CN-121972620-A - Method for predicting and regulating liquid level fluctuation of slab continuous casting crystallizer

CN121972620ACN 121972620 ACN121972620 ACN 121972620ACN-121972620-A

Abstract

The application discloses a method for predicting and regulating the liquid level fluctuation of a slab continuous casting crystallizer, which comprises the steps of obtaining the current process control parameters of the crystallizer, inputting the current process control parameters into a pre-constructed liquid level fluctuation amplitude prediction model to obtain the liquid level fluctuation amplitude of the crystallizer, which is output by the liquid level fluctuation amplitude prediction model and corresponds to the current process control parameters, wherein the liquid level fluctuation amplitude prediction model is a power function expression obtained by combining physical simulation experimental data taking the liquid level fluctuation amplitude of the crystallizer as a response variable after a dimensionless relational expression for describing the liquid level fluctuation of the crystallizer is determined based on a dimensionless analysis principle. The application can rapidly predict the fluctuation amplitude of the liquid level of the crystallizer based on the current process control parameters by using a prediction model. The model not only improves the prediction efficiency, but also quantifies the influence degree of each parameter on the liquid level fluctuation, and provides a clear regulation and control direction, thereby being beneficial to the improvement of the casting blank quality under the high-pulling-speed working condition.

Inventors

ZHU MIAOYONG
ZHENG SHIWEI
CAI ZHAOZHEN

Assignees

东北大学

Dates

Publication Date: 20260505
Application Date: 20260407

Claims (10)

1. The method for predicting the fluctuation of the liquid level of the slab continuous casting crystallizer is characterized by comprising the following steps of: obtaining current process control parameters of a crystallizer; inputting the current process control parameters into a pre-constructed liquid level fluctuation amplitude prediction model to obtain the crystallizer liquid level fluctuation amplitude corresponding to the current process control parameters, wherein the liquid level fluctuation amplitude prediction model is obtained by combining physical simulation experimental data taking the crystallizer liquid level fluctuation amplitude as a response variable after determining a dimensionless relational expression for describing the crystallizer liquid level fluctuation based on a dimensionality analysis principle, and carrying out regression analysis inversion to obtain a power function expression.
2. The method of claim 1, wherein the current process control parameters include at least a crystallizer width, a submerged nozzle side hole equivalent diameter, a submerged nozzle immersion depth, and a submerged nozzle side hole inclination, and operating parameters including at least a withdrawal speed.
3. The method of claim 1, wherein constructing the liquid level fluctuation amplitude prediction model comprises: Determining a target physical quantity based on the dimension analysis principle, wherein the target physical quantity at least comprises geometric parameters, operation parameters, molten steel physical parameters and physical constants of a crystallizer; Based on white gold Han dynasty Theorem and the target physical quantity, determining a dimensionless relation for describing the fluctuation amplitude of the liquid level of the crystallizer; constructing a physical simulation experiment, setting different experimental conditions based on a preset experimental design method, and collecting fluctuation amplitude of the liquid level of a crystallizer under different experimental conditions as a response variable, wherein the physical simulation experiment is used for simulating the flow and the fluctuation behavior of the liquid level of molten steel in the crystallizer in the slab continuous casting process; Converting the dimensionless relation into a power function form, wherein the power function contains undetermined coefficients; And carrying out linearization treatment on the power function, carrying out multiple linear regression analysis by combining the fluctuation amplitude of the liquid level of the crystallizer under different experimental conditions, determining undetermined coefficients in the power function, and carrying out inversion to obtain the prediction model of the fluctuation amplitude of the liquid level.
4. The method of claim 3, wherein the geometric parameters include at least a crystallizer width, an immersion nozzle side hole equivalent diameter, an immersion nozzle immersion depth, and an immersion nozzle side hole inclination angle, the operating parameters include at least a withdrawal speed, the molten steel physical parameters include at least a molten steel density, a molten steel dynamic viscosity, and a molten steel surface tension, and the physical constants include at least a gravitational acceleration.
5. The method of claim 4, wherein the non-dimensional relationship is expressed as: Wherein, the Is the fluctuation amplitude of the liquid level of the dimensionless crystallizer, For the fluctuation amplitude of the liquid level of the crystallizer, For the width of the crystallizer in question, Is the equivalent diameter of the dimensionless side hole, For the equivalent diameter of the side hole of the submerged nozzle, Is the immersion depth of the dimensionless immersion nozzle, For the immersion depth of the submerged entry nozzle, For the dip nozzle side hole inclination, Is Froude number; the expression of the power function is: Wherein, the For the fluctuation amplitude of the liquid level of the dimensionless crystallizer, Is a constant value, and is used for the treatment of the skin, For the dimensionless side hole equivalent diameter, For the non-dimensional immersion nozzle immersion depth, For the dip nozzle side hole inclination factor, For the friedel number to be the same, Are all the undetermined coefficients.
6. The method of claim 5, wherein the linearizing the power function, performing multiple linear regression analysis in combination with the fluctuation amplitude of the liquid level of the crystallizer under different experimental conditions, determining the undetermined coefficient in the power function, and inverting to obtain the prediction model of the fluctuation amplitude of the liquid level, comprises: taking natural logarithms of the power functions, and converting the power functions into a multi-element linear equation containing the undetermined coefficients; Performing multiple linear regression analysis on the multiple linear equation by combining the fluctuation amplitude of the liquid level of the crystallizer under different experimental conditions, and inverting to obtain the value of the undetermined coefficient; and inputting the value of the undetermined coefficient to the power function to obtain the liquid level fluctuation amplitude prediction model.
7. The method according to claim 1, wherein the expression of the liquid level fluctuation amplitude prediction model is: Wherein, the For the fluctuation amplitude of the liquid level of the crystallizer, For the width of the crystallizer, For the equivalent diameter of the side hole of the immersed nozzle, For the immersion depth of the immersion nozzle, For the dip angle of the side hole of the immersed nozzle, In order for the speed of the draw to be high, 、、、、 And Are all constant.
8. The method of claim 7, wherein the withdrawal speed and the crystallizer width satisfy a froude number similarity criterion , wherein, The value is the Froude number, Gravitational acceleration.
9. A method for controlling the fluctuation of the liquid level of a slab continuous casting crystallizer, characterized in that the fluctuation amplitude of the liquid level of the crystallizer is obtained based on the method of any one of claims 1 to 8, comprising: judging whether the fluctuation amplitude of the liquid level of the crystallizer is in a preset threshold value interval or not; If the fluctuation amplitude of the liquid level of the crystallizer is within the threshold value interval, keeping the current process control parameters unchanged, wherein the current process control parameters at least comprise the width of the crystallizer, the blank pulling speed, the equivalent diameter of the side hole of the immersed nozzle, the immersion depth of the immersed nozzle and the dip angle of the side hole of the immersed nozzle; And if the fluctuation amplitude of the liquid level of the crystallizer is not in the threshold value interval, adjusting at least one of the width of the crystallizer, the blank pulling speed, the equivalent diameter of the side hole of the immersed nozzle, the immersion depth of the immersed nozzle and the inclination angle of the side hole of the immersed nozzle so as to adjust the fluctuation amplitude of the liquid level of the crystallizer to be in the threshold value interval.
10. The method of claim 9, wherein adjusting at least one of the crystallizer width, the withdrawal speed, the submerged nozzle side hole equivalent diameter, the submerged nozzle immersion depth, and the submerged nozzle side hole inclination angle to adjust the crystallizer liquid level fluctuation amplitude to be within the threshold interval if the crystallizer liquid level fluctuation amplitude is not within the threshold interval comprises: when the fluctuation amplitude of the liquid level of the crystallizer is higher than the upper limit of the threshold interval, at least one mode of reducing the blank pulling speed, increasing the equivalent diameter of the side hole of the submerged nozzle, increasing the immersion depth of the submerged nozzle and increasing the dip angle of the side hole of the submerged nozzle is adopted to adjust the fluctuation amplitude of the liquid level of the crystallizer to be within the threshold interval; And under the condition that the fluctuation amplitude of the liquid level of the crystallizer is lower than the lower limit of the threshold interval, at least one mode of increasing the blank pulling speed, reducing the equivalent diameter of the side hole of the submerged nozzle, reducing the immersion depth of the submerged nozzle and reducing the dip angle of the side hole of the submerged nozzle is adopted to adjust the fluctuation amplitude of the liquid level of the crystallizer to be within the threshold interval.

Description

Method for predicting and regulating liquid level fluctuation of slab continuous casting crystallizer Technical Field The application relates to the technical field of crystallizers, in particular to a method for predicting and regulating liquid level fluctuation of a slab continuous casting crystallizer. Background In the continuous casting production process of the metallurgical industry, the stability of the liquid level of molten steel in a crystallizer is one of core factors influencing the quality and the production efficiency of casting blanks. Along with the transformation of steel enterprises to high efficiency and green, the improvement of the drawing speed becomes a key path for realizing the high efficiency of the continuous casting process, but the lifting of the drawing speed often aggravates the disturbance of molten steel flow in the crystallizer, so that the fluctuation amplitude of the liquid level of the crystallizer is increased, thereby easily winding the casting powder into the molten steel and forming surface or internal defects of casting blanks. Therefore, how to predict the fluctuation of the liquid level of the crystallizer rapidly with low cost and quantify the influence degree of the continuous casting process parameters on the fluctuation of the liquid level, and provide a quantification basis for regulating the fluctuation of the liquid level, has become a technical problem to be solved in the art. At present, in the slab production process, an electromagnetic or source type device is generally utilized to monitor the fluctuation condition of the liquid level of molten steel in real time, so that the fluctuation amplitude of the liquid level cannot be predicted in advance. In the research of liquid level fluctuation, toshio Teshima and other scholars put forward a fluctuation index F number through a physical model experiment, but the calculation of the index is required to obtain key parameters of a measured jet flow by a hydraulic experiment or numerical simulation, the process is complicated and the efficiency is low, and then Jin Xin and other researchers deduce an analytic formula of the F number by using a turbulent jet flow theory, but the formula is required to select a turbulent flow coefficient through experience, has subjective errors, has numerous formula parameters and complex structure, is inconvenient to practically apply and operate, and is easy to cause calculation errors. In summary, the existing liquid level fluctuation monitoring equipment cannot predict the liquid level fluctuation amplitude in advance, but the method capable of reflecting the liquid level fluctuation degree has the defects of dependence on experimental simulation, low calculation efficiency, complex formula or strong subjectivity in parameter selection, and the like, and can cause high cost and low efficiency in predicting the liquid level fluctuation amplitude of the crystallizer, thereby restricting the development of high-drawing-speed continuous casting and the improvement of casting blank quality. Disclosure of Invention In view of the above, the embodiment of the application provides a method for predicting and regulating the fluctuation of the liquid level of a slab continuous casting crystallizer, which can reduce the cost for predicting the fluctuation of the liquid level and improve the prediction efficiency, thereby being beneficial to the development of high-drawing-speed continuous casting and the improvement of the quality of casting blanks. In a first aspect, the application provides a method for predicting liquid level fluctuation of a slab continuous casting crystallizer, comprising the following steps: obtaining current process control parameters of a crystallizer; inputting the current process control parameters into a pre-constructed liquid level fluctuation amplitude prediction model to obtain the crystallizer liquid level fluctuation amplitude corresponding to the current process control parameters, wherein the liquid level fluctuation amplitude prediction model is obtained by combining physical simulation experimental data taking the crystallizer liquid level fluctuation amplitude as a response variable after determining a dimensionless relational expression for describing the crystallizer liquid level fluctuation based on a dimensionality analysis principle, and carrying out regression analysis inversion to obtain a power function expression. In some embodiments, the current process control parameters include a geometry including at least a crystallizer width, an immersion nozzle side hole equivalent diameter, an immersion nozzle immersion depth, and an immersion nozzle side hole inclination angle, and an operating parameter including at least a withdrawal speed. In some embodiments, the process of constructing the liquid level fluctuation amplitude prediction model includes: Determining a target physical quantity based on a dimension analysis principle, wherein th