JP6897260B2 - Phosphorus concentration estimation method in molten steel, converter blowing control device, program and recording medium - Google Patents

Description

The present invention relates to a method for estimating phosphorus concentration in molten steel, a converter blowing control device, a program and a recording medium in MURC operation.

In converter smelting, control of the components in molten steel at the time of blow-off, especially control of phosphorus concentration in molten steel, is very important for quality control of steel. In order to control the phosphorus concentration in molten steel, the amount of oxygen blown, the amount of auxiliary materials such as quicklime or scale added and the timing of adding the auxiliary materials, the height of the top blown lance, the flow rate of top blown oxygen, the flow rate of bottom blown gas, etc. However, it is generally used as an operation amount. These manipulated quantities are often determined by information obtained before the start of blowing, such as the target phosphorus concentration, hot metal data, and criteria created based on past operation results.

However, even under the same operating conditions, there is a problem that the reproducibility of the dephosphorization behavior in actual blowing is low and the variation in the phosphorus concentration in the molten steel at the time of blowing is large. Therefore, it is difficult to suppress the variation in the phosphorus concentration in the molten steel at the time of blowing stop by the blowing with the operation amount determined only based on the information obtained before the start of the blowing as described above.

In order to deal with the above problems, a technique has been developed that utilizes measured values such as exhaust gas components and exhaust gas flow rates that are sequentially obtained during smelting. For example, in Patent Document 1 below, the dephosphorization rate constant is estimated using the operating conditions related to smelting and the measured values related to exhaust gas, and the phosphorus concentration in molten steel during smelting is determined using the estimated dephosphorization rate constant. The technique of estimation is disclosed. Further, in Patent Document 1 below, the estimated phosphorus concentration in molten steel is compared with the target phosphorus concentration in molten steel, and the phosphorus concentration in molten steel is controlled by changing the operating conditions related to blowing based on the comparison result. The technology is disclosed.

Japanese Unexamined Patent Publication No. 2013-23696

In recent years, in primary refining, hot metal pretreatment such as dephosphorization using a converter is generally performed. In particular, the development of a technique called MURC (MUlti Refining Converter: multifunction converter method), which enables the hot metal pretreatment and the decarburization treatment to be consistently performed by the same converter in the primary refining, is underway. Specifically, MURC charges the hot metal into a converter (first step), and performs hot metal pretreatment including addition of flux and dephosphorization by blowing oxygen with a top-blown lance (second step). , A primary consisting of an intermediate waste treatment (third step) in which the converter is tilted to discharge the slag generated in the second step (third step), and then decarburization is carried out by the converter (fourth step). It is a refining operation method. MURC has less heat loss and lead time than the conventional SRP (Simple Refining Process), which is a primary refining operation method in which dephosphorization and decarburization are performed in different converters. Because it is short, it has the advantage of high production efficiency in the steelmaking process.

In this MURC, the slag generated in the dephosphorization treatment, which is the second step described above, is discharged by the intermediate slag treatment, which is the third step. At this time, the amount of slag discharged by the intermediate slag treatment differs depending on the amount of slag generated in the dephosphorization treatment or the quality of the slag.

The phosphorus contained in the hot metal after the intermediate slag treatment is desorbed from the hot metal and incorporated into the slag by the dephosphorization reaction represented by the following chemical formula (101), which may occur in parallel with the decarburization reaction during the decarburization treatment. Or, conversely, it may be separated from the slag and taken into the hot metal again. In the following chemical formula (101), "[substance X]" indicates the substance X in the hot metal, and "(substance Y)" indicates the substance Y in the slag.

The direction in which this dephosphorization reaction proceeds changes depending on the amount and component of slag discharged during the intermediate slag treatment (or the amount and component of slag remaining in the converter). That is, the reaction direction and reaction rate of the dephosphorization reaction depend on the amount of slag discharged during the intermediate slag treatment. Therefore, it is considered that the amount of slag discharged during the intermediate slag treatment affects the phosphorus concentration in the molten steel during the decarburization treatment.

In Patent Document 1, the phosphorus concentration in molten steel is estimated using the operating conditions during the operation of converter blowing, but the amount of slag discharged during the intermediate slag treatment is taken into consideration. Absent. Considering that the concentration of phosphorus in molten steel during the decarburization treatment affects the amount of slag discharged during the intermediate slag treatment, the technique disclosed in Patent Document 1 described above is used in primary refining involving the intermediate slag treatment. It is difficult to estimate the phosphorus concentration in molten steel with high accuracy.

Therefore, the present invention has been made in view of the above problems, and an object of the present invention is that it is possible to accurately estimate the phosphorus concentration in molten steel at the time of shutting down a converter blown in a MURC operation. , To provide new and improved methods for estimating phosphorus concentration in molten steel, converter blow control equipment, programs and recording media.

In order to solve the above problems, according to a certain viewpoint of the present invention, the dephosphorization treatment, the intermediate discharge treatment for discharging the slag generated by the dephosphorization treatment, and the decarburization treatment are carried out in the same manner. A method for estimating the concentration of phosphorus in molten steel used in primary refining using a furnace, in which the furnace tilt angle acquisition step for acquiring the furnace tilt angle of the converter during the intermediate effluent treatment and the furnace tilt angle acquisition step during the decarburization treatment are performed. The exhaust gas data acquisition step for acquiring the exhaust gas component and the exhaust gas flow rate, the molten steel data acquisition step for acquiring the molten steel temperature and the carbon concentration in the molten steel by the sublance measurement at the time of the decarburization treatment, and the desorption obtained in advance by the multiple regression analysis method. Based on the model formula with the phosphorus rate constant as the objective variable, among the operating conditions related to the dephosphorization treatment, the intermediate effluent treatment, and the decarburization treatment, at least the data related to the furnace tilt angle is used to obtain the phosphorus dephosphorization rate constant. The phosphorus concentration in the molten steel at the time of the decarburization treatment after the sublance measurement is estimated by using the calculated dephosphorization rate constant and the hot metal phosphorus concentration at the start of the dephosphorization treatment. A method for estimating the concentration of phosphorus in molten steel, including a concentration estimation step, is provided.
In the calculation of the dephosphorization rate constant, the operating conditions related to the dephosphorization treatment, the intermediate slag treatment, and the decarburization treatment including the data related to the exhaust gas component, the exhaust gas flow rate, the molten steel temperature, and the carbon concentration are further added. You may use it.

In the calculation of the dephosphorization rate constant, a categorical variable that identifies the cluster obtained by the time series clustering performed on the time series data of the plurality of furnace tilt angles acquired in the past operation may be used.

The method for estimating the phosphorus concentration in molten steel further includes a slag level data acquisition step for acquiring the slag level during the dephosphorization treatment, and the data related to the slag level may be further used in the calculation of the dephosphorization rate constant. ..

In the calculation of the dephosphorization rate constant, a categorical variable that identifies the cluster obtained by the time series clustering performed on the plurality of time series data of the slag level acquired in the past operation may be used.

In the calculation of the dephosphorization rate constant, data relating to the decarboxylation efficiency obtained by using the exhaust gas component and the exhaust gas flow rate at the time of the decarburization treatment may be further used.

In calculating the decarboxylation rate constant, a categorical variable that identifies a cluster obtained by time series clustering performed on a plurality of time series data of the decarboxylation efficiency acquired in the past operation may be used. ..

Further, in order to solve the above-mentioned problems, according to another viewpoint of the present invention, a dephosphorization treatment, an intermediate waste treatment for discharging the slag generated by the dephosphorization treatment, and a decarburization treatment are performed. It is a converter blowing control device used for primary refining performed using the same converter, and has a reactor tilt angle data acquisition unit that acquires the reactor tilt angle of the converter during the intermediate waste treatment, and a converter tilt angle data acquisition unit. An exhaust gas data acquisition unit that acquires the exhaust gas component and exhaust gas flow rate during charcoal treatment, a molten steel data acquisition unit that acquires the molten steel temperature and carbon concentration in the molten steel by sublance measurement during the decarburization treatment, and a multiple regression analysis method in advance. Based on the obtained model formula with the dephosphorization rate constant as the objective variable, at least the data related to the reactor tilt angle among the operating conditions related to the dephosphorization treatment, the intermediate effluent treatment, and the decarburization treatment are used. The phosphorus dephosphorization rate constant is calculated, and using the calculated dephosphorization rate constant and the hot metal phosphorus concentration at the start of the dephosphorization treatment, the phosphorus concentration in the molten steel during the decarburization treatment after the sublance measurement is performed. A converter blowing control device is provided, which comprises a phosphorus concentration estimation unit for estimating.

Further, in order to solve the above-mentioned problems, according to another viewpoint of the present invention, a dephosphorization treatment, an intermediate discharge treatment for discharging the slag generated by the dephosphorization treatment, and a decarburization treatment are performed. It is a program for operating a computer as a converter blowing control device used for primary refining performed using the same converter, and is a reactor tilt for acquiring the furnace tilt angle of the converter during the intermediate waste treatment. Angle data acquisition function, exhaust gas data acquisition function to acquire the exhaust gas component and exhaust gas flow rate during the decarburization process, and molten steel data acquisition function to acquire the molten steel temperature and carbon concentration in the molten steel by sublance measurement during the decarburization process. Based on the model formula with the dephosphorization rate constant as the objective variable, which was previously obtained by the multiple regression analysis method, at least the above furnace among the operating conditions related to the dephosphorization treatment, the intermediate waste treatment, and the decarburization treatment The dephosphorization rate constant is calculated using the data related to the tilt angle, and the calculated dephosphorization rate constant and the hot metal concentration at the start of the dephosphorization treatment are used to perform the decarburization treatment after the sublance measurement. A computer is provided with a phosphorus concentration estimation function for estimating the phosphorus concentration in the molten steel at that time.

Further, in order to solve the above-mentioned problems, according to another viewpoint of the present invention, a dephosphorization treatment, an intermediate discharge treatment for discharging the slag generated by the dephosphorization treatment, and a decarburization treatment are performed. It is a recording medium on which a program for operating a computer as a converter blowing control device used for primary refining using the same converter is recorded, and the reactor tilts of the converter during the intermediate waste treatment. The furnace tilt angle data acquisition function that acquires the angle, the exhaust gas data acquisition function that acquires the exhaust gas components and exhaust gas flow rate during the decarburization process, and the sublance measurement during the decarburization process are used to determine the molten steel temperature and carbon concentration in the molten steel. Based on the molten steel data acquisition function to be acquired and the model formula obtained in advance by the multiple regression analysis method with the dephosphorization rate constant as the objective variable, the operating conditions related to the dephosphorization treatment, the intermediate waste treatment, and the decarburization treatment. Of these, the dephosphorization rate constant is calculated using at least the data related to the furnace tilt angle, and the sublance measurement is performed using the calculated dephosphorization rate constant and the hot metal concentration at the start of the dephosphorization process. Provided is a recording medium in which a program for realizing a phosphorus concentration estimation function for estimating the phosphorus concentration in the molten steel at the time of the subsequent decarburization treatment and a computer for realizing the function is recorded.

In the above method for estimating the phosphorus concentration in molten steel, the dephosphorization rate constant is calculated using various data including the furnace tilt angle of the converter and operating conditions, and the phosphorus concentration in molten steel is estimated using the calculated dephosphorization rate constant. Will be done. As a result, in the primary refining in which the dephosphorization treatment, the intermediate slag treatment and the decarburization treatment are consistently performed in the same converter, the operating factor related to the intermediate slag waste generated in the converter is estimated as the phosphorus concentration in the molten steel. Can be reflected in.

Therefore, it is possible to estimate the phosphorus concentration in the molten steel at the time of blowing down the converter in the MURC operation with higher accuracy than before.

It is a graph which shows the 1st example of the time series data of the furnace tilt angle at the time of an intermediate slag processing. It is a graph which shows the 2nd example of the time series data of the furnace tilt angle at the time of an intermediate slag processing. It is a figure which shows the example of the result of the time series clustering performed on the time series data of the furnace tilt angle. It is a graph which shows the example of the time series data of the slag level at the time of dephosphorization processing. It is a figure which shows the example of the result of the time series clustering performed on the time series data of a slag level. It is a figure which shows the example of the result of the time series clustering performed on the time series data of decarboxylation efficiency. It is a figure which shows the structural example of the converter blowing system which concerns on one Embodiment of this invention. This is an example of a flowchart of a method for estimating the phosphorus concentration in molten steel by the converter blowing system according to the same embodiment. It is a graph which shows the example of various time series data acquired or estimated in the primary refining by the converter blowing system which concerns on the same embodiment. It is a graph which shows the standard deviation of the estimation error with respect to the actual value of the phosphorus concentration in molten steel at the time of sublance measurement which concerns on each Example and comparative example.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the present specification and the drawings, components having substantially the same functional configuration are designated by the same reference numerals, so that duplicate description will be omitted.

Pig iron or steel may be present in the converter during the decarburization treatment depending on its carbon concentration. However, in the following description, in order to avoid complicated explanation, the hot metal or the hot metal in the converter For the sake of convenience, molten steel will be referred to as molten steel. In addition, the word hot metal is used for the dephosphorization process.

<< 1. Method for estimating phosphorus concentration in molten steel according to this embodiment >>
Before explaining the configuration and function of the converter blowing system 1 according to the present embodiment, the method for estimating the phosphorus concentration in molten steel according to the present embodiment will be described. In the following description, unless otherwise specified, the unit of concentration of each component (mass%) is described as (%).

(Estimation method of phosphorus concentration in molten steel using operating conditions and operating factors)
Assuming that the time change of the phosphorus concentration [P] (%) in molten steel during blowing is represented by the first-order reaction formula, the first-order reaction formula is expressed as the following formula (1).

Here, [P] _ini is the initial value of phosphorus concentration (hot metal phosphorus concentration) (%), and k is the dephosphorization rate constant (sec ^-1 ). The "initial value of phosphorus concentration" referred to here means the phosphorus concentration at the start of the dephosphorization treatment.

If an accurate dephosphorization rate constant k is obtained, the phosphorus concentration in molten steel can be estimated with high accuracy. However, in general, the dephosphorization rate constant k in actual blowing is not constant and is considered to fluctuate under the influence of various operating conditions. Therefore, for example, as disclosed in Patent Document 1 (Japanese Unexamined Patent Publication No. 2013-23696), not only static information such as hot metal component and hot metal temperature, but also data relating to exhaust gas components to be measured sequentially. In addition, the dephosphorization rate constant k is estimated by utilizing dynamic information during blowing such as exhaust gas data such as data related to the exhaust gas flow rate. Hereinafter, a method for estimating the dephosphorization rate constant k will be described.

From the above formula (1), the phosphorus concentration in the molten steel t seconds after the start of blowing (start of dephosphorization treatment) is expressed as the following formula (2).

Then, the dephosphorization rate constant k for each charge can be obtained by using the past operation record data. For example, dephosphorization rate constant k _i in the charge i is calculated using the following equation (3).

Here, [P] _{end and i} are the phosphorus concentrations (%) in the molten steel at the time of blowing down, and _{tend and i} are the elapsed time (sec) from the start of the dephosphorization reaction up to the time of blowing down.

Then, a model formula with the dephosphorization rate constant k obtained by the above formula (3) as the objective variable is created in advance. This model formula can be constructed by various statistical methods. In this embodiment, a regression equation using various operating factors X as explanatory variables is used as the model equation. The regression equation is obtained by a well-known multiple regression analysis method, and is constructed as, for example, the following equation (4). In actual blowing, the dephosphorization rate constant k is estimated by substituting the operating factor X at the time of the blowing into the following equation (4), and the dephosphorization rate constant k is applied to the above equation (2). Can estimate the phosphorus concentration in molten steel.

Here, α _j is a regression coefficient corresponding to the j-th operating factor X _{j , and α 0} is a constant. Further, specific examples of the operating factor X include the operating factors shown in Table 1 below. However, the operating factors shown in Table 1 below are merely examples, and any operating factor X may be considered in estimating the dephosphorization rate constant k. In addition, all or part of the operating factors included in Table 1 below may be used to estimate the dephosphorization rate constant k.

Further, according to Patent Document 1, the basic unit of accumulated oxygen in the furnace obtained by calculating the oxygen balance from the exhaust gas flow rate during smelting, the exhaust gas component, the upper bottom blown gas flow rate, the amount of auxiliary raw material input, and the hot metal component is , It was shown that the effect on the dephosphorization rate constant is large. Therefore, the dynamic operating factors during blowing, such as the basic unit of accumulated oxygen in the furnace obtained by utilizing the exhaust gas data, the top blowing lance height, the oxygen gas flow rate, and the bottom blowing gas flow rate, are expressed by the above equation ( It is shown that the dephosphorization rate constant can be estimated more accurately by further adopting the explanatory variables of the regression equation shown in 4) in addition to the explanatory variables shown in Table 1.

(Use of data related to furnace tilt angle)
By the way, in the converter blowing method such as MURC described above, the dephosphorization treatment, the intermediate slag treatment and the decarburization treatment are continuously performed by the same converter. Therefore, not only the operating conditions related to the dephosphorization treatment and the decarburization treatment as disclosed in Patent Document 1 but also the operating conditions related to the intermediate slag treatment are used to estimate the dephosphorization rate constant according to the present embodiment. It is considered useful. Operating conditions related to the intermediate slag treatment include, for example, the intermediate slag treatment time and the amount of slag to be slagged.

The present inventors have found that the amount of slag discharged in the middle is closely related to the tilt angle of the furnace during the dephosphorization treatment. For example, in the intermediate slag treatment, when the furnace tilt angle is large or the furnace tilt time is long, a large amount of slag is discharged. On the other hand, when the furnace tilt angle is small or the furnace tilt time is short, the amount of slag discharged is small.

When a large amount of slag is discharged, a large amount of phosphorus contained in the slag is discharged, which is considered to improve the phosphorus removal efficiency. On the other hand, if the amount of slag excreted is small, phosphorus will not be discharged so much, so it is considered that the phosphorus removal efficiency will not be improved so much.

From this, it is considered that the furnace tilt angle in the intermediate slag treatment is related to the magnitude of the phosphorus concentration in the molten steel. Therefore, the present inventors have come up with the idea that the accuracy of estimating the phosphorus concentration in molten steel can be further improved by adopting the furnace tilt angle during the intermediate slag treatment as an operating factor related to the estimation of the phosphorus concentration in molten steel. did. Hereinafter, data related to the tilt angle of the furnace and an example of its use will be described.

FIG. 1 is a graph showing a first example of time-series data of the furnace tilt angle during the intermediate slag treatment. Graphs A to F in FIG. 1 are graphs showing time-series data of furnace tilt angles at different charges. The data shown by each graph is the data obtained by standardizing the actually obtained furnace tilt angle (converting it so that the average = 0 and the standard deviation = 1). The time-series data is time-series data acquired from the start time of tilting of the converter in the intermediate slag treatment to the end time of tilting (that is, the time when the tilt angle of the converter returns to 0 degrees). Further, the horizontal line included in each graph is a line indicating the intermediate discharge angle in the charge corresponding to each graph. The intermediate slag angle means the angle at which slag begins to be discharged when the converter is tilted.

As shown in FIG. 1, the transition of the furnace tilt angle from the start of tilting to reaching the intermediate slag angle is different between graphs A to F. For example, the slope of the change in the furnace tilt angle shown in Graph C is smaller than the slope of the change in the furnace tilt angle shown in Graph A. This is because, first, in the charge corresponding to Graph C, it is predicted that more slag was generated in the converter in the previous dephosphorization process, and the slag spilled out vigorously from the slag pan to receive the slag. It is probable that the converter was gradually tilted so as not to spill. On the other hand, in the charge corresponding to Graph A, it is predicted that not much slag was generated in the converter, and it is considered that the intermediate slag was reached as quickly as possible. That is, even if the intermediate slag angles are substantially the same, it is considered that the difference in the transition of the furnace tilt angle up to the intermediate slag angle indicates that the amount of slag discharged in the middle is different.

FIG. 2 is a graph showing a second example of time-series data of the furnace tilt angle during the intermediate slag treatment. Graphs A and B of FIG. 2 are graphs showing time-series data of furnace tilt angles at different charges. The standardization process of the furnace tilt angle, the acquisition period of the time series data, and the definition of the intermediate discharge angle are the same as the graph of the time series data shown in FIG.

As shown in FIG. 2, even if the transition of the furnace tilt angle from the start of tilting to the arrival at the intermediate slag angle is substantially the same, the subsequent transition of the furnace tilt angle may be different. For example, the intermediate slag angle shown in Graphs A and B and the time required to reach the intermediate slag angle are substantially the same. However, the transition of the furnace tilt angle after reaching the intermediate slag angle is significantly different between Graph A and Graph B. Specifically, the time from the time when the intermediate slag angle is reached to the time when the furnace tilt angle becomes maximum is longer in Graph B than in Graph A. Such a difference in the transition of the furnace tilt angle may be related to the amount of slag discharged from the converter. For example, when the amount of slag generated in the converter is small, the furnace tilt angle is controlled in an attempt to expel the slag quickly, so from the time when the intermediate discharge angle is reached to the time when the furnace tilt angle is maximized. Time will be shorter. On the other hand, when the amount of slag generated in the converter is large, the furnace tilt angle is controlled so that the slag does not flow out of the converter vigorously. Will take longer to reach the maximum.

As shown in FIGS. 1 and 2, the transition of the furnace tilt angle in the intermediate slag treatment is considered to be largely related to the amount of slag generated in the dephosphorization treatment. Therefore, the data related to the furnace tilt angle in the intermediate slag treatment can be used as one of the _{operating factors Xj, which is the explanatory variable of the above equation (4).}

For example, the average value of the time-series data of the furnace tilt angle in the intermediate slag treatment is used as the _{operating factor Xj,} which is an explanatory variable of the above equation (4), which is a regression equation for estimating the dephosphorization rate constant k. You may. As a result, the data related to the furnace tilt angle can be reflected in the estimation of the dephosphorization rate constant k.

Further, for example, a variable based on the time series data of the furnace tilt angle, such as the maximum angle of the furnace tilt angle or the time from the start of the furnace tilt to the arrival at the maximum angle, may be used as an explanatory variable.

Further, for example, a categorical variable that identifies a cluster obtained by performing time series clustering on the time series data of the furnace tilt angle may be used as an explanatory variable. Time-series clustering is a method of finding the distance between time-series data and performing clustering based on the distance.

In the present embodiment, first, time-series clustering is performed in advance on the time-series data of the furnace tilt angle at the beginning of the intermediate slag processing acquired from the past operation data. In this embodiment, the nearest neighbor method of hierarchical clustering is used as the method of time series clustering. The method of time-series clustering is not limited to this method, and may be, for example, the k-means method of non-hierarchical clustering. Further, in the present embodiment, time-series clustering is performed so that these time-series data are classified into four clusters, but the number of clusters is not particularly limited. The number of clusters is appropriately set according to the result of clustering.

FIG. 3 is a diagram showing an example of the result of time series clustering performed on the time series data of the furnace tilt angle. The graphs (a) to (d) of FIG. 3 are graphs showing the results of time-series clustering for the clusters corresponding to the respective categorical variables (No. 1 to 4). The data related to the furnace tilt angle shown in each figure is the data obtained by standardizing the actually obtained furnace tilt angle (converting it so that the average = 0 and the standard deviation = 1). Is. Further, the time-series data of the furnace tilt angle used for the time-series clustering according to the present embodiment is the data obtained from the furnace tilt angle from the start of the furnace tilt to the time when 50 seconds have passed. The time range for selecting the time-series data of the furnace tilt angle used for this time-series clustering is not particularly limited. For example, the time range is the trend of the time-series data of the furnace tilt angle actually obtained between a plurality of charges. , Or it can be set as appropriate based on the operating condition of the converter smelting equipment.

As shown in the graphs (a) to (d) of FIG. 3, the data having high similarity of the time series data of the furnace tilt angle are classified into the same cluster. For example, as shown in the graph of (b), the cluster No. In No. 2, time series data in which the rate of change of the furnace tilt angle up to the intermediate slag angle is relatively low and the rate of change of the furnace tilt angle after the intermediate slag angle is relatively low are classified. On the other hand, as shown in the graph of (c), the cluster No. In No. 3, time-series data in which the rate of change of the furnace tilt angle up to the intermediate slag angle is relatively high and the rate of change of the furnace tilt angle after the intermediate slag angle is relatively high are classified.

In this way, each cluster classified by the clustering executed in advance is compared with the time series data of the furnace tilt angle in the intermediate slag treatment, the cluster with the highest similarity is selected, and the cluster corresponds to the cluster. The categorical variable can be adopted as the _{operating factor Xj,} which is the explanatory variable of the above equation (4). As a result, the state of slag slag in the intermediate slag treatment can be reflected in the estimation of the phosphorus concentration in the molten steel. Such a difference in the slag slag discharge situation affects the dephosphorization efficiency in the subsequent decarburization treatment. Therefore, since the difference in the state of slag slag discharge in the intermediate slag treatment is added to the estimation of the phosphorus concentration in the molten steel, it is possible to further improve the estimation accuracy of the phosphorus concentration in the molten steel.

(Use of data related to slag level)
Further, in the method for estimating the phosphorus concentration in molten steel according to the embodiment of the present invention, data related to the slag level can be used in addition to the data related to the above-mentioned furnace tilt angle. As described above, the amount of slag discharged in the middle is considered to have a great influence on the phosphorus concentration in the molten steel during the decarburization treatment.

The present inventors have found that the amount of slag discharged in the middle is closely related to the slag level (slag height) during the dephosphorization treatment. For example, in the intermediate slag treatment, when the slag level is high, the slag is likely to be slag. In this case, since a larger amount of phosphorus contained in the slag is discharged, it is considered that the dephosphorization efficiency is improved. On the other hand, when the slag level is low, the slag is less likely to be discharged. In this case, phosphorus is not discharged so much, so it is considered that the phosphorus removal efficiency is not improved so much.

From this, it is considered that the slag level in the intermediate slag treatment is related to the magnitude of the phosphorus concentration in the molten steel. Therefore, the present inventors have adopted the slag level of slag that may occur in the converter during blowing during the dephosphorization process as an operating factor for estimating the phosphorus concentration in molten steel, thereby estimating the phosphorus concentration in molten steel. I came up with the idea that it can be improved. Hereinafter, data related to the slag level and an example of its use will be described.

FIG. 4 is a graph showing an example of time-series data of the slag level during the dephosphorization process. The data shown by the graph is data obtained by standardizing the actually obtained slag level (converting it so that the average = 0 and the standard deviation = 1). The time-series data is time-series data acquired from the start of blowing in the dephosphorization process to the time of stopping.

With reference to FIG. 4, it can be seen that the slag level is increased at the final stage of the dephosphorization treatment. That is, the formation of slag (slag forming) is progressing at the final stage of the dephosphorization treatment. Therefore, in the present embodiment, the data related to the slag level at the final stage of the dephosphorization treatment can be used as one of the _{operating factors Xj, which is the explanatory variable of the above equation (4).}

For example, the average value of the time-series data of the slag level at the end of the dephosphorization process is used as the _{operating factor Xj,} which is an explanatory variable of the above equation (4), which is a regression equation for estimating the dephosphorization rate constant k. May be good. As a result, the amount of slag generated by the dephosphorization treatment can be reflected in the estimation of the dephosphorization rate constant k.

Further, for example, the intermediate value of the time-series data of the slag level at the time of stopping the blowing in the dephosphorization treatment or the slag level at the end of the blowing (specifically, the slag level at the central time of the measurement target period) or Variables based on the slag level time series data, such as the rate of change of the time series data (specifically, the rate of change of the slag level during the measurement target period), may be used as the explanatory variables.

Further, for example, a categorical variable that identifies a cluster obtained by performing the above-mentioned time series clustering on slag level time series data may be used as an explanatory variable. In the present embodiment, first, time-series clustering is performed in advance on the slag-level time-series data at the end of the dephosphorization process acquired from the past operation data. Further, in the present embodiment, time-series clustering is performed so that these time-series data are classified into six clusters. The number of clusters is not particularly limited, and is appropriately set according to the result of clustering.

FIG. 5 is a diagram showing an example of the result of time series clustering performed on the slag level time series data. The graphs (a) to (f) of FIG. 5 are graphs showing the results of time-series clustering for the clusters corresponding to each categorical variable (No. 1 to 6). The data related to the slag level shown in each figure is the data obtained by standardizing the actually obtained slag level (converting it so that the average = 0 and the standard deviation = 1). .. Further, the time-series data of the slag level used for the time-series clustering according to the present embodiment is the data obtained from the slag level from the time of blowing down to the time of 50 seconds before each other. The time range for selecting the slag level time series data used for this time series clustering is not particularly limited. For example, the time range is the trend of the slag level time series data actually obtained by the level meter, or the converter. It can be set as appropriate based on the operating condition of the slag facility.

As shown in the graphs (a) to (f) of FIG. 5, the data having high similarity of the slag level time series data are classified into the same cluster. For example, as shown in the graph of (b), the cluster No. In No. 2, time-series data having a high rate of increase in slag level and having a high slag level over the entire time-series data are classified. On the other hand, as shown in the graph of (e), the cluster No. Time series data in which the change in the transition of the slag level is small is classified into No. 5.

In this way, the categorical variable that identifies the cluster obtained by the time series clustering performed on the slag level time series data can be adopted as the _{operating factor Xj which is the explanatory variable of the above equation (4).} As a result, not only the amount of slag generated in the dephosphorization treatment but also the tendency of slag forming at the final stage of the dephosphorization treatment can be reflected in the estimation of the phosphorus concentration in the molten steel. The difference in the tendency of slag forming is considered to be based on the slag properties such as the slag component. Therefore, the influence of the slag property on the dephosphorization reaction is further added to the estimation of the phosphorus concentration in the molten steel, so that the estimation accuracy of the phosphorus concentration in the molten steel can be further improved.

(Use of data related to decarboxylation efficiency)
Further, in the method for estimating the phosphorus concentration in molten steel according to the embodiment of the present invention, in addition to the above data on the furnace tilt angle, data on the decarboxylation efficiency in the decarburization treatment can be used. Decarboxylation efficiency is an index showing the efficiency of the reaction between oxygen blown into the converter and carbon in molten steel in the decarboxylation treatment.

The decarboxylation efficiency k ₀ [i] (% / (Nm ³ / ton)) is calculated using the following formula (5) based on the exhaust gas flow rate measured at regular intervals and the exhaust gas information including the exhaust gas components. To.

Here, CO [i + N] (%) is the CO concentration in the exhaust gas, CO ₂ [i + N] (%) is the CO ₂ concentration _{in the exhaust gas, and Voffgas} [i] (Nm ³ / hr (NTP)) is the total exhaust gas. flow ^{_{rate, F O2 [i] (Nm}} 3 / hr (NTP)) is an input amount of oxygen into the converter furnace until decarboxylation oxygen efficiency _k 0 [i] calculated from the blowing begin. Incidentally, F _{O2 [i]} can be calculated from the blowing amount of oxygen by a static control may be determined before blowing start. Further, i in square brackets [] represents the sampling period in the measurement of the exhaust gas flow rate and the exhaust gas component. Further, N in square brackets [] corresponds to the analysis delay by the exhaust gas component analyzer (the time delay until the exhaust gas reaches the installation position of the exhaust gas component analyzer). The specific value of the analysis delay N may be appropriately determined according to the installation position of the exhaust gas component analyzer in the flue and the like. In addition, "NTP" means Normal Temperature Pressure.

The above equation (5) is derived as follows. The decarburized amount wc [i] (g / sec) per unit time obtained from the exhaust gas information is calculated by the following formula (6).

Here, the _{reason why Voffgas} [i] is divided by 1000 × 3600 is to convert the unit to (L / sec). Moreover, the reason why it is divided by 22.4 (L / mol) is to convert it into the number of moles. Further, 12 is the atomic weight of carbon.

Since the decarboxylation efficiency k ₀ [i] is defined as the decarboxylation amount (% by weight ^{) divided by the oxygen intensity (Nm 3} / ton), the decarboxylation efficiency k ₀ [i] is as follows. It is expressed by the mathematical formula (7). Here, Wst is the weight of molten steel (ton). By substituting the following equation (7) into the above equation (6), the above equation (5) can be obtained.

In the decarburization treatment, a CaO source such as quicklime or slaked lime can be put into the converter in order to proceed with the further dephosphorization treatment in parallel with the decarburization treatment. By adding the CaO source, the dephosphorization reaction represented by the above formula (101) is promoted even in the decarburization treatment, and the phosphorus concentration in the molten steel can be further reduced. The degree of progression of such dephosphorization reaction is related to the slagging status of the CaO source. For example, if the dephosphorization reaction is promoted, the slagging of the CaO source will proceed.

It is considered that the slagging of the CaO source is facilitated by the oxygen blown into the converter reacting with Fe in the molten steel to generate a large amount of FeO. In this case, the rate at which oxygen blown into the converter reacts with carbon in the molten steel may decrease. That is, the decarboxylation efficiency can be low. From this, it can be considered that if the decarboxylation efficiency is low, more FeO is produced in the converter, CaO slagging progresses, and the dephosphorylation reaction proceeds more. Therefore, the decarboxylation efficiency can be an index that can reflect the phosphorus concentration in the molten steel.

Therefore, the present inventors adopted the decarboxylation efficiency, which reflects the CaO concentration in the slag during the decarburization treatment, as an operating factor for estimating the phosphorus concentration in the molten steel, thereby increasing the phosphorus concentration in the molten steel. I came up with the idea that the estimation accuracy can be further improved. Hereinafter, data on decarboxylation efficiency and examples of its use will be described.

The decarboxylation efficiency fluctuates greatly at the beginning of the decarboxylation treatment, and then gradually converges to a substantially constant value. The fluctuation in decarboxylation efficiency at the beginning is considered to be due to the slagging of the CaO source due to the progress of the decarboxylation reaction on the surface of the converter. Therefore, in the present embodiment, the data related to the decarboxylation efficiency at the beginning of the decarburization treatment can be used as one of the _{operating factors Xj, which is the explanatory variable of the above formula (4).}

For example, the average value of the time-series data of the decarboxylation efficiency at the beginning of the decarboxylation treatment is used as the _{operating factor Xj,} which is an explanatory variable of the above equation (4), which is a regression equation for estimating the decarboxylation rate constant k. May be done. Thereby, the degree of progress of slagging of the CaO source due to the progress of the dephosphorization reaction can be reflected in the estimation of the dephosphorization rate constant k.

Further, for example, the maximum value, the minimum value, or the intermediate value (specifically, the decarboxylation efficiency at the time in the middle of the measurement target period) or the time series of the time series data of the decarboxylation efficiency at the beginning of the decarboxylation treatment. Variables based on time-series data of decarboxylation efficiency, such as the rate of change of data (specifically, the rate of change of decarboxylation efficiency during the measurement target period), may be used as explanatory variables.

Further, for example, a categorical variable that identifies a cluster obtained by performing the above-mentioned time series clustering on the time series data of decarboxylation efficiency may be used as an explanatory variable. In the present embodiment, first, time-series clustering is performed in advance on the time-series data of the decarboxylation efficiency at the beginning of the decarburization treatment acquired from the past operation data. Further, in the present embodiment, time-series clustering is performed so that these time-series data are classified into six clusters. The number of clusters is not particularly limited, and is appropriately set according to the result of clustering.

FIG. 6 is a diagram showing an example of the result of time series clustering performed on the time series data of decarboxylation efficiency. The graphs (a) to (f) of FIG. 6 are graphs showing the results of time-series clustering for the clusters corresponding to each categorical variable (No. 1 to 6). The data related to the decarboxylation efficiency shown in each figure can be obtained by standardizing the actually calculated decarboxylation efficiency (converting the data so that the average = 0 and the standard deviation = 1). Data. Further, the time-series data of the decarboxylation efficiency used for the time-series clustering according to the present embodiment is the data obtained from the decarboxylation efficiency from the start of the decarboxylation treatment to the time when 50 seconds have passed. is there. The time range for selecting the time-series data of the decarboxylation efficiency used for this time-series clustering is not particularly limited. For example, the time range is the trend or change of the time-series data of the decarboxylation efficiency actually obtained. It can be set as appropriate based on the operating conditions of the furnace smelting equipment.

As shown in the graphs (a) to (f) of FIG. 6, the data having high similarity of the time series data of the decarboxylation efficiency are classified into the same cluster. For example, as shown in the graph of (b), the cluster No. Time series data in which the decarboxylation efficiency is gradually increasing is classified into 2. On the other hand, cluster No. In No. 4, time series data in which the decarboxylation efficiency hardly changes are classified.

In this way, the categorical variable that identifies the cluster obtained by the time-series clustering performed on the time-series data of the decarboxylation efficiency can be adopted as the _{operating factor Xj which is the explanatory variable of the above equation (4).} it can. As a result, the degree of progress of slagging of the CaO source input during the decarburization treatment can be reflected in the estimation of the phosphorus concentration in the molten steel. The degree of progress of slagging of CaO sources is closely related to the degree of progress of dephosphorization reaction. Therefore, since the degree of progress of the dephosphorization reaction in the decarburization treatment is further added to the estimation of the phosphorus concentration in the molten steel, it is possible to further improve the estimation accuracy of the phosphorus concentration in the molten steel.

(Use of clustering results during actual operation)
Next, a method of using the above-mentioned clustering result of each time series data for estimating the dephosphorization rate constant k during actual operation will be described. Here, an example using time-series data of the furnace tilt angle will be described.

First, time-series clustering is performed in advance on the time-series data of the furnace tilt angle at the beginning of the intermediate waste treatment acquired from the past operation data, and the time-series data is classified into a plurality of clusters. Then, a regression equation (the above equation (4)) in which the categorical variable for each cluster is one of the explanatory variables is constructed.

_{Next, the average values β ave and j} at the measurement points j (j = 1 to n) of the plurality of time series data of the furnace tilt angles classified into each cluster are calculated for each measurement point. The measurement point means the time point at which the furnace tilt angle is measured in the target range of the time series data. For example, in each cluster shown in FIG. 3, each time series data from the start of tilting the furnace to the time when 50 seconds have passed is classified. If the furnace tilt angle is measured every second, the number of measurement points will be 50 points.

_{Next, the time-series data (S j} ) of the furnace tilt angle at the time of the actual intermediate waste treatment, which is the target for estimating the dephosphorization rate constant k, is acquired, and the time-series data S _j and the above average value β _{ave are acquired. Find the difference from, j} for each cluster. The cluster with the smallest difference is determined to be the cluster to which the time series data ( _Sj ) belongs, and the categorical variables corresponding to this cluster are used as explanatory variables related to the operating factors. The difference may be, for example, the sum of squared differences represented by the following equation (8). The difference is appropriately obtained by a known statistical method. The dephosphorization rate constant k can be calculated by substituting the obtained categorical variable into the constructed regression equation together with other explanatory variables.

Further, the clustering result of the time series data of the slag level and the time series data of the decarboxylation efficiency can also be used for estimating the decarboxylation rate constant k by the above-mentioned method. It is also possible to estimate the decarboxylation rate constant k using the time-series data of the furnace tilt angle, the time-series data of the slag level, and / or the time-series data of the decarboxylation efficiency. That is, if time-series clustering is performed for each type of time-series data in advance and a regression equation is constructed in which the categorical variable corresponding to the clustering result is one of the explanatory variables, the dephosphorization rate of a plurality of time-series data can be obtained. It can be used to estimate the constant k. Thereby, the estimation accuracy of the dephosphorization rate constant k can be further improved.

The method for estimating the phosphorus concentration in molten steel according to the present embodiment has been described above.

<< 2. Converter blowing system according to this embodiment >>
<2.1. Configuration of converter blowing system>
Subsequently, an example of a system for realizing the method for estimating the phosphorus concentration in molten steel according to the present embodiment shown above will be described. FIG. 7 is a diagram showing a configuration example of a converter blowing system according to an embodiment of the present invention. Referring to FIG. 7, the converter smelting system 1 according to the present embodiment includes a converter smelting facility 10, a converter smelting control device 20, a measurement control device 30, and an operation database 40.

(Conversion furnace blowing equipment)
The converter blowing equipment 10 includes a converter 11, a flue 12, a top blowing lance 13, a sub lance 14, an exhaust gas component analyzer 101, an exhaust gas flow meter 102, a level meter 103, and an angle meter 104. The converter blowing facility 10 starts and stops the supply of oxygen to the hot metal by the top blowing lance 13 based on the control signal output from the measurement control device 30, for example, the component concentration in the molten steel by the sublance 14 and the molten steel. The temperature is measured, cold materials and auxiliary raw materials (for example, quicklime, etc.) are added, and the hot metal and slag slag are discharged by the converter 11. The converter blowing facility 10 includes an acid feeder for supplying oxygen to the top blowing lance 13, a cold material charging device having a drive system for charging cold material to the converter 11, and a converter. Various devices used for blowing by a general converter, such as an auxiliary raw material charging device having a drive system for charging the auxiliary raw material into the furnace 11, may be provided.

A top-blown lance 13 used for blowing is inserted from the furnace mouth of the converter 11, and oxygen 15 sent from the acid feeder is supplied to the hot metal in the furnace through the top-blown lance 13. Further, for stirring the hot metal, an inert gas such as nitrogen gas or argon gas may be introduced from the bottom of the converter 11 as a bottom-blown gas 16. In the converter 11, hot metal from the blast furnace, a small amount of iron scrap, a cold material for adjusting the hot metal (molten steel) temperature, and auxiliary raw materials for forming slag such as quicklime, which is a CaO source, are input. Will be done. When the auxiliary material is powder, it may be supplied into the converter 11 together with oxygen 15 through the top-blown lance 13.

In the primary refining, as shown in the chemical formula (101), phosphorus contained in the hot metal chemically reacts with FeO contained in the slag in the converter and auxiliary raw materials containing CaO-containing substances (phosphorus dephosphorization reaction). Phosphorus is taken into the slag. That is, the dephosphorization reaction is promoted by increasing the concentration of iron oxide in the slag by blowing. The dephosphorization reaction can proceed mainly during the dephosphorization treatment, but it can also occur during the decarburization treatment.

Further, in the primary refining, carbon in the hot metal undergoes an oxidation reaction with oxygen supplied from the top-blown lance 13 (decarburization reaction). As a result, CO or CO ₂ exhaust gas is generated. These exhaust gases are discharged from the converter 11 to the flue 12.

As described above, in the converter blowing, the blown oxygen reacts with carbon, phosphorus, silicon or the like in the hot metal to generate an oxide. The oxide produced here is discharged as exhaust gas or stabilized as slag. Carbon is removed by the oxidation reaction in blowing, and phosphorus and the like are taken into the slag and removed to produce steel with low carbon content and few impurities.

Further, the sublance 14 inserted from the furnace opening of the converter 11 has its tip immersed in molten steel at a predetermined timing during decarburization treatment to measure the component concentration in the molten steel including the carbon concentration, the molten steel temperature, and the like. Used for. The measurement of molten steel data such as component concentration and / or molten steel temperature by the sublance 14 is called sublance measurement. The molten steel data obtained by the sublance measurement is transmitted to the converter blowing control device 20 via the measurement control device 30.

The exhaust gas generated by blowing flows into the flue 12 provided outside the converter 11. The flue 12 is provided with an exhaust gas component analyzer 101 and an exhaust gas flow meter 102. The exhaust gas component analyzer 101 analyzes the components contained in the exhaust gas. The exhaust gas component analyzer 101 analyzes, for example, the concentrations of _{CO and CO 2 contained in the exhaust gas.} The exhaust gas flow meter 102 measures the flow rate of the exhaust gas. The exhaust gas component analyzer 101 and the exhaust gas flow meter 102 sequentially perform component analysis and flow rate measurement of the exhaust gas in a predetermined sampling cycle (for example, 5 to 10 (sec) cycle). The component analysis and flow rate measurement of the exhaust gas are preferably performed at least during the decarburization treatment, and are converted to the calculation of the oxygen accumulated oxygen intensity in the furnace used as the explanatory variable of the regression equation shown in the above equation (4). It is preferably carried out throughout the furnace smelting. The data related to the exhaust gas component analyzed by the exhaust gas component analyzer 101 and the data related to the exhaust gas flow rate measured by the exhaust gas flow meter 102 (hereinafter, these data are referred to as "exhaust gas data") are the measurement control device 30. It is output as time-series data to the converter smelting control device 20 via the above. In order for the converter smelting control device 20 to sequentially estimate the phosphorus concentration in molten steel, it is preferable that the exhaust gas data is sequentially output to the converter smelting control device 20.

Further, the converter blowing facility 10 may include a level meter 103 in the vicinity of the opening of the converter 11. The level meter 103 is a device for measuring the bath surface level of hot metal (molten steel), slag, etc. in the converter 11 at the time of blowing the converter. In this specification, this bath surface level is referred to as a slag level.

The slag level obtained by the level meter 103 is information that reflects the slag slag status, and is used directly or indirectly as an explanatory variable of the regression equation shown in the equation (4). The level meter 103 sequentially measures the slag level in a predetermined sampling cycle (for example, a 1-second cycle). The data related to the slag level obtained by the level meter 103 is output as time series data to the converter blowing control device 20 via the measurement control device 30.

This level meter 103 can be realized by, for example, a microwave emitting device, an antenna, an arithmetic device, or the like as disclosed in Japanese Patent Application Laid-Open No. 2015-110817. In the level meter disclosed in the above document, the microwave emitting device emits microwaves into the inside of the converter, the antenna detects the reflected waves reflected on the bath surface, and the arithmetic device detects the emitted microwaves and the emitted microwaves. The bath surface level is measured based on the detected reflected wave.

When the data related to the slag level is not used for estimating the dephosphorization rate constant k in the present embodiment, the level meter 103 may not be provided in the converter blowing facility 10.

Further, the converter blowing facility 10 includes an angle meter 104 attached to the tilt shaft of the converter 11. The angle meter 104 is a device for detecting the tilt angle of the converter 11 in the intermediate slag treatment.

The furnace tilt angle obtained by the angle meter 104 is information that reflects the slag slag discharge status in the intermediate slag treatment, and is directly or indirectly as an explanatory variable of the regression equation shown in the above equation (4). Used. The angle meter 104 detects the tilt angle of the furnace sequentially at a predetermined sampling cycle (for example, a cycle of 1 second). The data related to the furnace tilt angle obtained by the angle meter 104 is output as time series data to the converter blowing control device 20 via the measurement control device 30.

The angle meter 104 can be realized by, for example, an absolute coder. In addition, the angle meter 104 can be realized by a known measuring device such as a gyroscope or an inclinometer that can detect the rotation angle of the tilt axis of the converter 11.

(Conversion furnace blowing control device)
The converter smelting control device 20 includes a data acquisition unit 201, a cluster determination unit 202, a clustering execution unit 203, a phosphorus concentration estimation unit 204, a converter smelting database 21 and an input / output unit 22. The rotary furnace blowing control device 20 includes hardware configurations such as a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), a storage and a communication device, and data is obtained by these hardware configurations. The functions of the acquisition unit 201, the cluster determination unit 202, the clustering execution unit 203, and the phosphorus concentration estimation unit 204 are realized. Further, the converter smelting database 21 is a database for storing various data used in the converter smelting control device 20, and is realized by a storage device such as storage. Further, the input / output unit 22 is realized by an input device such as a keyboard, a mouse or a touch panel, an output device such as a display or a printer, and a communication device.

The converter smelting control device 20 has various data stored in the converter smelting database 21, exhaust gas data acquired from the exhaust gas component analyzer 101 and the exhaust gas flow meter 102, molten steel data acquired from the sublance 14, and levels. The phosphorus concentration in molten steel is estimated using the data related to the slag level acquired from the total 103 and the data related to the reactor tilt angle acquired from the angle meter 104 as input values. The phosphorus concentration in molten steel is estimated by the function of each functional unit of the converter blowing control device 20. Further, the converter smelting control device 20 may use the estimated phosphorus concentration in molten steel to control the operation in the converter smelting. For example, when it is determined that the estimated phosphorus concentration in molten steel exceeds the target phosphorus concentration in molten steel (stored in the target data 212), the converter blown control device 20 targets the phosphorus concentration in molten steel. The operating conditions of converter blowing can be changed so that the concentration is lower than the phosphorus concentration in molten steel. If the phosphorus concentration in the molten steel can be estimated with high accuracy in this way, the quality of the molten steel obtained by the primary refining can be maintained high.

The specific functions of each functional unit of the converter blowing control device 20 according to the present embodiment will be described later.

Further, the converter blowing control device 20 has a function of controlling the entire process related to converter blowing such as blowing oxygen into the converter 11 and charging cold materials and auxiliary raw materials. Further, for example, the converter blowing control device 20 uses a predetermined mathematical model or the like before the start of blowing, which is performed in general static control, to blow oxygen into the converter 11 and to reduce the amount of cold material. It has a function of determining the input amount (hereinafter referred to as the cold material amount) and the input amount of auxiliary raw materials. Further, for example, the converter blowing control device 20 has a function of controlling the measurement target, the measurement timing, and the like of the sublance measurement performed in general dynamic control.

Specific treatments for each function (not shown) (for example, the above-mentioned control method for inputting cold materials and auxiliary materials, static control determines the amount of oxygen blown and the amount of input of various cold materials and auxiliary materials before the start of blowing. Since various known methods can be applied as the method of performing the sublance measurement and the method of controlling the sublance measurement), detailed description thereof will be omitted here.

The converter blowing database 21 stores, for example, hot metal data 211, target data 212, parameter 213, and the like, as shown in FIG. These data may be added, updated, modified, or deleted via an input device or communication device (not shown). For example, among various data stored in the operation database 40 described later, data used for converter blowing may be added to the converter blowing database 21. Various data stored in the converter blowing database 21 are read out by the data acquisition unit 201. The storage device having the converter blowing database 21 according to the present embodiment is configured integrally with the converter blowing control device 20 as shown in FIG. 7, but in other embodiments, it is configured. The storage device having the converter blowing database 21 may have a configuration separated from the converter blowing control device 20.

The hot metal data 211 is various data related to hot metal in the converter 11. For example, the hot metal data 211 includes information about hot metal (initial hot metal weight for each charge, concentration of hot metal components (carbon, phosphorus, silicon, iron, manganese, etc.), hot metal temperature, hot metal ratio, etc.). In addition to the hot metal data 211, various information generally used in the hot metal pretreatment and the decarburization treatment (for example, information on the input of auxiliary raw materials and cold materials (information on the amount of auxiliary raw materials and cold materials)). , Information about sublance measurement (information about measurement target, measurement timing, etc.), information about blown oxygen amount, etc.) may be included. The target data 212 includes data such as a target component concentration and a target temperature in hot metal (in molten steel) after dephosphorization treatment, after decarburization treatment, and during sublance measurement. Parameter 213 is various parameters used in the cluster determination unit 202 and the phosphorus concentration estimation unit 204. For example, the parameter 213 includes a parameter in the regression equation using the operating factor as an explanatory variable, and a parameter for estimating the phosphorus concentration (such as the dephosphorization rate constant).

The input / output unit 22 has a function of acquiring, for example, the estimation result of the phosphorus concentration in molten steel by the phosphorus concentration estimation unit 204 and outputting it to various output devices. For example, the input / output unit 22 may display the estimated phosphorus concentration in molten steel to the operator. Further, when the converter blowing control device 20 performs converter blowing control based on the estimated phosphorus concentration in molten steel, the input / output unit 22 relates to converter blowing based on the estimated phosphorus concentration in molten steel. The instruction may be output to the measurement control device 30. In this case, the instruction may be an instruction automatically generated by the function related to the converter smelting control of the converter smelting control device 20, or the indicated phosphorus concentration in molten steel (estimated value). It may be an instruction input by the operation of the operator who browses the information related to. Further, the input / output unit 22 may have an input interface function for adding, updating, changing, or deleting various data stored in the converter blowing database 21. Further, the input / output unit 22 may output various data acquired by the data acquisition unit 201, the determination result by the cluster determination unit 202, and the estimation result by the phosphorus concentration estimation unit 204 to the operation database 40.

(Measurement control device)
The measurement control device 30 includes a hardware configuration such as a CPU, ROM, RAM, storage, and a communication device. The measurement control device 30 has a function of communicating with each device provided in the converter blowing facility 10 and controlling the overall operation of the converter blowing facility 10. For example, the measurement control device 30 tilts the converter 11 for intermediate waste treatment, inputs cold materials and auxiliary raw materials to the converter 11, and top blows in response to an instruction from the converter blowing control device 20. It controls the operations related to the blowing of oxygen 15 of the lance 13, the immersion of the sub lance 14 in the molten steel, the measurement of the sub lance, and the like. Further, the measurement control device 30 acquires data obtained from each device of the converter blowing equipment 10 such as the exhaust gas component analyzer 101, the exhaust gas flow meter 102, the level meter 103, the angle meter 104, and the sublance 14. It is transmitted to the converter smelting control device 20.

(Operation database)
The operation database 40 is a database realized by a storage device such as storage, and is a database for storing various data related to the operation of converter blowing. The various data include data obtained from each device of the converter blowing facility 10 acquired by the data acquisition unit 201, a determination result by the cluster determination unit 202, and an estimation result by the phosphorus concentration estimation unit 204.

For example, the operation database 40 according to the present embodiment accumulates data related to the furnace tilt angle measured by the angle meter 104 for each operation. Further, the operation database 40 according to the present embodiment can accumulate data related to the slag level measured by the level meter 103 for each operation. In addition, the operation database 40 according to the present embodiment can accumulate data related to decarboxylation efficiency obtained from exhaust gas data measured by the exhaust gas component analyzer 101 and the exhaust gas flow meter 102 for each operation.

The operation database 40 according to the present embodiment outputs data related to the furnace tilt angle for each operation to the clustering execution unit 203. Further, the operation database 40 according to the present embodiment can output data related to the slag level for each operation and / or data related to the decarboxylation efficiency for each operation to the clustering execution unit 203. The storage device having the operation database 40 according to the present embodiment is configured separately from the converter blowing control device 20 as shown in FIG. 7, but in other embodiments, the operation database 40 The storage device having the above may be configured to be integrated with the converter blowing control device 20.

<2.2. Configuration and functions of each functional part>
Next, the configuration and function of each functional unit of the converter blowing control device 20 according to the present embodiment will be described.

Referring to FIG. 7 again, the converter blowing control device 20 according to the present embodiment is provided with each functional unit of the data acquisition unit 201, the cluster determination unit 202, the clustering execution unit 203, and the phosphorus concentration estimation unit 204.

(Data acquisition department)
The data acquisition unit 201 acquires various data for estimating the phosphorus concentration in the molten steel. For example, the data acquisition unit 201 acquires the hot metal data 211, the target data 212, and the parameter 213 stored in the converter blowing database 21. That is, the data acquisition unit 201 has a function as a hot metal data acquisition unit. These data are acquired at the latest before the process of estimating the phosphorus concentration in molten steel by the phosphorus concentration estimation unit 204 is started. The data acquisition unit 201 according to the present embodiment acquires various data stored in the converter blowing database 21 before the start of converter blowing.

Further, the data acquisition unit 201 acquires exhaust gas data output from the exhaust gas component analyzer 101 and the exhaust gas flow meter 102. That is, the data acquisition unit 201 has a function as an exhaust gas data acquisition unit. The acquired exhaust gas data is time series data. The acquisition of exhaust gas data is carried out throughout the primary refining. The data acquisition unit 201 according to the present embodiment sequentially acquires exhaust gas data sequentially measured by the exhaust gas component analyzer 101 and the exhaust gas flow meter 102. In another embodiment, the data acquisition unit 201 may collectively acquire the exhaust gas data during the dephosphorization treatment after the dephosphorization treatment.

In addition, the data acquisition unit 201 can calculate the decarboxylation efficiency from the acquired exhaust gas data. That is, the data acquisition unit 201 has a function as a decarboxylation efficiency calculation unit. The decarboxylation efficiency is time-series data obtained by using the above formula (5) from the acquired time-series data of the exhaust gas flow rate and the exhaust gas component. The data acquisition unit 201 according to the present embodiment calculates at least time-series data of the decarboxylation efficiency from the start time of the decarburization treatment to the elapse of a predetermined time from the exhaust gas data measured sequentially. In another embodiment, the data acquisition unit 201 collectively acquires the exhaust gas data from the start time of the decarboxylation process to the elapse of a predetermined time before the intermediate sublance measurement, and removes the exhaust gas data from the acquired exhaust gas data. Time series data of carbonate efficiency may be calculated.

Further, the data acquisition unit 201 acquires data related to the slag level output from the level total 103. That is, the data acquisition unit 201 has a function as a slag level data acquisition unit. The data related to the acquired slag level is time series data. The acquisition of the slag level is performed during the dephosphorization process. The data acquisition unit 201 according to the present embodiment sequentially acquires data related to the slag level, which is sequentially measured by the level meter 103 during the dephosphorization process. In another embodiment, the data acquisition unit 201 may collectively acquire the data related to the slag level during the dephosphorization process after the dephosphorization process.

Further, the data acquisition unit 201 acquires data related to the furnace tilt angle output from the angle meter 104. That is, the data acquisition unit 201 has a function as a furnace tilt angle data acquisition unit. The acquired data related to the tilt angle of the furnace is time series data. The acquisition of the furnace tilt angle is performed during the intermediate slag treatment. The data acquisition unit 201 according to the present embodiment sequentially acquires data related to the furnace tilt angle of the converter 11 which is sequentially measured by the angle meter 104 during the intermediate slag processing. In another embodiment, the data acquisition unit 201 may collectively acquire the data related to the furnace tilt angle during the intermediate slag processing after the intermediate slag processing.

In addition, the data acquisition unit 201 acquires molten steel data obtained by sublance measurement by the sublance 14 during the decarburization process. That is, the data acquisition unit 201 has a function as a molten steel data acquisition unit.

In addition to the various data described above, the data acquisition unit 201 acquires data related to the dephosphorization process, the intermediate slag removal process, and the decarburization process. The data acquisition unit 201 acquires data output from various devices provided in the converter blowing facility 10 via the measurement control device 30.

The data acquisition unit 201 outputs the acquired data to the cluster determination unit 202 and the phosphorus concentration estimation unit 204. Further, the data acquired by the data acquisition unit 201 is stored in the operation database 40.

(Cluster determination unit, clustering execution unit)
The cluster determination unit 202 determines the cluster having the highest degree of similarity with respect to the time-series data of the furnace tilt angle acquired from the data acquisition unit 201 among the plurality of clusters fetched by the clustering execution unit 203. The categorical variables corresponding to the clusters determined by the cluster determination unit 202 are output to the phosphorus concentration estimation unit 204. _{The categorical variable is used as an operating factor Xj,} which is an explanatory variable of the regression equation shown in the equation (4) used for estimation by the phosphorus concentration estimation unit 204.

Further, the clustering execution unit 203 clusters the time-series data of the furnace tilt angle in the past operation acquired from the operation database 40 to obtain a plurality of clusters. The information related to the cluster obtained by the clustering execution unit 203 is output to the cluster determination unit 202. Further, the information related to the cluster may be output to the operation database 40. Further, the clustering execution unit 203 may appropriately perform clustering when the time series data of the furnace tilt angle in the past operation stored in the operation database 40 is updated.

The slag level time series data and the decarboxylation efficiency time series data can also be processed by the cluster determination unit 202 and the clustering execution unit 203 according to the present embodiment. For example, the clustering execution unit 203 may perform clustering on the slag level time series data in the past operation acquired from the operation database 40 to obtain a plurality of clusters. In this case, the cluster determination unit 202 may determine the cluster having the highest degree of similarity with respect to the slag level time series data acquired by the data acquisition unit 201 among the plurality of clusters.

Further, for example, the clustering execution unit 203 may perform clustering on the time series data of the decarboxylation efficiency in the past operation acquired from the operation database 40 to obtain a plurality of clusters. In this case, the cluster determination unit 202 may determine the cluster having the highest degree of similarity with respect to the time series data of the decarboxylation efficiency acquired by the data acquisition unit 201 among the plurality of clusters.

When the above categorical variables are not used as explanatory variables in other embodiments, the cluster determination unit 202 and the clustering execution unit 203 may not be included in the converter blowing control device 20.

(Rin concentration estimation unit)
The phosphorus concentration estimation unit 204 according to the present embodiment uses various data output from the data acquisition unit 201 and a categorical variable output from the cluster determination unit 202 to identify the cluster, and uses the phosphorus dephosphorization rate constant k. And estimate the phosphorus concentration in the molten steel. Specifically, the phosphorus concentration estimation unit 204 first calculates the dephosphorization rate constant k by substituting the above-mentioned various data and categorical variables into the regression equation shown in the above equation (4) as explanatory variables. Then, the phosphorus concentration estimation unit 204 estimates the phosphorus concentration in the molten steel by substituting the calculated dephosphorization rate constant k into the above equation (2). The phosphorus concentration estimation unit 204 sequentially estimates the dephosphorization rate constant k and the phosphorus concentration in the molten steel after the sublance measurement by the sublance 14 (that is, after the start of acquisition of molten steel data by the data acquisition unit 201). That is, the phosphorus concentration estimation unit 204 estimates the dephosphorization rate constant k and the phosphorus concentration in the molten steel in the range from the sublance measurement to the time when the decarburization process is stopped (at the end point).

When the above categorical variable is not used as an explanatory variable in another embodiment, a variable based on the time series data of the furnace tilt angle (for example, an average value or the like) can be used as the explanatory variable. Similarly, variables based on slag level time series data and / or variables based on decarboxylation efficiency time series data can also be used as the explanatory variables.

As described above, the configuration and function of each functional unit of the converter blowing control device 20 according to the present embodiment have been described with reference to FIG. 7. Although not shown in FIG. 7, the converter blowing control device 20 may further include an operation amount calculation unit. The operation amount calculation unit calculates the operation amount such as the amount of oxygen blown or the amount of cold material in the decarburization treatment or the height of the top blown lance based on the phosphorus concentration in the molten steel estimated by the phosphorus concentration estimation unit 204. May be good. The function of the manipulated variable calculation unit may be, for example, the same as the function disclosed in Patent Document 1. The phosphorus concentration in molten steel estimated by the phosphorus concentration estimation unit 204 according to the present embodiment is higher in accuracy than the phosphorus concentration in molten steel estimated by the technique disclosed in Patent Document 1. Therefore, since the reliability of the manipulated variable calculated by the manipulated variable calculation unit is high, it is possible to bring the actual phosphorus concentration in molten steel closer to the target phosphorus concentration in molten steel.

<< 3. Flow of method for estimating phosphorus concentration in molten steel >>
FIG. 8 is an example of a flowchart of a method for estimating the phosphorus concentration in molten steel by the converter blowing system according to the present embodiment. Further, FIG. 9 is a graph showing examples of various time series data acquired or estimated in the primary refining by the converter blowing system according to the present embodiment. The flow of the method for estimating the phosphorus concentration in molten steel by the converter blowing system 1 according to the present embodiment will be described with reference to FIGS. 8 and 9. Each process shown in FIG. 8 corresponds to each process executed by the converter blowing control device 20 shown in FIG. 7. Therefore, the details of each process shown in FIG. 8 will be omitted, and the outline of each process will be described.

In the method for estimating the phosphorus concentration in molten steel according to the present embodiment, first, the data acquisition unit 201 acquires various data such as data stored in the converter smelting database 21 before the start of converter smelting (step S101). ). Specifically, the data acquisition unit 201 acquires the hot metal data 211, the target data 212, and the parameter 213.

Next, the data acquisition unit 201 acquires data related to the dephosphorization process and the intermediate slag process during the dephosphorization process and the intermediate slag process (step S103). Specifically, the data acquisition unit 201 sequentially acquires data related to the furnace tilt angle measured by the angle meter 104 from the angle meter 104. Further, the data acquisition unit 201 sequentially acquires data related to the slag level measured by the level meter 103 from the level meter 103.

Next, the cluster determination unit 202 determines the cluster to be used as an operating factor based on the time-series data of the furnace tilt angle acquired in step S103 and the time-series data of the slag level during the dephosphorization process (step S105). ). Specifically, as shown in FIG. 8, the cluster determination unit 202 obtains time-series data of the furnace tilt angle at the beginning of the intermediate slag treatment of the main charge and time-series data of the slag level at the end of the dephosphorization treatment. , The cluster having the highest degree of similarity among the clusters fetched by the clustering execution unit 203 is determined. The cluster determination unit 202 outputs each of the categorical variables corresponding to the cluster determined here to the phosphorus concentration estimation unit 204.

Next, the data acquisition unit 201 acquires data related to the decarburization process from the start of the decarburization process (step S107). Specifically, the data acquisition unit 201 sequentially acquires the exhaust gas data measured by the exhaust gas component analyzer 101 and the exhaust gas flow meter 102 from the exhaust gas component analyzer 101 and the exhaust gas flow meter 102. The exhaust gas data is continuously acquired from the start time to the end time of the decarburization treatment. The data acquisition process related to the decarburization process according to step S107 is a process that is repeatedly performed from the start time of the decarburization process to the time point when a predetermined time elapses (step S109). Such a predetermined time corresponds to the time range of the time series data of the decarboxylation efficiency used for the determination process by the cluster determination unit 202 in the subsequent stage.

Next, the data acquisition unit 201 determines whether or not a predetermined time (predetermined time range) has elapsed from the start time of the decarburization process (step S109). When the predetermined time has not elapsed from the start time of the decarburization process (step S109 / NO), the data acquisition unit 201 acquires the data related to the decarboxylation efficiency (step S111). Specifically, the data acquisition unit 201 sequentially calculates the decarboxylation efficiency from the sequentially acquired exhaust gas data from the start time of the decarboxylation treatment to the time when a predetermined time elapses, and decarboxylates the data. Acquire time-series data of elementary efficiency.

Next, when a predetermined time has elapsed from the start time of the decarburization process (step S109 / YES), the cluster determination unit 202 sets the operation factor as an operation factor based on the time series data of the decarboxylation efficiency acquired in step S111. The cluster to be used is determined (step S113). Specifically, as shown in FIG. 8, the cluster determination unit 202 is most similar among the clusters extracted by the clustering execution unit 203 with respect to the time series data of the decarboxylation efficiency at the beginning of the decarburization process of this charge. Determine the cluster with the highest degree. The cluster determination unit 202 outputs the categorical variables corresponding to the cluster determined here to the phosphorus concentration estimation unit 204.

Next, the data acquisition unit 201 continues to acquire data related to the decarburization process (step S115). The data acquisition process related to the decarburization process according to step S115 is a process that is repeatedly performed from the time when a predetermined time elapses from the start time of the decarburization process to the end point of the decarburization process (step S121). The process according to step S115 is the same as the process according to step S107. Further, at the timing when the sublance measurement is performed, the data acquisition unit 201 acquires molten steel data.

Next, the phosphorus concentration estimation unit 204 determines whether or not the sublance measurement has already been performed in the method for estimating the phosphorus concentration in molten steel according to the present embodiment (step S117). If the sublance measurement has not been performed yet (step S117 / NO), the phosphorus concentration estimation unit 204 does not estimate the phosphorus concentration in the molten steel, and the data acquisition unit 201 repeatedly obtains data related to decarburization such as exhaust gas data. Acquire (step S115). On the other hand, when the sublance measurement has already been performed (step S117 / YES), the phosphorus concentration estimation unit 204 estimates the phosphorus concentration in the molten steel (step S119). Specifically, the phosphorus concentration estimation unit 204 first estimates the phosphorus dephosphorization rate constant k and the phosphorus concentration in molten steel at the time of sublance measurement using various data acquired by the data acquisition unit 201. This is because the actual molten steel temperature value and the actual carbon concentration value in the molten steel obtained by the sublance measurement are effective by improving the accuracy of the estimation of the dephosphorization rate constant k. More specifically, first, by substituting the explanatory variables based on various data including the actual molten steel temperature value and the actual carbon concentration value in the molten steel obtained by the sublance measurement into the regression equation of the above equation (4), the dephosphorization rate constant. get k. Next, assuming that the obtained dephosphorization rate constant k is the same value from the start of the dephosphorization treatment to the time of sublance measurement, the hot metal phosphorus concentration is set to the initial phosphorus concentration value [P] _ini , and the dephosphorization treatment is performed. By substituting the elapsed time from the start to the time of sublance measurement into the above equation (2) as t, the phosphorus concentration [P] at the time of sublance measurement is obtained. In this way, even if the phosphorus concentration at the time of sublance measurement is estimated from the start of the dephosphorization process using the dephosphorization rate constant k estimated at the time of sublance measurement, the phosphorus concentration can be estimated with sufficient accuracy as shown in the following examples. Since it can be estimated, there is no practical problem.

After the sublance measurement, the phosphorus concentration estimation unit 204 determines whether or not the decarburization treatment is completed (step S121). When the decarburization treatment is not completed (step S121 / NO), the phosphorus concentration estimation unit 204 uses the estimated value of phosphorus concentration in molten steel at the time of the above sublance measurement as an initial value until the time when the decarburization treatment is completed. The estimation of the dephosphorization rate constant k according to the equation (4) and the estimation of the phosphorus concentration in the molten steel according to the equation (2) using the estimated k are repeated (process according to steps S115 to S119). On the other hand, when the decarburization treatment is completed (step S121 / YES), the phosphorus concentration estimation unit 204 ends the phosphorus concentration estimation process in the molten steel according to the present embodiment.

As described above, the flow of the method for estimating the phosphorus concentration in molten steel according to the present embodiment has been described with reference to FIGS. 8 and 9. The steps shown in the flowchart of the method for estimating the phosphorus concentration in molten steel according to the present embodiment shown in FIG. 8 are merely examples.

For example, the timing at which the processes according to steps S101 to S105 and the processes according to steps S111 and S113 are executed is not particularly limited as long as it is before the process for estimating the phosphorus concentration in molten steel in step S119 is started. Specifically, in another embodiment, when the data acquisition unit 201 collectively acquires the data related to the furnace tilt angle, the data related to the slag level, and the data related to the decarboxylation efficiency from various devices, step S101, The data acquisition process in steps S103 and S111, and the cluster determination process in steps S105 and S113 may be completed before the process for estimating the phosphorus concentration in molten steel in step S119 is started. This is because it is sufficient to have all the data used for estimating the phosphorus concentration in molten steel at the start of the process for estimating the phosphorus concentration in molten steel in step S119.

<< 4. Summary >>
The amount of slag discharged in the intermediate slag treatment affects the reaction direction and reaction rate of the dephosphorization reaction, which affects the phosphorus concentration in the molten steel. Further, it is said that the furnace tilt angle of the converter is related to the amount of slag discharged in the intermediate waste treatment. According to this embodiment, as one of the operating factors used as an explanatory variable for calculating the dephosphorization rate constant k, time-series data (or its average value) of the furnace tilt angle of the converter in the intermediate waste treatment is used. Is used. That is, the amount of slag discharged during the intermediate slag treatment, which is related to the furnace tilt angle, is applied to the estimation of the phosphorus concentration in the molten steel. Therefore, it is possible to improve the estimation accuracy of the phosphorus concentration in the molten steel in the converter smelting in which the intermediate slag treatment is performed.

Further, according to the present embodiment, the categorical variable that identifies the cluster obtained by the time series clustering performed on the time series data of the furnace tilt angle at the time of the past operation is used as the explanatory variable related to the operation factor. Then, a cluster similar to the tendency shown by the time-series data of the furnace tilt angle obtained during actual operation is determined, and the categorical variable corresponding to the determined cluster is a regression equation as an explanatory variable related to the operation factor of the charge. Is assigned to. As a result, not only the amount of slag generated in the dephosphorization treatment but also the degree of slag discharge in the intermediate slag treatment can be reflected in the estimation of the dephosphorization rate constant k. That is, it is possible to further improve the estimation accuracy of the phosphorus concentration in the molten steel in the converter smelting in which the intermediate slag treatment is performed.

In addition to the tilt angle of the furnace, the slag level in the converter, which is said to be related to the amount of slag discharged in the intermediate slag treatment, and the decarbonization, which is said to be related to the progress of the dephosphorization reaction during the decarburization treatment. By using the data related to the elementary efficiency as one of the operating factors, the estimation accuracy of the phosphorus concentration in the molten steel can be further improved. Furthermore, by applying the time-series clustering method to the time-series data of slag level and decarboxylation efficiency, the tendency of slag forming at the end of blowing during the decarboxylation treatment and the decarboxylation reaction during the decarboxylation treatment The degree of progress can be reflected in the estimation of the decarboxylation rate constant k. That is, the accuracy of estimating the phosphorus concentration in molten steel can be further improved.

The configuration shown in FIG. 7 is merely an example of the converter blowing system 1 according to the present embodiment, and the specific configuration of the converter blowing system 1 is not limited to such an example. The converter blowing system 1 may be configured so as to be able to realize the functions described above, and can take any generally conceivable configuration.

For example, each function included in the converter blowing control device 20 may not be all executed by one device, or may be executed by the cooperation of a plurality of devices. For example, one device having only one or a plurality of functions of the data acquisition unit 201, the cluster determination unit 202, the clustering execution unit 203, and the phosphorus concentration estimation unit 204 is combined with another device having other functions. By being communicatively connected, the same function as the illustrated converter blowing control device 20 may be realized.

Further, it is possible to create a computer program for realizing each function of the converter blowing control device 20 according to the present embodiment shown in FIG. 7 and mount it on a processing device such as a PC. It is also possible to provide a computer-readable recording medium on which such a computer program is recorded. The recording medium is, for example, a magnetic disk, an optical disk, a magneto-optical disk, a flash memory, or the like. Further, the above computer program may be distributed via, for example, a network without using a recording medium.

Next, examples of the present invention will be described. In order to confirm the effect of the present invention, in this example, the estimation accuracy of the phosphorus concentration in molten steel obtained by the phosphorus concentration estimation method in molten steel according to the present embodiment was verified. The following examples are merely for verifying the effect of the present invention, and the present invention is not limited to the following examples.

For each Example and Comparative Example, the phosphorus concentration in the molten steel at the time of sublance measurement was calculated. The phosphorus concentration in the molten steel was obtained by substituting the dephosphorization rate constant k obtained by the above formula (4) into the above formula (2). The calculated phosphorus concentration in molten steel is hereinafter referred to as an "estimated value".

In order to verify the estimation accuracy of the phosphorus concentration in molten steel according to each example and comparative example, the actual value of the phosphorus concentration in molten steel at the time of sublance measurement was measured. The error (estimation error) between the estimated value and the actual value of the phosphorus concentration in molten steel according to each Example and Comparative Example was calculated, and the standard deviation (%) of the estimated error was obtained. It can be said that the smaller the standard deviation, the smaller the estimation error, that is, the higher the estimation accuracy.

The explanatory variables used in the regression equation represented by the equation (4) are as shown in Table 2 below. Specifically, in the comparative example, the conventional operating factors shown in Table 1 were used as explanatory variables. On the other hand, in the first embodiment, as explanatory variables, in addition to the operating factors shown in Table 1, the categorical variables corresponding to the clusters determined by the cluster determination unit 202 for the time series data of the furnace tilt angle (category related to the furnace tilt angle). (Called a variable) was used. In the second embodiment, as explanatory variables, in addition to the operating factors shown in Table 1 and the categorical variables related to the furnace tilt angle, the categorical variables corresponding to the clusters determined by the cluster determination unit 202 for the slag level time-series data ( (Called a categorical variable related to the slag level) was used. In Example 3, as explanatory variables, in addition to the operating factors shown in Table 1 and the category variables related to the furnace tilt angle, the category corresponding to the cluster determined by the cluster determination unit 202 for the time-series data of decarboxylation efficiency. Variables (referred to as categorical variables related to decarboxylation efficiency) were used. Further, in Example 4, the operating factors shown in Table 1, the categorical variables related to the furnace tilt angle, the categorical variables related to the slag level, and the categorical variables related to the decarboxylation efficiency were used as explanatory variables.

Next, the verification results of the estimation accuracy of the phosphorus concentration in the molten steel according to each example and the comparative example are shown. FIG. 10 is a graph showing the standard deviation of the estimation error with respect to the actual value of the phosphorus concentration in the molten steel at the time of sublance measurement according to each Example and Comparative Example. With reference to FIG. 10, it can be seen that in each of the examples, the estimation accuracy of the phosphorus concentration in the molten steel is improved as compared with the comparative example.

First, it was shown that the estimation accuracy according to Example 1 is higher than the estimation accuracy according to Comparative Example. As a result of analyzing the regression result by the regression equation represented by the equation (4) for each charge, the present inventors tended to have a high dephosphorization efficiency when the furnace tilt angle remained relatively large. I found that there is. That is, the slag generated in the converter was discharged to the outside of the furnace as soon as possible (the furnace tilt angle remained relatively large), so that more phosphorus-rich slag was discharged. As a result, it is considered that the efficiency of dephosphorization has increased. Therefore, it is considered that the estimation accuracy of the phosphorus concentration in the molten steel was improved because the slag slag discharge state in the intermediate slag treatment was reflected in the calculation of the dephosphorization rate constant k by the explanatory variables based on the time series data of the furnace tilt angle. Be done.

Furthermore, it was shown that the estimation accuracy according to Example 2 and Example 3 is even higher than the estimation accuracy according to Example 1. It was also shown that the estimated concentration according to Example 4 in which the three categorical variables were combined was even higher than the estimated accuracy according to the other examples. By using not only the categorical variable related to the furnace tilt angle but also the categorical variable related to the slag level and the categorical variable related to the decarbonate efficiency as explanatory variables, slag forming at the end of blowing during the dephosphorization process was used. It is considered that the tendency and the degree of progress of the dephosphorization reaction at the beginning of the decarburization treatment were further reflected in the calculation of the dephosphorization rate constant k.

From the above, it was shown that in each example, the phosphorus concentration in the molten steel at the time of sublance measurement can be estimated more accurately than in the comparative example. In particular, by using not only the categorical variables related to the furnace tilt angle but also the categorical variables related to the slag level and the categorical variables related to the decarboxylation efficiency, it is possible to further improve the estimated concentration of phosphorus in molten steel. It was shown to be.

Although the preferred embodiments of the present invention have been described in detail with reference to the accompanying drawings, the present invention is not limited to such examples. It is clear that a person having ordinary knowledge in the field of technology to which the present invention belongs can come up with various modifications or modifications within the scope of the technical idea described in the claims. , These are also naturally understood to belong to the technical scope of the present invention.

1 converter blowing system 10 converter blowing equipment 11 converter 12 flue 13 top blowing lance 14 sublance 20 converter blowing control device 21 converter blowing database 22 input / output unit 30 measurement control device 40 operation database 101 exhaust gas Component analyzer 102 Exhaust gas flow meter 103 Level meter 104 Angle meter 201 Data acquisition unit 202 Cluster determination unit 203 Clustering execution unit 204 Phosphorus concentration estimation unit

Claims (10)

A method for estimating the concentration of phosphorus in molten steel used in primary refining, in which dephosphorization treatment, intermediate slag removal treatment for slag generated by the dephosphorization treatment, and decarburization treatment are performed using the same converter. There,
A furnace tilt angle data acquisition step for acquiring the furnace tilt angle of the converter during the intermediate slag treatment, and a furnace tilt angle data acquisition step.
Exhaust gas data acquisition step to acquire the exhaust gas component and exhaust gas flow rate during the decarburization process,
The molten steel data acquisition step of acquiring the molten steel temperature and the carbon concentration in the molten steel by the sublance measurement during the decarburization treatment, and
Based on a model formula with the dephosphorization rate constant as the objective variable, which was previously obtained by a multiple regression analysis method, at least the furnace tilt angle among the operating conditions related to the dephosphorization treatment, the intermediate waste treatment, and the decarburization treatment. The dephosphorization rate constant was calculated using the data related to the above, and the calculated dephosphorization rate constant and the hot metal concentration at the start of the dephosphorization treatment were used to perform the decarburization treatment after the sublance measurement. The phosphorus concentration estimation step for estimating the phosphorus concentration in the molten steel and the phosphorus concentration estimation step
A method for estimating the phosphorus concentration in molten steel, including. In the calculation of the dephosphorization rate constant, the operating conditions related to the dephosphorization treatment, the intermediate slag treatment, and the decarburization treatment including data on the exhaust gas component, the exhaust gas flow rate, the molten steel temperature, and the carbon concentration are further added. The method for estimating the phosphorus concentration in molten steel, which is used. Claim 1 uses a categorical variable that identifies a cluster obtained by time-series clustering performed on a plurality of time-series data of the furnace tilt angles acquired in the past operation in the calculation of the dephosphorization rate constant. Alternatively, the method for estimating the phosphorus concentration in molten steel according to 2. A slag level data acquisition step for acquiring the slag level at the time of the dephosphorization process is further included.
The method for estimating the phosphorus concentration in molten steel according to any one of claims 1 to 3, further using the data related to the slag level in the calculation of the dephosphorization rate constant. In claim 4 , the calculation of the dephosphorization rate constant uses a categorical variable that identifies a cluster obtained by time series clustering performed on a plurality of the slug level time series data acquired in the past operation. The method for estimating the phosphorus concentration in molten steel described. The invention according to any one of claims 1 to 5 , further using the data relating to the decarboxylation efficiency obtained by using the exhaust gas component and the exhaust gas flow rate at the time of the decarburization treatment in the calculation of the decarboxylation rate constant. Method for estimating the phosphorus concentration in molten steel. A claim that uses in the calculation of the decarboxylation rate constant to use a categorical variable that identifies a cluster obtained by time series clustering performed on a plurality of time series data of the decarboxylation efficiency acquired in the past operation. The method for estimating the phosphorus concentration in molten steel according to 6. A converter blowing control device used for primary refining in which the dephosphorization treatment, the intermediate waste removal treatment for discharging the slag generated by the dephosphorization treatment, and the decarburization treatment are performed using the same converter. There,
A furnace tilt angle data acquisition unit that acquires the furnace tilt angle of the converter during the intermediate slag treatment, and a furnace tilt angle data acquisition unit.
An exhaust gas data acquisition unit that acquires the exhaust gas component and exhaust gas flow rate during the decarburization process,
A molten steel data acquisition unit that acquires the molten steel temperature and carbon concentration in the molten steel by sublance measurement during the decarburization treatment, and
Based on a model formula with the dephosphorization rate constant as the objective variable, which was previously obtained by a multiple regression analysis method, at least the furnace tilt angle among the operating conditions related to the dephosphorization treatment, the intermediate waste treatment, and the decarburization treatment. The dephosphorization rate constant was calculated using the data related to the above, and the calculated dephosphorization rate constant and the hot metal concentration at the start of the dephosphorization treatment were used to perform the decarburization treatment after the sublance measurement. A phosphorus concentration estimation unit that estimates the phosphorus concentration in the molten steel, and a phosphorus concentration estimation unit.
A converter blowing control device equipped with. As a converter blowing control device used for primary refining in which dephosphorization treatment, intermediate slag removal treatment for discharging slag generated by the dephosphorization treatment, and decarburization treatment are performed using the same converter. A program to make a computer work
A furnace tilt angle data acquisition function for acquiring the furnace tilt angle of the converter during the intermediate slag treatment, and a furnace tilt angle data acquisition function.
An exhaust gas data acquisition function that acquires the exhaust gas component and exhaust gas flow rate during the decarburization process, and
A molten steel data acquisition function that acquires the molten steel temperature and carbon concentration in the molten steel by sublance measurement during the decarburization process, and
Based on a model formula with the dephosphorization rate constant as the objective variable, which was previously obtained by a multiple regression analysis method, at least the furnace tilt angle among the operating conditions related to the dephosphorization treatment, the intermediate waste treatment, and the decarburization treatment. The dephosphorization rate constant was calculated using the data related to the above, and the calculated dephosphorization rate constant and the hot metal concentration at the start of the dephosphorization treatment were used to perform the decarburization treatment after the sublance measurement. The phosphorus concentration estimation function for estimating the phosphorus concentration in the molten steel and the phosphorus concentration estimation function
A program to realize the above on a computer. As a converter blowing control device used for primary refining in which dephosphorization treatment, intermediate slag removal treatment for discharging slag generated by the dephosphorization treatment, and decarburization treatment are performed using the same converter. A recording medium on which programs for operating a computer are recorded.
A furnace tilt angle data acquisition function for acquiring the furnace tilt angle of the converter during the intermediate slag treatment, and a furnace tilt angle data acquisition function.
An exhaust gas data acquisition function that acquires the exhaust gas component and exhaust gas flow rate during the decarburization process, and
A molten steel data acquisition function that acquires the molten steel temperature and carbon concentration in the molten steel by sublance measurement during the decarburization process, and
Based on a model formula with the dephosphorization rate constant as the objective variable, which was previously obtained by a multiple regression analysis method, at least the furnace tilt angle among the operating conditions related to the dephosphorization treatment, the intermediate waste treatment, and the decarburization treatment. The dephosphorization rate constant was calculated using the data related to the above, and the calculated dephosphorization rate constant and the hot metal concentration at the start of the dephosphorization treatment were used to perform the decarburization treatment after the sublance measurement. The phosphorus concentration estimation function for estimating the phosphorus concentration in the molten steel and the phosphorus concentration estimation function
A recording medium on which a program for realizing a computer is recorded.

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