TECHNICAL FIELD
[0001] 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
[0002] 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.
[0003] 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.
[0004] 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
SUMMARY
(Technical Problem)
[0006] 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.
[0007] 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)
[0008] 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.
[0009] 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.
[0010] 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.
[0011] 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.
[0012] 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.
[0013] 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.
[0014] 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.
[0015] 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)
[0016] 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
[0017] 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
[0018] 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.
[0019] 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.
[0020] 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. 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.
[0021] The physical model can be expressed by the following Equations (1) and (2).
![](https://data.epo.org/publication-server/image?imagePath=2024/14/DOC/EPNWA1/EP22841997NWA1/imgb0002)
[0022] 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 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.
![](https://data.epo.org/publication-server/image?imagePath=2024/14/DOC/EPNWA1/EP22841997NWA1/imgb0003)
[0023] 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. Here, other key process
variables can be included, such as the temperature below the sintering bed.
[0024] 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.
[0025] 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. 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.
[0026] 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.
[0027] The reasons for the selection of the unknown parameters (three correction parameters)
in the present embodiment are explained below.
[0028] In the sintering machine, air is sucked from the top of the sintering bed, and 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. 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.
[0029] Assuming that the raw material bulk density inputted in the physical model is ρ [kg/m
3], ρ is calculated by Equation (3) below.
![](https://data.epo.org/publication-server/image?imagePath=2024/14/DOC/EPNWA1/EP22841997NWA1/imgb0004)
[0030] 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.
[0031] 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).
[0032] 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.
[0033] First, when the exhaust gas flow rate was increased by 10%, the BTP shortened, the
O
2 ratio increased, the CO
2 ratio decreased, and the partial combustion rate remained nearly unchanged. When
the raw material bulk density was increased by 10%, the BTP lengthened, the O
2 ratio decreased, the CO
2 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 O
2 ratio decreased, the CO
2 ratio increased slightly, and the partial combustion rate increased.
[0034] 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 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.
[0035] First, as step (a), the state variables and key process variables for the past A
steps are calculated by Equations (4) and (5) below.
![](https://data.epo.org/publication-server/image?imagePath=2024/14/DOC/EPNWA1/EP22841997NWA1/imgb0006)
[0036] Here, k varies between A and 1. In addition, actual values are used as input variables.
[0037] As step (b), x(t - A + 1) is stored for use as the initial condition for the iterative
calculation.
[0038] As step (c), the degree of deviation is calculated by Equation (6) below.
![](https://data.epo.org/publication-server/image?imagePath=2024/14/DOC/EPNWA1/EP22841997NWA1/imgb0007)
[0039] Here, y
act is the actual value, and y
cal is the estimated value.
[0040] 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).
![](https://data.epo.org/publication-server/image?imagePath=2024/14/DOC/EPNWA1/EP22841997NWA1/imgb0008)
[0041] Here, q identifies the key process variable. In the present embodiment, q = 1, 2,
3, and 4 represent the BTP, the O
2 ratio, the CO
2 ratio, and the partial combustion rate, respectively. R
qp(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.
[0043] 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.
[0044] 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 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.
[0045] 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.
[0046] 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.
[0047] 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.
[0048] 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.
[0049] 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.
[0050] The process variable calculator 12 calculates observable process variables using
the physical model. In the present embodiment, the process variables are the BTP,
the O
2 ratio and CO
2 ratio in the exhaust gas composition, and the partial combustion rate.
[0051] The deviation calculator 13 calculates the deviation between the estimated values
and the actual values, in an actual plant, of the calculated process variables.
[0052] The model parameter adjustor 14 modifies unknown parameters of the physical model
so that the calculated deviation is reduced.
[0053] 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.
[0054] 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.
[0055] 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.
[0056] 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.
[0057] 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.
[0058] 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.
[0059] 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.
[0060] 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.
[0061] 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.
[0062] 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).
[0063] 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.
[0064] 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).
[0065] 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.
[0066] 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.
[0067] 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.
[0068] 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.
[0069] 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.
[0070] 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.
[0071] 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
[0072]
- 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
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.