Method for monitoring molten iron level of blast furnace slag in multiple iron tapping shared with multiple sets of slag granulation treatment system

Abstract

The present application relates to iron-making technology field, specifically relates to a kind of multi-iron mouth shared multi-set blast furnace slag granulation processing system's blast furnace slag liquid level monitoring method, by the corresponding deviation relationship between the theoretical slag generation amount and slag discharge rate sequence in historical reference heats, determine the independent correction parameter corresponding to each slag granulation processing system, and using the independent correction parameter, the slag discharge rate sequence of each slag granulation processing system associated with the current heats is weightedly corrected and accumulated summation, and the modified total slag discharge rate sequence is obtained;This kind of dynamic correction mode for the error characteristic difference of each system under the mapping relationship of multi-iron mouth sharing effectively eliminates the systematic deviation in measured data and its drift accumulated with time, solves the problem of liquid level monitoring failure caused by measurement distortion.

Description

Technical Field

[0001] This invention relates to the field of ironmaking technology, specifically to a method for monitoring the molten iron level in blast furnace slag using a shared slag granulation treatment system with multiple tapholes. Background Technology

[0002] For extra-large blast furnaces, in order to balance the huge investment in equipment, the limited space of the tapping area and the need for continuous production, an asymmetric layout of multiple tapping points sharing a slag granulation system is often adopted. Taking the typical INBA Inba process system as an example, its structure is usually configured with three circumferentially distributed tapping points, but only two sets of granulation devices are set up. Through a specific channel allocation logic, two of the tapping points take turns sharing one set of systems, while the third tapping point is independently connected to the other set.

[0003] Because the high-temperature, high-pressure environment inside the furnace hearth makes it impossible to directly measure the liquid level, the industry mainly relies on material balance models to indirectly estimate the slag and iron accumulation based on data from charging, tapping, and slag removal. However, existing slag granulation systems, such as the INBA system, often estimate the slag discharge rate through indirect signals like drum current, which are highly susceptible to interference from flushing water flow, moisture content, and equipment operating conditions, leading to significant systematic biases in the measured data. Especially under the complex mapping of multiple tapholes, this bias not only accumulates over time, causing severe distortion in the liquid level calculation, but also dynamically changes the error characteristics due to uneven load on the shared system, rendering traditional single correction methods ineffective. Ultimately, this results in the model failing to accurately reflect the true state of the furnace hearth, making it difficult to guide the judgment of taphole clogging timing and safe operations at the furnace front. Summary of the Invention

[0004] This invention provides a method for monitoring the molten slag and iron level in blast furnaces using multiple slag granulation systems shared by multiple tapholes. This method addresses the problem in existing technologies where the molten slag and iron level monitoring fails due to the accumulation of metering deviations over time and the lack of an adaptive correction mechanism in the shared system, making it difficult to support refined blast furnace operations.

[0005] In a first aspect, the present invention provides a method for monitoring the molten iron level in blast furnaces using multiple tapholes and multiple slag granulation systems. The blast furnace has multiple tapholes and at least two slag granulation systems. A preset mapping relationship exists between the tapholes and the slag granulation systems, wherein at least one slag granulation system simultaneously corresponds to two or more tapholes. The method includes the following steps: obtaining the slag discharge rate sequence of each slag granulation system associated with the current furnace run; obtaining the theoretical slag generation amount for each furnace run in historical reference furnace runs, and the slag discharge rate sequence of each slag granulation system associated with the historical reference furnace runs; based on... The corresponding deviation between the theoretical slag generation of each heat in the historical reference heats and the slag discharge rate sequence of each slag granulation treatment system is used to determine the independent correction parameters corresponding to each slag granulation treatment system. Using the independent correction parameters corresponding to each slag granulation treatment system, the slag discharge rate sequence of each slag granulation treatment system associated with the current heat is weighted and corrected, and the corrected sequences are summed to obtain the corrected total slag discharge rate sequence of the current heat. Based on the corrected total slag discharge rate sequence, the slag accumulation of the current heat is calculated. The slag and iron accumulation of the current heat is determined based on the slag accumulation of the current heat.

[0006] The blast furnace slag molten iron level monitoring method provided by this invention, based on the corresponding deviation relationship between the theoretical slag generation and slag discharge rate sequence in historical reference furnaces, determines the independent correction parameters corresponding to each slag granulation system. These independent correction parameters are then used to perform weighted correction and summation on the slag discharge rate sequences of each slag granulation system associated with the current furnace, resulting in a corrected total slag discharge rate sequence. This multi-channel dynamic correction method, addressing the differences in error characteristics of each system under the shared mapping relationship of multiple tapholes, effectively eliminates systematic deviations in the measured data and their drift accumulated over time, solving the problem of molten iron level monitoring failure caused by measurement distortion.

[0007] In some optional implementations, determining the independent correction parameters for each slag granulation system based on the corresponding deviation between the theoretical slag generation of each heat in historical reference heats and the slag discharge rate sequence of each slag granulation system includes: selecting N consecutive historical reference heats prior to the current heat; integrating the slag discharge rate sequence of each slag granulation system for each selected historical reference heat over time to obtain the total discharge per heat for each slag granulation system corresponding to each historical reference heat; constructing a multiple linear regression model with the theoretical slag generation per heat of the N historical reference heats as the dependent variable and the total discharge per heat of each slag granulation system of the N historical reference heats as the independent variable, and the multiple linear regression model does not include an intercept term; solving the multiple linear regression model and determining the regression coefficients corresponding to each independent variable as the independent correction parameters for each slag granulation system.

[0008] This implementation method obtains the total discharge volume of a single furnace by integrating the slag discharge rate sequence over time, and constructs a multiple linear regression model without intercept term to solve for the regression coefficients as independent correction parameters. This method strictly follows the physical characteristics of zero slag discharge corresponding to zero raw slag, and utilizes the corresponding deviation relationship of N consecutive historical reference furnaces to achieve precise decoupling of the independent correction parameters of each slag granulation treatment system, effectively eliminating the error coupling caused by multiple tapholes sharing, and ensuring the accuracy of slag accumulation and slag-iron accumulation calculations.

[0009] In some optional implementations, solving the multiple linear regression model and determining the regression coefficients corresponding to each independent variable as independent correction parameters for each slag granulation system includes: constructing an objective function using the least squares method, where the objective function is the sum of squared residuals between the theoretical slag generation per furnace of N historical reference furnaces and the predicted values ​​of the multiple linear regression model; solving for the regression coefficients that minimize the objective function, and determining the obtained regression coefficients as independent correction parameters for each slag granulation system.

[0010] This implementation method constructs and minimizes the objective function of the residual sum of squares using the least squares method, and solves for the regression coefficients as independent correction parameters. Mathematically, this ensures that the independent correction parameters of each slag granulation treatment system minimize the overall deviation between the theoretical slag generation and the predicted value. This statistically optimal strategy effectively smooths out the random noise in the data of a single furnace, ensures the optimality of the independent correction parameters, and thus significantly improves the reliability of the corrected total slag discharge rate sequence and the accuracy of the slag accumulation calculation.

[0011] In some optional implementations, when the blast furnace is equipped with a first slag granulation treatment system and a second slag granulation treatment system, the regression coefficients that minimize the objective function are obtained by: constructing a system of two linear equations consisting of the total discharge amount per furnace of the first slag granulation treatment system, the total discharge amount per furnace of the second slag granulation treatment system, and the theoretical slag generation amount per furnace; solving the system of two linear equations to obtain the first correction coefficient corresponding to the first slag granulation treatment system and the second correction coefficient corresponding to the second slag granulation treatment system.

[0012] This implementation method directly obtains the first and second correction coefficients by constructing and solving a system of two linear equations containing the total discharge amount per furnace and the theoretical slag generation amount per furnace of the first and second slag granulation treatment systems. This method transforms the abstract least squares optimization into a specific algebraic analytical process, which not only has high computational efficiency and strong real-time performance, but also accurately decouples the independent error characteristics of the two systems in the scenario of multiple tapholes.

[0013] In some optional implementations, the slag discharge rate sequences of each slag granulation system associated with the current furnace are weighted and corrected using independent correction parameters corresponding to each slag granulation system. The corrected sequences are then summed to obtain the corrected total slag discharge rate sequence for the current furnace. This includes: multiplying the rate values ​​at each moment in the slag discharge rate sequence of each slag granulation system associated with the current furnace by the independent correction parameters of the corresponding system to obtain the corrected slag discharge rate sequence for each system; summing the rate values ​​in the corrected slag discharge rate sequences of each system at the same moment to obtain the corrected total slag discharge rate at the corresponding moment; and arranging the corrected total slag discharge rates at all moments within the time range of the current furnace in chronological order to form the corrected total slag discharge rate sequence for the current furnace.

[0014] This implementation method achieves point-to-point synchronous correction of slag discharge data from multiple systems by multiplying the rate values ​​at each moment by the corresponding independent correction parameters and accumulating them at the same moment. This refined processing not only eliminates the dynamic measurement deviation caused by load differences in each system, but also retains the instantaneous change characteristics of the slag discharge process, ensuring the authenticity of the corrected total slag discharge rate sequence and providing a reliable data foundation for high-precision calculation of slag accumulation and slag-iron accumulation.

[0015] In some optional implementations, calculating the current furnace slag accumulation based on the corrected slag discharge rate sequence includes: obtaining the theoretical slag generation rate sequence of the current furnace, which is determined based on the composition of the raw materials fed into the furnace and the charging data; performing a difference operation between the theoretical slag generation rate sequence and the corrected slag discharge rate sequence to obtain the current furnace net slag accumulation rate sequence; performing an accumulation operation on the net slag accumulation rate sequence to obtain the current furnace slag storage; and determining the current furnace slag accumulation based on the slag storage and the hearth structural parameters of the current furnace.

[0016] This implementation method obtains the net slag accumulation rate sequence by performing a difference calculation between the theoretical slag generation rate sequence and the corrected slag discharge rate sequence, and then obtains the slag storage amount through accumulation calculation. In combination with the hearth structural parameters, the slag storage amount is accurately determined. Based on the principle of real-time material balance, this scheme uses the corrected high-precision slag discharge data to dynamically restore the slag quantity change process in the furnace, effectively eliminating false accumulation or loss of liquid level caused by metering deviation, and ensuring that the slag storage amount calculation result can truly reflect the actual state of the slag-iron interface in the hearth.

[0017] Secondly, the present invention provides a blast furnace slag-iron liquid level monitoring device that shares multiple slag granulation treatment systems across multiple tapholes. The blast furnace is equipped with multiple tapholes and at least two slag granulation treatment systems. A preset mapping relationship exists between the tapholes and the slag granulation treatment systems, wherein at least one slag granulation treatment system simultaneously corresponds to two or more tapholes. The device includes a first acquisition module, a second acquisition module, a correction parameter determination module, a correction module, a slag accumulation determination module, and a slag-iron accumulation determination module. The first acquisition module is used to acquire the slag discharge rate sequence of each slag granulation treatment system associated with the current furnace. The second acquisition module is used to acquire the theoretical slag generation amount of each furnace in the historical reference furnace, as well as the slag granulation treatment systems associated with the historical reference furnace. The slag discharge rate sequence is determined by the following modules: The correction parameter determination module determines the independent correction parameters for each slag granulation system based on the corresponding deviation between the theoretical slag generation of each heat in historical reference heats and the slag discharge rate sequence of each slag granulation system; the correction module uses the independent correction parameters for each slag granulation system to perform weighted correction on the slag discharge rate sequences of each slag granulation system associated with the current heat, and sums the corrected sequences to obtain the corrected total slag discharge rate sequence for the current heat; the slag accumulation determination module calculates the slag accumulation for the current heat based on the corrected total slag discharge rate sequence; and the slag and iron accumulation determination module determines the slag and iron accumulation for the current heat based on the slag accumulation for the current heat.

[0018] Thirdly, the present invention provides an electronic device, including a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes the computer instructions to perform the blast furnace slag-iron level monitoring method for a multi-tap shared multi-set slag granulation treatment system described in the first aspect or any of its corresponding embodiments.

[0019] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the blast furnace slag-iron level monitoring method for a multi-tap shared multi-set slag granulation treatment system according to the first aspect or any corresponding embodiment described above.

[0020] Fifthly, the present invention provides a computer program product, including computer instructions, which are used to cause the computer to execute the blast furnace slag-iron level monitoring method of a multi-tap shared multi-set slag granulation treatment system in the first aspect or any corresponding embodiment described above. Attached Figure Description

[0021] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of an application scenario according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the slag-iron liquid level curve in the blast furnace hearth of a multi-tap slag granulation treatment system in related technologies. Figure 3 This is a first flowchart of a method for monitoring the molten iron slag level in a blast furnace with multiple tapholes sharing multiple sets of slag granulation treatment systems, according to an embodiment of the present invention. Figure 4 This is a second flowchart of a method for monitoring the molten iron slag level in a blast furnace using multiple sets of slag granulation treatment systems shared by multiple tapholes, according to an embodiment of the present invention. Figure 5 This is a schematic diagram of the blast furnace hearth slag-iron liquid level verification of a multi-tap shared slag granulation treatment system according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the slag-iron liquid level curve in the blast furnace hearth of a multi-tap shared slag granulation treatment system according to an embodiment of the present invention. Figure 7 This is a structural block diagram of a blast furnace slag-iron liquid level monitoring device for a multi-tap shared slag granulation treatment system according to an embodiment of the present invention; Figure 8 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0025] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0026] As an optional application scenario of this invention, such as Figure 1 As shown, a monitoring system for slag and iron accumulation in the blast furnace hearth may include at least one terminal device and at least one server. Figure 1 The system is illustrated in the example, which includes a computer 101, a mobile terminal 102, and a server 103, and the terminal devices such as the computer 101 and the mobile terminal 102 are connected to the server 103 through a network 110.

[0027] Specifically, the terminal device can be a smartphone, tablet, laptop, PDA, desktop computer, game console, smart TV, smart wearable device, in-vehicle terminal, VR (Virtual Reality) device, AR (Augmented Reality) device, etc. Server 103 can be a standalone physical server, a server cluster, a distributed system, or a cloud server providing cloud services. Network 110 can be a wired or wireless network, examples of which include, but are not limited to, the Internet, corporate intranet, local area network, wide area network, mobile communication network, and combinations thereof.

[0028] Figure 2 This is a schematic diagram of the slag-iron molten metal level curve in the blast furnace hearth of a multi-tap slag granulation treatment system in related technologies, such as... Figure 1 As shown, the horizontal axis is the time axis, and the vertical axis is the mass (based on the taphole). The black curve represents the mass of molten iron accumulated based on the vertical distance from the taphole to the top surface of the molten iron; the red curve represents the mass of slag accumulated based on the vertical distance from the top surface of the molten iron to the top surface of the slag; and the blue curve represents the total mass of slag and iron accumulated based on the total vertical height from the taphole to the top surface of the slag. These values ​​represent the sum of the masses of molten iron and slag accumulated mentioned above. It should be noted that... Figure 2 The red and blue curve data are both comprehensive results obtained by simply summing the measured discharge rates of multiple slag granulation treatment systems (such as 1#INBA and 2#INBA) and then back-calculating them using a material balance model.

[0029] from Figure 2 As can be clearly seen, the red curve (i.e., slag accumulation) shows a continuous upward trend. However, during normal blast furnace tapping and slag removal, slag should be discharged periodically along with the molten iron, and the slag accumulation usually fluctuates within a certain range, rather than increasing monotonically for a long period. If the slag accumulation continues to rise, it means that the slag discharge calculated by the model is significantly lower than the actual amount generated. This often stems from the INBA system's underestimation of the slag removal rate, for example, interference from factors such as the amount of flushing water and the moisture content in the slag, leading to a smaller cumulative slag discharge and thus an inflated calculated slag accumulation. Therefore, the slag accumulation curve is clearly inconsistent with the actual operating conditions of the blast furnace, and a systematic verification and correction of the slag removal data and the liquid level curve derived from it is necessary.

[0030] According to an embodiment of the present invention, a method for monitoring the molten iron level of blast furnace slag shared by multiple tapholes and multiple sets of slag granulation treatment systems is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0031] This embodiment provides a method for monitoring the molten iron level in blast furnaces using multiple tapholes and multiple slag granulation systems, which can be used in the aforementioned mobile terminal. The blast furnace has multiple tapholes and at least two slag granulation systems. A preset mapping relationship exists between the tapholes and the slag granulation systems, wherein at least one slag granulation system corresponds to two or more tapholes simultaneously.

[0032] Figure 3 This is a first flowchart of a blast furnace slag-iron level monitoring method according to an embodiment of the present invention, which uses multiple sets of slag granulation treatment systems shared by multiple tapholes. Figure 3 As shown, the process includes the following steps: Step S301: Obtain the slag discharge rate sequence of each slag granulation treatment system associated with the current furnace.

[0033] Specifically, the slag discharge rate sequence can be the amount of slag discharged per unit time in chronological order from the slag granulation treatment system (such as INBA), i.e., the slag discharge rate.

[0034] Step S302: Obtain the theoretical slag generation amount for each heat in the historical reference heat, and the slag discharge rate sequence of each slag granulation treatment system associated with the historical reference heat.

[0035] Specifically, the theoretical slag production refers to the mass of dry slag that should theoretically be generated during blast furnace smelting, calculated based on the chemical composition and charge amount of the raw materials fed into the furnace, using the principles of material balance (especially the conservation of basic oxides). It does not rely on actual slag discharge measurements but is determined by the mineral composition of the input materials, thus possessing high accuracy and reliability.

[0036] For example, the method for determining the theoretical slag production includes the following steps: First, according to the blast furnace feeding system, obtain the mass and chemical composition (e.g., slag-forming components such as CaO, MgO, SiO2, Al2O3, etc.) of the raw materials such as iron ore, sinter, pellets, flux (such as limestone, dolomite), and coke fed into the furnace in each batch; second, based on the target basicity of the slag (such as binary basicity R = CaO / SiO2) or the set final slag composition, and in conjunction with the conservation of elements, calculate the total amount of slag required to neutralize the acidic gangue; finally, by comprehensively considering the contributions of each component, calculate the total mass of dry slag that should be generated in this furnace under ideal conditions, which is the theoretical slag production of this furnace.

[0037] Step S303: Based on the corresponding deviation relationship between the theoretical slag generation of each heat in the historical reference heat and the slag discharge rate sequence of each slag granulation treatment system, determine the independent correction parameters corresponding to each slag granulation treatment system.

[0038] Among them, the independent correction parameter refers to the error correction coefficient calculated separately for each slag granulation treatment system. It represents the proportional mapping relationship between the measured slag discharge rate and the actual theoretical slag quantity of the system.

[0039] Step S304: Using the independent correction parameters corresponding to each slag granulation treatment system, the slag discharge rate sequence of each slag granulation treatment system associated with the current furnace is weighted and corrected respectively, and the corrected sequences are summed to obtain the corrected total slag discharge rate sequence of the current furnace.

[0040] In other words, using the previously calculated independent correction parameters, the measured slag discharge rate data of each slag granulation treatment system in the current furnace are multiplied and corrected to eliminate the inherent measurement errors of each system. Then, the corrected rate values ​​of each system at the same time are summed up. Finally, a total rate sequence that can truly reflect the overall slag discharge situation of the current furnace is generated, which serves as the direct basis for subsequent calculation of slag layer height.

[0041] Step S305: Calculate the slag accumulation for the current furnace based on the corrected total slag discharge rate sequence.

[0042] Slag accumulation refers to the total amount of slag that has not yet been discharged from the blast furnace hearth. In this embodiment, the accumulation is a comprehensive state parameter, which can be expressed as either the physical mass of the slag or the vertical liquid level of the slag within the hearth. Given that the cross-sectional area of ​​the hearth and the slag density are considered known constants under specific operating conditions, and there is a strict one-to-one linear conversion relationship between the two, they can be interchangeably represented numerically.

[0043] In other words, by combining the current slag generation information of the furnace with the corrected discharge information, the storage status of the slag that has not been discharged in the hearth is estimated, and further converted into the slag accumulation amount that characterizes the slag layer height.

[0044] Step S306: Determine the current slag and iron accumulation in the furnace based on the current slag accumulation.

[0045] The slag-iron accumulation refers to the total mass of molten iron and slag within the blast furnace hearth. Similarly, the slag-iron accumulation can represent either the total physical mass of the slag-iron mixture or the total vertical height from the taphole reference surface to the top surface of the slag. Since the molten iron and slag are clearly separated and their physical properties are known, the mass value of the total accumulation is equal to the sum of their masses, and the height value of the total accumulation is equal to the sum of their liquid level heights.

[0046] Specifically, the current amount of molten iron in the furnace can be obtained (e.g., calculated based on the amount of molten iron stored), and then added to the already obtained amount of slag stored to finally obtain the amount of slag and iron stored, which reflects the absolute position of the slag surface in the hearth, and is used for visual monitoring and operation guidance.

[0047] The blast furnace slag molten iron level monitoring method provided in this embodiment, which uses the corresponding deviation relationship between the theoretical slag generation and slag discharge rate sequence in historical reference furnaces, determines the independent correction parameters corresponding to each slag granulation system. These independent correction parameters are then used to perform weighted correction and summation on the slag discharge rate sequences of each slag granulation system associated with the current furnace, resulting in a corrected total slag discharge rate sequence. This multi-channel dynamic correction method, which addresses the differences in error characteristics of each system under the shared mapping relationship of multiple tapholes, effectively eliminates systematic deviations in the measured data and their drift over time, solving the problem of molten iron level monitoring failure caused by measurement distortion.

[0048] This embodiment provides a method for monitoring the molten iron level in blast furnaces using multiple tapholes and multiple slag granulation systems, which can be used in the aforementioned mobile terminal. The blast furnace has multiple tapholes and at least two slag granulation systems. A preset mapping relationship exists between the tapholes and the slag granulation systems, wherein at least one slag granulation system corresponds to two or more tapholes simultaneously.

[0049] Figure 4 This is a second flowchart of a blast furnace slag-iron level monitoring method according to an embodiment of the present invention, which uses multiple sets of slag granulation treatment systems shared by multiple tapholes. Figure 4 As shown, the process includes the following steps: Step S401: Obtain the slag discharge rate sequence of each slag granulation treatment system associated with the current furnace.

[0050] Step S402: Obtain the theoretical slag generation amount for each heat in the historical reference heat, and the slag discharge rate sequence of each slag granulation treatment system associated with the historical reference heat.

[0051] Step S403: Based on the corresponding deviation relationship between the theoretical slag generation of each heat in the historical reference heat and the slag discharge rate sequence of each slag granulation treatment system, determine the independent correction parameters corresponding to each slag granulation treatment system.

[0052] In one optional implementation, the independent correction parameters corresponding to each slag granulation system are determined based on the corresponding deviation relationship between the theoretical slag generation of each heat in the historical reference heat and the slag discharge rate sequence of each slag granulation system, including the following steps S4031 to S4034.

[0053] Step S4031: Select N consecutive historical reference furnaces preceding the current furnace.

[0054] Selecting N consecutive historical furnaces immediately preceding the current furnace as samples can provide sufficient statistical samples and ensure that the data closely matches the current raw material, equipment and operating conditions of the blast furnace.

[0055] Step S4032: Perform time integration on the slag discharge rate sequence of each slag granulation treatment system for each selected historical reference furnace to obtain the total discharge amount per furnace for each slag granulation treatment system corresponding to each historical reference furnace.

[0056] By integrating the rate sequence over time, the instantaneous fluctuation data is transformed into a stable total discharge volume per furnace. This not only eliminates short-term noise interference but also ensures that the measured data and theoretical output remain consistent at the granularity of a single furnace, thus meeting the sample requirements for regression analysis.

[0057] Step S4033: Construct a multiple linear regression model with the theoretical slag generation per furnace of N historical reference furnaces as the dependent variable and the total discharge per furnace of each slag granulation treatment system of N historical reference furnaces as the independent variable. The multiple linear regression model does not include an intercept term.

[0058] The multiple linear regression model that does not include an intercept term (i.e., uses regression through the origin) is based on strict physical conservation laws. When the measured slag discharge rate of all systems is zero, the theoretical slag production rate must also be zero. If the intercept term is retained, it will lead to the calculation of a non-zero theoretical slag production rate under the condition of no slag discharge. This not only violates the basic physical laws of blast furnace material balance, but also introduces systematic bias and reduces the accuracy of the model.

[0059] Step S4034: Solve the multiple linear regression model and determine the regression coefficients corresponding to each independent variable as the independent correction parameters corresponding to each slag granulation treatment system.

[0060] Specifically, solving the multiple linear regression model and determining the regression coefficients corresponding to each independent variable as the independent correction parameters for each slag granulation treatment system includes the following steps a1 to a2.

[0061] Step a1: Construct the objective function using the least squares method. The objective function is the sum of squared residuals between the theoretical slag generation per furnace of N historical reference furnaces and the predicted values ​​of the multiple linear regression model.

[0062] In other words, by using the principle of least squares, an objective function with the sum of squared residuals as its core is constructed. This function transforms the problem of finding the optimal correction parameters into a mathematical problem of extreme value optimization.

[0063] Step a2: Solve for the regression coefficients that minimize the objective function, and determine the obtained regression coefficients as the independent correction parameters corresponding to each slag granulation treatment system.

[0064] For example, when the blast furnace is equipped with a first slag granulation treatment system and a second slag granulation treatment system, the regression coefficients that minimize the objective function are obtained by: constructing a system of two linear equations consisting of the total discharge amount per furnace of the first slag granulation treatment system, the total discharge amount per furnace of the second slag granulation treatment system, and the theoretical slag generation amount per furnace; solving the system of two linear equations to obtain the first correction coefficient corresponding to the first slag granulation treatment system and the second correction coefficient corresponding to the second slag granulation treatment system.

[0065] Assuming the theoretical slag production per furnace is y, b1 is the correction coefficient for INBA #1, b2 is the correction coefficient for INBA #2, x1 is the slag production of INBA #1 per furnace, and x2 is the slag production of INBA #2 per furnace, based on the principle of least squares, by solving the normal equations that minimize the sum of squared residuals, the analytical solutions for b1 and b2 are obtained as follows:

[0066] Where ∑ represents the selected continuous N N The historical reference furnaces are summed up; y, x1, and x2 represent the theoretical slag generation per furnace of the i-th historical reference furnace, the total discharge of the 1#INBA system per furnace, and the total discharge of the 2#INBA system per furnace, respectively. , x1x2, yx1, and yx2 are the squared terms or product terms of the corresponding variables, respectively; the final solution b1 and b2 are the independent correction parameters (correction coefficients) corresponding to the 1#INBA system and the 2#INBA system, respectively, used to characterize the proportional mapping relationship between the measured slag discharge and the actual theoretical slag discharge of each system.

[0067] Based on this, in order to further evaluate the goodness of fit of the constructed regression model and the reliability of the correction parameters, it is also necessary to calculate the coefficient of determination R. 2 The calculation formula is as follows:

[0068] In this formula, the numerator represents the regression sum of squares, which is the part of the variation in theoretical raw slag quantity that the model can explain; the denominator represents the total sum of squares (since the model passes through the origin, it is directly the sum of squares of y), which is the total degree of variation in theoretical raw slag quantity in historical data.

[0069] Step S404: Using the independent correction parameters corresponding to each slag granulation treatment system, the slag discharge rate sequence of each slag granulation treatment system associated with the current furnace is weighted and corrected, and the corrected sequences are summed to obtain the corrected total slag discharge rate sequence of the current furnace.

[0070] In some optional implementations, the slag discharge rate sequence of each slag granulation system associated with the current furnace is weighted and corrected using the independent correction parameters corresponding to each slag granulation system, and the corrected sequences are summed to obtain the corrected total slag discharge rate sequence of the current furnace, including the following steps S4041 to S4043.

[0071] Step S4041: Multiply the rate value at each moment in the slag discharge rate sequence of each slag granulation treatment system associated with the current furnace by the independent correction parameter of the corresponding system to obtain the corrected slag discharge rate sequence for each system.

[0072] Specifically, for a blast furnace equipped with two slag granulation systems (System 1 and System 2), the correction calculation for any time t follows the following linear weighted model:

[0073] in, t represents the predicted total slag discharge rate after correction at time t; b1 and b2 are the independent correction parameters of the slag granulation treatment systems of No. 1 and No. 2 obtained from the previous steps, respectively. and The measured slag discharge rates of the two systems at time t are respectively.

[0074] Step S4042: Accumulate the rate values ​​in the corrected slag discharge rate sequence of each system at the same time to obtain the corrected total slag discharge rate at the corresponding time.

[0075] In other words, the rate data of each system after independent correction are aligned and superimposed at each moment; by calculating the algebraic sum of the corrected rate values ​​of all systems at the same timestamp, the scattered single-system data are integrated into an instantaneous total rate that represents the true slag discharge capacity of the blast furnace as a whole.

[0076] Step S4043: Arrange the corrected total slag discharge rates of all times within the time range of the current furnace in chronological order to form the corrected total slag discharge rate sequence of the current furnace.

[0077] In other words, the total slag discharge rate calculated at all times in the current furnace is connected in chronological order to form a complete curve, which is then used to calculate the amount of slag in the furnace.

[0078] Step S405: Calculate the slag accumulation for the current furnace based on the corrected total slag discharge rate sequence.

[0079] Specifically, the calculation of the slag accumulation for the current furnace batch based on the corrected total slag discharge rate sequence includes the following steps b1 to b3.

[0080] Step b1: Obtain the theoretical slag generation rate sequence of the current furnace.

[0081] Among them, the theoretical slag generation rate sequence is the amount of dry slag that should be generated per unit time, which is dynamically calculated by the material balance model based on the real-time charging data of the blast furnace (such as the types and amounts of ore, flux, and coke) and their chemical composition.

[0082] Step b2: Perform a difference calculation between the theoretical slag generation rate sequence and the corrected slag discharge rate sequence to obtain the current net slag accumulation rate sequence of the furnace.

[0083] In other words, the difference between the theoretical slag generation rate sequence of the current furnace and the slag discharge rate sequence after system deviation correction is calculated time by time to obtain the rate of change of the amount of slag added in the furnace but not yet discharged at each time, which is the net slag accumulation rate sequence.

[0084] Step b3: Calculate the current slag accumulation in the furnace based on the slag net accumulation rate sequence.

[0085] Specifically, the total mass of slag is obtained by first performing a time-cumulative calculation on the slag net accumulation rate sequence; When the slag accumulation needs to be characterized by height, it is further converted by combining the current furnace hearth structural parameters; when the slag accumulation needs to be characterized by mass, the total mass of the slag is directly determined as the slag accumulation.

[0086] For example, the structural parameters of the blast furnace hearth include the effective cross-sectional area of ​​the hearth, the inner diameter of the hearth, the height of the hearth, and the geometric mapping relationship between the hearth volume and the liquid level.

[0087] Step S406: Determine the current slag and iron accumulation in the furnace based on the current slag accumulation.

[0088] In one optional implementation, determining the current slag and iron accumulation in the furnace based on the current slag accumulation includes steps c1 to c2.

[0089] Step c1: Obtain the current amount of molten iron in the furnace.

[0090] The amount of molten iron accumulated is defined as a characterization parameter with the same physical dimensions as the amount of slag accumulated in the furnace at the current time: when the amount of slag accumulated is characterized by height, the amount of molten iron accumulated refers to the height of the molten iron layer; when the amount of slag accumulated is characterized by mass, the amount of molten iron accumulated refers to the total mass of molten iron. Specifically, the process of obtaining the amount of molten iron accumulated includes: firstly, based on the theoretical molten iron generation rate of the blast furnace and the actual tapping records, the total mass of molten iron that has not yet been discharged from the hearth at the current moment is dynamically calculated using the material balance method. Specifically, the theoretical molten iron generation rate can be estimated based on the iron content of the raw materials (such as iron ore, coke, etc.) and the charging rate, combined with the smelting reduction efficiency, while the actual tapping amount is obtained through the molten iron ladle weighing system or the tapping time and flow rate model. The total mass of molten iron is obtained by subtracting the amount of molten iron that has been discharged from the theoretically generated amount of molten iron and accumulating it over time. Subsequently, the total mass of molten iron is processed according to the specific representation mode of slag accumulation: if slag accumulation is represented by mass, the calculated total mass of molten iron is directly used as the molten iron accumulation; if slag accumulation is represented by height, the total mass of molten iron is converted into the molten iron layer height using the hearth structural parameters, and this is used as the molten iron accumulation. This method ensures that the obtained molten iron accumulation and slag accumulation are strictly consistent in physical dimensions, laying the foundation for subsequent addition calculations.

[0091] Step c2: Add the amount of molten iron to the amount of slag to obtain the current amount of slag and iron in the furnace.

[0092] In the blast furnace hearth, molten iron and slag naturally separate into layers, with the slag floating on top of the iron. Therefore, by adding the amount of molten iron accumulated to the amount of slag accumulated, the amount of slag and iron accumulated can be obtained.

[0093] Steps c1 to c2 involve adding the accurately calculated slag accumulation to the molten iron accumulation to reasonably reconstruct the slag-iron accumulation that reflects the true physical state inside the hearth, thus achieving a precise characterization of the overall position of the slag-iron interface.

[0094] To more clearly illustrate the method for monitoring slag and iron accumulation in the blast furnace hearth according to the present invention, a specific example is given, which includes the following steps: The first step is to calculate the slag-iron molten metal level curve in the blast furnace hearth using the method described in CN117051190A, such as... Figure 2 As shown, the horizontal axis is the time axis, and the vertical axis is the liquid level curve. The black line represents the change curve of the molten iron liquid level, the red line represents the change curve of the molten slag liquid level, and the blue line represents the slag-iron liquid level curve. It can be clearly seen that the slag liquid level curve is in a relatively rising state. However, this is inconsistent with the actual iron and slag tapping situation in the blast furnace, and the slag liquid level curve needs to be verified.

[0095] The second step is to divide the slag-iron molten metal surface curves according to the furnace batch, using custom division rules. For example... Figure 2The slag liquid level curve is a cyclical alternating upward curve. A single cycle is similar to the shape of a bridge. The low point of the liquid level change in a single cycle is recorded as the end time of the current furnace and the start time of the next furnace. The start time and end time of a single furnace constitute a cycle, which is set as 1 furnace.

[0096] The third step is to verify the slag liquid level data according to the furnace batch, using 5800 m 3 Taking a high-grade blast furnace as an example, the rule of verifying one furnace every 36 furnaces is adopted. For example, the 37th furnace is verified using furnaces 1-36, and the nth furnace is verified using furnaces n-36 to n-1. Assuming the theoretical slag output per furnace is y, b1 is the INBA correction coefficient for #1, b2 is the INBA correction coefficient for #2, VINBA-1# is the slag output of INBA for #1 per furnace, and VINBA-2# is the slag output of INBA for #2 per furnace. The INBA correction coefficients b1 and b2 are calculated using furnaces n-36 to n-1 as the INBA correction coefficient for the nth furnace. Figure 5 As shown; then with n 36 to n A multivariate linear regression model was constructed using data from one furnace to obtain independent correction coefficients b1 and b2 specific to the nth furnace. Subsequently, these coefficients were used to perform point-by-point weighted correction and summation on the real-time slag discharge rate sequences of the two INBA systems for the nth furnace to obtain a high-precision corrected total slag discharge rate. Finally, this was substituted into the material balance model to recalculate the slag storage volume and reconstruct the true slag liquid level curve that eliminates false upward trends.

[0097] The fourth step is to verify the results; by verifying the deviation value of the slag discharge rate, the change in the slag-iron molten level is recalculated, such as... Figure 6 As shown, the slag-iron molten level curve after verification basically matches the slag-iron molten level in the blast furnace hearth. Figure 2 and Figure 6 To make a comparison, Figure 2 During a 6-hour period, the slag accumulation inside the furnace hearth reached 550 tons. Figure 6 After the intermediate verification, the amount of slag stored was only 35 tons.

[0098] The method for monitoring the slag and iron accumulation in the blast furnace hearth provided in this embodiment has the following beneficial effects: (1) The actual slag discharge rate can be obtained by mathematical calculation using the existing INBA equipment, without the need for new equipment or equipment upgrades, so the cost is relatively low. More than 80% of the existing blast furnace slag discharge systems use INBA equipment, so it can be widely used.

[0099] (2) By verifying the slag tapping speed, the change curve of slag and iron liquid level in the actual blast furnace hearth can be calculated. Under the premise of lacking reliable safety basis, it is of great significance for guiding the tapping of iron and slag in front of the blast furnace, gradually transforming the subjective judgment of the furnace front operation into digitalization, guiding the tapping of iron in the blast furnace, and reducing the increase of furnace pressure difference caused by iron blockage.

[0100] (3) The calculation method of correcting the next furnace based on 36 furnaces effectively corrects the slag liquid level curve. This invention is equivalent to proposing a real-time correction calculation method, that is, the verification parameters of the current furnace are taken from the previous 36 furnaces. Compared with proposing a fixed verification parameter, this verification method is more scientific and effective, and eliminates factors such as human intervention.

[0101] (4) The method of correcting the two INBAs separately proposed in this embodiment can be widely used, especially when the slag discharge speeds of the two INBAs differ greatly, the verification parameters will inevitably have a large deviation. The verification method using a two-variable linear equation can effectively solve this problem.

[0102] This embodiment also provides a blast furnace slag-iron liquid level monitoring device for multiple taphole shared slag granulation treatment systems. This device is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0103] This embodiment provides a blast furnace slag-iron liquid level monitoring device for multiple slag granulation treatment systems shared by multiple tapholes, such as... Figure 7 As shown, it includes a first acquisition module 701, a second acquisition module 702, a correction parameter determination module 703, a correction module 704, a slag accumulation determination module 705, and a slag and iron accumulation determination module 706.

[0104] The first acquisition module 701 is used to acquire the slag discharge rate sequence of each slag granulation treatment system associated with the current furnace.

[0105] The second acquisition module 702 is used to acquire the theoretical slag generation amount of each heat in the historical reference heat, and the slag discharge rate sequence of each slag granulation treatment system associated with the historical reference heat.

[0106] The correction parameter determination module 703 is used to determine the independent correction parameters corresponding to each slag granulation system based on the corresponding deviation relationship between the theoretical slag generation of each heat in the historical reference heat and the slag discharge rate sequence of each slag granulation treatment system.

[0107] The correction module 704 is used to perform weighted correction on the slag discharge rate sequence of each slag granulation treatment system associated with the current furnace by using the independent correction parameters corresponding to each slag granulation treatment system, and summing the corrected sequences to obtain the corrected total slag discharge rate sequence of the current furnace.

[0108] The slag accumulation determination module 705 is used to calculate the slag accumulation of the current furnace based on the corrected total slag discharge rate sequence.

[0109] The slag and iron accumulation determination module 706 is used to determine the current slag and iron accumulation of the furnace based on the current slag accumulation of the furnace.

[0110] In some optional implementations, the correction parameter determination module 703 is specifically used for: selecting N consecutive historical reference furnaces prior to the current furnace; performing time integration on the slag discharge rate sequence of each slag granulation treatment system for each selected historical reference furnace to obtain the total discharge amount per furnace for each slag granulation treatment system corresponding to each historical reference furnace; constructing a multiple linear regression model with the theoretical slag generation amount per furnace of the N historical reference furnaces as the dependent variable and the total discharge amount per furnace for each slag granulation treatment system of the N historical reference furnaces as the independent variable, and the multiple linear regression model does not include an intercept term; solving the multiple linear regression model and determining the regression coefficients corresponding to each independent variable as the independent correction parameters corresponding to each slag granulation treatment system.

[0111] In some optional implementations, the correction parameter determination module 703 is specifically used to: construct an objective function using the least squares method, the objective function being the sum of squared residuals between the theoretical slag generation per furnace of N historical reference furnaces and the predicted values ​​of the multiple linear regression model; solve for the regression coefficients that minimize the objective function, and determine the solved regression coefficients as independent correction parameters corresponding to each slag granulation treatment system.

[0112] In some optional embodiments, when the blast furnace is equipped with a first slag granulation treatment system and a second slag granulation treatment system, the correction parameter determination module 703 is specifically used to: construct a system of two linear equations consisting of the total discharge amount per furnace of the first slag granulation treatment system, the total discharge amount per furnace of the second slag granulation treatment system, and the theoretical slag generation amount per furnace; solve the system of two linear equations to obtain the first correction coefficient corresponding to the first slag granulation treatment system and the second correction coefficient corresponding to the second slag granulation treatment system.

[0113] In some optional implementations, the correction module 704 is specifically used to: multiply the rate value at each moment in the slag discharge rate sequence of each slag granulation treatment system associated with the current furnace by the independent correction parameter of the corresponding system to obtain the corrected slag discharge rate sequence for each system; accumulate the rate values ​​in the corrected slag discharge rate sequences of each system at the same moment to obtain the corrected total slag discharge rate at the corresponding moment; and arrange the corrected total slag discharge rates at all moments within the time range of the current furnace in chronological order to form the corrected total slag discharge rate sequence for the current furnace.

[0114] In some optional implementations, the slag accumulation determination module 705 is specifically used to: obtain the theoretical slag generation rate sequence of the current furnace, the theoretical slag generation rate sequence being determined based on the composition of the raw materials fed into the furnace and the charging data; perform a difference calculation between the theoretical slag generation rate sequence and the corrected slag discharge rate sequence to obtain the net slag accumulation rate sequence of the current furnace; perform an accumulation calculation on the net slag accumulation rate sequence to obtain the slag storage amount of the current furnace; and determine the slag accumulation amount of the current furnace based on the slag storage amount and the hearth structure parameters of the current furnace.

[0115] The blast furnace slag-iron liquid level monitoring device for a multi-tap shared multi-set slag granulation treatment system provided in this embodiment of the invention can execute the blast furnace slag-iron liquid level monitoring method for a multi-tap shared multi-set slag granulation treatment system provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the above modules and units are the same as in the corresponding embodiments described above, and will not be repeated here.

[0116] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0117] The following is a detailed reference. Figure 8 This diagram illustrates a suitable structural schematic for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 801, which can perform various appropriate actions and processes based on a program stored in read-only memory (ROM) 802 or a program loaded from memory 808 into random access memory (RAM) 803. The RAM 803 also stores various programs and data required for the operation of the electronic device. The processor 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0118] Typically, the following devices can be connected to I / O interface 805: input devices 806 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 807 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 808 including, for example, magnetic tapes, hard disks, etc.; and communication devices 809. Communication device 809 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 8 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0119] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 809, or installed from a memory 808, or installed from a ROM 802. When the computer program is executed by the processor 801, it performs the functions defined in the blast furnace slag-iron liquid level monitoring method for a multi-tap shared multi-set slag granulation treatment system according to embodiments of the present invention.

[0120] Figure 8 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0121] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the blast furnace slag-iron liquid level monitoring method shown in the above embodiments for a multi-tap shared multi-set slag granulation treatment system is implemented.

[0122] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0123] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for monitoring the molten iron level in a blast furnace using multiple tapholes and multiple slag granulation systems, wherein the blast furnace has multiple tapholes and at least two slag granulation systems, a preset mapping relationship exists between the tapholes and the slag granulation systems, and at least one slag granulation system simultaneously corresponds to two or more tapholes, characterized in that... The method includes: Obtain the slag discharge rate sequence of each slag granulation treatment system associated with the current furnace batch; Obtain the theoretical slag generation amount for each heat in the historical reference heat, and the slag discharge rate sequence of each slag granulation treatment system associated with the historical reference heat. Based on the corresponding deviation relationship between the theoretical slag generation of each heat in the historical reference heat and the slag discharge rate sequence of each slag granulation treatment system, the independent correction parameters corresponding to each slag granulation treatment system are determined. Using the independent correction parameters corresponding to each slag granulation treatment system, the slag discharge rate sequence of each slag granulation treatment system associated with the current furnace is weighted and corrected respectively, and the corrected sequences are summed to obtain the corrected total slag discharge rate sequence of the current furnace. Based on the corrected total slag discharge rate sequence, calculate the slag accumulation for the current furnace batch; The slag and iron accumulation in the current furnace is determined based on the current slag accumulation. The determination of independent correction parameters for each slag granulation system, based on the corresponding deviation relationship between the theoretical slag generation rate for each heat in the historical reference heats and the slag discharge rate sequence of each slag granulation system, includes: Select N consecutive historical reference furnaces preceding the current furnace batch; The slag discharge rate sequence of each slag granulation treatment system for each selected historical reference furnace is integrated over time to obtain the total discharge amount per furnace for each slag granulation treatment system corresponding to each historical reference furnace. A multiple linear regression model is constructed, with the theoretical slag generation per furnace of the N historical reference furnaces as the dependent variable and the total discharge per furnace of each slag granulation treatment system of the N historical reference furnaces as the independent variable. The multiple linear regression model does not include an intercept term. Solve the multiple linear regression model and determine the regression coefficients corresponding to each independent variable as independent correction parameters for each slag granulation treatment system.

2. The method according to claim 1, characterized in that, The process of solving the multiple linear regression model, and determining the regression coefficients corresponding to each independent variable as independent correction parameters for each slag granulation system, includes: The objective function is constructed using the least squares method. The objective function is the sum of squared residuals between the theoretical slag generation per furnace of the N historical reference furnaces and the predicted values ​​of the multiple linear regression model. Solve for the regression coefficients that minimize the objective function, and determine the obtained regression coefficients as independent correction parameters for each slag granulation treatment system.

3. The method according to claim 2, characterized in that, When the blast furnace is equipped with a first slag granulation treatment system and a second slag granulation treatment system, the regression coefficients that minimize the objective function include: A system of two linear equations is constructed, consisting of the total discharge amount per furnace run of the first slag granulation treatment system, the total discharge amount per furnace run of the second slag granulation treatment system, and the theoretical slag generation amount per furnace run. Solving the system of two linear equations in two variables yields the first correction coefficient corresponding to the first slag granulation treatment system and the second correction coefficient corresponding to the second slag granulation treatment system.

4. The method according to claim 1, characterized in that, The step involves using the independent correction parameters corresponding to each slag granulation treatment system to perform weighted correction on the slag discharge rate sequence of each slag granulation treatment system associated with the current furnace, and summing the corrected sequences to obtain the corrected total slag discharge rate sequence for the current furnace, including: Multiply the rate value at each moment in the slag discharge rate sequence of each slag granulation treatment system associated with the current furnace batch by the independent correction parameter of the corresponding system to obtain the corrected slag discharge rate sequence for each system. The rate values ​​in the corrected slag discharge rate sequence of each system at the same time are summed to obtain the corrected total slag discharge rate at the corresponding time. The corrected total slag discharge rate sequence for the current furnace is formed by arranging the corrected total slag discharge rates at all times within the current furnace time range in chronological order.

5. The method according to claim 1, characterized in that, The calculation of the current furnace slag accumulation based on the corrected slag discharge rate sequence includes: Obtain the theoretical slag formation rate sequence of the current furnace, which is determined based on the composition of the raw materials fed into the furnace and the charging data; The difference between the theoretical slag generation rate sequence and the corrected slag discharge rate sequence is calculated to obtain the current slag net accumulation rate sequence of the furnace. The current slag storage capacity of the furnace is obtained by performing cumulative calculations on the slag net accumulation rate sequence. The slag accumulation of the current furnace is determined based on the slag storage volume and the hearth structural parameters of the current furnace.

6. A blast furnace slag-iron level monitoring device for multiple tapholes sharing multiple slag granulation treatment systems, characterized in that, The blast furnace is equipped with multiple tapholes and at least two slag granulation systems. A preset mapping relationship exists between the tapholes and the slag granulation systems, wherein at least one slag granulation system simultaneously corresponds to two or more tapholes. The device includes: The first acquisition module is used to acquire the slag discharge rate sequence of each slag granulation treatment system associated with the current furnace batch; The second acquisition module is used to acquire the theoretical slag generation amount of each heat in the historical reference heat, and the slag discharge rate sequence of each slag granulation treatment system associated with the historical reference heat. The correction parameter determination module is used to determine the independent correction parameters corresponding to each slag granulation treatment system based on the corresponding deviation relationship between the theoretical slag generation of each heat in the historical reference heat and the slag discharge rate sequence of each slag granulation treatment system. The correction module is used to use the independent correction parameters corresponding to each slag granulation treatment system to perform weighted correction on the slag discharge rate sequence of each slag granulation treatment system associated with the current furnace, and to sum the corrected sequences to obtain the corrected total slag discharge rate sequence of the current furnace. The slag accumulation determination module is used to calculate the slag accumulation of the current furnace based on the corrected total slag discharge rate sequence. The slag and iron accumulation determination module is used to determine the slag and iron accumulation of the current furnace based on the slag accumulation of the current furnace. The correction parameter determination module is specifically used for: selecting N consecutive historical reference furnaces prior to the current furnace; performing time integration on the slag discharge rate sequence of each slag granulation treatment system for each selected historical reference furnace to obtain the total discharge amount per furnace for each slag granulation treatment system corresponding to each historical reference furnace; constructing a multiple linear regression model, with the theoretical slag generation amount per furnace for the N historical reference furnaces as the dependent variable and the total discharge amount per furnace for each slag granulation treatment system for the N historical reference furnaces as the independent variable, and the multiple linear regression model does not include an intercept term; solving the multiple linear regression model, and determining the regression coefficients corresponding to each independent variable as the independent correction parameters corresponding to each slag granulation treatment system.

7. An electronic device, characterized in that, include: The system includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes these computer instructions to perform the blast furnace slag-iron level monitoring method for a multi-tap shared slag granulation treatment system as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the blast furnace slag-iron level monitoring method of any one of claims 1 to 5, which uses a multi-tap shared multi-set slag granulation treatment system.

9. A computer program product, characterized in that, The method includes computer instructions for causing a computer to execute the blast furnace slag-iron level monitoring method according to any one of claims 1 to 5, which involves multiple slag granulation treatment systems shared by multiple tapholes.

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