KR20180114919A - Method for Estimating Concentration in Molten Steel and Converter Switching Control Device - Google Patents

Abstract

[PROBLEMS] To estimate the concentration of molten steel at the time of turning over in the operation by the multifunctional converter method with high precision. [MEANS FOR SOLVING PROBLEMS] A molten steel concentration estimation method is applied to a primary refining using a converter accompanied by an intermediate disposing treatment, and includes a slag level data acquiring step for acquiring a slag level in the denitration processing, An exhaust gas data acquiring step of acquiring an exhaust gas flow rate and an exhaust gas flow rate of the slag, an exhaust gas data acquiring step of acquiring a slag level, an exhaust gas component, and an exhaust gas flow rate; Data on the gas flow rate, the molten steel temperature and the carbon concentration, and the operating conditions for the untreating, intermediate disposing and decarburizing treatments are used to calculate the untieing rate constant, and the calculated untieing rate constant and the calculated molten steel rate Concentration to estimate the phosphorus concentration in the molten steel at the time of decarburization treatment after the sub-lance measurement, It includes a forward step.

Description

Method for Estimating Concentration in Molten Steel and Converter Switching Control Device

The present invention relates to a molten steel concentration estimation method and a molten steel concentration estimation device for accurately estimating the phosphorus concentration in molten steel at the time of traveling by a multifunctional converter method.

Control of the components in the molten steel (particularly, control of the concentration in the molten steel) at the time of transferring is very important for the quality control of steel. In order to control the phosphorus concentration in the molten steel, the amount of injected oxygen, the amount of the submerged feed such as burnt lime or scale, the timing of injection of the submaterial, the height of the upturned lance, the oxygenated oxygen flow rate and the flow rate of the off gas are generally used as the manipulated variable. These manipulated variables are often determined by the information obtained before the start of the sweeping, such as a target density, charter data, and a criterion created on the basis of past operating results and the like.

However, even under the same operating conditions, the reproducibility of the de-invasion behavior in actual winding was low, and there was a problem that fluctuation in the concentration in the molten steel at the time of trial was increased. Therefore, it is difficult to suppress the fluctuation of the phosphorus concentration in the molten steel at the time of tanning with the manipulated variable determined based only on the information obtained before the start of the above-described curing.

In order to cope with the above problem, techniques utilizing exhaust gas component and exhaust gas flow rate, which are obtained at the time of blowing, have been developed. For example, in Patent Document 1 below, a removal rate constant is estimated by using a measurement value relating to operating conditions and exhaust gas relating to blowing, and a concentration in the molten steel at the time of blowing is estimated using an estimated removal rate constant Technology is disclosed. Patent Document 1 discloses a technique for controlling the concentration of molten steel by comparing the estimated molten metal concentration with the molten metal concentration in the target molten steel and changing the operating conditions relating to the metal melting based on the comparison result .

Japanese Patent Application Laid-Open No. 2013-23696

BACKGROUND ART [0002] In recent years, in preliminary refining, molten iron preliminary processing such as demolition processing using a converter is generally performed. Particularly, development of technology capable of performing preliminary ironing and decarburization treatment in the primary refining by the same converter, called multifunctional converter (MUlti Refining Converter: MURC), is progressing. Specifically, the MURC carries out a preliminary ironing process (step 2) in which a molten iron is charged into a converter (first step) and a depletion treatment is carried out by addition of flux and oxygen ingestion by the uprange lance (second step) (Third step), and then decarburizing the treated slag by the transfer (fourth step). The first refining method is a method of refining the first refining process. Since MURC has less heat loss and shorter lead time than the conventional refining operation method in which unturning treatment and decarburization treatment such as a simple simple refining process (SRP) are performed in different converters, And the production efficiency in the process is high.

In this MURC, the slag generated in the second step of the dephosphorization process is dispensed by the intermediate process of the third process. At this time, depending on the amount of slag generated in the denitrification process or the quality of the slag, the amount of slag discharged by the intermediate disposing process differs depending on the operation.

The phosphorus contained in the molten iron after the intermediate disposing treatment is desorbed from the molten iron and introduced into the slag by a denitration reaction represented by the following formula (101), which may occur in parallel with the decarburization reaction at the time of decarburization, Or may be reintroduced into the molten iron. In the following formula (101), the notation " [substance X] " indicates that the substance X is a substance present in the molten iron, and the notation " (substance Y) .

The direction in which the denitrification reaction represented by the formula (101) proceeds varies depending on the amount and composition of the slag discharged during the intermediate disposal treatment (or the amount and composition of the slag remaining in the converter). In other words, the reaction direction and the reaction rate of the dephosphorization reaction depend on the amount of slag discharged during the intermediate impregnation treatment. Therefore, it is considered that the amount of slag discharged during the intermediate disposal process affects the phosphorus concentration in the molten steel during the decarburization treatment.

In Patent Document 1, the phosphorus concentration in molten steel is estimated by using operational conditions at the time of operation of the transfer furnace. However, in Patent Document 1, the amount of slag discharged during the intermediate disposal treatment is not considered. Considering that the concentration of phosphorus in molten steel at the time of decarburization treatment affects the amount of slag discharged at the time of the intermediate disposal treatment, in the technique disclosed in the above Patent Document 1, in the primary refining accompanied by the intermediate disposal treatment It is difficult to estimate the phosphorus concentration in the molten steel with high accuracy.

SUMMARY OF THE INVENTION It is therefore an object of the present invention to provide a method for estimating the concentration in molten steel capable of accurately estimating the concentration of molten steel in the molten steel during the MURC operation And a converter switching control device.

In order to solve the above problems, according to one aspect of the present invention, there is provided a method for producing a slag, which comprises the steps of: removing the slag produced by the removal of the slag, A molten steel concentration estimation method comprising the steps of: a charter data acquiring step of acquiring charter data relating to charcoal prior to the de-lining process; a slag level data acquiring step of acquiring a slag level in the de-lining process; An exhaust gas data acquiring step of acquiring an exhaust gas flow rate and an exhaust gas flow rate of the exhaust gas; a molten steel obtaining step of obtaining a molten steel temperature and a carbon concentration in the molten steel by sub- The exhaust gas flow rate, the molten steel temperature and the carbon concentration, and Calculating a removal rate constant using the operating conditions relating to the removal, the intermediate removal, and the decarburization treatment, and using the calculated removal rate constant and the concentration of the cleaning agent at the start of the removal treatment, And a phosphorus concentration estimating step of estimating phosphorus concentration in the molten steel during the decarburization treatment after the measurement.

In the calculation of the removal rate constant, a category variable for identifying a cluster obtained by time-series clustering performed on time series data of a plurality of slag levels acquired in the past operation may be used.

In the calculation of the removal rate constant, the average value of the slag level data obtained at the time of the removal process may be used.

According to another aspect of the present invention, in order to solve the above-described problems, according to another aspect of the present invention, there is provided a method of treating a slag produced by the above- A slag level data acquiring section for acquiring a slag level at the time of the removal processing; and a slag level data acquiring section for acquiring a slag level data acquiring section for acquiring slag level data of the exhaust gas component An exhaust gas data acquiring section for acquiring an exhaust gas flow rate and an exhaust gas flow rate; a molten steel data acquiring section for acquiring a molten steel temperature and a carbon concentration in the molten steel by sub-lance measurement during the decarburization treatment; , The exhaust gas flow rate, the molten steel temperature and the carbon concentration, , The removal rate constant is calculated using the operating conditions relating to the intermediate disposal treatment and the decarburization treatment, and using the calculated removal rate constant and the concentration of the waste carrier at the start of the removal treatment, And a phosphorus concentration estimating section for estimating phosphorus concentration in the molten steel during the decarburization treatment.

The phosphorus concentration estimating unit may use a category variable for identifying clusters obtained by time series clustering performed on time series data of a plurality of slag levels acquired in past operations in the calculation of the desorption rate constant.

The phosphorus concentration estimating unit may use the average value of the slag level time series data obtained during the removal process in the calculation of the removal rate constant.

In the method for estimating the phosphorus concentration in the molten steel and the converter control apparatus, the removal rate constant is calculated using various data including the slag level and the operating conditions, and the phosphorus concentration in the molten steel is estimated using the calculated removal rate constant . Thus, in the primary refining in which the untreating treatment, the intermediate disposal treatment, and the decarburization treatment are carried out in the same manner by the same converter, it is possible to reflect the operating factor concerning the disposal of the slag generated in the converter in the estimation of the concentration in the molten steel have. Therefore, it is possible to estimate the phosphorus concentration in the molten steel with higher accuracy.

INDUSTRIAL APPLICABILITY As described above, according to the present invention, it is possible to estimate the phosphorus concentration in the molten steel at the time of turning the furnace during the MURC operation with high accuracy.

FIG. 1 is a graph showing time series data of slag levels at the time of the denitration process.
2A is a diagram showing a result of time-series clustering performed on time series data of a slag level.
2B is a diagram showing a result of time series clustering performed on slag level time series data.
2C is a diagram showing a result of time series clustering performed on slag level time series data.
2D is a diagram showing a result of time series clustering performed on slag level time series data.
FIG. 2E is a diagram showing a result of time series clustering performed on slag level time series data. FIG.
2F is a diagram showing a result of time series clustering performed on slag level time series data.
3 is a diagram showing an example of the configuration of a transfer passage cascade system according to an embodiment of the present invention.
Fig. 4 is a diagram showing an example of a flowchart of a method for estimating the concentration of molten steel by the transfer winding system according to the same embodiment. Fig.
5A is a graph showing an estimation error of an actual value of the removal rate constant k in the sub-lance measurement.
Fig. 5B is a graph showing an estimation error with respect to the actual value of the removal rate constant k in the sub-lance measurement.
FIG. 5C is a graph showing an estimation error of the actual value of the removal rate constant k at the time of the sub-lance measurement.
FIG. 5D is a graph showing an estimation error with respect to the actual value of the removal rate constant k at the time of the sub-lance measurement.
FIG. 6A is a graph showing an estimation error of an actual value of the concentration of molten steel in the sub-lance measurement.
Fig. 6B is a diagram showing an estimation error of the actual value of the phosphorus concentration in the molten steel during the sub-lance measurement.
6C is a diagram showing an estimation error of the actual value of the phosphorus concentration in the molten steel at the time of the sub-lance measurement.
6D is a graph showing an estimation error of the actual value of the phosphorus concentration in the molten steel during the sub-lance measurement.
Fig. 7A is a diagram showing an estimation error with respect to the actual value of the removal rate constant k at the end point. Fig.
Fig. 7B is a diagram showing an estimation error with respect to the actual value of the removal rate constant k at the end point.
7C is a diagram showing an estimation error with respect to the actual value of the removal rate constant k at the end point.
FIG. 7D is a diagram showing an estimation error with respect to the actual value of the removal rate constant k at the end point. FIG.
8A is a graph showing an estimation error of the actual value of the concentration of molten steel at the end point.
8B is a diagram showing an estimation error of the actual value of the concentration in the molten steel at the end point.
8C is a diagram showing an estimation error of the actual value of the concentration in the molten steel at the end point.
FIG. 8D is a graph showing an estimation error of the actual value of the concentration in the molten steel at the end point. FIG.

BEST MODE FOR CARRYING OUT THE INVENTION Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the present specification and drawings, elements having substantially the same functional configuration are denoted by the same reference numerals, and redundant description will be omitted.

In the following description, in order to avoid the complication of the description, the term " molten iron or molten steel in the converter " is referred to as " Molten steel ". Further, in the case of the removal process, the word " charter line " is used.

<< 1. Method of estimating phosphorus concentration in molten steel according to the present embodiment >>

Before describing the configuration and functions of the converter tuning system 1 according to the present embodiment, a method of estimating the phosphorus concentration in the molten steel according to the present embodiment will be described. In the following description, unless otherwise stated, the unit (mass%) of the concentration of each component is expressed as (%).

(Estimation of phosphorus concentration in molten steel using operating conditions and operating factors)

Assuming that the time variation of the concentration [P] (%) in the molten steel during the blowing is expressed by the first reaction formula, the first reaction formula is expressed as the following formula (1).

Herein, in the above formula (1), [P] _ini is an initial phosphorus concentration value (concentration in molten iron) (%) and k is a removal rate constant (sec ^-1 ). The &quot; phosphorus concentration initial value &quot; as used herein refers to the phosphorus concentration at the start of the phosphorus removal treatment.

If an accurate removal rate constant k is obtained, the phosphorus concentration in the molten steel can be estimated with high accuracy. However, it is generally considered that the removal rate constant k is not constant in the actual blowing, and is influenced by various operating conditions. Therefore, as disclosed in, for example, Patent Document 1 (Japanese Patent Laid-open Publication No. 2013-23696), not only the static information such as the charcoal component and the molten iron temperature but also the exhaust gas component The removal rate constant k is estimated using the dynamic information during the blowing such as the exhaust gas data such as data on the data and the exhaust gas flow rate. Hereinafter, a method of estimating the removal rate constant k will be described.

From the formula (1), the phosphorus concentration in the molten steel after t seconds from the start of the fusing (the start of the fusing process) is expressed by the following formula (2).

Then, using the past performance data, it is possible to obtain the removal rate constant k for each charge. For example, the removal rate constant k _i in charge i is calculated using the following equation (3).

Here, in the formula (3), [P] _{end, i} is, the concentration (%) of the molten steel at the time of the spirit, t _{end, i} is from dephosphorization processing start time (blow time of starting) to effect the time Elapsed time (seconds).

Then, a model equation having the removal rate constant k obtained by the above equation (3) as an objective variable is prepared in advance. This model equation can be properly constructed by various statistical methods. In the present embodiment, as the model formula, a regression equation obtained by using a known multiple regression analysis method and using various operating factors X as explanatory variables is used. This regression equation is constructed as shown in the following equation (4). In the actual winding, the removal factor k is estimated by substituting the operating factor X at the winding time into the following equation (4), and by applying the removal rate constant k to the above formula (2) The concentration can be estimated.

Here, in the formula (4), α _j is a coefficient corresponding to the j-th operation factor X _j, α ₀ is a constant. Specific examples of the operating factor X include the operating factors shown in Table 1 below. However, the operating factors shown in the following Table 1 are merely examples, and all of the operating factors X may be considered in estimating the de-denying rate constant k. Further, all or part of the operating factors included in the following Table 1 may be used for estimating the removal rate constant k.

In addition, according to Patent Document 1, the influence of the basic amount of stored oxygen in the furnace obtained by calculating the oxygen resin from the flow rate of the exhaust gas during blowing, the exhaust gas component, the flow rate of the off gas, the amount of admission of raw materials, . Therefore, in Patent Document 1, a dynamic operating factor in the tune such as the height of the accumulated oxygen amount in the furnace obtained by using exhaust gas data or the like, the height of the outlet lance, the flow rate of the oxygen gas, the flow rate of the off gas, It is described that it is possible to estimate the dephosphorization rate constant more precisely by employing, as an explanatory variable of the regression equation to be expressed, other than the explanatory variables described in Table 1. [

(Utilization of data on slag level)

Incidentally, in the above-mentioned converter winding method such as MURC, the removal treatment, the intermediate discharge treatment and the decarburization treatment are continuously performed by the same converter. Therefore, as well as the operating conditions relating to the untreated and decarburized treatments as disclosed in the above-mentioned Patent Document 1, the operating conditions relating to the intermediate disposal process can also be used for estimating the removal rate constant according to the present embodiment. The operating conditions for the intermediate disposal process include, for example, the intermediate disposal time and the amount of slag to be dispensed at an intermediate stage.

Of these, it is considered that the amount of the slag to be dispensed in the middle greatly affects the phosphorus concentration in the molten steel during the decarburization treatment. The inventors of the present invention have found that the amount of the slag to be discharged in the middle is deeply related to the slag level (slag height) at the time of the removal treatment. For example, when the slag level is high in the intermediate disposal process, slag is likely to be dispensed, and when the slag level is low, it is considered that slag is difficult to dispense. That is, the amount of slag to be discharged at an intermediate stage may vary depending on the slag level. Therefore, the inventors of the present invention can further improve the estimation accuracy of the phosphorus concentration in molten steel by adopting the slag level of the slag, which can occur in the converter during the smelting process, as a factor for operating the estimation of the concentration in the molten steel I overpaid. Hereinafter, data relating to the slag level and an application example thereof will be described.

FIG. 1 is a graph showing time series data of slag levels at the time of the denitration processing. FIG. Further, the data represented by the graph is data obtained by performing a normalization process so that the mean = 0 and the standard deviation = 1 with respect to actually obtained slag level data. The time-series data is time-series data acquired from the start to the end of the blowing in the removal process.

Referring to FIG. 1, it can be seen that the slag level is rising at the end of the removal process. That is, slag formation (slag forming) is proceeding at the end of the removal process. Therefore, in the present embodiment, the data on the slag level at the end of blasting at the time of the removal process can be used as one of the operating factors X _j as explanatory variables in the equation (4). Refers to a period of time corresponding to about 1/3 to 1/4 of the total elapsed time from the start of the blowing to the time of starting the blowing in the denitration process , The period from the point of origin to the point in time. For example, when the total elapsed time from the start of the sifting operation to the start of the sifting operation is 180 seconds, the end of the removal processing corresponds to the period from the time of about 120 seconds to 135 seconds elapsed from the start of the sifting operation do.

In the present embodiment, for example, the average value of the time series data of the slag level at the end of the removal process may be used as the operating factor X _j , which is a description variable of the equation (4) for estimating the removal rate constant k. Thus, the amount of slag generated by the dephosphorization process can be reflected in the estimation of the dephosphorization rate constant k.

Further, in the present embodiment, for example, a category variable for identifying a cluster obtained by performing time-series clustering on slag-level time series data may be used as an explanatory variable. Time series clustering refers to a method of obtaining the distance between time series data and performing clustering based on the distance. By treating the transition of the slag level as time-series data, the complex behavior of the slag level that can not be represented by a simple average value (in other words, the change in the slag level behavior that is averaged in the process of calculating the average value) This makes it possible to more accurately reflect the complex behavior of the slag level.

Hereinafter, a case where a category variable for identifying a cluster obtained by performing time-series clustering on slag-level time-series data is used as an explanatory variable will be described in detail.

In the present embodiment, time series clustering is performed in advance on the slag level time series data at the end of shunting acquired from past operation data. In this embodiment, as a method of time-series clustering, a recent clustering method of hierarchical clustering is used. The method of time-series clustering is not limited to the present method, but may be a k-means method of non-hierarchical clustering or the like. In the present embodiment, time series clustering is performed so that these time series data are classified into six clusters. However, the number of clusters is not particularly limited. The number of clusters is appropriately set according to the result of clustering.

FIGS. 2A to 2F are diagrams showing the results of time-series clustering performed on slag-level time-series data. FIG. Figs. 2A to 2F are diagrams showing the results of time-series clustering on clusters corresponding to the category variables (Nos. 1 to 6), respectively. The data on the slag levels shown in the respective drawings are data obtained by performing a normalization process so that the mean = 0 and the standard deviation = 1 for the actual slag level data. The time series data of the slag level used in the time-series clustering according to the present embodiment is data obtained from the slag level from the time of culling to the point of time 50 seconds from the culling effect in the removal process (see Figs. 2A to 2F , The time of the fusing time = 50 seconds corresponds to the time of the fusing in the removal processing, and the time of the fusing time = 0 seconds corresponds to the time point when the fusing time goes back 50 seconds from the point of time). The time range for selecting the time series data of the slag level used in the time series clustering is not particularly limited. For example, the target range may be a trend of the slag level time series data actually obtained by the level system, And the like.

In FIGS. 2A to 2F, each of the broken lines in each figure shows a change with time in the slag level in the one-time removal process. As shown in Figs. 2A to 2F, data having high similarity in time series data of slag level are classified into the same clusters. For example, in the cluster No. 2, time series data having a high slag level rise rate and a high slag level at the time of intermediate disposal (that is, a slag level at the time of culling in the removal process) are classified have. On the other hand, in the cluster No. 5, time series data having a small change in slag level transition are classified.

As described above, the time series data of the slag level obtained at the time of culling in the removal process is compared with each of the clusters classified by the previously performed clustering to select the cluster having the highest degree of similarity, , And can be employed as the operating factor X _j , which is the explanatory variable of equation (4). This makes it possible to reflect not only the amount of slag generated in the dephosphorization treatment but also the tendency of the slag forming at the end of the sweep in the dephosphorization treatment to the estimation of the concentration in the molten steel. The difference in tendency of the slag forming is considered to be based on the slag property such as the slag component. Therefore, the influence of the slag property in the denitration reaction is further added to the estimation of the concentration in the molten steel, so that it is possible to further improve the estimation accuracy of the phosphorus concentration in the molten steel.

Here, a method of using the clustering result of the slag level data for estimating the removal rate constant k in actual operation will be described. First, time-series clustering is performed in advance on slag-level time series data at the end of shunting acquired from 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 category variables for each cluster are set as one of the explanatory variables is constructed in advance for each cluster.

Next, the average value beta _{ave , j} at the measurement point j (j = 1 to n) of a plurality of time series data of the slag level classified into each cluster is calculated for each measurement point. The measurement point means a measurement time point of the slag level in the target range of the time series data. For example, in each of the clusters shown in Figs. 2A to 2F, each time-series data from the point of origin to the point of 50 seconds back is classified. When the slag level is measured every second, the measurement score is 50 points.

Next, time series data (S _j ) of the slag level at the time of the actual removal processing, which is an object for estimating the removal rate constant k, is acquired, and the time series data of the obtained slag level and the similarity of each cluster are stored, for example, The difference between the time series data S _j and the average value beta _{ave , j} is obtained for each cluster. It is judged that the smallest cluster of the difference belongs to the cluster to which the time series data S _j belongs and the category variable corresponding to this cluster is used as the explanatory variable relating to the operating factor. Any known one can be used as the difference, but the difference may be, for example, a sum of squared difference (SSD) represented by the following equation (5). The difference is appropriately determined by a known statistical method.

The case where the category variable for identifying the clusters obtained by performing the time series clustering on the time series data of the slag level is used as the explanatory variable has been described in detail.

The explanatory variables based on the time series data of the slag level are not limited to the above examples. For example, an intermediate value of time series data of the slag level at the time of blasting or a slag level at the end of blasting, or a rate of change of the time series data at the time of blasting in the removal process may be used as explanatory variables.

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

<< 2. Conversion system of the present embodiment >>

<2.1. Configuration of converter switching system>

Next, an example of a system for realizing the method of estimating the phosphorus concentration in the molten steel according to the embodiment described above will be described. Fig. 3 is a diagram showing an example of the configuration of the transfer passage culling system 1 according to the embodiment of the present invention. Referring to Fig. 3, the converter lighting system 1 according to the present embodiment includes a converter 10, a converter control unit 20, a measurement control unit 30, and a operation database 40. Fig.

(Converter conversion equipment)

The converter assembly 10 includes a converter 11, a flue 12, a lancing lance 13, a sub-lance 14, an exhaust gas component analyzer 101, an exhaust gas flow meter 102 and a level meter 103 Respectively. On the basis of the control signal output from the measurement control device 30, for example, the converter 10 receives start and stop of supply of oxygen to the molten iron by the uplength lance 13, Measurement of the component concentration and molten steel temperature in the molten steel, introduction of the coolant, and disposal of molten iron and slag by the converter 11 are carried out. The converter 10 is provided with a circulating device for supplying oxygen to the outlet lance 13, a cold material feeding device having a driving system for feeding a cold material to the converter 11, and a sub- Various devices generally used for blowing by a converter, such as a sub-material feeding device having a driving system for driving the apparatus, may be provided.

An outlet lance 13 used for blowing is inserted from the furnace of the converter 11 and the oxygen 15 sent to the transmission device is supplied to the molten iron in the furnace through the outlet lance 13. [ In order to stir the molten iron, an inert gas such as nitrogen gas or argon gas or the like can be introduced from the bottom of the converter 11 as the off gas 16. In the converter 11, a charcoal, a small amount of iron scrap, a coolant for adjusting the temperature of molten iron (molten steel), and a subsidiary material for forming slag such as burnt lime are charged / introduced into the furnace. In the case where the additive material is powder, the additive material of the powder may be supplied into the converter 11 together with the oxygen 15 through the take-up lance 13.

In the primary refining, phosphorus contained in the molten iron is chemically reacted with the subordinate containing iron oxide and calcium oxide-containing material contained in the slag in the converter, as represented by the formula (101) . Namely, by increasing the concentration of the iron oxide of the slag by blowing, the de-phosphorus reaction is promoted.

In the primary refining, the carbon in the charcoal is oxidized and reacted with the oxygen supplied from the ladle lance 13 (decarburization reaction). Thereby, exhaust gas of CO or CO ₂ is produced. These exhaust gases are discharged from the converter 11 to the flue 12.

As described above, in the transferring blowing, the blown oxygen reacts with carbon, phosphorus or silicon in the molten iron and generates oxides. The oxide produced by the blowing is discharged as exhaust gas or stabilized as slag. Carbon is removed by the oxidation reaction in the blowing, and phosphorus and the like are introduced into the slag and removed to produce a low-carbon and low-impurity steel.

The sub-lance 14 inserted from the furnace of the converter 11 is immersed in the molten steel at the predetermined timing at the time of the decarburization treatment to measure the component concentration and the molten steel temperature in the molten steel containing the carbon concentration . The measurement of the molten steel data such as the component concentration and / or the molten steel temperature by the sub-lance 14 is hereinafter referred to as "sub-lance measurement". The molten steel data obtained by the sub-lance measurement is transmitted to the converter control unit 20 via the metering control device 30. [

The exhaust gas generated by the blowing flows to the flue 12 provided outside the converter 11. [ In the flue 12, an exhaust gas component analyzer 101 and an exhaust gas flow meter 102 are provided. The exhaust gas component analyzer 101 analyzes the components contained in the exhaust gas. The exhaust gas component analyzer 101 analyzes the concentrations of CO and CO ₂ contained in the exhaust gas, for example. 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 perform component analysis and flow rate measurement of the exhaust gas in a sequential manner at a predetermined sampling period (for example, a period of 5 to 10 seconds). The component analysis and the flow rate measurement of the exhaust gas are performed at least at the time of decarburization treatment, but for the calculation of the basic component of the accumulated oxygen amount in the furnace used as the explanatory variable of the regression equation expressed by the formula (4) . The data on the exhaust gas component analyzed by the exhaust gas component analyzer 101 and the data on the exhaust gas flow rate measured by the exhaust gas flow meter 102 (hereinafter, these data are referred to as &quot; exhaust gas data &quot; , And output to the converter control unit 20 via the measurement control device 30 as time series data. Further, it is preferable that the exhaust gas data is output to the sequential, converter control unit 20 in order for the converter control unit 20 to estimate the concentration in the molten steel.

The converter assembly 10 includes a level meter 103 in the vicinity of the opening of the converter 11. The level meter 103 is a device for measuring the level of the bath surface of the molten steel (molten steel) and slag in the converter 11 at the time of turning on the transformer. In this specification, the bath level is referred to as a slag level.

The slag level obtained by the level meter 103 is information reflecting slag goods status and is used directly or indirectly as an explanatory variable of the regression equation expressed by the equation (4). The level meter 103 measures the slag level in order at a predetermined sampling period (for example, one second cycle). The data on the slag level obtained by the level meter 103 is output to the converter control device 20 via the measurement control device 30 as time series data.

The level meter 103 can be realized by a microwave injection device, an antenna, a calculation device, or the like as disclosed in, for example, Japanese Patent Application Laid-Open No. 2015-110817. In the leveling system disclosed in the above document, a microwave irradiation apparatus radiates a microwave into the interior of the converter, and the antenna detects reflected waves reflected from the bath surface, and the arithmetic unit measures the bath surface level based on the emitted microwaves and the detected reflected waves do.

(Converter control device)

The converter control unit 20 includes a data acquiring unit 201, a cluster determining unit 202, a clustering executing unit 203, a phosphorus concentration estimating unit 204, a transfer consent database 21, and an input / Respectively. The converter control unit 20 has a hardware configuration such as a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), a storage and a communication device, The functions of the unit 201, the cluster determining unit 202, the clustering executing unit 203, the phosphorus concentration estimating unit 204, and the transferring solicitation database 21 are realized. 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 tuning control device 20 acquires various data stored in the converter tuning database 21, exhaust gas data acquired from the exhaust gas component analyzer 101 and the exhaust gas flow meter 102, And the slag level data (i.e., slag level time series data) obtained from the level meter 103 as input values. The concentration of molten steel in the molten steel is estimated by the function of each functional unit of the converter control unit 20. Further, the converter control unit 20 may use the estimated phosphorus concentration in the molten steel for control of the operation in the converter winding. For example, when it is determined that the estimated phosphorus concentration in the molten steel exceeds the phosphorus concentration in the target molten steel stored as one of the target data 212, the converter's tuning control device 20 determines that the phosphorus concentration The operating conditions of the transferring brewing can be changed so as to fall below the phosphorus concentration in the target molten steel. As described above, if the phosphorus concentration in the molten steel can be estimated with high accuracy, the quality of the molten steel obtained by the primary refining can be kept high.

Specific functions of each functional unit of the converter control unit 20 according to the present embodiment will be described later.

In addition, the converter control unit 20 has a function of controlling the entire process relating to the preliminary processing of the molten iron such as the blowing of oxygen to the converter 11 and the input of the coolant and the subordinate material. In addition, for example, the converter control unit 20 controls the amount of oxygen input to the converter 11, the amount of the coolant to be introduced (hereinafter, referred to as &quot;Quot; discretion &quot;) and the amount of the subordinate material. For example, the converter tuning control device 20 has a function of controlling an object to be measured, a measurement timing, and the like with respect to the sub-lance measurement performed in general dynamic control.

(For example, the above-described control method of the coolant and the sub-raw material introduction, the method of determining the amount of oxygen to be blown, the amount of various kinds of coolant and sub-raw material, etc. before the start of the operation in the static control, As a method of controlling lance measurement, various known methods can be applied, and therefore, detailed description thereof will be omitted here.

The converter switching database 21 is a database for storing various types of data used in the converter control unit 20 and is realized by a storage device such as a storage. The converter switching database 21 stores the chartered line data 211, the target data 212, and the parameters 213, for example, as shown in Fig. These data may be added, updated, changed or deleted through an input device or a communication device (not shown). For example, among the various data stored in the operation database 40, which will be described later, data used for turning on the electric power may be added to the electric-power conversion database 21. The various data stored in the converter switching database 21 are called by the data acquisition unit 201. [ 3, the storage device having the converter tuning database 21 according to the present embodiment is configured integrally with the converter tuning control device 20. However, in another embodiment, the storage device having the converter tuning database 21, The storage device having the storage unit 21 may be configured separately from the converter control unit 20.

The charter data 211 is various data related to charcoal in the converter 11. [ For example, the charter data 211 includes information on the charter (initial charter weight per charge, concentration of charcoal component (carbon, phosphorus, iron, manganese, etc.), charcoal temperature, . The charter data 211 also includes various kinds of information generally used in the charcoal preliminary processing and decarburization processing (for example, information on the addition of the sub materials and cold materials (information on the sub materials and the amount of cold materials) (Information on the measurement object, measurement timing, and the like), information on the amount of oxygen to be taken, and the like). The target data 212 includes data such as the target component concentration and the target temperature in the molten iron (in the molten steel) after the denitration treatment, the decarburization treatment and the sublance measurement. The 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 a regression formula using the operating factor as an explanatory variable and a parameter (a removal rate constant, etc.) for estimating the phosphorus concentration.

The input / output unit 22 has a function of acquiring, for example, the estimation result of the phosphorus concentration in the molten steel by the phosphorus concentration estimating unit 204, and outputting it to various output devices. For example, the input / output unit 22 may display the concentration of the estimated molten steel on the operator. In addition, when the converter control unit 20 performs the bypass solenoid control on the basis of the concentration in the estimated molten steel, the input / output unit 22 outputs an instruction relating to the passage turning based on the estimated molten steel concentration, It may be outputted to the control device 30. In this case, the instruction may be an instruction to be automatically generated by a function relating to the control of the passage-winding control of the converter control apparatus 20, and may be an instruction to the operator who reads the information about the concentration (estimated value) Or an instruction input by the user. The input / output unit 22 may also have the function of an input interface for adding, updating, changing, or deleting various data stored in the converter switching database 21. The input / output unit 22 outputs the various data obtained by the data acquisition unit 201, the determination result of the cluster determination unit 202, and the estimation result of the phosphorus concentration estimation unit 204 to the operation database 40 .

(Measurement control device)

The measurement control device 30 has a hardware configuration such as a CPU, a ROM, a RAM, a storage, and a communication device. The metering control device 30 has a function of communicating with each device included in the converter assembly facility 10 and controlling the entire operation of the converter assembly facility 10. [ For example, in accordance with an instruction from the converter control unit 20, the measurement control device 30 controls the tilting of the converter 11 for the intermediate disposal process, the input of the coolant and the subordinate material to the converter 11, The injection of the oxygen 15 of the lance 13, and the operation of immersing the sub-lance 14 in the molten steel and measuring the sub-lance. The measurement control device 30 also includes data obtained from the respective devices of the exhaust gas component analyzer 101, the exhaust gas flow meter 102, the level meter 103, and the converter assembly facility 10 such as the sublance 14 And transmits it to the converter control unit 20.

(Operation database)

The operation database 40 is a database realized by a storage device such as a storage, and is a database for storing various data relating to the operation of the transfer passage. The various types of data are obtained by the data obtained from the respective apparatuses of the transfer finishing facility 10 acquired by the data acquisition unit 201 and the results of the determination by the cluster determination unit 202 and the estimation results by the phosphorus concentration estimation unit 204 Results. The operation database 40 according to the present embodiment accumulates data relating to the slag level (i.e., time series data of slag level) measured by the level meter 103 for each operation. In addition, the operation database 40 according to the present embodiment outputs the time series data of the slag level for each operation to the clustering execution unit 203. 3, the storage device having the operation database 40 according to the present embodiment is configured to be separate from the inverter control device 20. However, in another embodiment, the storage device having the operation database 40, May be integrated with the converter ignition control device 20. In this case,

<2.2. Configuration and function of each functional unit>

Next, the configuration and function of each functional section of the converter control unit 20 according to the present embodiment will be described.

3, the converter control unit 20 of the present embodiment is provided with a data acquisition unit 201, a cluster determination unit 202, a clustering execution unit 203, and a phosphorus concentration estimation unit 204 Each functional unit is provided.

(Data acquisition unit)

The data acquisition unit 201 acquires various data for estimating the concentration in the molten steel. For example, the data acquisition unit 201 acquires the charcoal data 211, the target data 212, and the parameters 213 stored in the transfer consent database 21. That is, the data acquisition unit 201 has a function as a chartered-data acquisition unit. These data are acquired at the latest before the phosphorus concentration estimation processing by the phosphorus concentration estimation unit 204 is started. The data acquiring unit 201 according to the present embodiment acquires various data stored in the transfer concealment database 21 before starting the transferring.

The data acquisition unit 201 acquires the 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 exhaust gas data to be acquired is time-series data. The data acquisition unit 201 according to the present embodiment sequentially acquires exhaust gas data that are measured by the exhaust gas component analyzer 101 and the exhaust gas flow meter 102 in a sequential manner. In another embodiment, the data acquisition unit 201 may acquire the exhaust gas data collectively after the denial process.

The data acquisition unit 201 acquires data concerning the slag level output from the level meter 103. [ That is, the data acquisition unit 201 has a function as a slag level data acquisition unit. The data on the slag level to be acquired is time series data. The slag level is obtained at the time of the removal process. The data acquiring unit 201 according to the present embodiment sequentially acquires data relating to the slag level measured by the level meter 103 in a sequential manner at the time of the denial process. Further, in another embodiment, the data acquisition unit 201 may acquire the data on the slag level collectively after the removal processing.

Further, the data acquisition unit 201 acquires the steel melt data obtained by the sub-lance measurement by the sub-lance 14 during the decarburization process. That is, the data acquisition unit 201 has a function as a steel melt data acquisition unit.

Further, the data acquiring unit 201 acquires data relating to the dephasing process, the intermediate disposal process, and the decarburization process, in addition to the above-described various data. The data acquisition unit 201 acquires data output from various apparatuses provided in the converter installation facility 10 through 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. [ The data acquired by the data acquisition unit 201 is stored in the operation database 40. [

(Cluster determination unit, clustering execution unit)

The cluster determining unit 202 determines clusters having the highest degree of similarity with respect to time series data of the slag level acquired from the data acquiring unit 201 among a plurality of clusters extracted by the clustering executing unit 203. [ Here, the method of calculating the degree of similarity is not particularly limited, and various known methods can be appropriately used. As such similarity, for example, slag-level time-series data of interest noted above and differential sum of squares of respective clusters can be used. The categorical variable corresponding to the cluster determined by the cluster determination unit 202 is output to the phosphorus concentration estimation unit 204. [ The category variable is used as the operating factor X _j , which is an explanatory variable of the regression equation expressed by the equation (4) used for the estimation by the phosphorus concentration estimating section 204.

Further, the clustering execution unit 203 clusters the time series data of the slag level in the past operation acquired from the operation database 40, and extracts a plurality of clusters. The cluster information extracted by the clustering execution unit 203 is output to the cluster determination unit 202. [ Information about the cluster may also be output to the operation database 40. [ The clustering execution unit 203 may appropriately perform the clustering when the time series data of the slag level in the past operation stored in the operation database 40 is updated.

In another embodiment, when the category variable is not used as an explanatory variable, the cluster determination unit 202 and the clustering execution unit 203 may not be included in the converter control unit 20.

(Phosphorus concentration estimating unit)

The phosphorus concentration estimating unit 204 uses the category variables that are variables that identify the various data output from the data acquiring unit 201 and clusters output from the cluster determining unit 202 to calculate the phosphorus concentration constant k and the phosphorus concentration Estimate the concentration. Specifically, the phosphorus concentration estimating unit 204 first calculates the removal rate constant k by substituting the above-described various data and category variables as the explanatory variables into the regression equation expressed by the equation (4). The phosphorus concentration estimating unit 204 estimates the phosphorus concentration in the molten steel by substituting the removal rate constant k calculated in the above equation (2). The phosphorus concentration estimating unit 204 sequentially determines the removal rate constant k and the concentration in the molten steel after the sub-lance measurement by the sub-lance 14 (i.e., after the start of acquisition of the molten steel data by the data acquiring unit 201) . That is, the phosphorus concentration estimating unit 204 estimates the phosphorus concentration constant k and the phosphorus concentration constant in the range from the sub-lance measurement to the decarburization treatment (end point).

As described above, the configuration and the function of each functional section of the converter control unit 20 relating to the present embodiment have been described with reference to Fig. Although not shown in Fig. 3, the converter control unit 20 may further include an operation amount calculating unit. The manipulated variable computing section may calculate an manipulated variable such as a fetched oxygen amount, a cold material amount, or a height of a dressing lance in decarburization processing based on the concentration of molten steel estimated by the phosphorus concentration estimating section 204. [ The function of the manipulated variable calculating section may be the same as the function disclosed in, for example, Patent Document 1. The concentration of molten steel estimated by the phosphorus concentration estimating unit 204 according to the present embodiment is higher than the concentration of molten steel estimated by the technique disclosed in Patent Document 1 above. Therefore, since the reliability of the manipulated variable calculated by the manipulated variable computing section is high, it is possible to bring the concentration in actual molten steel closer to the concentration in the target molten steel.

<< 3. Flow of Estimating Concentration in Molten Steel >>

Fig. 4 is a diagram showing an example of a flowchart of a method for estimating the phosphorus concentration in the molten steel by the converter tuning system 1 according to the present embodiment. The flow of the method for estimating the phosphorus concentration in the molten steel by the transfer path winding system 1 according to the present embodiment will be described with reference to FIG. Each process shown in Fig. 4 corresponds to each process executed by the converter control apparatus 20 shown in Fig. Therefore, the details of each process shown in Fig. 4 are omitted, and the outline of each process is explained.

In the method for estimating the concentration of molten steel according to the present embodiment, various data such as the data stored in the passage-turning simulation database 21 are acquired (Step S101) before the start of the passage-winding operation. Specifically, in step S101, the data acquisition unit 201 acquires the charac- terized line data 211, the target data 212, and the parameters 213. [

Then, at the time of the dephasing process and the intermediate deashing process, data relating to the dehulling process and the intermediate deashing process are acquired (step S103). Specifically, in step S103, the data acquiring unit 201 acquires data on the slag level measured by the level meter 103 from the level meter 103 in a cyclic manner.

Subsequently, a cluster to be used as the operation factor is determined based on the time series data of the slag level at the time of the removal processing acquired at step S103 (step S105). More specifically, in step S105, the cluster determining unit 202 determines the cluster having the highest degree of similarity among the clusters extracted by the clustering executing unit 203 with respect to the time-series data of the slag level at the time of the main- . The categorical variable corresponding to the cluster thus determined is output to the phosphorus concentration estimating unit 204. [

Subsequently, data on decarburization processing is acquired (step S107). More specifically, in step S107, the data acquiring unit 201 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). Acquisition of the exhaust gas data is continuously performed from the start to the end point of the decarburization treatment. Further, at the timing when the sub-lance measurement is performed, the data acquisition unit 201 acquires the steel melt data.

In the method for estimating the phosphorus concentration in the molten steel according to the present embodiment, the subsequent processing changes depending on whether or not the sub-lance measurement has already been performed (step S109). If the sub-lance measurement has not been performed yet (S109 / NO), data on decarburization processing such as exhaust gas data is acquired repeatedly without estimating the concentration in the molten steel (step S107). On the other hand, when the sub-lance measurement has already been performed (S109 / YES), the concentration in the molten steel is estimated (step S111). Specifically, the phosphorus concentration estimating unit 204 estimates the removal rate constant k and the phosphorus concentration in the molten steel at the time of the sub-lance measurement using various data acquired by the data acquisition unit 201. [ This is because the molten steel temperature actual value obtained in the sub-lance measurement and the carbon concentration actual value in the molten steel are more effective in the high-precision estimation of the de-phosphorus rate constant k. More specifically, first, by substituting an explanatory variable based on various data including the molten steel temperature actual value obtained in the sub-lance measurement and the carbon concentration actual value of molten steel into the regression equation of the above equation (4), the removal rate constant k . Subsequently, the obtained removal rate constant k is regarded as the same value from the start of the detoxification process to the measurement of the sub-lance, and the concentration of the phosphorus is set as the initial phosphorus concentration value [P] _ini . And the phosphorus concentration [P] at the time of the sub-lance measurement is obtained by substituting the elapsed time with the above formula (2). As described above, even when the phosphorus concentration at the time of the measurement of the sub-lance is estimated from the start of the phosphorus removal process using the estimated removal rate constant k at the time of the sub-lance measurement, the phosphorus concentration can be estimated There is no practical problem.

From the estimation of the concentration of phosphorus in the molten steel at the time of the sub-lance measurement to the point at which the decarburization process is finished after the measurement of the sub-lance, the estimation of the rate of denitration k according to the equation (4) , The estimation of the phosphorus concentration in the molten steel according to the above formula (2) is repeated (step S113). Specifically, when the decarburization process is not completed (S113 / NO), the processes of steps S107 to S111 are repeatedly performed. On the other hand, when the decarburization process is completed (S113 / YES), the process of estimating the phosphorus concentration in the molten steel according to the present embodiment is terminated.

The flow of the method for estimating the phosphorus concentration in the molten steel according to the present embodiment has been described above with reference to Fig. The steps shown in the flow chart of the method for estimating the phosphorus concentration in the molten steel according to the present embodiment shown in Fig. 4 are merely examples.

For example, the timing at which the processing relating to the steps S101 to S105 is performed is not particularly limited as long as the processing for estimating the concentration in the molten steel at the step S111 is started. Specifically, in another embodiment, when the data acquisition unit 201 collects the exhaust gas data and the slag level data collectively from various apparatuses, the data acquisition processing in steps S101 and S103, and The cluster determination processing in S105 may be completed before the estimation processing of the concentration in the molten steel in step S111 is started. It is sufficient if the data used for estimating the concentration in the molten steel at the start of the estimation process of the concentration in the molten steel in step S111 is sufficient.

<< 4. Theorem >>

The amount of slag discharged in the intermediate disposal process affects the reaction direction and the reaction rate of the exothermic reaction affecting the phosphorus concentration in the molten steel. It is also known that the slag level in the denitrification treatment is related to the amount of slag discharged in the intermediate disposing treatment. According to the present embodiment, as one of the operating factors used in the explanatory variables for calculating the removal rate constant k, time series data of the slag level (and / or the average value of the slag level time series data) Is used. That is, the amount of slag dislodged at the time of the intermediate disposal treatment related to the denitration reaction is applied to the estimation of the phosphorus concentration in the molten steel. Therefore, according to the present embodiment, it is possible to further improve the estimation accuracy of the concentration of molten steel in the transferring operation in which the intermediate disposal process is performed.

Further, according to the present embodiment, a category variable for identifying a cluster obtained by time-series clustering performed on time series data of slag levels in the past operation is used as an explanatory variable relating to the operating factor. Then, a cluster similar to the tendency indicated by the time series data of the slag level obtained at the time of actual operation is determined, and the category variable corresponding to the determined cluster is substituted into the regression equation as the explanatory variable relating to the factor of operation of the charge. Thereby, not only the amount of slag generated in the dephosphorization treatment but also the tendency of slag formation at the end of shuffling in the dephosphorization treatment can be reflected in the estimation of the dephosphorization rate constant k. That is, it is possible to further increase the estimation accuracy of the concentration of molten steel in the transverse winding operation in which the intermediate discharge processing is performed.

The configuration shown in Fig. 3 is merely an example of the converter tuning system 1 according to the present embodiment, and the specific configuration of the converter tuning system 1 is not limited to this example. The converter lighting system 1 may be configured so as to be capable of realizing the above-described functions, and can take all the configurations that can be generally assumed.

For example, each function of the converter control apparatus 20 may not be executed in all of the apparatuses, or may be executed by cooperation of a plurality of apparatuses. 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 may have different functions So that functions equivalent to those of the illustrated inverter control apparatus 20 may be realized.

It is also possible to manufacture a computer program for realizing each function of the converter control apparatus 20 according to the present embodiment shown in Fig. 3 and to mount the processing program on a processing device such as a PC. In addition, a computer-readable recording medium storing such a computer program can also be provided. The recording medium is, for example, a magnetic disk, an optical disk, a magneto-optical disk, a flash memory, or the like. The above-described computer program may be distributed via a network, for example, without using a recording medium.

Example

Next, an embodiment of the present invention will be described. In order to confirm the effect of the present invention, in this embodiment, the estimation accuracy of the removal rate constant k and the phosphorus concentration in the molten steel obtained by the phosphorus concentration estimation method according to the present embodiment was verified. The following examples are merely made to verify the effects of the present invention, and the present invention is not limited to the following examples.

As the explanatory variables used in the regression equation expressed by the equation (4), in the comparative example 1, the operating factors shown in the above Table 1 were used. On the other hand, in Example 1, as an explanatory variable, in addition to the operating factors shown in Table 1, the average value of the time series data of the slag level at the end of the blasting during the removal process was used. In the second embodiment, as the explanatory variables, the category variables corresponding to the clusters determined by the cluster determination unit 202 are used for time series data of the slag level in addition to the operating factors shown in Table 1 above. In addition, in the third embodiment, as explanatory variables, in addition to the average value of the time series data of the slag level and the operating factors shown in the above Table 1, the slag level time series data of the slag level data corresponding to the clusters determined by the cluster determination section 202 Category variables were used.

With respect to each of the examples and the comparative examples, the removal rate constant k and the phosphorus concentration in the molten steel at the time of the sub-lance measurement and in the decarburization treatment (at the end point) were respectively calculated. The removal rate constant k was calculated using the above equation (4). The phosphorus concentration in the molten steel was calculated by substituting the removal rate constant k obtained by the above formula (4) into the above formula (2). The calculated removal rate constant k and the phosphorus concentration in the molten steel are hereinafter referred to as &quot; estimated values &quot;.

In order to verify the estimation accuracy of the removal rate constant k and the phosphorus concentration in each of the examples and the comparative examples, the actual values of the phosphorus concentration in the molten steel at the time of the sub-lance measurement and at the end point were measured. Further, by substituting the actual value of the phosphorus concentration in the molten steel into the above equation (2), the removal rate constant k based on the actual value was calculated. The error (estimation error) between the estimated values of the removal rate constant k and the concentration of phosphorus in the molten steel and the actual values of each of the examples and comparative examples was calculated and the standard deviation SD (%) of the estimation error was calculated. The smaller the standard deviation S.D., the smaller the estimation error (i. E. The estimation accuracy is high).

First, Figs. 5A to 6D show results of estimation accuracy of the removal rate constant k and the concentration of phosphorus in the molten steel at the time of measuring the sub-lance. 5A to 5D are diagrams showing estimation errors of actual values of the removal rate constant k in the sub-lance measurement. 5A is a diagram showing an estimation error of the removal rate constant k at the time of the sublance measurement in the first embodiment. 5B is a diagram showing an estimation error of the removal rate constant k at the time of the sub-lance measurement in the second embodiment. 5C is a diagram showing an estimation error of the removal rate constant k at the time of the sub-lance measurement in the third embodiment. 5D is a graph showing an estimation error of the removal rate constant k at the time of the measurement of the sub-lance in the comparative example.

6A to 6D are diagrams showing an estimation error with respect to the actual value of the concentration in the molten steel at the time of the sub-lance measurement. 6A is a diagram showing an estimation error of the actual value of the concentration of molten steel in the sub-lance measurement in the first embodiment. 6B is a diagram showing an estimation error of the actual value of the phosphorus concentration in the molten steel at the time of the sub-lance measurement in the second embodiment. 6C is a diagram showing an estimation error of the actual value of the phosphorus concentration in the molten steel at the time of the sub-lance measurement in the third embodiment. FIG. 6D is a graph showing the estimation error of the actual value of the phosphorus concentration in the molten steel during the sub-lance measurement in the comparative example.

Referring to Figs. 5A to 5D, it can be seen that, in each of the embodiments, the estimation accuracy of the removal rate constant k is improved compared with the comparative example. Specifically, as shown in Fig. 5D, in the comparative example, the standard deviation SD of the estimation error was 0.00395. 5A, 5B and 5C, the standard deviation SD of the estimation error is 0.00385 in the first embodiment, the standard deviation SD of the estimation error is 0.00368 in the second embodiment, , The standard deviation SD of the estimation error was 0.00361.

6A to 6D, 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. Specifically, as shown in Fig. 6D, in the comparative example, the standard deviation SD of the estimation error was 0.00420. 6A, 6B and 6C, in the first embodiment, the standard deviation SD of the estimation error is 0.00406, the standard deviation SD of the estimation error is 0.00385 in the second embodiment, , The standard deviation SD of the estimation error was 0.00377.

From the above results, it can be seen that, in each of the examples, the removal rate constant k and the phosphorus concentration in molten steel at the time of the sub-lance measurement can be estimated with high accuracy, as compared with the comparative example. Particularly, in the second and third embodiments using variables corresponding to the clusters obtained from the time series data relating to the slag level as the explanatory variables, it is shown that the removal rate constant k and the phosphorus concentration in the molten steel can be estimated more accurately.

Next, Figs. 7A to 8D show results of estimation accuracy of the removal rate constant k and the phosphorus concentration in the molten steel at the end point in the decarburization treatment.

7A to 7D are diagrams showing an estimation error with respect to the actual value of the removal rate constant k at the end point. Fig. 7A is a diagram showing an estimation error of the removal rate constant k at the end point in the first embodiment. Fig. Fig. 7B is a diagram showing an estimation error of the removal rate constant k at the end point in the second embodiment. Fig. 7C is a diagram showing an estimation error of the removal rate constant k at the end point in the third embodiment. Fig. 7D is a diagram showing an estimation error of the removal rate constant k at the end point in the comparative example. Fig.

8A to 8D are diagrams showing an estimation error with respect to an actual value of the concentration in the molten steel at the end point. 8A is a graph showing an estimation error of the actual value of the phosphorus concentration in the molten steel at the end point in Example 1. FIG. 8B is a diagram showing the estimation error of the actual value of the phosphorus concentration in the molten steel at the end point in the second embodiment. 8C is a diagram showing the estimation error of the actual value of the phosphorus concentration in the molten steel at the end point in Example 3. FIG. FIG. 8D is a graph showing an estimation error with respect to the actual value of the phosphorus concentration in the molten steel at the end point in the comparative example. FIG.

7A to 7D, it can be seen that, in each of the embodiments, the estimation precision of the removal rate constant k is improved compared with the comparative example. Specifically, as shown in Fig. 7D, in the comparative example, the standard deviation SD of the estimation error was 0.00664. 7A, 7B and 7C, in the first embodiment, the standard deviation SD of the estimation error is 0.00656, the standard deviation SD of the estimation error is 0.00656 in the second embodiment, and in the third embodiment, , And the standard deviation SD of the estimation error was 0.00650.

8A to 8D, it can be seen that, in each of the embodiments, the estimation accuracy of the phosphorus concentration in the molten steel is improved as compared with the comparative example. Specifically, as shown in Fig. 8D, in the comparative example, the standard deviation S.D. of the estimation error was 0.00102. 8A, 8B and 8C, in the first embodiment, the standard deviation SD of the estimation error is 0.000101, the standard deviation SD of the estimation error is 0.000986 in the second embodiment, , And the standard deviation SD of the estimation error was 0.000982.

From the above results, it can be seen that, in each of the examples, the removal rate constant k at the end point and the phosphorus concentration in the molten steel can be estimated with high accuracy, as compared with the comparative example. Particularly, in the second and third embodiments using variables corresponding to the clusters obtained from the time series data relating to the slag level as the explanatory variables, it is shown that the removal rate constant k and the phosphorus concentration in the molten steel can be estimated more accurately.

From the above, it can be seen that, in each of the examples, the denudation rate constant k at the time of the sub-lance measurement and at the end point and the phosphorus concentration in the molten steel can be estimated with high accuracy, as compared with the comparative example. Particularly, as shown in Examples 2 and 3, it has been shown that the accuracy is further improved by using the variable corresponding to the cluster obtained from the time-series data relating to the slag level as the explanatory variable for calculation of the rate of extinction k.

While 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 these examples. It will be apparent to those skilled in the art that various changes and modifications may be made without departing from the scope of the invention as defined in the appended claims. It is to be understood that they fall within the technical scope of the present invention.

1: Conversion coil system
10: Converter installation
11: Converter
12: Year
13:
14: Servant
20: Converter control device
21: Transmission-blown 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
201: Data acquisition unit
202: Cluster determination unit
203: Clustering execution unit
204: phosphorus concentration estimating unit

Claims (6)

A method for estimating the phosphorus concentration in molten steel used for primary refining performed by using the same converter as the dephosphorization treatment, the intermediate discharge treatment for discharging slag generated by the above-mentioned dephosphorization treatment, and the decarburization treatment,
A slag level data acquiring step of acquiring a slag level during the removal process;
An exhaust gas data acquiring step of acquiring an exhaust gas component and an exhaust gas flow rate during the decarburization treatment;
A molten steel obtaining step of obtaining the molten steel temperature and the carbon concentration in the molten steel by the sub-
The removal rate constant is calculated using the slag level, the exhaust gas component, the exhaust gas flow rate, the molten steel temperature and the data on the carbon concentration, and the operating conditions related to the removal process, the intermediate removal process and the decarburization process A phosphorus concentration estimation step of estimating phosphorus concentration in the molten steel at the decarburization treatment after the sub-lance measurement using the calculated de-phosphorus rate constant and the phosphorus concentration at the start of the de-
And estimating the concentration in the molten steel. The method according to claim 1, wherein, in the calculation of the removal rate constant, using a category variable for identifying clusters obtained by time series clustering performed on time series data of a plurality of slag levels acquired in past operations, Method of estimating heavy concentration. The method according to claim 1 or 2, wherein, in the calculation of the de-lining rate constant, the average value of the slag level data obtained at the time of the de-lining process is used. Which is used for primary refining which is carried out by using the same converter, wherein the deodorizing treatment, the intermediate disposal treatment for discharging the slag generated by the deodorizing treatment,
A slag level data acquisition unit for acquiring a slag level during the removal process;
An exhaust gas data acquisition unit for acquiring an exhaust gas component and an exhaust gas flow rate during the decarburization treatment;
A molten steel obtaining unit for obtaining the molten steel temperature and the carbon concentration in the molten steel by the sub-
The removal rate constant is calculated using the slag level, the exhaust gas component, the exhaust gas flow rate, the molten steel temperature and the data on the carbon concentration, and the operating conditions related to the removal process, the intermediate removal process and the decarburization process And a phosphorus concentration estimating section for estimating phosphorus concentration in the molten steel at the time of the decarburization treatment after the sub-lance measurement by using the dediffering rate constant calculated and the phosphorus concentration at the start of the removal treatment,
And a control unit for controlling the switching unit. The method according to claim 4, characterized in that the phosphorus concentration estimating section calculates the phosphorus concentration rate in a category that identifies clusters obtained by time series clustering performed on time series data of a plurality of slag levels obtained in past operations Using a variable. The transfer passage controlling apparatus according to claim 4 or 5, wherein the phosphorus concentration estimating section uses an average value of the time series data of the slag level obtained in the removal process in the calculation of the removal rate constant.

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