Sintering process state estimation method, operation guidance method, sinter ore manufacturing method, sintering process state estimation device, operation guidance device, sintering operation guidance system, sintering operation guidance server and terminal device

Abstract

To provide an estimation method and estimation device capable of estimating a state of a sintering process with high accuracy.SOLUTION: A method for estimating a state of a sintering process includes: a process variable calculation step S1 in which observable process variables are calculated using a physical model that takes into account chemical reactions and heat transfer phenomena in the sintering process; a deviation degree calculation step S2 that calculates the deviation degree between an estimation value of the calculated process variable and an actual value; a model parameter adjustment step S3 that corrects unknown parameters of the physical model so that the calculated deviation degree becomes smaller; and a feature data calculation step S4 of calculating feature data of the sintering process based on the corrected physical model, and the unknown parameter is corrected by iterative calculation that is performed while innovating a time step, with an evaluation function that counts an influence on the estimated value of the process variable accompanying correction of the degree of deviation and the unknown parameter.SELECTED DRAWING: Figure 8

Description

[Technical Field]

[0001] The present disclosure relates to a sintering process state estimation method, an operation guidance method, a sinter ore manufacturing method, a sintering process state estimation device, an operation guidance device, a sintering operation guidance system, a sintering operation guidance server, and a terminal device. [Background technology]

[0002] In the steel industry, the quality of iron ore has declined over many years of mining. As a result, the proportion of fine ore with a high fineness obtained through ore dressing at the mine site is increasing, and the sintering process, in which the fine ore is solidified to produce sintered ore before being charged into the blast furnace, is becoming increasingly important. To ensure the permeability of the blast furnace, sintered ore below a specified particle size is not charged into the blast furnace, but is instead fired again in the sintering machine as return ore. Improving the yield, which is the proportion of ore above a specified particle size, is directly linked to the productivity of the sintering machine, and there is a strong demand for improving the yield.

[0003] Figure 1 shows an overview of the sintering process. Sinter raw materials (quasi-particles), a mixture of fine ore, coke powder, and limestone, are charged into the sintering machine through a surge hopper at the inlet side. The sinter raw materials melt within the sintering machine due to the heat of combustion of the coke, causing the quasi-particles to fuse together. The sinter raw materials are then cooled by air drawn in from above and discharged. The heat pattern during this heating and cooling process significantly affects product yield. The heat pattern is the temperature distribution of the sinter material along the length and thickness of the sintering machine. Ensuring a high-temperature retention time (high-temperature retention time) above 1200°C, for example, at which the ore melts, has a significant impact on yield. Therefore, accurate estimation of characteristic data, such as the heat pattern, which affects yield, and calculation of characteristic quantities, such as high-temperature retention time, are required. Then, guidance control variables, such as the coke ratio and pallet speed, are provided to control the characteristic quantities to the desired values, thereby improving yield.

[0004] As a conventional method for controlling the heat pattern, Patent Document 1 discloses a method for controlling the position of the BTP (Burn-through point) to a constant value. In the technology of Patent Document 1, the BTP is defined as the position in the machine longitudinal direction where the temperature of the exhaust gas measured in the wind box at the bottom of the sintering machine is the highest. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Laid-Open No. 2006-307259 Summary of the Invention [Problem to be solved by the invention]

[0006] However, simply controlling the BTP position to a constant can make it difficult to control the high-temperature holding time. For example, even if the BTP position is constant, increasing the pallet speed shortens the high-temperature holding time. Thus, conventional methods of controlling the heat pattern can result in variations in the high-temperature holding time.

[0007] The present disclosure has been made to solve the above problems and aims to provide a sintering process state estimation method and a sintering process state estimation device that can estimate the state of the sintering process with high accuracy, and also to provide an operation guidance method, a sinter ore manufacturing method, an operation guidance device, a sintering operation guidance system, a sintering operation guidance server, and a terminal device that can provide guidance for improving yield based on the sintering process state estimated with high accuracy. [Means for solving the problem]

[0008] A method for estimating a state of a sintering process according to an embodiment of the present disclosure includes: a process variable calculation step of calculating observable process variables using a physical model that takes into account chemical reactions and heat transfer phenomena in the sintering process; a deviation calculation step of calculating a deviation between the calculated estimated value and the actual value of the process variable; a model parameter adjustment step of correcting unknown parameters of the physical model so that the calculated deviation becomes smaller; and a characteristic data calculation step of calculating characteristic data of the sintering process based on the corrected physical model.

[0009] An operation guidance method according to an embodiment of the present disclosure includes: The characteristic data is a heat pattern of the sintered material in the longitudinal direction of the sintering machine, a high-temperature holding time calculation step of calculating a high-temperature holding time of the sintered material using the heat pattern calculated by the above-mentioned sintering process state estimation method; and a guidance operation variable presentation step of presenting a guidance operation variable including at least one of a raw coke ratio and a pallet speed in order to maintain the high-temperature holding time at a predetermined value or more.

[0010] A method for producing sintered ore according to an embodiment of the present disclosure includes: Sintered ore is produced using the guidance operation amount presented by the above-described operation guidance method.

[0011] A state estimation device for a sintering process according to an embodiment of the present disclosure includes: a storage unit that stores a physical model that takes into account chemical reactions and heat transfer phenomena in the sintering process; a process variable calculation unit that calculates an observable process variable using the physical model; a deviation calculation unit that calculates a deviation between the calculated estimated value and the actual value of the process variable; a model parameter adjustment unit that corrects unknown parameters of the physical model so as to reduce the calculated deviation; and a characteristic data calculation unit that calculates characteristic data of the sintering process based on the corrected physical model.

[0012] An operation guidance device according to an embodiment of the present disclosure includes: a high-temperature holding time calculation unit that calculates a high-temperature holding time of the sintered material using the heat pattern calculated by the sintering process state estimation device, wherein the characteristic data is a heat pattern of the sintered material in the longitudinal direction of the sintering machine; and a guidance operation amount presentation unit that presents guidance operation amounts including at least one of the raw coke ratio and the pallet speed in order to maintain the high-temperature holding time at a predetermined value or more.

[0013] A sintering operation guidance system according to an embodiment of the present disclosure comprises: A sintering operation guidance server and a terminal device are provided, The sintering operation guidance server an actual value acquisition unit that acquires actual values indicating the operating status of the sintering process; a storage unit that stores a physical model that takes into account chemical reactions and heat transfer phenomena in the sintering process; a process variable calculation unit that calculates an observable process variable using the physical model; a deviation calculation unit that calculates a deviation between the calculated estimated value and the actual value of the process variable; a model parameter adjustment unit that corrects unknown parameters of the physical model so as to reduce the calculated deviation; a characteristic data calculation unit that calculates characteristic data of the sintering process based on the corrected physical model; The characteristic data is a heat pattern of the sintered material in the longitudinal direction of the sintering machine, and a high-temperature holding time calculation unit calculates a high-temperature holding time of the sintered material using the heat pattern; a guidance operation amount presentation unit that presents a guidance operation amount including at least one of a raw coke ratio and a pallet speed in order to maintain the high-temperature holding time at a predetermined value or more, The terminal device a guidance operation amount acquisition unit that acquires the guidance operation amount presented by the sintering operation guidance server; and a display unit that displays the obtained guidance operation amount.

[0014] The sintering operation guidance server according to an embodiment of the present disclosure includes: an actual value acquisition unit that acquires actual values indicating the operating status of the sintering process; a storage unit that stores a physical model that takes into account chemical reactions and heat transfer phenomena in the sintering process; a process variable calculation unit that calculates an observable process variable using the physical model; a deviation calculation unit that calculates a deviation between the calculated estimated value and the actual value of the process variable; a model parameter adjustment unit that corrects unknown parameters of the physical model so as to reduce the calculated deviation; a characteristic data calculation unit that calculates characteristic data of the sintering process based on the corrected physical model; The characteristic data is a heat pattern of the sintered material in the longitudinal direction of the sintering machine, and a high-temperature holding time calculation unit calculates a high-temperature holding time of the sintered material using the heat pattern; and a guidance operation amount presentation unit that presents guidance operation amounts including at least one of the raw coke ratio and the pallet speed in order to maintain the high-temperature holding time at a predetermined value or more.

[0015] A terminal device according to an embodiment of the present disclosure includes: A terminal device constituting a sintering operation guidance system together with a sintering operation guidance server, a guidance operation amount acquisition unit that acquires a guidance operation amount presented by the sintering operation guidance server; a display unit that displays the acquired guidance operation amount, the sintering operation guidance server corrects unknown parameters of the physical model so as to reduce a discrepancy between an estimated value of a process variable calculated using the physical model taking into account a chemical reaction and a heat transfer phenomenon in the sintering process and an actual value; The guidance manipulated variable is a manipulated variable including at least one of the raw coke ratio and the pallet speed, for maintaining the high-temperature holding time of the sintered material at a predetermined value or more based on the heat pattern of the sintered material in the longitudinal direction of the sintering machine calculated using the physical model in which the unknown parameters have been corrected. [Effects of the Invention]

[0016] According to the present disclosure, it is possible to provide a sintering process state estimation method and a sintering process state estimation device that can estimate the state of the sintering process with high accuracy. Also, according to the present disclosure, it is possible to provide an operation guidance method, a sintered ore manufacturing method, an operation guidance device, a sintering operation guidance system, a sintering operation guidance server, and a terminal device that can provide guidance for improving yield based on the sintering process state estimated with high accuracy. [Brief explanation of the drawings]

[0017] [Figure 1] FIG. 1 is a diagram showing an outline of the sintering process. [Figure 2] FIG. 2 is a diagram showing input / output information of a physical model used in the present disclosure. [Figure 3] FIG. 3 is a diagram showing an example of main process variables calculated by a physical model without modifying unknown parameters. [Figure 4] FIG. 4 is a diagram showing the response of the process variable when the unknown parameter is changed stepwise. [Figure 5] FIG. 5 is a diagram showing an example of main process variables calculated by a physical model that corrects unknown parameters. [Figure 6] FIG. 6 is a diagram showing an example of the transition of unknown parameters. [Figure 7] FIG. 7 is a diagram showing an example of the configuration of a state estimation device and an operation guidance device for a sintering process according to an embodiment. [Figure 8] FIG. 8 is a flowchart illustrating a method for estimating the state of a sintering process according to one embodiment. [Figure 9]FIG. 9 is a flowchart illustrating an operation guidance method according to one embodiment. [Figure 10] FIG. 10 is a diagram showing an example of the configuration of a sintering operation guidance system according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0018] Hereinafter, with reference to the drawings, a sintering process state estimation method, an operation guidance method, a sinter ore manufacturing method, a sintering process state estimation device, an operation guidance device, a sintering operation guidance system, a sintering operation guidance server, and a terminal device according to an embodiment of the present disclosure will be described. The physical model used in this disclosure is a model capable of calculating the state inside a sintering machine, which is composed of a group of partial differential equations that take into account the physical phenomena of coke breeze combustion, limestone pyrolysis, and water evaporation, similar to the method described in Reference 1 (Yamaoka et al., ISIJ International, Vol. 45, No. 4, pp. 522). In this embodiment, this physical model is a two-dimensional unsteady model capable of calculating the temperature distribution (heat pattern) of the sintered material in the machine length direction and thickness direction and the distribution of exhaust gas composition. Furthermore, the position of the BTP can be determined from the calculated heat pattern. Hereinafter, the "position of the BTP" may be simply referred to as the BTP.

[0019] As shown in Figure 2, the main time-varying input variables given to the physical model are pallet speed, exhaust gas flow rate, raw material bulk density, raw material moisture ratio, raw material limestone ratio, and raw material coke ratio. These input variables can be operational variables or operating factors of the sinter machine. Pallet speed is the speed at which the sinter raw material carried on the pallet of the sinter machine illustrated in Figure 1 moves. Exhaust gas flow rate is the flow rate per unit time of the exhaust gas from the sinter machine and is adjusted, for example, by an exhaust fan. Raw material bulk density is the bulk density of the sinter raw material calculated from the layer thickness, sinter machine width, etc. Raw material moisture ratio, raw material limestone ratio, and raw material coke ratio are the ratios of moisture, limestone, and coke in the sinter raw material, respectively. Here, coke is the main coking agent, and the raw material coke ratio is sometimes referred to as the coking agent ratio.

[0020] The main output variables of the physical model are the BTP and exhaust gas composition. The exhaust gas composition includes the proportions of O2, CO2, and CO. Here, the output variables may include the temperature under the sintering bed. The output variables that change from moment to moment are calculated using the physical model. The time interval for this calculation (the time difference between "t+1" and "t" in the equation for the physical model described below) is not particularly limited, but is 5 minutes as an example.

[0021] The physical model can be expressed by the following equations (1) and (2).

[0022]

number

[0023] Here, u(t) is the input variable mentioned above, which can be manipulated by the operator who operates the sintering machine. x(t) is a state variable calculated within the physical model. State variables include, for example, the heat pattern within the sintering machine, the coke reaction rate, and the gas fractions of CO and CO2. y(t) is the output variable (process variable) mentioned above, which includes BTP, the O2 fraction, CO2 fraction, and partial combustion rate in the exhaust gas composition. y(t) can be defined as the main process variable as follows:

[0024]

number

[0025] Here, the partial combustion rate is the value obtained by dividing the CO in the exhaust gas by (CO + CO2) (i.e., CO / (CO + CO2)). An increase in the partial combustion rate means that the endothermic coke gasification reaction (C + CO2 → 2CO) is more active, which means that the average temperature level in the sintering process is increasing. Other key process variables can also be included, such as the temperature below the sintering bed.

[0026] As in the past, it is possible to calculate BTP and exhaust gas composition using a physical model as is. Figure 3 is a diagram showing an example of major process variables for 30 hours calculated using a physical model as is. In Figure 3, the values (estimated values) calculated using the physical model are shown as solid lines, and the actual values measured in an actual plant (actual sinter machine) are shown as dashed lines. Here, BTP is shown as the distance [m] from the position of the surge hopper in the direction of pallet movement.

[0027] The average estimation error for each of the major process variables was calculated as follows: BTP 2.4914 [m], O2 fraction 0.0086, CO2 fraction 0.0086, and partial burn rate 0.0169. The average estimation error was calculated by summing the squared deviations between the estimated and actual values over all steps and then dividing the sum by the number of steps to find the square root. Performing such long-term physical model calculations poses the challenge of generating significant errors in the estimated values (estimation errors) using conventional methods. While the example in Figure 3 uses data for 30 hours, reducing the estimation error is necessary to perform calculations over longer periods, such as years, to control the sintering process.

[0028] In order to reduce the estimation error, it is effective to successively adjust the reaction rate parameters, boundary conditions, etc. of the physical model so that the estimated value matches the actual value. Therefore, it is preferable to perform calculations after including variable factors in the physical model as one or more unknown parameters. In this embodiment, for the reasons explained below, three unknown parameters are selected: a correction parameter for the exhaust gas flow rate, a correction parameter for the raw material bulk density, and a correction parameter for the raw material coke ratio. Here, other variable factors such as the raw material moisture ratio, the carbon combustion rate, and the coke gasification reaction rate can also be considered as unknown parameters. For example, the carbon combustion rate depends on the solid temperature and the oxygen concentration in the gas, and the proportionality coefficient in these relational expressions can be used as the unknown parameter. The unknown parameters need to be selected depending on the raw materials used in the target process, the equipment configuration, etc.

[0029] The reasons for selecting the unknown parameters (three correction parameters) in this embodiment will be explained below.

[0030] In a sintering machine, air is sucked in from above the sintering bed, and the flow rate of exhaust gas containing CO2, CO, etc. is measured below the sintering bed. The measured exhaust gas flow rate includes the flow rate of gas that does not pass through the sintering bed but passes through other voids, known as leakage flow rate (leakage flow rate). Since leakage flow rate is difficult to measure, it is difficult to input directly into a physical model. Therefore, it is considered reasonable to correct the exhaust gas flow rate in the physical model so that it matches the actual values of the main process variables.

[0031] The raw material bulk density input in the physical model is ρ [kg / m 3 ], and ρ is calculated using the following equation (3).

[0032]

number

[0033] Here, V [kg / min] is the measurable raw material discharge speed. H [m] is the raw material layer thickness. W [m] is the sinter machine width. PS [m / min] is a value calculated from the pallet speed. Here, the raw material discharge speed is a value measured at the discharge device upstream of the sinter machine. In other words, the actual charging speed of the raw material into the sinter machine has not been measured. Therefore, it is difficult to accurately estimate the raw material bulk density inside the sinter machine. Therefore, it is considered appropriate to correct the raw material bulk density.

[0034] The coke ratio of raw materials is affected by the fact that miscellaneous raw materials containing carbon, such as blast furnace dust, are blended with the fine ore in advance at the raw material yard, separate from the coke charged to the sintering machine. Because there is a large variation in this blend ratio, it is considered appropriate to correct the coke ratio of raw materials (coke ratio).

[0035] Figure 4 shows the response of the process variables when the unknown parameters are changed stepwise. Figure 4 was obtained by applying certain operating conditions to the physical model until it reached a steady state, and then changing the three correction parameters stepwise.

[0036] First, when the exhaust gas flow rate was increased by 10%, the BTP was shortened, the O2 ratio increased, the CO2 ratio decreased, and the partial combustion rate remained almost unchanged.When the raw material bulk density was increased by 10%, the BTP was extended, the O2 ratio decreased, the CO2 ratio increased, and the partial combustion rate remained almost unchanged.When the raw material coke ratio was increased by 10%, the BTP remained almost unchanged, the O2 ratio decreased, the CO2 ratio increased slightly, and the partial combustion rate increased.

[0037] Using the step response to the unknown parameters obtained as described above, the parameters are corrected so that the BTP, O2 fraction, CO2 fraction, and partial burn rate match, according to the following steps (a) to (f). The algorithm described below is called MHE (Moving Horizon Estimation), but other state estimation methods such as particle filters and Kalman filters may also be used.

[0038] First, in step (a), the state variables and main process variables for the past A steps are calculated using the following equations (4) and (5).

[0039]

number

[0040] Here, k varies between A and 1. Also, actual values are used as input variables.

[0041] As step (b), x(t-A+1) is saved for use as the initial condition for the iterative calculation.

[0042] In step (c), the deviation is calculated by the following equation (6):

number

[0043] where y act is the actual value. cal is an estimate.

[0044] In step (d), the correction amounts Δα, Δβ, and Δγ of the unknown parameters are found so as to minimize the evaluation function, which combines the deviation and the step response of the main process variables to each of the unknown parameters described above, as shown in the following equation (7). The unknown parameters α, β, and γ in equation (7) correspond to the correction parameter for the exhaust gas flow rate, the correction parameter for the raw material bulk density, and the correction parameter for the raw material coke ratio, respectively. A smaller evaluation function corresponds to a smaller deviation. Here, a term is added to the evaluation function to prevent the unknown parameters from deviating significantly from "1" (see Figure 6).

number

[0045] Here, q identifies the main process variables. In this embodiment, q=1, 2, 3, 4 respectively represent BTP, O2 fraction, CO2 fraction, and partial burn rate. q p (s) denotes the value of the response at time step s in the step response of the primary process variable q to the unknown parameter p.

[0046] In step (e), the unknown parameters are corrected as shown in the following equations (8) to (10).

number

[0047] In step (f), the time step t is updated to t + 1, and the process returns to step (a). In this way, the unknown parameters are corrected by sequential calculations.

[0048] In this embodiment, unknown parameters of a physical model are corrected using MHE. FIG. 5 is a diagram showing an example of key process variables calculated by a physical model in which unknown parameters are corrected. FIG. 6 is a diagram showing an example of the transition of unknown parameters corresponding to FIG. 5. When the average estimation error was calculated for each of the key process variables, the results were BTP: 0.9961 [m], O2 fraction: 0.0044, CO2 fraction: 0.0047, and partial burn fraction: 0.0064. In other words, it can be seen that the estimation error is smaller than in the case of FIG. 3 due to the correction of unknown parameters using MHE.

[0049] Here, A in formula (7) may be determined so that the time required from the inlet to the outlet of the sintering can be evaluated, specifically, about 30 to 60 minutes. In the example of Fig. 5, the time step width is 5 minutes, A is 8, and the evaluation time is 40 minutes.

[0050] The sintering process state estimation device according to this embodiment (details will be described later) can estimate the BTP and exhaust gas composition with high accuracy by correcting the unknown parameters. Furthermore, by performing high-accuracy estimation using such a physical model, the estimation accuracy of the high-temperature holding time of the sintered material can also be improved. The high-temperature holding time is the time during which the temperature of the sintered material is held above a threshold (for example, 1200°C) that affects the improvement of the yield.

[0051] The operation guidance device according to this embodiment (details will be described later) can provide guidance to ensure the high-temperature holding time by, for example, increasing the proportion of raw coke when the calculated high-temperature holding time of the sintered material falls below a predetermined value (for example, 3 minutes). The operation guidance device may also provide guidance to ensure the high-temperature holding time by reducing the pallet speed. The operation guidance device is expected to improve yield by presenting the operator with information (guidance operation amount) that leads to appropriate action.

[0052] FIG. 7 is a diagram illustrating an example of the configuration of a sintering process state estimation device 10 and an operation guidance device 20 according to an embodiment. As shown in FIG. 7, the sintering process state estimation device 10 includes a memory unit 11, a process variable calculation unit 12, a deviation calculation unit 13, a model parameter adjustment unit 14, and a feature data calculation unit 15. The operation guidance device 20 includes a memory unit 21, a high-temperature holding time calculation unit 22, and a guidance operation variable presentation unit 23. The sintering process state estimation device 10 acquires various measured values (also referred to as actual values) from sensors and the like provided in the sintering machine and performs calculations using the above-described physical model. The operation guidance device 20 acquires the feature data of the sintering process calculated by the sintering process state estimation device 10, calculates the guidance operation variables, and displays guidance for operating the sintering machine on the display unit 30. In this embodiment, the feature data is the heat pattern of the sintered material in the longitudinal direction of the sintering machine. When the high-temperature holding time of the sintered material falls below a predetermined value (for example, 3 minutes), the operation guidance device 20 displays a guidance operation amount on the display unit 30 as guidance for ensuring the high-temperature holding time. The guidance operation amount may be at least one operation amount (amount to be adjusted) of the raw material coke ratio and the pallet speed required to ensure the high-temperature holding time. The display unit 30 may be a display device such as a liquid crystal display (LCD) or an organic electroluminescence panel (OLED).

[0053] First, the components of the sintering process state estimation device 10 will be described. The memory unit 11 stores a physical model that takes into account chemical reactions and heat transfer phenomena in the sintering process. The memory unit 11 also stores programs and data related to state estimation of the sintering process. The memory unit 11 may include any memory device, such as a semiconductor memory device, an optical memory device, or a magnetic memory device. The semiconductor memory device may include, for example, a semiconductor memory. The memory unit 11 may include multiple types of memory devices.

[0054] The process variable calculation unit 12 calculates observable process variables using a physical model. In this embodiment, the process variables are BTP, the O2 ratio, the CO2 ratio, and the partial combustion ratio in the exhaust gas composition.

[0055] The deviation calculation unit 13 calculates the deviation between the calculated estimated value of the process variable and the actual value in the actual plant.

[0056] The model parameter adjustment unit 14 corrects the unknown parameters of the physical model so that the calculated deviation becomes smaller.

[0057] The characteristic data calculation unit 15 calculates the characteristic data of the sintering process based on the corrected physical model. As described above, in this embodiment, the characteristic data is the heat pattern of the sintered material in the longitudinal direction of the sintering machine.

[0058] The process variable calculation unit 12, deviation calculation unit 13, and model parameter adjustment unit 14 perform calculations according to the above steps (a) to (f) to correct the unknown parameters of the physical model. In this embodiment, the unknown parameters are corrected by iterative calculations performed while updating the time step using the above-mentioned evaluation function including the deviation, process variables, and unknown parameters. The feature data calculation unit 15 calculates a heat pattern using the corrected physical model and outputs it to the operation guidance device 20 as feature data.

[0059] Next, the components of the operation guidance device 20 will be described. The storage unit 21 stores programs and data related to the operation guidance. The storage unit 21 may include any storage device, such as a semiconductor storage device, an optical storage device, or a magnetic storage device. The semiconductor storage device may include, for example, a semiconductor memory. The storage unit 21 may include multiple types of storage devices.

[0060] The high-temperature holding time calculation unit 22 calculates the high-temperature holding time of the sintered material using the heat pattern calculated by the sintering process state estimation device 10.

[0061] If the calculated high-temperature holding time of the sintered material is less than a predetermined value, the guidance operation variable presentation unit 23 presents a guidance operation variable on the display unit 30 to maintain the high-temperature holding time at or above the predetermined value. In this embodiment, the guidance operation variable includes at least one of the raw coke rate and the pallet speed. The guidance operation variable presentation unit 23 may, for example, cause the display unit 30 to display a 10% increase in the raw coke rate as the guidance operation variable. The guidance operation variable presentation unit 23 may, for example, cause the display unit 30 to display a 5% decrease in the pallet speed as the guidance operation variable. Here, the guidance operation variable presentation unit 23 may cause the sintering process state estimation device 10 to calculate the increase in the raw coke rate and the decrease in the pallet speed using a physical model. That is, the guidance operation variable presentation unit 23 may cause the sintering process state estimation device 10 to perform a simulation using a physical model in order to determine the guidance operation variable to be presented.

[0062] The operator may change the operating conditions of the sinter machine based on the guidance operation amount displayed on the display unit 30. Such operational guidance for the sinter machine can be executed as part of a manufacturing method for producing sintered ore.

[0063] Here, the sintering process state estimation device 10 and the operation guidance device 20 may be separate devices or may be an integrated device. In the case of an integrated device, the memory unit 11 and the memory unit 21 may be realized by the same memory device.

[0064] The sintering process state estimation device 10 and the operation guidance device 20 may be realized by a computer, such as a process computer that controls the operation of a sinter machine or the production of sintered ore. The computer includes, for example, a memory, a hard disk drive (storage device), a CPU (processing device), and a display device such as a monitor. The operating system (OS) and application programs for performing various processes can be stored in the hard disk drive and are read from the hard disk drive to the memory when executed by the CPU. Data during processing is stored in the memory and, if necessary, stored on the HDD. Various functions are realized by organic cooperation between hardware such as the CPU and memory and the OS and necessary application programs. The memory units 11 and 21 may be realized by, for example, a storage device. The process variable calculation unit 12, the deviation calculation unit 13, the model parameter adjustment unit 14, the feature data calculation unit 15, the high-temperature holding time calculation unit 22, and the guidance operation amount presentation unit 23 may be realized by, for example, a CPU. The display unit 30 may be realized by, for example, a display device.

[0065] Fig. 8 is a flowchart showing a state estimation method for a sintering process according to one embodiment. The sintering process state estimation device 10 outputs characteristic data of the sintering process according to the flowchart shown in Fig. 8. The state estimation method shown in Fig. 8 may be executed as part of a method for producing sintered ore.

[0066] The process variable calculation unit 12 calculates the process variable using the physical model (step S1, process variable calculation step). The deviation calculation unit 13 calculates the deviation between the calculated estimated value and actual value of the process variable (step S2, deviation calculation step). The model parameter adjustment unit 14 corrects the unknown parameters of the physical model so as to reduce the deviation (step S3, model parameter adjustment step). Then, the feature data calculation unit 15 calculates feature data based on the corrected physical model (step S4, feature data calculation step).

[0067] Fig. 9 is a flowchart showing an operation guidance method according to one embodiment. The operation guidance device 20 presents guidance operation variables in accordance with the flowchart shown in Fig. 9. The operation guidance method shown in Fig. 9 may be executed as part of a method for producing sintered ore.

[0068] The high-temperature holding time calculation unit 22 calculates the high-temperature holding time of the sintered material using the heat pattern calculated as the above-mentioned characteristic data (step S11, high-temperature holding time calculation step). The guidance operation amount presentation unit 23 presents the guidance operation amount on the display unit 30 in order to maintain the high-temperature holding time at or above a predetermined value (step S12, guidance operation amount presentation step).

[0069] FIG. 10 is a diagram showing the configuration of a sintering operation guidance system according to one embodiment. The sintering operation guidance system may be configured, for example, as shown by the dashed line in FIG. 10 , with a sintering operation guidance server 40 and a terminal device 50. The sintering operation guidance server 40 has the functions of the sintering process state estimation device 10 and the operation guidance device 20 and may be realized, for example, by a computer. The terminal device 50 functions at least as a display unit 30 and may be realized, for example, by a mobile terminal device such as a tablet or a computer. The sintering operation guidance server 40 and the terminal device 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 device 50 may be located in the same place (e.g., within the same factory) or may be physically separated. The sintering operation guidance system is not limited to the above configuration and may further include, for example, an operation data server 60 that aggregates sintering machine operation data (e.g., performance values and operation parameters indicating the operation status). The operation data server 60 can communicate with the sintering operation guidance server 40 and the terminal device 50 via a network, and may be realized by, for example, a computer that manages the production of sintered ore. The operation data server 60 may be located in the same place as the sintering operation guidance server 40 or the terminal device 50, or may be located physically separated from them. Below, components and the like will be described using as an example a sintering operation guidance system configured with the sintering operation guidance server 40 and the terminal device 50.

[0070] The sintering operation guidance server 40 acquires actual values indicating the operational state of the sintering process, performs calculations using the above-mentioned physical model, and calculates the high-temperature holding time of the sintered material using the calculated heat pattern as feature data. The sintering operation guidance server 40 also displays guidance operation variables, including at least one of the raw coke ratio and the pallet speed, on a terminal device 50 functioning as a display unit 30 in order to maintain the high-temperature holding time at or above a predetermined value. The sintering operation guidance server 40 includes the components of the sintering process state estimation device 10 and the operation guidance device 20 described with reference to FIG. 7. Specifically, the sintering operation guidance server 40 includes a memory unit, a process variable calculation unit 12, a deviation calculation unit 13, a model parameter adjustment unit 14, a feature data calculation unit 15, a high-temperature holding time calculation unit 22, and a guidance operation variable presentation unit 23. The memory unit 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, etc. The process variable calculation unit 12, deviation calculation unit 13, model parameter adjustment unit 14, feature data calculation unit 15, high-temperature holding time calculation unit 22, and guidance operation variable presentation unit 23 are the same as those described above. In addition, the sintering operation guidance server 40 may include an actual value acquisition unit that acquires actual values that indicate the operation status of the sintering process. The actual value acquisition unit may acquire the actual values directly from a sensor or a sintering process computer provided in the sintering machine, or may acquire the actual values via the operation data server 60.

[0071] The terminal device 50, together with the sintering operation guidance server 40, constitutes a sintering operation guidance system and displays guidance operation variables. The terminal device 50 includes at least a display unit 30. The display unit 30 is the same as described above. The terminal device 50 may also include a guidance operation variable acquisition unit that acquires the guidance operation variables presented by the sintering operation guidance server 40.

[0072] As described above, the sintering process state estimation method and sintering process state estimation device 10 according to this embodiment can estimate the state of the sintering process with high accuracy using the above-mentioned configuration. Furthermore, the operation guidance method, sinter ore manufacturing method, operation guidance device 20, sintering operation guidance system, sintering operation guidance server 40, and terminal device 50 according to this embodiment can provide guidance for improving yield based on the sintering process state estimated with high accuracy. For example, an operator can change the operating conditions based on the displayed guidance operation amount, thereby ensuring high-temperature holding time for the sintered material early and improving yield.

[0073] Although embodiments of the present disclosure have been described based on the drawings and examples, it should be noted that those skilled in the art would easily be able to make various modifications or alterations based on the present disclosure. Therefore, it should be noted that these modifications and alterations are included within the scope of the present disclosure. For example, functions included in each component or step can be rearranged so as not to cause logical inconsistencies, and multiple components or steps can be combined or divided into one. The embodiments of the present disclosure can also be realized as a program executed by a processor included in an apparatus or a storage medium on which a program is recorded. It should be understood that these are also included within the scope of the present disclosure.

[0074] The configurations of the sintering process state estimating device 10 and the operation guidance device 20 shown in Fig. 7 are examples. The sintering process state estimating device 10 and the operation guidance device 20 do not need to include all of the components shown in Fig. 7. Furthermore, the sintering process state estimating device 10 and the operation guidance device 20 may include components other than those shown in Fig. 7. For example, the operation guidance device 20 may be configured to further include a display unit 30.

[0075] Although the unknown parameters in the above embodiment include three correction parameters, it is sufficient to include at least one parameter. In other words, if at least one unknown parameter of the physical model is corrected, the estimation error can be reduced. [Explanation of symbols]

[0076] 10. Sintering process state estimation device 11 Storage section 12 Process variable calculation section 13 Deviation calculation section 14 Model parameter adjustment section 15 Feature data calculation unit 20 Operation guidance device 21 Memory section 22 High temperature holding time calculation section 23 Guidance operation amount presentation unit 30 Display section

Claims

1. a process variable calculation step of calculating observable process variables using a physical model that takes into account chemical reactions and heat transfer phenomena in the sintering process; a deviation calculation step of calculating a deviation between the calculated estimated value and the actual value of the process variable; a model parameter adjustment step of correcting unknown parameters, which are variable factors in the physical model that are difficult to measure, and which are used to correct input variables given to the physical model, so that the calculated degree of deviation becomes smaller; a characteristic data calculation step of calculating characteristic data of the sintering process based on the corrected physical model; a method for estimating a state of a sintering process, wherein the unknown parameters are corrected by iterative calculations performed while updating the time step using an evaluation function that takes into account the deviation and the effect on the estimated value of the process variable due to the correction of the unknown parameters.

2. The method for estimating a state of a sintering process according to claim 1 , wherein the process variables include at least one of BTP, exhaust gas composition, and temperature under the sintering bed.

3. 3. The method for estimating a state of a sintering process according to claim 1, wherein the unknown parameters include at least one correction parameter of 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 method for estimating a state of a sintering process according to claim 1 or 2, wherein the characteristic data is a heat pattern of the sintered material in the longitudinal direction of the sintering machine.

5. a high-temperature holding time calculation step of calculating a high-temperature holding time of the sintered material using the heat pattern calculated by the sintering process state estimation method according to claim 4; and a guidance operation variable presentation step of presenting a guidance operation variable including at least one of a raw coke ratio and a pallet speed in order to maintain the high-temperature holding time at a predetermined value or more.

6. A method for producing sintered ore, comprising producing sintered ore using the guidance operation amount presented by the operation guidance method according to claim 5.

7. a storage unit that stores a physical model that takes into account chemical reactions and heat transfer phenomena in the sintering process; a process variable calculation unit that calculates an observable process variable using the physical model; a deviation calculation unit that calculates a deviation between the calculated estimated value and the actual value of the process variable; a model parameter adjustment unit that corrects unknown parameters, which are variable factors in the physical model that are difficult to measure, and which are used to correct input variables given to the physical model, so that the calculated degree of deviation becomes smaller; a characteristic data calculation unit that calculates characteristic data of the sintering process based on the corrected physical model, a sintering process state estimation device, wherein the unknown parameters are corrected by iterative calculations performed while updating the time step using an evaluation function that takes into account the deviation and the effect on the estimated value of the process variable due to the correction of the unknown parameters.

8. a high-temperature holding time calculation unit that calculates a high-temperature holding time of the sintered material using the heat pattern calculated by the sintering process state estimation device according to claim 7, wherein the characteristic data is a heat pattern of the sintered material in the longitudinal direction of the sintering machine; a guidance operation variable presentation unit that presents guidance operation variables including at least one of a raw coke ratio and a pallet speed in order to maintain the high-temperature holding time at a predetermined value or more.

9. A sintering operation guidance server and a terminal device are provided, The sintering operation guidance server an actual value acquisition unit that acquires actual values indicating the operating status of the sintering process; a storage unit that stores a physical model that takes into account chemical reactions and heat transfer phenomena in the sintering process; a process variable calculation unit that calculates an observable process variable using the physical model; a deviation calculation unit that calculates a deviation between the calculated estimated value and the actual value of the process variable; a model parameter adjustment unit that corrects unknown parameters, which are variable factors in the physical model that are difficult to measure, and which are used to correct input variables given to the physical model, so that the calculated degree of deviation becomes smaller; a characteristic data calculation unit that calculates characteristic data of the sintering process based on the corrected physical model; The characteristic data is a heat pattern of the sintered material in the longitudinal direction of the sintering machine, and a high-temperature holding time calculation unit calculates a high-temperature holding time of the sintered material using the heat pattern; a guidance operation variable presentation unit that presents a guidance operation variable including at least one of a raw coke ratio and a pallet speed in order to maintain the high-temperature holding time at a predetermined value or more, The terminal device a guidance operation amount acquisition unit that acquires the guidance operation amount presented by the sintering operation guidance server; a display unit that displays the acquired guidance operation amount, the unknown parameters are corrected by iterative calculations performed while updating the time step using an evaluation function that takes into account the deviation and the influence on the estimated value of the process variable resulting from the correction of the unknown parameters.

10. an actual value acquisition unit that acquires actual values indicating the operating status of the sintering process; a storage unit that stores a physical model that takes into account chemical reactions and heat transfer phenomena in the sintering process; a process variable calculation unit that calculates an observable process variable using the physical model; a deviation calculation unit that calculates a deviation between the calculated estimated value and the actual value of the process variable; a model parameter adjustment unit that corrects unknown parameters, which are variable factors in the physical model that are difficult to measure, and which are used to correct input variables given to the physical model, so that the calculated degree of deviation becomes smaller; a characteristic data calculation unit that calculates characteristic data of the sintering process based on the corrected physical model; The characteristic data is a heat pattern of the sintered material in the longitudinal direction of the sintering machine, and a high-temperature holding time calculation unit calculates a high-temperature holding time of the sintered material using the heat pattern; a guidance operation variable presentation unit that presents a guidance operation variable including at least one of a raw coke ratio and a pallet speed in order to maintain the high-temperature holding time at a predetermined value or more, The unknown parameters are corrected by iterative calculations performed while updating the time step using an evaluation function that takes into account the deviation and the effect on the estimated value of the process variable due to the correction of the unknown parameters.

11. A terminal device constituting a sintering operation guidance system together with a sintering operation guidance server, a guidance operation amount acquisition unit that acquires a guidance operation amount presented by the sintering operation guidance server; a display unit that displays the acquired guidance operation amount, The sintering operation guidance server corrects unknown parameters, which are variable elements in the physical model that are difficult to actually measure and are used to correct input variables given to the physical model, so that the degree of discrepancy between estimated values of process variables calculated using a physical model that takes into account chemical reactions and heat transfer phenomena in the sintering process and actual values becomes small, the guidance manipulated variable is a manipulated variable including at least one of a raw coke ratio and a pallet speed, for maintaining a high-temperature holding time of the sintered material at a predetermined value or more based on a heat pattern of the sintered material in the longitudinal direction of the sintering machine calculated using the physical model in which the unknown parameters have been corrected; The unknown parameters are corrected by iterative calculations performed while updating the time step using an evaluation function that takes into account the deviation and the effect on the estimated value of the process variable due to the correction of the unknown parameters.

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