CO2 ratio, and the partial combustion rate, respectively. Rq p(s) means the value of the response at s, which is a time step in the step response of q, the key process variable, with respect to p, the unknown parameter.
  • As step (e), the unknown parameters are modified as in Equations (8) through (10) below. α = α + Δ α
    Figure imgb0009
    β = β + Δ β
    Figure imgb0010
    γ = γ + Δ γ
    Figure imgb0011
  • As step (f), the process updates t in the time step to t + 1 and returns to step (a). The modification of unknown parameters is thus performed by sequential arithmetic operations.
  • In the present embodiment, MHE is performed to modify the unknown parameters of the physical model. FIG. 5 is a diagram illustrating an example of key process variables calculated by a physical model that modifies unknown parameters. FIG. 6 is a diagram illustrating an example of the change over time in unknown parameters corresponding to FIG. 5. The average estimation error for each of the key process variables was calculated at 0.9961 [m] for the BTP, 0.0044 for the O2 ratio, 0.0047 for the CO2 ratio, and 0.0064 for the partial combustion rate. In other words, it is clear that modification of the unknown parameters using MHE results in a smaller estimation error as compared to the case in FIG. 3.
  • Here, it suffices for A in Equation (7) to be determined so that the equivalent of the time required from the input side to the exit side of sintering, for example, can be evaluated. Specifically, 30 to 60 minutes is sufficient. In the example in FIG. 5, the time step width is 5 minutes, A is 8, and the evaluation time is 40 minutes.
  • The sintering process state estimation apparatus according to the present embodiment (detailed provided below) can estimate the BTP and exhaust gas composition with high accuracy by performing the aforementioned modification of the unknown parameters. Highly accurate estimation using such a physical model also improves the estimation accuracy for the calculation of the high-temperature holding time of the sintered material. The high-temperature holding time is the time during which the temperature of the sintered material is held at or above a threshold (such as 1200°C) at which improvement in yield is affected.
  • In a case in which the calculated high-temperature holding time of the sintered material falls below a predetermined value (such as 3 minutes), the operation guidance apparatus (details provided below) can provide guidance to increase the temperature by increasing the raw material coke ratio, for example, so as to ensure the high-temperature holding time. The operation guidance apparatus may also provide guidance to ensure the high-temperature holding time by reducing the pallet speed. It is expected that the operation guidance apparatus will achieve the effect of improved yield by presenting the operator with information (guidance operation quantities) that leads to appropriate action.
  • FIG. 7 is a diagram illustrating example configurations of a sintering process state estimation apparatus 10 and an operation guidance apparatus 20 according to an embodiment. As illustrated in FIG. 7, the sintering process state estimation apparatus 10 includes a memory 11, a process variable calculator 12, a deviation calculator 13, a model parameter adjustor 14, and a feature data calculator 15. The operation guidance apparatus 20 includes a memory 21, a high-temperature holding time calculator 22, and a guidance operation quantity presentation interface 23. The sintering process state estimation apparatus 10 acquires actual values (also referred to as measured values), which are various measurements from sensors and the like installed in the sintering machine, and performs calculations using the aforementioned physical model. The operation guidance apparatus 20 acquires the feature data for the sintering process as calculated by the sintering process state estimation apparatus 10, determines the guidance operation quantities, and displays guidance for the operation of the sintering machine on the display 30. In the present embodiment, the feature data is the heat pattern of the sintered material in the sintering machine length direction. In a case in which the high-temperature holding time of the sintered material falls below a predetermined value (such as 3 minutes), the operation guidance apparatus 20 displays the guidance operation quantities on the display 30 as guidance to ensure the high-temperature holding time. The guidance operation quantities can be at least one operation quantity (quantity to be adjusted) among the raw material coke ratio and the pallet speed, which are required to ensure the high-temperature holding time. The display 30 may be a liquid crystal display (LCD), an organic electroluminescence panel (OLED panel), or other display apparatus.
  • First, the components of the sintering process state estimation apparatus 10 are described. The memory 11 stores a physical model that takes into account chemical reactions and heat transfer phenomena in the sintering process. The memory 11 also stores programs and data related to sintering process state estimation. The memory 11 may include any memory device, such as semiconductor memory devices, optical memory devices, and magnetic memory devices. Semiconductor memory devices may, for example, include semiconductor memories. The memory 11 may include a plurality of types of memory devices.
  • The process variable calculator 12 calculates observable process variables using the physical model. In the present embodiment, the process variables are the BTP, the O2 ratio and CO2 ratio in the exhaust gas composition, and the partial combustion rate.
  • The deviation calculator 13 calculates the deviation between the estimated values and the actual values, in an actual plant, of the calculated process variables.
  • The model parameter adjustor 14 modifies unknown parameters of the physical model so that the calculated deviation is reduced.
  • The feature data calculator 15 calculates feature data of the sintering process based on the modified physical model. As described above, in the present embodiment, the feature data is the heat pattern of the sintered material in the sintering machine length direction.
  • The process variable calculator 12, the deviation calculator 13, and the model parameter adjustor 14 perform operations according to the aforementioned steps (a) through (f) to modify the unknown parameters of the physical model. In the present embodiment, the unknown parameters are modified by iterative calculations performed while updating time steps, using the aforementioned evaluation function that includes the deviation, the process variables, and the unknown parameters. The feature data calculator 15 calculates the heat patterns using the modified physical model and outputs the heat pattern as feature data to the operation guidance apparatus 20.
  • Next, the components of the operation guidance apparatus 20 are described. The memory 21 stores programs and data related to operation guidance. The memory 21 may include any memory device, such as semiconductor memory devices, optical memory devices, and magnetic memory devices. Semiconductor memory devices may, for example, include semiconductor memories. The memory 21 may include a plurality of types of memory devices.
  • The high-temperature holding time calculator 22 calculates the high-temperature holding time of the sintered material by using the heat pattern calculated by the sintering process state estimation apparatus 10.
  • If the calculated high-temperature holding time of the sintered material is less than a predetermined value, the guidance operation quantity presentation interface 23 presents the guidance operation quantity on the display 30 to maintain the high-temperature holding time at or above the predetermined value. In the present embodiment, the guidance operation quantity includes at least one of the raw material coke ratio and the pallet speed. The guidance operation quantity presentation interface 23 may, for example, display a 10% increase in the raw material coke ratio on the display 30 as the guidance operation quantity. The guidance operation quantity presentation interface 23 may, for example, display a 5% decrease in pallet speed on the display 30 as the guidance operation quantity. Here, the guidance operation quantity presentation interface 23 may have the sintering process state estimation apparatus 10 calculate the amount of increase in the raw material coke ratio and the amount of decrease in pallet speed using the physical model. In other words, the guidance operation quantity presentation interface 23 may have the sintering process state estimation apparatus 10 perform a simulation using the physical model to determine the guidance operation quantity to be presented.
  • The operator may change the operating conditions of the sintering machine based on the guidance operation quantity displayed on the display 30. Such operation guidance for the sintering machine can be implemented as part of a method of manufacturing sintered ore.
  • Here, the sintering process state estimation apparatus 10 and the operation guidance apparatus 20 may be separate apparatuses or integrated into one apparatus. In the case of an integrated apparatus, the memory 11 and the memory 21 may be realized by the same memory device.
  • The sintering process state estimation apparatus 10 and the operation guidance apparatus 20 may be realized by a computer, such as a process computer that controls the operation of a sintering machine or the production of sintered ore, for example. The computer includes, for example, a memory and hard disk drive (memory device), a CPU (processing unit), and a display device such as a display. An operating system (OS) and application programs for carrying out various processes can be stored on the hard disk drive and are read from the hard disk drive into memory when executed by the CPU. Data during processing is stored in memory, and if necessary, on the HDD. Various functions are realized through the organic collaboration of hardware (such as the CPU and memory), the OS, and necessary application programs. The memory 11 and the memory 21 may, for example, be realized on a memory device. The process variable calculator 12, the deviation calculator 13, the model parameter adjustor 14, the feature data calculator 15, the high-temperature holding time calculator 22, and the guidance operation quantity presentation interface 23 may be realized by the CPU, for example. The display 30 may, for example, be realized by a display device.
  • FIG. 8 is a flowchart illustrating a sintering process state estimation method according to an embodiment. The sintering process state estimation apparatus 10 outputs the feature data of the sintering process according to the flowchart illustrated in FIG. 8. The state estimation method illustrated in FIG. 8 may be performed as part of a method of manufacturing sintered ore.
  • The process variable calculator 12 calculates observable process variables using the physical model (step S1, process variable calculation step). The deviation calculator 13 calculates the deviation between the estimated values and the actual values of the calculated process variables (step S2, deviation calculation step). The model parameter adjustor 14 modifies unknown parameters of the physical model so that the deviation is reduced (step S3, model parameter adjustment step). The feature data calculator 15 then calculates feature data based on the modified physical model (step S4, feature data calculation step).
  • FIG. 9 is a flowchart illustrating an operation guidance method according to an embodiment. The operation guidance apparatus 20 presents the guidance operation quantity according to the flowchart illustrated in FIG. 9. The operation guidance method illustrated in FIG. 9 may be performed as part of a method of manufacturing sintered ore.
  • The high-temperature holding time calculator 22 calculates the high-temperature holding time of the sintered material using the heat pattern calculated as the aforementioned feature data (step S11, high-temperature holding time calculation step). The guidance operation quantity presentation interface 23 presents the guidance operation quantity on the display 30 to maintain the high-temperature holding time at or above the predetermined value (step S12, guidance operation quantity presentation step).
  • FIG. 10 is a diagram illustrating a configuration of a sintering operation guidance system according to an embodiment. The sintering operation guidance system may be configured by a sintering operation guidance server 40 and a terminal apparatus 50, as illustrated by the dashed lines in FIG. 10, for example. The sintering operation guidance server 40 has the functions of the sintering process state estimation apparatus 10 and the operation guidance apparatus 20 and may, for example, be realized by a computer. The terminal apparatus 50 functions at least as a display 30 and may, for example, be realized by a portable terminal apparatus, such as a tablet, or a computer. The sintering operation guidance server 40 and the terminal apparatus 50 can transmit and receive data to and from each other via a network, such as the Internet. The sintering operation guidance server 40 and the terminal apparatus 50 may be in the same location (for example, within the same plant) or may be physically separated. The sintering operation guidance system is not limited to the above configuration and may, for example, further include an operation data server 60 that aggregates sintering machine operation data (for example, the actual values and operation parameters indicating operation status). The operation data server 60 is capable of communicating with the sintering operation guidance server 40 and the terminal apparatus 50 via a network and may, for example, be realized by a computer that manages the manufacturing of sintered ore. The operation data server 60 may be in the same location as the sintering operation guidance server 40 or the terminal apparatus 50 or may be physically separated. Hereinafter, components and the like will be described using the example of a sintering operation guidance system configured to include the sintering operation guidance server 40 and the terminal apparatus 50.
  • The sintering operation guidance server 40 acquires performance values indicating the sintering process operating state, performs calculations using the aforementioned physical model, and calculates the high-temperature holding time of the sintered material using the heat pattern as the calculated feature data. The sintering operation guidance server 40 causes the terminal apparatus 50, which functions as the display 30, to display a guidance operation quantity, including at least one of the raw material coke ratio and the pallet speed, to maintain the high-temperature holding time at a predetermined value or higher. The sintering operation guidance server 40 includes the components of the sintering process state estimation apparatus 10 and the components of the operation guidance apparatus 20 described with reference to FIG. 7. In greater detail, the sintering operation guidance server 40 includes a memory, a process variable calculator 12, a deviation calculator 13, a model parameter adjustor 14, a feature data calculator 15, a high-temperature holding time calculator 22, and a guidance operation quantity presentation interface 23. The memory stores a physical model that takes into account chemical reactions and heat transfer phenomena in the sintering process, programs and data related to sintering process state estimation, programs and data related to operation guidance, and the like. The process variable calculator 12, the deviation calculator 13, the model parameter adjustor 14, the feature data calculator 15, the high-temperature holding time calculator 22, and the guidance operation quantity presentation interface 23 are the same as in the above explanation. The sintering operation guidance server 40 may also include a performance value acquisition interface to acquire performance values indicating the sintering process operation state. The performance value acquisition interface may acquire the performance values directly from sensors provided in the sintering machine, from the sintering process computer, or the like, or may acquire the performance values via the operation data server 60.
  • The terminal apparatus 50 forms a sintering operation guidance system, together with the sintering operation guidance server 40, and displays the guidance operation quantity. The terminal apparatus 50 includes at least a display 30. The display 30 is the same as described above. The terminal apparatus 50 may include a guidance operation quantity acquisition interface to acquire the guidance operation quantity presented by the sintering operation guidance server 40.
  • As described above, the sintering process state estimation method and sintering process state estimation apparatus 10 according to the present embodiment can, with the aforementioned configuration, estimate the state of the sintering process to a high degree of accuracy. The operation guidance method, the method of manufacturing sintered ore, the operation guidance apparatus 20, the sintering operation guidance system, the sintering operation guidance server 40, and the terminal apparatus 50 according to the present embodiment can indicate guidance for yield improvement based on the accurately estimated state of the sintering process. For example, the operator can change the operating conditions based on the indicated guidance operation quantity to ensure the high-temperature holding time of the sintered material at an early stage and thereby improve the yield.
  • While embodiments of the present disclosure have been described based on the drawings and examples, it should be noted that various changes and modifications may be made by those skilled in the art based on the present disclosure. Accordingly, such changes and modifications are included within the scope of the present disclosure. For example, the functions and the like included in each component, step, or the like can be rearranged in a logically consistent manner. Components, steps, or the like may also be combined into one or divided. An embodiment of the present disclosure may also be implemented as a program executed by a processor provided in an apparatus or as a storage medium with the program recorded thereon. These are also encompassed within the scope of the present disclosure.
  • The configurations of the sintering process state estimation apparatus 10 and the operation guidance apparatus 20 illustrated in FIG. 7 are only examples. The sintering process state estimation apparatus 10 and the operation guidance apparatus 20 need not include all of the components illustrated in FIG. 7. The sintering process state estimation apparatus 10 and the operation guidance apparatus 20 may include components other than those illustrated in FIG. 7. For example, the operation guidance apparatus 20 may further include the display 30.
  • The unknown parameters in the above embodiment include three correction parameters, but it suffices for at least one parameter to be included. In other words, if at least one unknown parameter of the physical model is modified, the estimation error can be reduced.
  • REFERENCE SIGNS LIST
  • 10
    Sintering process state estimation apparatus
    11
    Memory
    12
    Process variable calculator
    13
    Deviation calculator
    14
    Model parameter adjustor
    15
    Feature data calculator
    20
    Operation guidance apparatus
    21
    Memory
    22
    High-temperature holding time calculator
    23
    Guidance operation quantity presentation interface
    30
    Display

Claims (12)

  1. A sintering process state estimation method comprising:
    calculating an observable process variable using a physical model that takes into account a chemical reaction and a heat transfer phenomenon in a sintering process;
    calculating a deviation between an estimated value and an actual value of the calculated process variable;
    modifying an unknown parameter of the physical model so that the calculated deviation is reduced; and
    calculating feature data of the sintering process based on a modified physical model.
  2. The sintering process state estimation method according to claim 1, wherein the process variable includes at least one of burn through point, exhaust gas composition, and temperature below a sintering bed.
  3. The sintering process state estimation method according to claim 1 or 2, wherein the unknown parameter includes at least one correction parameter from among an exhaust gas flow rate, a raw material bulk density, a raw material moisture ratio, a raw material coke ratio, a carbon combustion rate, and a coke gasification reaction rate.
  4. The sintering process state estimation method according to any one of claims 1 to 3, wherein the unknown parameter is modified by an iterative calculation performed while updating a time step, using an evaluation function that includes the deviation, the process variable, and the unknown parameter.
  5. The sintering process state estimation method according to any one of claims 1 to 4, wherein the feature data is a heat pattern of sintered material in a sintering machine length direction.
  6. An operation guidance method comprising:
    calculating a high-temperature holding time of sintered material by using the heat pattern calculated by the sintering process state estimation method according to claim 5; and
    presenting a guidance operation quantity, including at least one of a raw material coke ratio and a pallet speed, to maintain the high-temperature holding time at a predetermined value or higher.
  7. A method of manufacturing sintered ore, the method comprising manufacturing sintered ore using the guidance operation quantity presented by the operation guidance method according to claim 6.
  8. A sintering process state estimation apparatus comprising:
    a memory configured to store a physical model that takes into account a chemical reaction and a heat transfer phenomenon in a sintering process;
    a process variable calculator configured to calculate an observable process variable using the physical model;
    a deviation calculator configured to calculate a deviation between an estimated value and an actual value of the calculated process variable;
    a model parameter adjustor configured to modify an unknown parameter of the physical model so that the calculated deviation is reduced; and
    a feature data calculator configured to calculate feature data of the sintering process based on a modified physical model.
  9. An operation guidance apparatus comprising:
    a high-temperature holding time calculator configured to calculate a high-temperature holding time of sintered material by using a heat pattern of sintered material in a sintering machine length direction, the heat pattern being the feature data calculated by the sintering process state estimation apparatus according to claim 8; and
    a guidance operation quantity presentation interface configured to present a guidance operation quantity, including at least one of a raw material coke ratio and a pallet speed, to maintain the high-temperature holding time at a predetermined value or higher.
  10. A sintering operation guidance system comprising a sintering operation guidance server and a terminal apparatus, wherein
    the sintering operation guidance server comprises
    a performance value acquisition interface configured to acquire a performance value indicating a sintering process operation state;
    a memory configured to store a physical model that takes into account a chemical reaction and a heat transfer phenomenon in the sintering process;
    a process variable calculator configured to calculate an observable process variable using the physical model;
    a deviation calculator configured to calculate a deviation between an estimated value and an actual value of the calculated process variable;
    a model parameter adjustor configured to modify an unknown parameter of the physical model so that the calculated deviation is reduced;
    a feature data calculator configured to calculate feature data of the sintering process based on a modified physical model;
    a high-temperature holding time calculator configured to calculate a high-temperature holding time of sintered material by using a heat pattern of sintered material in a sintering machine length direction, the heat pattern being the feature data; and
    a guidance operation quantity presentation interface configured to present a guidance operation quantity, including at least one of a raw material coke ratio and a pallet speed, to maintain the high-temperature holding time at a predetermined value or higher, and
    the terminal apparatus comprises
    a guidance operation quantity acquisition interface configured to acquire the guidance operation quantity presented by the sintering operation guidance server; and
    a display configured to display the acquired guidance operation quantity.
  11. A sintering operation guidance server comprising:
    a performance value acquisition interface configured to acquire a performance value indicating a sintering process operation state;
    a memory configured to store a physical model that takes into account a chemical reaction and a heat transfer phenomenon in the sintering process;
    a process variable calculator configured to calculate an observable process variable using the physical model;
    a deviation calculator configured to calculate a deviation between an estimated value and an actual value of the calculated process variable;
    a model parameter adjustor configured to modify an unknown parameter of the physical model so that the calculated deviation is reduced;
    a feature data calculator configured to calculate feature data of the sintering process based on a modified physical model;
    a high-temperature holding time calculator configured to calculate a high-temperature holding time of sintered material by using a heat pattern of sintered material in a sintering machine length direction, the heat pattern being the feature data; and
    a guidance operation quantity presentation interface configured to present a guidance operation quantity, including at least one of a raw material coke ratio and a pallet speed, to maintain the high-temperature holding time at a predetermined value or higher.
  12. A terminal apparatus forming part of a sintering operation guidance system together with a sintering operation guidance server, the terminal apparatus comprising:
    a guidance operation quantity acquisition interface configured to acquire a guidance operation quantity presented by the sintering operation guidance server; and
    a display configured to display the acquired guidance operation quantity, wherein
    the sintering operation guidance server modifies an unknown parameter of a physical model that takes into account a chemical reaction and a heat transfer phenomenon in a sintering process so that a deviation between an estimated value and an actual value of a process variable calculated using the physical model is reduced, and
    the guidance operation quantity is an operation quantity including at least one of a raw material coke ratio and a pallet speed to maintain a high-temperature holding time of sintered material at a predetermined value or higher, the high-temperature holding time being based on a heat pattern of sintered material in a sintering machine length direction as calculated using the physical model with the modified unknown parameter.
EP22841997.4A 2021-07-12 2022-07-04 State estimation method for sintering process, operation guidance method, method for producing sintered ore, state estimation device for sintering process, operation guidance device, sintering operation guidance system, sintering operation guidance server, and terminal device Pending EP4345178A1 (en)

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JPS6223940A (en) * 1985-07-24 1987-01-31 Kobe Steel Ltd Method for controlling sintering in continuous annealing machine
JPS6223939A (en) * 1985-07-24 1987-01-31 Kobe Steel Ltd Method for controlling heat pattern in continuous sintering machine
JP4826129B2 (en) 2005-04-27 2011-11-30 Jfeスチール株式会社 Method for producing sintered ore
JP5544784B2 (en) * 2009-08-17 2014-07-09 Jfeスチール株式会社 Sintering machine
JP5729251B2 (en) * 2011-10-11 2015-06-03 新日鐵住金株式会社 Sintering process operation monitoring device, sintering process operation monitoring method, and program

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