JP7384150B2 - Operation guidance method, blast furnace operation method, hot metal production method and operation guidance device - Google Patents

Description

The present disclosure relates to an operation guidance method, a blast furnace operation method, a hot metal manufacturing method, and an operation guidance device.

Hot metal temperature (HMT) is an important control index in the blast furnace process in the steel industry. When the hot metal temperature rises, not only is the excess reducing agent consumed, but also the raw material descent becomes unstable due to the expansion of the gas in the furnace. Furthermore, when the hot metal temperature drops extremely, the slag removal performance deteriorates and the productivity of the blast furnace decreases. By reducing the variation in hot metal temperature, it becomes possible to lower the temperature target value without sacrificing the productivity of the blast furnace, which leads to a reduction in the reducing agent ratio.

The blast furnace process operates with solids filled, so the heat capacity of the entire process is large, and the time constant of response to operational actions is long. Therefore, in order to properly operate the blast furnace, control is sometimes performed based on predictions. As a blast furnace control method based on prediction, there is a method using a physical model as disclosed in Patent Document 1, for example.

Japanese Patent Application Publication No. 11-335710

Patent Document 1 describes that when the predicted value of the hot metal temperature deviates from the management target range, it is possible to take operational action on the assumption that there is an operational abnormality in the blast furnace. However, the technique of Patent Document 1 does not present abnormal factors that are used to determine what operational action to take.

The purpose of the present disclosure, which was made to solve the above problems, is to provide an operation guidance method, a blast furnace operation method, a hot metal production method, and an operation guidance device that can quantify operational abnormalities in a blast furnace and indicate the abnormality along with its basis. It is about providing.

An operation guidance method according to an embodiment of the present disclosure includes:
An operation guidance method for supporting the operation of the blast furnace using a physical model that includes hot metal temperature as an output variable and is capable of calculating the internal state of the blast furnace,
predicting a furnace heat index correlated with the hot metal temperature using the physical model;
calculating the furnace heat index based on actual measurements in the blast furnace during operation;
calculating a difference between the predicted furnace heat index and the furnace heat index calculated based on the actual measured value;
The method includes the step of displaying the cause of the abnormality when it is determined that the operation of the blast furnace is abnormal based on the difference.

A blast furnace operating method according to an embodiment of the present disclosure includes:
The operating conditions are changed based on the abnormality factor indicated by the above-mentioned operation guidance method.

A method for producing hot metal according to an embodiment of the present disclosure includes:
Hot metal is produced using the blast furnace operated by the blast furnace operating method described above.

An operation guidance device according to an embodiment of the present disclosure includes:
An operation guidance device that supports the operation of the blast furnace using a physical model that includes hot metal temperature as an output variable and is capable of calculating the internal state of the blast furnace,
a storage unit that stores the physical model;
a prediction unit that uses the physical model to predict a furnace heat index correlated with the hot metal temperature;
a furnace heat index calculation unit that calculates the furnace heat index based on actual measurements in the blast furnace during operation;
a difference calculation unit that calculates a difference between the predicted furnace heat index and the furnace heat index calculated based on the actual measured value;
and a display control unit that displays the cause of the abnormality when it is determined that the operation of the blast furnace is abnormal based on the difference.

According to the present disclosure, it is possible to provide an operation guidance method, a blast furnace operation method, a method for producing hot metal, and an operation guidance device that can quantify operational abnormalities in a blast furnace and indicate the abnormality together with its basis.

FIG. 1 is a diagram showing input/output information of a physical model used in the present disclosure. FIG. 2 shows a conceptual diagram of the heat balance in the lower part of the furnace. FIG. 3 is a diagram showing changes in the furnace heat index of the actual furnace and the physical model under normal operation. FIG. 4 is a diagram showing the correlation between the furnace heat index and the hot metal temperature in an actual furnace and a physical model. FIG. 5 is a diagram showing changes in the furnace heat index of the actual furnace and the physical model under abnormal operation. FIG. 6 is a diagram illustrating an example of differences for each item of the furnace heat index. FIG. 7 is a diagram showing the differences in FIG. 6 in percentages. FIG. 8 is a diagram illustrating a configuration example of an operation guidance device according to an embodiment. FIG. 9 is a flowchart illustrating an operation guidance method according to an embodiment.

Hereinafter, an operation guidance method, a blast furnace operation method, a hot metal production method, and an operation guidance device according to an embodiment of the present disclosure will be described with reference to the drawings. The physical model used in this disclosure is similar to the method described in Reference 1 (Michiharu Hadano et al., "Study of burning operation using an unsteady blast furnace model", Tetsu to Hagane, vol. 68, p. 2369). Physics that can calculate the state inside the blast furnace (furnace) in an unsteady state, consisting of a group of partial differential equations that take into account physical phenomena such as reduction of carbon dioxide, heat exchange between ore and coke, and melting of ore. It's a model. This physical model may be referred to as an unsteady model below.

As shown in FIG. 1, the main input variables given to the unsteady model that change over time are the air flow rate, the air oxygen flow rate, the pulverized coal flow rate, the coke ratio, the air humidity, and the air temperature. These input variables are operating variables or operating factors of the blast furnace. The blast flow rate, the blast oxygen flow rate, and the pulverized coal flow rate are the flow rates of air, oxygen, and pulverized coal sent to the blast furnace, respectively. The coke ratio is the coke ratio at the top of the furnace, and is the weight of coke used for one ton of hot metal production. The blast humidity is the humidity of the air sent to the blast furnace. The blowing temperature is the temperature of the air sent to the blast furnace.

The main output variables of the unsteady model are top gas composition, ironmaking rate, and hot metal temperature. Using the unsteady model, it is possible to calculate the ever-changing hot metal temperature and iron making rate. Furthermore, in the operation guidance method according to the present embodiment, a furnace heat index, which will be described later, is calculated using an unsteady model. Although the time interval for this calculation is not particularly limited, it is 30 minutes in this embodiment. In this embodiment, the time difference between "t+1" and "t" in the unsteady model equation described later is 30 minutes.

Here, the prerequisite for the unsteady model is that the raw material descends smoothly inside the furnace. If the preconditions do not hold, the accuracy of predicting the hot metal temperature will decrease. In other words, if the preconditions do not hold, the hot metal temperature, which is one of the multiple output variables of the unsteady model, is likely to be affected. Furthermore, if a measurement error or analysis error occurs in the coke ratio at the top of the furnace, which is an input variable of the unsteady model, the calculated value and actual value of the hot metal temperature will dissociate. Therefore, by monitoring the deviation between the unsteady model and the measured data, it is possible to determine a dissociation from the preconditions and set conditions of the unsteady model, in other words, an operational abnormality related to the furnace thermal state. Furthermore, if the operational abnormality can be broken down into elements, it is possible to implement operational actions according to the type of abnormality and recover from the abnormal furnace heat state.

The unsteady model can be expressed by the following equation.

Here x(t) is a state variable calculated within the unsteady model. State variables include, for example, coke temperature, iron temperature, ore oxidation degree, and raw material fall rate. y(t) is the hot metal temperature. u(t) is the input variable described above, and is a variable that can be operated by the operator who operates the blast furnace. In other words, the input variables are blast flow rate BV (t), blast oxygen flow rate BVO (t), pulverized coal flow rate PCI (t), coke ratio CR (t), blast moisture BM (t), and blast temperature BT (t). It is. It can be expressed as u(t)=(BV(t), BVO(t), PCI(t), CR(t), BM(t), BT(t)).

A furnace heat index for determining abnormal operation of a blast furnace is defined below. As described above, regarding the hot metal temperature, which is an output variable of the unsteady model, an operational abnormality can be determined from the dissociation between the calculated value and the actual value. However, in order to facilitate the breakdown of the operational abnormality into elements, that is, to enable efficient determination of the basis of the abnormality, a furnace heat index that is correlated with the hot metal temperature is defined.

FIG. 2 shows a conceptual diagram of the heat balance in the lower part of the furnace. The concept of heat balance is described, for example, in Reference 2 (Yoichi Ono, Rist Operation Diagram (I), Tetsu-to-Hagane, 79 (1993), N618). There is a heat storage zone inside the furnace, and the heat balance between the upper part (upper furnace) and the lower part (lower furnace) can be treated independently. In this embodiment, the furnace heat index uses components of the heat balance in the lower part of the furnace. As shown in FIG. 2, the heat balance in the lower part of the furnace includes two elements regarding heat input (Q1 and Q2) and three elements regarding heat output (Q3, Q4 and Q5). Here, the furnace heat index in the present disclosure is an example, and is described, for example, in Reference Document 3 (A. Agrawal et.al., Ironmaking and Steelmaking, Vol. 46 (2019), pp. 133-140). Other furnace heat indicators may be used.

First, regarding heat input, there is sensible heat Q1(t) [MJ/min] of hot air blown from the tuyere, which is expressed by the following equation (3).

Here, C _p,g is the gas specific heat. Sensible heat Q1(t) of the air is assumed to be the temperature of the thermal storage zone of 1000°C, and is the sensible heat based on 1000°C.

Another heat input element is the combustion heat Q2(t) of coke and pulverized coal at the tuyere, which is expressed by the following equation (4).

Here, PCI_C means the proportion of carbon in pulverized coal. ΔH (coke) is the heat of combustion of carbon in coke. ΔH (PC) is the amount of heat generated at the tuyere, which is the sum of the heat of combustion of carbon in the pulverized coal and the heat of decomposition of the pulverized coal. Further, TotalC is the carbon burning rate [kg/min], and is expressed by the following equation (5).

Here, PCI_O means the proportion of oxygen in pulverized coal.

In addition, as the heat output, the heat of decomposition of the blown moisture Q3 (t) shown by the following equation (6), the heat absorption by direct reduction Q4 (t) shown by the equation (7), and the furnace shown by the equation (8) There is a heat loss of the body Q5(t).

Here, SLC(t) is the amount of carbon consumed per hour by the direct reduction reaction. SLC(t) is determined by the carbon balance in the furnace, as described in Reference 4 (Y. Hashimoto et. al., ISIJ Int., Vol. 59 (2019), pp. 1534-1544), for example. Calculable.

Furnace heat index TQ(t) is qi, which is the amount of heat per ton of hot metal obtained by dividing Qi(t), which is the amount of heat per unit time, by the ironmaking rate Vprod(t), where i is an integer from 1 to 5. It is defined by summing (t). In other words, the furnace heat index TQ(t) is a heat quantity index per unit amount. The furnace heat index TQ(t) is expressed by the following equation (9).

The pig iron making rate Vprod(t) can be calculated from the oxygen balance as shown in the following equation (10).

Here, v _O ^out (t) [kg/min] is the flow rate of oxygen discharged from the top of the furnace. v _O ⁱⁿ (t) [kg/min] is the flow rate of oxygen blown into the tuyere. Ore [kg/t] is the amount of oxygen to be reduced necessary to produce 1 ton of pig iron. v _O ^out (t) is the result of the reaction in the furnace and depends on the reducibility of the ore. Therefore, the iron making rate Vprod(t) is not uniquely determined from variables that can be operated by the operator who operates the blast furnace.

FIG. 3 is a diagram showing an example of changes in the furnace heat index of an actual furnace and a physical model under normal operation. In FIG. 3, the furnace heat index TQ(t) calculated based on the actual measured value of the actual furnace, q1(t) to q5(t) which are the items constituting the furnace heat index TQ(t), and the iron making rate Vprod (t) is shown as a solid line. Further, FIG. 3 also shows the above-mentioned Q1(t) to Q5(t). For these values, the values calculated as predictions using a physical model are shown by broken lines.

As shown in FIG. 3, there is no difference between the results based on actual measurements and the predictions for Q1(t), Q2(t), and Q3(t). This is because Q1(t), Q2(t), and Q3(t) are uniquely determined by manipulable variables (boundary conditions). Here, since there is a difference in the pig iron making speed Vprod(t), a difference occurs between q1(t), q2(t), and q3(t). Furthermore, since there is a difference between the actual in-furnace reaction and the physical model, there is a difference in Q4(t) and Q5(t). However, the differences that occur are all small. In other words, regarding the furnace heat index TQ(t) and q1(t) to q5(t), which are the items that make up the furnace heat index TQ(t), the trends in value fluctuations are the same between the results based on actual measurements and the predictions. We are doing so.

Moreover, FIG. 4 is a diagram showing the correlation between the furnace heat index TQ and the hot metal temperature HMT of the actual furnace and the physical model. Here, since the furnace heat index TQ changes before the hot metal temperature HMT, the hot metal temperature HMT is made to correspond using data 4 hours after the furnace heat index TQ. As shown in FIG. 4, a good correlation is observed between the furnace heat index TQ and the hot metal temperature HMT. Therefore, the blast furnace can be operated using the furnace heat index TQ in the same way as when using the hot metal temperature HMT. That is, the furnace heat index TQ can be used as an operating index of the blast furnace. In addition, as explained with reference to FIG. 3, regarding the furnace heat index TQ(t) and q1(t) to q5(t), the actual values based on the measured values and the predicted values are used to compare the values under normal operation. The trends of fluctuations are consistent. Therefore, it is possible to determine an operational abnormality based on the discrepancy between the actual value based on the actual measurement value and the predicted value for the furnace heat index TQ(t) and q1(t) to q5(t).

FIG. 5 is a diagram showing changes in the furnace heat index of the actual furnace and the physical model under abnormal operation. The meanings of TQ(t), q1(t) to q5(t), Q1(t) to Q5(t), Vprod(t), and the solid and broken lines are the same as in FIG. 3. Further, in the same time series as these, the pulverized coal flow rate PCI (t) and the hot metal temperature HMT (t) are shown. The target value is the target temperature of the hot metal temperature HMT.

In the example of FIG. 5, the difference between the solid line and the broken line of the furnace heat index TQ(t) is large, and the same is true of the transition of the hot metal temperature HMT(t). In other words, the difference between the predicted furnace heat index TQ(t) and the furnace heat index TQ(t) calculated based on the actual measurement value becomes large in the latter half, and the same holds true for the hot metal temperature HMT(t). A trend can be seen. At this time, according to prediction calculations using a physical model, the pulverized coal flow rate PCI (t) is increased, resulting in an increase in both the furnace heat index TQ (t) and the hot metal temperature HMT (t). . On the other hand, in actual reactors, both show a tendency to decrease. This indicates that the effect (furnace heat increase) of increasing the pulverized coal flow rate PCI(t) was not achieved in the actual furnace, and can be said to be an abnormality in the operation of the blast furnace.

The cause of the abnormality, that is, what is the origin of this abnormality can be determined based on the deviation of q1(t) to q5(t), which are items forming the furnace heat index TQ(t). At this time, by using the contribution rate, which is the ratio of the difference between q1(t) to q5(t), it is possible to efficiently determine the cause of the abnormality.

The contribution rate can be calculated as follows. qiAct(t) is qi(t) of the furnace heat index TQ(t) calculated based on the actual measurement value of the actual furnace, where i is an integer from 1 to 5. Moreover, qiMod(t) is qi(t) of the furnace heat index TQ(t) calculated as a prediction using a physical model. The contribution rate can be obtained by calculating the ratio of these differences, Δqi(t)=|qiAct(t)−qiMod(t)|, to the sum of Δqi(t) for i=1 to 5. FIG. 6 is a diagram showing the difference for each qi(t) in the example of FIG. FIG. 7 shows the difference in FIG. 6 as a ratio (expressed as a percentage) to the total sum of Δqi(t), and corresponds to the contribution rate.

In FIGS. 6 and 7, Δq2 is the largest. That is, in the example of FIG. 5, q2 is considered to be the main abnormality factor. Moreover, as shown in FIG. 5, since there is no difference in the heat of combustion Q2 between coke and pulverized coal, it can be seen that the more detailed cause of the abnormality is the difference in iron making speed Vprod(t). This is due to, for example, the deviation of v _O ^out (t) in equation (10), and it is considered that the physical model is different from the actual furnace regarding unloading, top coke ratio, and ore reducibility. It will be done.

As another example, if Δq4 is large compared to other Δqi, this means that the endotherm Q4 due to direct reduction behaved differently between the physical model and the actual reactor. The detailed cause of the abnormality is thought to be that the physical model is different from the actual reactor regarding the reducibility of ore, changes in the contact state between CO gas and ore due to uneven flow of gas in the furnace, and reaction specific surface area due to changes in ore particle size. It will be done. As yet another example, if Δq5 is larger than other Δqi's, this means that the heat loss Q5 of the furnace body behaved differently between the physical model and the actual furnace. The detailed cause of the abnormality is thought to be that the physical model differs from the actual reactor in terms of changes in the shape of the cohesive zone due to the burden distribution, uneven flow of gas in the reactor, etc.

Through such an analysis, in the present disclosure, it is possible to indicate at least which of the five items constituting the furnace heat index TQ is dominant as an abnormality factor.

FIG. 8 is a diagram showing a configuration example of the operation guidance device 10 according to an embodiment. As shown in FIG. 8, the operation guidance device 10 according to the present embodiment includes a storage unit 11, a prediction unit 12, a furnace heat index calculation unit 13, a difference calculation unit 14, an abnormality determination unit 15, and a display control unit 11. 16. The operation guidance device 10 acquires various measured values from sensors provided in the blast furnace. Further, the operation guidance device 10 causes the display unit 20 to display guidance for operating the blast furnace. Specifically, when it is determined that there is an operational abnormality in the blast furnace, the operation guidance device 10 causes the display unit 20 to display the cause of the abnormality. The display unit 20 may be a display device such as a liquid crystal display or an organic electroluminescence panel.

The storage unit 11 stores a physical model. Furthermore, the storage unit 11 stores programs and data related to determination of operational abnormality. The storage unit 11 may include any storage device such as a semiconductor storage device, an optical storage device, and a magnetic storage device. A semiconductor storage device may include, for example, a semiconductor memory. The storage unit 11 may include multiple types of storage devices.

The prediction unit 12 uses a physical model to predict a furnace heat index that is correlated with the hot metal temperature. The prediction unit 12 calculates the future furnace heat index according to the above formula. In this embodiment, the future is 30 minutes later. The prediction unit 12 also performs calculations for each item that constitutes the furnace heat index.

The furnace heat index calculation unit 13 calculates a furnace heat index based on actual measurements in the blast furnace in operation. The furnace heat index calculation unit 13 performs calculation for each item that constitutes the furnace heat index.

The difference calculation unit 14 calculates the difference between the furnace heat index predicted by the prediction unit 12 and the furnace heat index calculated by the furnace heat index calculation unit 13 based on the actual measurement value. To be more specific, the difference calculation unit 14 calculates, in addition to the difference in the furnace heat index, the difference for each item that constitutes the furnace heat index. Here, the difference calculation unit 14 calculates the difference by considering the time difference between the furnace heat index calculated by the prediction unit 12 and the furnace heat index calculated by the furnace heat index calculation unit 13. In this embodiment, the difference calculation unit 14 calculates the difference between the furnace heat index predicted by the prediction unit 12 and the furnace heat index calculated based on the actual measurement value acquired 30 minutes later.

The abnormality determination unit 15 determines whether there is an operational abnormality in the blast furnace based on the difference calculated by the difference calculation unit 14. The abnormality determining unit 15 determines that there is an operational abnormality when the difference is large. When determining that there is an operational abnormality, the abnormality determination unit 15 determines the cause of the abnormality based on the difference between items. The abnormality determination unit 15 may calculate the above-mentioned contribution rate and determine the cause of the abnormality. In other words, the abnormality determination unit 15 may identify the abnormality factor based on the ratio of differences between items that constitute the abnormality factor.

The display control unit 16 causes the display unit 20 to display the cause of the abnormality when the abnormality determination unit 15 determines that the operation of the blast furnace is abnormal. The display control unit 16 may cause the display unit 20 to display detailed abnormality cause candidates, such as the reducibility of the ore and changes in the contact state between the CO gas and the ore due to the drift of the gas in the furnace. Furthermore, the display control unit 16 may cause the display unit 20 to display which of the five items forming the furnace heat index is dominant as an abnormality factor.

The operator may change the operating conditions for operating the blast furnace based on the abnormality factor shown on the display unit 20. For example, if the above-mentioned q3 regarding the heat of decomposition of the blown moisture is shown to be a dominant abnormality factor, the operator may stabilize future operations by adjusting the air blowing. Such a blast furnace operation may be performed as part of a production method for producing hot metal. In a blast furnace, the raw material iron ore is melted and reduced to become pig iron, which is tapped as hot metal.

The operation guidance device 10 may be realized, for example, by a computer such as a process computer that controls the operation of a blast furnace. A computer includes, for example, a memory and a hard disk drive (storage device), a CPU (processing unit), and a display control device that controls a display device such as a display. An operating system (OS) and application programs for performing various processes can be stored in a hard disk drive, and are read into memory from the hard disk drive when executed by a CPU. If necessary, the CPU controls the display control device to display necessary images on the display. Furthermore, data that is being processed is stored in the memory, and if necessary, stored in the HDD. Various functions are realized by organically cooperating hardware such as a CPU and memory with an OS and necessary application programs. The storage unit 11 may be realized by, for example, a storage device. The prediction unit 12, the furnace heat index calculation unit 13, the difference calculation unit 14, and the abnormality determination unit 15 may be realized by, for example, a CPU. The display control unit 16 may be realized by, for example, a display control device.

FIG. 9 is a flowchart illustrating an operation guidance method according to an embodiment. The operation guidance device 10 executes guidance to support recovery in the event of abnormal operation of the blast furnace, according to the flowchart shown in FIG. 9 . The operation guidance method shown in FIG. 9 may be executed as part of a blast furnace operating method and a hot metal manufacturing method.

The prediction unit 12 of the operation guidance device 10 uses a physical model to predict a furnace heat index correlated with the hot metal temperature (step S1).

The furnace heat index calculation unit 13 of the operation guidance device 10 acquires actual measured values in the blast furnace in operation, and calculates a furnace heat index based on the actual measured values (step S2).

The difference calculation unit 14 of the operation guidance device 10 calculates the difference between the predicted furnace heat index and the furnace heat index calculated based on the actual measurement value (step S3). At this time, the difference calculation unit 14 of the operation guidance device 10 calculates the difference for each item constituting the furnace heat index in addition to the difference in the furnace heat index.

The abnormality determination unit 15 of the operation guidance device 10 determines whether there is an operational abnormality in the blast furnace based on the calculated difference (step S4).

When it is determined that the operation of the blast furnace is abnormal (Step S4: Yes), the display control unit 16 of the operation guidance device 10 causes the display unit 20 to display the cause of the abnormality (Step S5). As described above, the abnormality factor may be identified based on the ratio of differences between items.

If the operation guidance device 10 does not determine that the operation is abnormal (No in step S4), the operation guidance device 10 ends the series of processes. At this time, the display control unit 16 of the operation guidance device 10 may cause the display unit 20 to display that there is no operational abnormality before ending the series of processes.

As described above, the operation guidance method, blast furnace operation method, hot metal production method, and operation guidance device 10 according to the present embodiment automatically determine and classify the state of disturbance in the temperature distribution of the blast furnace with the above-described configuration. , operational abnormalities can be quantified. Further, the operation guidance method, blast furnace operation method, hot metal manufacturing method, and operation guidance device 10 according to the present embodiment can indicate operational abnormalities along with their grounds. For example, the operator can change the operating conditions based on the indicated abnormality factor to quickly eliminate the disturbance in the temperature distribution of the blast furnace. Further, it is also possible to change operating conditions based on an abnormal factor using, for example, a process computer that controls the operation of a blast furnace, and it is possible to increase the automation rate of operation.

Although embodiments according to the present disclosure have been described based on various drawings and examples, it should be noted that those skilled in the art can easily make various changes or modifications based on the present disclosure. It should therefore be noted that these variations or modifications are included within the scope of this disclosure. For example, the functions included in each component or each step can be rearranged to avoid logical contradictions, and multiple components or steps can be combined or divided into one. It is. Embodiments according to the present disclosure can also be realized as a program executed by a processor included in the device or a storage medium recording the program. It is to be understood that these are also encompassed within the scope of the present disclosure.

The configuration of the operation guidance device 10 shown in FIG. 8 is an example. The operation guidance device 10 does not need to include all of the components shown in FIG. Further, the operation guidance device 10 may include components other than those shown in FIG. For example, the operation guidance device 10 may further include a display section 20.

10 Operation guidance device 11 Storage unit 12 Prediction unit 13 Furnace heat index calculation unit 14 Difference calculation unit 15 Abnormality determination unit 16 Display control unit 20 Display unit

Claims (5)

An operation guidance method for supporting the operation of the blast furnace using a physical model that includes hot metal temperature as an output variable and is capable of calculating the internal state of the blast furnace,
predicting a furnace heat index correlated with the hot metal temperature using the physical model;
calculating the furnace heat index based on actual measurements in the blast furnace during operation;
calculating a difference between the predicted furnace heat index and the furnace heat index calculated based on the actual measured value;
Displaying the cause of the abnormality when it is determined that the operation of the blast furnace is abnormal based on the difference ,
The furnace heat index is the amount of heat per unit time of the heat balance calculated using elements including sensible heat of air, combustion heat of coke and pulverized coal, heat of decomposition of air moisture, heat absorption due to direct reduction, and heat loss. Calculated by dividing by the pig iron speed, each of the above elements per unit amount of hot metal is an item,
The step of calculating the difference includes calculating a difference for each item in addition to the difference in the furnace heat index,
An operation guidance method in which the abnormality factor is identified based on a difference between the items . The operation guidance method according to claim 1 , wherein the abnormality factor is identified based on a ratio of a difference between the items to a total sum of the items . A method for operating a blast furnace, comprising changing operating conditions based on the abnormality factor indicated by the operation guidance method according to claim 1 or 2 . A method for producing hot metal, comprising producing hot metal using the blast furnace operated by the blast furnace operating method according to claim 3 . An operation guidance device that supports the operation of the blast furnace using a physical model that includes hot metal temperature as an output variable and is capable of calculating the internal state of the blast furnace,
a storage unit that stores the physical model;
a prediction unit that uses the physical model to predict a furnace heat index correlated with the hot metal temperature;
a furnace heat index calculation unit that calculates the furnace heat index based on actual measurements in the blast furnace during operation;
a difference calculation unit that calculates a difference between the predicted furnace heat index and the furnace heat index calculated based on the actual measured value;
a display control unit that displays the cause of the abnormality when it is determined that the operation of the blast furnace is abnormal based on the difference ;
The furnace heat index is the amount of heat per unit time of the heat balance calculated using elements including sensible heat of air, combustion heat of coke and pulverized coal, heat of decomposition of air moisture, heat absorption due to direct reduction, and heat loss. Calculated by dividing by the pig iron speed, each of the above elements per unit amount of hot metal is an item,
The difference calculation unit calculates a difference for each item in addition to the difference in the furnace heat index,
The operation guidance device is characterized in that the cause of the abnormality is identified based on the difference between the items .

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