Melt height detection method, melt height detection device, and melt production method

Abstract

To provide a method and a device for detecting a melt height, which can accurately detect the melt height in a blast furnace.SOLUTION: A melt height detection method for detecting a melt height in a blast furnace, includes the steps of: measuring a vibration at least one or more positions of a furnace wall in a furnace lower section of the blast furnace; analyzing a frequency of the vibration to calculate a vibration intensity of a frequency correlated with a vibration generated by introducing a gas into an inlet of the furnace lower section; and detecting a melt height in the blast furnace using a corrected vibration intensity obtained by removing influences of a blowing amount of the gas introduced from the inlet and physical properties of a packed bed present in the furnace lower section from the vibration intensity of the frequency.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a molten material height detection method for detecting the molten material height inside a blast furnace, a molten material height detection device, and a molten material manufacturing method. [Background technology]

[0002] An example of a blast furnace whose interior cannot be directly inspected is the blast furnace used in the steelmaking process. A blast furnace is a facility that produces pig iron by heating iron ore, the raw material for iron, and coke, the fuel, with high-temperature gas, causing them to react. The molten pig iron and slag produced in the blast furnace accumulate as a liquid pool at the bottom of the furnace and are discharged from the furnace approximately once every three hours to be supplied to the next process.

[0003] During blast furnace operation, if the furnace experiences insufficient heat or the particle size of the packed bed at the bottom of the furnace decreases, the resistance to the flow of molten material increases, which can reduce the amount of molten material discharged outside the furnace. As a result, the molten material level (molten material height) rises, causing a deterioration in the gas permeability inside the blast furnace, leading to furnace cooling and damage to furnace equipment. In this case, the blast furnace may eventually be forced to shut down, raising concerns that this could significantly reduce the production of steel products throughout the steelworks. For this reason, it is essential to constantly monitor the amount of molten material accumulated inside the blast furnace and to detect blast furnace problems early.

[0004] In light of this background, technologies have been proposed for measuring the height of molten material inside a blast furnace and detecting excessive accumulation of molten material. Specifically, Patent Document 1 describes a technology in which two or more images of the molten material discharge flow from a blast furnace are taken to determine the molten material discharge rate, and the determined discharge rate is substituted into an energy balance equation to calculate the molten material height. Patent Document 2 describes a technology in which elastic waves are input into a blast furnace and the molten material height is measured from the wave height of the reflected echo. Patent Document 3 describes a technology in which the vibration intensity of the furnace wall in the lower part of the blast furnace is measured, the frequency of the vibration intensity is analyzed to calculate the vibration intensity in a frequency band correlated with fluctuations in the molten metal and slag height, and the calculated vibration intensity is used to calculate the molten metal and slag height. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Laid-Open No. 2017-160498 [Patent Document 2] Japanese Patent Application Publication No. 10-185654 [Patent Document 3] International Publication No. 2022 / 201717 Summary of the Invention [Problem to be solved by the invention]

[0006] However, the technology described in Patent Document 1 utilizes the positive correlation between the discharge rate of the molten material and the molten material height. Therefore, if the discharge rate decreases due to clogging of the molten material discharge hole, it cannot detect an increase in the molten material height. Furthermore, visibility around the molten material discharge hole is poor due to dust in the factory, and the discharge flow may also be violently ejected, making it difficult to accurately capture images of the discharge flow. On the other hand, the technology described in Patent Document 2 may not be able to accurately measure the molten material height because there are many factors that affect the reflection characteristics of elastic waves, such as crack propagation in the furnace wall bricks that make up the blast furnace and solidification of the molten material. Furthermore, the technology described in Patent Document 3 does not know the actual molten metal / slag height in a blast furnace, making it difficult to identify a frequency band correlated with fluctuations in the molten metal / slag height.

[0007] The present invention has been made in view of the above-mentioned problems, and an object of the present invention is to provide a smelt height detection method and detection device capable of detecting the smelt height inside a blast furnace with high accuracy. Another object of the present invention is to provide a smelt manufacturing method capable of suppressing the occurrence of operational problems and manufacturing smelt with a high yield. [Means for solving the problem]

[0008] The smelt height detection method of the present invention is a method for detecting the smelt height inside a blast furnace, and includes the steps of measuring vibrations at at least one position on the furnace wall in the lower part of the blast furnace, analyzing the frequency of the vibrations and calculating the vibration intensity of a frequency that is correlated with the vibration generated by introducing gas into an inlet in the lower part of the furnace, and detecting the smelt height inside the blast furnace using a corrected vibration intensity that removes the effects of the blast volume of gas introduced from the inlet and the physical properties of the packed bed present in the lower part of the furnace from the vibration intensity of the frequency.

[0009] The frequency correlated with the vibrations generated by introducing gas into the inlet may be determined based on the correlation between the vibration intensity in a frequency band having a predetermined width, the gas blowing rate, and the physical properties of the packed bed present in the lower part of the furnace.

[0010] The physical properties of the packed bed preferably include at least particle size.

[0011] When the time transition of the corrected vibration intensity becomes a maximum or minimum, it may be determined that the height of the molten material inside the blast furnace is the position where the vibration is being measured.

[0012] The vibration may be measured at two or more different positions in the height direction of the furnace wall in the lower part of the furnace.

[0013] It is preferable to determine in advance the correspondence relationship between the corrected vibration intensity and the molten material height, and then use the corrected vibration intensity obtained from the vibration measurement and the correspondence relationship to detect the molten material height inside the blast furnace.

[0014] The smelt height detection device of the present invention is a smelt height detection device that detects the smelt height inside a blast furnace, and includes at least one vibration meter installed on the furnace wall in the lower part of the blast furnace and measuring the vibration of the furnace wall, and a calculation device that performs frequency analysis of the vibrations measured by the vibration meter to calculate the vibration intensity of a frequency correlated with the vibration generated by introducing gas into an inlet in the lower part of the furnace, calculates the vibration intensity of the gas blast volume introduced from the inlet from the vibration intensity of the frequency, and detects the smelt height in the blast furnace using a corrected vibration intensity that removes the effects of the gas blast volume introduced from the inlet and the physical properties of the packed bed present in the lower part of the furnace from the vibration intensity of the frequency.

[0015] The method for producing a molten material according to the present invention is a method for producing a molten material using a blast furnace, and includes the steps of measuring vibrations at at least one position on the furnace wall in the lower part of the blast furnace, analyzing the frequency of the vibrations and calculating the vibration intensity of a frequency correlated with the vibration generated by introducing gas into an inlet in the lower part of the furnace, detecting the molten material height inside the blast furnace using a corrected vibration intensity obtained by removing the effects of the gas blast volume introduced from the inlet and the physical properties of the packed bed present in the lower part of the furnace from the vibration intensity of the frequency, and adjusting the production conditions for the molten material so that the detected molten material height is within a target molten material height range. [Effects of the Invention]

[0016] The smelt height detection method and detection device according to the present invention can detect the smelt height inside a blast furnace with high accuracy. Also, the smelt production method according to the present invention can suppress the occurrence of operational problems and produce smelt with high yield. [Brief explanation of the drawings]

[0017] [Figure 1] FIG. 1 is a partial cross-sectional schematic diagram showing the configuration of the lower part of a blast furnace. [Figure 2] FIG. 2 is a partial cross-sectional schematic diagram showing the configuration of the lower part of a blast furnace and the molten material height detection device according to the first embodiment of the present invention. [Figure 3] FIG. 3 is a graph showing the time progression of the corrected vibration intensity. [Figure 4] FIG. 4 is a flow chart showing a method for identifying frequencies correlated to vibrations caused by introducing a gas. [Figure 5] FIG. 5 is a graph showing vibration data and vibration intensity data obtained by FFT processing of the vibration data. [Figure 6] FIG. 6 is a partial cross-sectional schematic diagram showing the configuration of the lower part of a blast furnace and a molten material height detection device according to the second embodiment of the present invention. [Figure 7] FIG. 7 is a graph showing the relationship between corrected vibration intensity and melt height. [Figure 8] FIG. 8 is a schematic diagram showing the configuration of the vibrometer of the first embodiment and its peripheral devices. [Figure 9] FIG. 9 is a contour diagram showing the coefficient of determination between the vibration intensity and the airflow rate calculated from the measurements of the vibration meter. [Figure 10] FIG. 10 is a graph showing the relationship between the vibration intensity measured by the vibration meter and the airflow rate. [Figure 11] FIG. 11 is a graph showing the relationship between the vibration intensity measured by the vibration meter and the particle size of the packed bed in the lower part of the furnace. [Figure 12] FIG. 12 is a graph showing the time course of the molten material height and corrected vibration intensity obtained from operational data. [Figure 13] FIG. 13 is a graph showing a regression equation between corrected vibration intensity and melt height. [Figure 14] FIG. 14 is a graph showing the relationship between the detected value of the molten material height calculated from the corrected vibration intensity and the actual value of the molten material height obtained from the operational data. DETAILED DESCRIPTION OF THE INVENTION

[0018] Hereinafter, a method and device for detecting the height of a molten material according to first and second embodiments of the present invention will be described with reference to the drawings.

[0019] [First embodiment] First, a molten material height detection method and detection device according to a first embodiment of the present invention will be described with reference to Figures 1 to 5. In this embodiment, the present invention is applied to a process for detecting the height of molten metal and slag, which is molten material accumulated at the bottom of a blast furnace, which is an example of a blast furnace.

[0020] Fig. 1 is a partial cross-sectional schematic diagram showing the configuration of the lower part of a blast furnace. As shown in Fig. 1, molten material (molten pig iron and slag) 12 composed of pig iron and slag is accumulated in the lower part of a blast furnace 10. The molten material 12 is discharged to the outside of the furnace through a discharge hole 14, generating a molten material flow 16. In addition, a blast tuyere 20 for introducing a gas 18 into the blast furnace 10 is provided in the lower part of the blast furnace 10. The blast tuyere 20 is an example of an inlet for introducing the gas 18 into the blast furnace 10.

[0021] Fig. 2 is a partial cross-sectional schematic diagram showing the configuration of a lower part of a blast furnace and a smelt height detection device according to a first embodiment of the present invention. As shown in Fig. 2, a smelt height detection device 22 according to a second embodiment of the present invention includes three vibrometers 24a to 24c and a computing device 26. The three vibrometers 24a to 24c are installed at equal intervals in the height direction on the furnace wall between the discharge hole 14 and the blast tuyere 20, and measure the vibration of the furnace wall to generate vibration data. The vibrometers 24a to 24c are configured, for example, by piezoelectric elements.

[0022] The vibration data generated by the vibration meters 24a to 24c is output to and recorded by the calculation device 26. The calculation device 26 is configured by a general-purpose computer such as a personal computer including a calculation unit such as a CPU and a storage unit such as a memory. The calculation device 26 performs frequency analysis on the vibration data acquired from the vibration meters 24a to 24c, and calculates the vibration intensity of a frequency that is correlated with the vibration generated by introducing gas from the blower tuyere 20.

[0023] In order to remove the influence of the gas blowing rate (introduction rate) and the particle size of the packed bed present in the lower part of the furnace from the calculated vibration intensity, the computing device 26 corrects the vibration intensity to a corrected vibration intensity using the following formula (1): By correcting the vibration intensity to the corrected vibration intensity, the influence of the gas blowing rate and the variation in particle size of the packed bed present in the lower part of the furnace on the vibration intensity can be removed.

[0024] G 0 =G+(BV 0 -BV)×a+(DP 0 -DP)×b (1)

[0025] In the above formula, G 0 (m / s 2 ) is the corrected vibration intensity, G (m / s 2 ) is the vibration intensity before correction, BV 0 (Nm 3 / min) is the desired gas flow rate, BV (Nm 3 / min) is the volume of gas blown at the time when the vibration data used to calculate the vibration intensity G was measured, a is the slope of the regression line when the vibration intensity of the frequency band of vibration caused by the blown air is on the y-axis and the volume of blown air is on the x-axis, and DP 0 (m) is an arbitrary particle size in the packed bed at the bottom of the furnace, DP(m) is the average particle size in the packed bed at the time when the vibration data used to calculate the vibration intensity G was measured, and b is the slope of the regression line when the vibration intensity in the frequency band of the vibration caused by the air blowing is plotted on the y-axis and the average particle size in the packed bed at the bottom of the furnace is plotted on the x-axis.

[0026] FIG. 3 is a graph showing the time progression of the corrected vibration intensity. The horizontal axis of FIG. 3 represents time, and the vertical axis represents the corrected vibration intensity. As shown in FIG. 3, when the height of the molten material 12 is lower than the installation height of the vibration meters 24a to 24c, a positive correlation is obtained between the corrected vibration intensity and time. On the other hand, when the height of the molten material 12 is higher than the installation height of the vibration meters 24a to 24c, a negative correlation is obtained between the corrected vibration intensity and time. Therefore, for example, if the time progression of the corrected vibration intensity shown in FIG. 3 is the corrected vibration intensity calculated from the vibration data generated by the vibration meter 24b, the height of the molten material 12 at the time when the relationship between the corrected vibration intensity and time changes from a positive correlation to a negative correlation and reaches a maximum can be determined to be the installation height of the vibration meter 24b.

[0027] The change in the relationship between corrected vibration intensity and time from a positive correlation to a negative correlation means that the vibration meter has detected the phenomenon of the molten liquid level rising. On the other hand, when the molten liquid level falls, the relationship between corrected vibration intensity and time changes from a negative correlation to a positive correlation. In this case, too, the height of the molten liquid 12 at the time when the relationship between corrected vibration intensity and time changes from a negative correlation to a positive correlation and reaches a minimum is the installation height of the vibration meter.

[0028] The computing device 26 monitors the time transition of the corrected vibration intensity obtained from the vibration data generated by the vibrometers 24a to 24c, and identifies a vibrometer in which the relationship between the corrected vibration intensity and time has changed from a positive correlation to a negative correlation, or a vibrometer in which the relationship between the corrected vibration intensity and time has changed from a negative correlation to a positive correlation. After identifying a vibrometer, the computing device 26 determines the installation height of the identified vibrometer as the height of the molten material 12 and detects the height of the molten material 12.

[0029] On the other hand, even if it is not possible to identify a vibrometer in which the relationship between the corrected vibration intensity and time has changed from a positive correlation to a negative correlation, or a vibrometer in which the relationship between the corrected vibration intensity and time has changed from a negative correlation to a positive correlation, if there is a vibrometer in which the relationship between the corrected vibration intensity and time is positive and a vibrometer in which the relationship between the corrected vibration intensity and time is negative, the computing device 26 detects the height of the molten material 12 by determining that the height is between the installation heights of those vibrometers. In this way, the computing device 26 detects the height of the molten material 12 in the blast furnace 10 from the vibration data generated by the vibrometers 24a to 24c.

[0030] Although this embodiment has three vibrometers 24a to 24c, the number of vibrometers is not limited to this. The smelt height detection device 22 only needs to have at least one vibrometer, and the height of the smelt 12 can be detected if the relationship between the corrected vibration intensity obtained from the vibration data generated by this vibrometer and time changes from a positive correlation to a negative correlation. However, since the height of the smelt 12 is detected based on the installation height of the vibrometer as described above, it is preferable that the smelt height detection device 22 have two or more vibrometers installed at different positions in the height direction of the lower part of the blast furnace 10. This allows the detection range for the height of the smelt 12 in the lower part of the blast furnace 10 to be expanded in the height direction.

[0031] 4 is a flowchart illustrating a method for identifying a frequency correlated with vibrations generated by introducing gas. A method for identifying a frequency correlated with vibrations generated by introducing gas from the blast tuyere 20 will be described with reference to FIG. 4. This frequency identification is preferably performed using a vibration meter 24a installed closest to the blast tuyere 20, and is preferably performed during a period when operation of the blast furnace 10 is stable. A period when operation of the blast furnace 10 is stable means a period when the coke rate in blast furnace operation is within a target range and fluctuations in permeability within the blast furnace are low.

[0032] In this identification method, first, the vibrometer 24a measures the vibration of the lower part of the blast furnace 10 to generate vibration data (step S101). Next, the arithmetic unit 26 performs FFT processing on the vibration data to perform frequency analysis of the vibration data (step S102). The arithmetic unit 26 may perform overlap processing, smoothing processing, window function processing, etc., as necessary, on the vibration data before performing FFT processing.

[0033] FIG. 5 is a graph showing vibration data and vibration intensity data obtained by FFT-processing the vibration data. FIG. 5(a) shows the vibration data, and FIG. 5(b) shows the vibration intensity data after FFT processing. In this way, the arithmetic unit 26 performs FFT processing on the vibration data shown in FIG. 5(a) to convert it into the vibration intensity data shown in FIG. 5(b). It is preferable that the arithmetic unit 26 uses this vibration intensity data to calculate vibration intensity at all frequencies. For example, when the frequency band is 1000 to 1200 kHz, the arithmetic unit 26 determines the vibration intensity for the frequency band 1000 to 1200 kHz as the arithmetic mean of the vibration intensities in the 1000 to 1200 kHz range.

[0034] Returning to FIG. 4, next, if the calculation device 26 has not acquired multiple pieces of this vibration intensity data under conditions where the gas blow rate is changed (step S103: No), it changes the gas blow rate (step S104) and repeats the processes of steps S101 and S102 again. On the other hand, if the calculation device 26 has acquired multiple pieces of vibration intensity data under conditions where the gas blow rate is changed (step S103: Yes), it calculates the coefficient of determination (R 2 ) is calculated (step S105).

[0035] The coefficient of determination (R 2 ), the calculation device 26 then identifies the frequency with the highest coefficient of determination among them as the frequency correlated with the vibration caused by introducing the gas (step S106). In this way, the calculation device 26 identifies in advance the frequency correlated with the vibration caused by introducing the gas.

[0036] The frequency correlated with the vibration caused by the introduction of gas may be identified using a plurality of vibration meters. For example, when the vibration meter 24a and the vibration meter 24b are used, the coefficient of determination (R 2 ) and average the coefficients of determination of the vibration meters 24a and 24b, and identify the frequency at which this average value is highest.

[0037] Furthermore, when calculating the coefficient of determination between the airflow rate and vibration intensity, the coefficient of determination (R 2 For example, the coefficient of determination may be calculated by taking into account a frequency range of ±25 Hz to ±300 Hz for each frequency. In this case, the coefficient of determination (R 2 ) and identify the frequency and frequency range where the coefficient of determination obtained by averaging these values ​​is the largest as the frequency and frequency range correlated with the vibration caused by introducing gas. By considering a predetermined frequency range for each frequency, the coefficient of determination becomes high.

[0038] As described above, the molten material height detection method and detection device according to the first embodiment of the present invention detects the height of the molten material 12 using the vibration intensity of a frequency correlated with the vibration generated by introducing gas through the blast tuyere 20. The frequency correlated with the vibration generated by introducing gas into the inlet of the blast furnace can be easily identified by acquiring vibration data obtained by changing the blast rate, making it easy to identify the frequency of the vibration intensity at which the molten material height in the blast furnace can be detected. Then, the molten material height inside the blast furnace, which cannot be directly observed with the naked eye, can be detected with high accuracy using a corrected vibration intensity obtained by removing the influence of the blast rate of the gas introduced through the inlet and the average particle size of the packed bed in the lower part of the furnace from the vibration intensity of the identified frequency.

[0039] It is also preferable to adjust the melt production conditions so that the melt height detected in this manner falls within a target melt height range in the blast furnace. For example, if the melt height is likely to be higher than the target range, the melt production conditions can be adjusted to reduce the amount of raw material charged or increase the amount of melt discharged. If the melt height is likely to be lower than the target range, the melt production conditions can be adjusted to increase the amount of raw material charged or decrease the amount of melt discharged. By adjusting the melt production conditions in this way so that the melt height falls within the target melt height range, for example, in a blast furnace, excessive rise in the melt level can be suppressed, and melt can be produced with a high yield while suppressing furnace cooling and damage to furnace equipment due to poor permeability.

[0040] Second Embodiment Next, a molten material height detection method and detection device according to a second embodiment of the present invention will be described with reference to Figures 6 and 7. In this embodiment, the present invention is applied to a process for detecting the height of molten metal and slag, which is a molten material accumulated at the bottom of a blast furnace, which is an example of a blast furnace.

[0041] Figure 6 is a partial cross-sectional schematic diagram showing the configuration of the lower part of a blast furnace and a smelt height detection device according to a second embodiment. As shown in Figure 6, a smelt height detection device 30 according to the second embodiment of the present invention includes one vibration meter 32 and a computing device 34. In Figure 6, the same components as those in Figure 2 are designated by the same reference numerals, and their description will be omitted.

[0042] The vibrometer 32 generates vibration data by measuring the vibration of the furnace wall at the bottom of the blast furnace 10. The vibrometer 32 is configured by, for example, a piezoelectric element.

[0043] The vibration data generated by the vibration meter 32 is output to and recorded by the calculation device 34. The calculation device 34 is configured by a general-purpose computer such as a personal computer including a calculation unit such as a CPU and a storage unit such as a memory. The calculation device 34 performs frequency analysis on the vibration data acquired from the vibration meter 32 and calculates the vibration intensity of a frequency correlated with the vibration generated by introducing gas from the blast tuyere 20. In order to remove the influence of the gas blast rate and the particle size of the packed bed present in the lower part of the furnace from the calculated vibration intensity, the calculation device 34 corrects the vibration intensity to a corrected vibration intensity using the above formula (1).

[0044] FIG. 7 is a graph showing the relationship between corrected vibration intensity and melt height. The horizontal axis of FIG. 7 is the corrected vibration intensity (m / s 2 ), and the vertical axis represents the height (m) of the molten material. A regression equation showing the correspondence relationship between the corrected vibration intensity and the height of the molten material 12 as shown in Fig. 7 is calculated in advance and stored in the computing device 34. It is preferable to create the regression equation showing the correspondence relationship between the corrected vibration intensity and the height of the molten material 12 using operational data from as long a period as possible.

[0045] After calculating the corrected vibration intensity, the calculation device 34 reads out data of the regression equation showing the correspondence relationship between the corrected vibration intensity and the height of the molten material shown in Figure 7, and detects the height of the molten material 12 using the regression equation and the calculated corrected vibration intensity. In this way, the molten material height detection device 30 detects the height of the molten material 12 in the blast furnace 10.

[0046] As described above, the molten material height detection method and detection device according to the second embodiment of the present invention detects the height of the molten material 12 using the vibration intensity of a frequency correlated with the vibration generated by introducing gas through the blast tuyere 20. The frequency correlated with the vibration generated by introducing gas into the inlet of the blast furnace can be easily identified by acquiring vibration data obtained by changing the blast flow rate, making it easy to identify the frequency of the vibration intensity at which the molten material height in the blast furnace can be detected. Then, by using the above regression equation and a corrected vibration intensity obtained by removing the effects of the blast flow rate of the gas introduced through the inlet and the particle size of the packed bed present in the lower part of the furnace from the vibration intensity of the identified frequency, the molten material height inside the blast furnace, which cannot be directly observed with the naked eye, can be detected with high accuracy.

[0047] [Example 1] Next, in order to confirm the validity of the present invention, 3 Example 1 will be described, in which the height of molten material accumulated in the lower part of a large blast furnace was detected. In this example, a device having the same configuration as the molten material height detection device 22 shown in Fig. 2 was used. Vibration meters 24a to 24c were installed at equal intervals between the blast tuyere 20 and the discharge hole 14 provided in the lower part of the blast furnace 10. The installation heights of the vibration meters 24a to 24c from the hearth, the heights of the blast tuyere 20, and the discharge hole 14 are shown in Table 1 below.

[0048] [Table 1]

[0049] FIG. 8 is a schematic diagram showing the configuration of a vibrometer and its peripheral devices according to Example 1. In FIG. 8, the same components as those in FIG. 2 are assigned the same reference numerals, and their description will be omitted. In this example, amplifiers 40a to 40c were connected to the vibrometers 24a to 24c to amplify the vibration data. The vibration data amplified by the amplifiers 40a to 40c was stored in data loggers 42a to 42c. The vibration data stored in the data loggers 42a to 42c was then processed using a computing device 26. The conditions for measuring the vibration were a sampling frequency of 10,000 Hz and a recording length of 10 seconds, assuming the vibration frequency due to the air blowing measured in a blast furnace. Under these conditions, the vibration of the furnace wall was measured every three minutes for four days, and vibration data for that period was obtained.

[0050] In this example, prior to FFT analysis, the vibration data underwent overlap processing, smoothing processing, and window function processing. In the overlap processing, the raw vibration data was divided into 3 / 10 of the recording length, and processed so that half of the data overlapped. Furthermore, each divided frame was subjected to smoothing processing using a Gaussian filter. Furthermore, a Hanning window was applied in the window function processing. After processing the divided frames in this way, FFT analysis was performed on all divided frames, and the average value of the vibration intensity calculated by FFT analysis was used.

[0051] After FFT analysis, the vibration intensity for all frequency bands was calculated. In Example 1, vibrations with frequencies of 5000 Hz or less were measured using the vibration meters 24a to 24c. To evaluate the vibration intensity for all of these frequencies, the vibration frequency was divided into a reference vibration frequency f (Hz) and a frequency range Δf (Hz). That is, the average value of the vibration intensity of f±Δf was defined as the vibration intensity of f±Δf (Hz), and f was varied from 300 (Hz) to 4700 (Hz) in 50 (Hz) increments, and Δf was varied from 25 (Hz) to 300 (Hz) in 25 (Hz) increments to define the frequency band of f±Δf (Hz).

[0052] After calculating the vibration intensity at each frequency in this way, the coefficient of determination (R 2 In Example 1, the coefficient of determination (R 2 ) was calculated.

[0053] FIG. 9 shows the coefficient of determination (R 2 9(a) is a contour diagram of the vibration meter 24a, and FIG. 9(b) is a contour diagram of the vibration meter 24b. In Example 1, R 2 Therefore, f±Δf=1400±250 (Hz) was set as the frequency correlated with the vibration generated by introducing gas.

[0054] Next, the vibration intensity was corrected for the airflow rate and the particle size of the packed bed in the lower part of the furnace. The correction was carried out by determining the regression line to be used in the above formula (1) using the vibration intensity, airflow rate, and particle size of the packed bed in the lower part of the furnace for two days out of the four days for which vibration data was measured, when the amount of accumulated molten material in the lower part of the furnace was small.

[0055] FIG. 10 is a graph showing the relationship between the vibration intensity of the vibration meters 24a to 24c and the airflow rate. FIG. 10(a) shows the graph and regression line of the vibration meter 24a, FIG. 10(b) shows the graph and regression line of the vibration meter 24b, and FIG. 10(c) shows the graph and regression line of the vibration meter 24c. The horizontal axis of these graphs represents the airflow rate (Nm 3 / min, and the vertical axis is the vibration intensity (m / s 2 ) Fig. 11 is a graph showing the relationship between the vibration intensity of the vibration meters 24a to 24c and the particle size of the packed bed in the lower part of the furnace. Fig. 11(a) shows the graph of the vibration meter 24a and the regression line, Fig. 11(b) shows the graph of the vibration meter 24b and the regression line, and Fig. 11(c) shows the graph of the vibration meter 24c and the regression line. The horizontal axis of these graphs is the particle size (m) of the packed bed in the lower part of the furnace, and the vertical axis is the vibration intensity (m / s 2) The slopes of these regression lines were substituted into the above formula (1) to calculate the following formulas (2), (3), and (4).

[0056] G 0 =G+(BV-BV 0 )×2.00×10 -3 +(DP-DP 0 )×3.91×10 -3 ···(2)

[0057] G 0 =G+(BV-BV 0 )×1.72×10 -3 +(DP-DP 0 )×4.12×10 -3 ···(3)

[0058] G 0 =G+(BV-BV 0 )×1.04×10 -3 +(DP-DP 0 )×3.78×10 -3 ···(4)

[0059] The corrected vibration intensity was calculated by using the above formulas (2) to (4), eliminating the influence of the blast rate and the particle size of the packed bed in the lower part of the furnace.The calculated corrected vibration intensity was then used to detect the melt height.

[0060] FIG. 12 is a graph showing the time transition of the molten material height and the time transition of the corrected vibration intensity obtained from the operational data. FIG. 12(a) is a graph showing the time transition of the molten material height obtained from the operational data, with the horizontal axis representing time and the vertical axis representing the molten material height (m). FIG. 12(b) to (d) are graphs showing the time transition of the corrected vibration intensity of the vibration meters 24a to 24c, with the horizontal axis representing time and the vertical axis representing the corrected vibration intensity (m / s 2 )

[0061] As shown in Figure 12, the corrected vibration intensity value for vibration meter 24c began to decrease from 4:30 PM on August 3, while it continued to increase for vibration meters 24a and 24b. Therefore, from 4:30 PM to 11:59 PM on August 3, the molten material height was between 4.8 and 5.2 m, which is between vibration meters 24b and 24c. The molten material height values ​​estimated and calculated at the same time showed an increase from approximately 4.4 m to 5.2 m between 4:30 PM and 11:59 PM on April 19. Thus, the molten material height detected from the vibration intensity and the molten material height estimated and calculated from the operational data were nearly identical, confirming that the molten material height could be detected using the method of Example 1.

[0062] [Example 2] Next, Example 2 will be described, in which it was confirmed that the melt height can be detected using a single vibration meter. In Example 2, the same capacity as Example 1 was used, but the melt height was 5000 m 3 The molten material height of the large blast furnace was detected using vibration data from the vibration meter 24a. As in Example 1, the vibration data acquired from the vibration meter 24a was subjected to overlap processing, smoothing processing, and window function processing, and then FFT analysis.

[0063] The frequency correlated with the vibration caused by the air blowing was set to f±Δf=1400±250 (Hz), the same as in Example 1. The vibration intensity at this frequency from 0:00 to 23:59 on August 3rd was corrected using the above formula (2) to calculate the corrected vibration intensity. In addition, the molten material height in the blast furnace was calculated using the operation data obtained from the blast furnace from 0:00 to 23:59 on August 3rd and the following formula (5).

[0064] h=(Wi / ρi+Ws / ρs) / (ε×Sb)···(5)

[0065] In the above formula (5), h is the melt height (m), Wi (kg) is the weight of the hot metal at the hearth, and ρi (kg / m 3 ) is the density of the hot metal, Ws (kg) is the weight of the molten slag at the hearth, ρs (kg / m 3 ) is the density of the molten slag, ε(-) is the hearth void ratio, Sb(m 3) is the cross-sectional area of ​​the hearth. The weights of the molten pig iron and molten slag at the hearth were calculated by adding the amounts of pig iron and slag obtained at each tapping operation minus the amounts of pig iron and slag tapped, and correcting for the error of the weighing machine in the actual machine. In Example 2, the density of the molten pig iron was 6800 (kg / m 3 ), and the molten slag density is 2650 (kg / m 3 ) and the hearth void ratio was set to 0.35. Using the corrected vibration intensity and molten material height calculated in this way, a regression equation showing the correspondence relationship between the corrected vibration intensity and the molten material height was obtained.

[0066] FIG. 13 is a graph showing a regression equation between corrected vibration intensity and melt height. The horizontal axis of FIG. 13 is the corrected vibration intensity (m / s 2 ), and the vertical axis is the melt height (m). The regression equation shown in Figure 13 is the calibration curve for detecting the melt height from the corrected vibration intensity. The regression equation obtained from the graph in Figure 13 is the following formula (6).

[0067] h=G 0 ×0.6953-18.486···(6)

[0068] In the above formula (6), G 0 is the corrected vibration intensity (m / s 2 ) The melt height was detected using this formula (6). The melt height was calculated using the corrected vibration intensity at four points around midnight on August 3rd and the formula (6) above. The actual melt height was calculated using the operational data at four points at the same time and the formula (5) above.

[0069] Fig. 14 is a graph showing the relationship between the detected molten material height calculated from the corrected vibration intensity and the actual molten material height calculated from operational data. The horizontal axis of Fig. 14 represents the detected molten material height (m) calculated from the corrected vibration intensity, and the vertical axis represents the actual molten material height (m). As shown in Fig. 14, the detected molten material height calculated from the regression equation of Equation (6) and the actual molten material height calculated from operational data were almost identical. This result confirmed that the molten material height can be detected by the method of Example 2. [Explanation of symbols]

[0070] 10 blast furnace 12 Melt 14 Discharge hole 16 Melt flow 18 Gases 20 Blow tuyere 22 Melt height detection device 24a~24c Vibration meter 26 Arithmetic unit 30 Melt height detection device 32 Vibration meter 40a~40c amplifier 42a~42c Data logger

Claims

1. A method for detecting a molten material height inside a blast furnace, comprising: measuring vibrations at at least one position on the furnace wall in the lower part of the blast furnace; A step of analyzing the frequency of the vibration and calculating the vibration intensity of a frequency correlated with the vibration generated by introducing gas into the inlet at the lower part of the furnace; Detecting the molten material height inside the blast furnace using a corrected vibration intensity obtained by removing the influence of the amount of gas introduced from the inlet and the physical properties of the packed bed present in the lower part of the furnace from the vibration intensity of the frequency; 10. A method for detecting a melt height, comprising:

2. 2. The method for detecting the height of a molten material according to claim 1, wherein the frequency correlated with the vibration generated by introducing gas into the inlet is identified based on a correlation between the vibration intensity of a frequency band having a predetermined width, the blowing rate of the gas, and the physical properties of the packed bed present in the lower part of the furnace.

3. The method for detecting a melt height according to claim 1 , wherein the physical properties of the packed bed include at least a particle size.

4. 2. The method for detecting a molten material height according to claim 1, wherein when the time transition of the corrected vibration intensity becomes a maximum or a minimum, it is determined that the molten material height inside the blast furnace is at the position where the vibration is being measured.

5. The method for detecting a molten material height according to claim 1 , wherein the vibration is measured at two or more different positions in a height direction of the furnace wall in the lower part of the furnace.

6. A correspondence relationship between the corrected vibration intensity and the melt height is determined in advance, 2. The method for detecting a smelt height according to claim 1, further comprising the step of detecting a smelt height inside a blast furnace using the corrected vibration intensity obtained from the vibration measurement and the correspondence relationship.

7. A molten material height detection device for detecting the molten material height inside a blast furnace, At least one vibration meter is provided on a furnace wall in a lower part of the blast furnace to measure vibration of the furnace wall; a computing device that performs frequency analysis on the vibrations measured by the vibration meter to calculate the vibration intensity of a frequency that is correlated with the vibration generated by introducing gas into the inlet at the bottom of the furnace, calculates the vibration intensity of the gas flow rate introduced from the inlet from the vibration intensity of the frequency, and detects the molten material height in the blast furnace using a corrected vibration intensity obtained by removing the influence of the gas flow rate introduced from the inlet and the physical properties of the packed bed present in the bottom of the furnace from the vibration intensity of the frequency; 1. A melt height detection device comprising:

8. A method for producing a molten material using a blast furnace, measuring vibrations at at least one position on the furnace wall in the lower part of the blast furnace; A step of analyzing the frequency of the vibration and calculating the vibration intensity of a frequency correlated with the vibration generated by introducing gas into the inlet at the lower part of the furnace; Detecting the molten material height inside the blast furnace using a corrected vibration intensity obtained by removing the influence of the amount of gas introduced from the inlet and the physical properties of the packed bed present in the lower part of the furnace from the vibration intensity of the frequency; adjusting the melt production conditions so that the detected melt height is within a target melt height range; A method for producing a melt, comprising:

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